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cc-backend/fc/3be444ef4c/0/full.jsonl
Jan Eitzinger dfa7def694 Checkpoint: fc3be444ef4c 
Entire-Session: 5de2a23c-09cd-4d6c-a97c-fab8657d094c
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Entire-Agent: Claude Code
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2026-03-04 16:43:19 +01:00

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{"parentUuid":"c396186a-6571-4923-a531-41f096333b61","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Consolidate buildQueries / Scope Transformation Logic\n\n## Context\n\n`pkg/metricstore/query.go` (InternalMetricStore) and `internal/metricstoreclient/cc-metric-store-queries.go` (CCMetricStore) both implement the `MetricDataRepository` interface. They contain nearly identical scope-transformation logic for building metric queries, but the code has diverged:\n\n- **metricstoreclient** has the cleaner design: a standalone `buildScopeQueries()` function handling all transformations\n- **metricstore** has the same logic inlined as a long if-chain inside `buildQueries()` and duplicated in `buildNodeQueries()`\n- **metricstore is missing** the `MemoryDomain → Socket` transformation that metricstoreclient has\n- Both packages duplicate scope string constants, `intToStringSlice`, and `sanitizeStats`\n\nGoal: Extract shared scope-transformation logic, synchronize behavior, and eliminate duplication.\n\n## Approach\n\nExtract `BuildScopeQueries` as a shared exported function in `pkg/metricstore/` (since metricstoreclient already imports it). Return a package-independent intermediate type (`ScopeQueryResult`) that each package converts to its own `APIQuery` — this avoids coupling the two different `APIQuery` types (they differ in `Resolution` type: `int64` vs `int`, and internal has `ScaleFactor`).\n\n## Steps\n\n### 1. Create `pkg/metricstore/scopequery.go`\n\nNew file containing:\n\n- **`ScopeQueryResult`** struct — intermediate type with fields: `Metric`, `Hostname`, `Aggregate`, `Type *string`, `TypeIds []string`, `Scope schema.MetricScope` (no Resolution — callers set it)\n- **`BuildScopeQueries()`** — exported function ported from `metricstoreclient/buildScopeQueries()` (lines 257-517), returning `([]ScopeQueryResult, error)`. Returns empty slice for expected exceptions, error for unhandled cases\n- **Scope string constants** — `HWThreadString`, `CoreString`, `MemoryDomainString`, `SocketString`, `AcceleratorString` (exported, move from both packages)\n- **`IntToStringSlice()`** — exported, using the optimized buffer-reuse version from metricstore\n- **`SanitizeStats(avg, min, max *schema.Float)`** — exported, using the metricstoreclient behavior (zero ALL if ANY is NaN)\n\n### 2. Update `pkg/metricstore/query.go`\n\n- Replace inline if-chain in `buildQueries()` (lines 317-534) with call to `BuildScopeQueries()`, converting each `ScopeQueryResult` → local `APIQuery` (adding `Resolution`)\n- Replace inline if-chain in `buildNodeQueries()` (lines 1099-1316) with same pattern\n- Delete local scope string constants, `intToStringSlice`, local `sanitizeStats`\n- Update `sanitizeStats` calls in `LoadData`/`LoadScopedStats`/`LoadNodeData`/`LoadNodeListData` to use `SanitizeStats(&res.Avg, &res.Min, &res.Max)`\n- Switch scope dedup from `map[schema.MetricScope]bool` to labeled-loop + slice (matches metricstoreclient, avoids allocation for typical 1-3 scopes)\n- This **adds the missing MemoryDomain → Socket transformation** to the internal store\n\n### 3. Update `internal/metricstoreclient/cc-metric-store-queries.go`\n\n- Replace call to local `buildScopeQueries()` with `metricstore.BuildScopeQueries()`, converting each `ScopeQueryResult` → local `APIQuery` (adding `Resolution`)\n- Delete local `buildScopeQueries()` function\n- Delete local scope string constants and `intToStringSlice`\n- Update `sanitizeStats` in `cc-metric-store.go` to call `metricstore.SanitizeStats()`\n\n### 4. Add tests: `pkg/metricstore/scopequery_test.go`\n\nTable-driven tests for `BuildScopeQueries` covering all transformation cases:\n- Same-scope (HWThread→HWThread, Core→Core, Socket→Socket, Node→Node, etc.)\n- Aggregation (HWThread→Core, HWThread→Socket, HWThread→Node, Core→Socket, Core→Node, etc.)\n- Accelerator cases (Accelerator→Accelerator, Accelerator→Node)\n- MemoryDomain cases including MemoryDomain→Socket\n- Unhandled case returns error\n\n## Files Modified\n\n| File | Action |\n|------|--------|\n| `pkg/metricstore/scopequery.go` | **New** — shared types and functions |\n| `pkg/metricstore/scopequery_test.go` | **New** — tests for BuildScopeQueries |\n| `pkg/metricstore/query.go` | Refactor buildQueries/buildNodeQueries to use BuildScopeQueries; remove duplicated helpers |\n| `internal/metricstoreclient/cc-metric-store-queries.go` | Replace local buildScopeQueries with shared; remove duplicated helpers |\n| `internal/metricstoreclient/cc-metric-store.go` | Update sanitizeStats to use shared SanitizeStats |\n\n## What is NOT shared (intentionally)\n\n- **`APIQuery`/`APIMetricData` types** — different Resolution types, Data types, ScaleFactor field\n- **`buildQueries`/`buildNodeQueries` themselves** — different topology access (caching vs inline), different receiver types\n- **Load* result-processing functions** — depend on package-specific types and fetch mechanisms\n\n## Verification\n\n1. `go build ./...` — compile check\n2. `go test ./pkg/metricstore/...` — existing + new scopequery tests\n3. `go test ./internal/metricstoreclient/...` — compile check\n4. `make test` — full test suite\n\n\nIf you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-ClusterCockpit-cc-backend/eec1fc87-d8f6-42f6-b296-d7a2f79af002.jsonl"},"uuid":"f85e4624-4151-4749-9da5-af54060de4d0","timestamp":"2026-03-04T15:29:45.120Z","planContent":"# Consolidate buildQueries / Scope Transformation Logic\n\n## Context\n\n`pkg/metricstore/query.go` (InternalMetricStore) and `internal/metricstoreclient/cc-metric-store-queries.go` (CCMetricStore) both implement the `MetricDataRepository` interface. They contain nearly identical scope-transformation logic for building metric queries, but the code has diverged:\n\n- **metricstoreclient** has the cleaner design: a standalone `buildScopeQueries()` function handling all transformations\n- **metricstore** has the same logic inlined as a long if-chain inside `buildQueries()` and duplicated in `buildNodeQueries()`\n- **metricstore is missing** the `MemoryDomain → Socket` transformation that metricstoreclient has\n- Both packages duplicate scope string constants, `intToStringSlice`, and `sanitizeStats`\n\nGoal: Extract shared scope-transformation logic, synchronize behavior, and eliminate duplication.\n\n## Approach\n\nExtract `BuildScopeQueries` as a shared exported function in `pkg/metricstore/` (since metricstoreclient already imports it). Return a package-independent intermediate type (`ScopeQueryResult`) that each package converts to its own `APIQuery` — this avoids coupling the two different `APIQuery` types (they differ in `Resolution` type: `int64` vs `int`, and internal has `ScaleFactor`).\n\n## Steps\n\n### 1. Create `pkg/metricstore/scopequery.go`\n\nNew file containing:\n\n- **`ScopeQueryResult`** struct — intermediate type with fields: `Metric`, `Hostname`, `Aggregate`, `Type *string`, `TypeIds []string`, `Scope schema.MetricScope` (no Resolution — callers set it)\n- **`BuildScopeQueries()`** — exported function ported from `metricstoreclient/buildScopeQueries()` (lines 257-517), returning `([]ScopeQueryResult, error)`. Returns empty slice for expected exceptions, error for unhandled cases\n- **Scope string constants** — `HWThreadString`, `CoreString`, `MemoryDomainString`, `SocketString`, `AcceleratorString` (exported, move from both packages)\n- **`IntToStringSlice()`** — exported, using the optimized buffer-reuse version from metricstore\n- **`SanitizeStats(avg, min, max *schema.Float)`** — exported, using the metricstoreclient behavior (zero ALL if ANY is NaN)\n\n### 2. Update `pkg/metricstore/query.go`\n\n- Replace inline if-chain in `buildQueries()` (lines 317-534) with call to `BuildScopeQueries()`, converting each `ScopeQueryResult` → local `APIQuery` (adding `Resolution`)\n- Replace inline if-chain in `buildNodeQueries()` (lines 1099-1316) with same pattern\n- Delete local scope string constants, `intToStringSlice`, local `sanitizeStats`\n- Update `sanitizeStats` calls in `LoadData`/`LoadScopedStats`/`LoadNodeData`/`LoadNodeListData` to use `SanitizeStats(&res.Avg, &res.Min, &res.Max)`\n- Switch scope dedup from `map[schema.MetricScope]bool` to labeled-loop + slice (matches metricstoreclient, avoids allocation for typical 1-3 scopes)\n- This **adds the missing MemoryDomain → Socket transformation** to the internal store\n\n### 3. Update `internal/metricstoreclient/cc-metric-store-queries.go`\n\n- Replace call to local `buildScopeQueries()` with `metricstore.BuildScopeQueries()`, converting each `ScopeQueryResult` → local `APIQuery` (adding `Resolution`)\n- Delete local `buildScopeQueries()` function\n- Delete local scope string constants and `intToStringSlice`\n- Update `sanitizeStats` in `cc-metric-store.go` to call `metricstore.SanitizeStats()`\n\n### 4. Add tests: `pkg/metricstore/scopequery_test.go`\n\nTable-driven tests for `BuildScopeQueries` covering all transformation cases:\n- Same-scope (HWThread→HWThread, Core→Core, Socket→Socket, Node→Node, etc.)\n- Aggregation (HWThread→Core, HWThread→Socket, HWThread→Node, Core→Socket, Core→Node, etc.)\n- Accelerator cases (Accelerator→Accelerator, Accelerator→Node)\n- MemoryDomain cases including MemoryDomain→Socket\n- Unhandled case returns error\n\n## Files Modified\n\n| File | Action |\n|------|--------|\n| `pkg/metricstore/scopequery.go` | **New** — shared types and functions |\n| `pkg/metricstore/scopequery_test.go` | **New** — tests for BuildScopeQueries |\n| `pkg/metricstore/query.go` | Refactor buildQueries/buildNodeQueries to use BuildScopeQueries; remove duplicated helpers |\n| `internal/metricstoreclient/cc-metric-store-queries.go` | Replace local buildScopeQueries with shared; remove duplicated helpers |\n| `internal/metricstoreclient/cc-metric-store.go` | Update sanitizeStats to use shared SanitizeStats |\n\n## What is NOT shared (intentionally)\n\n- **`APIQuery`/`APIMetricData` types** — different Resolution types, Data types, ScaleFactor field\n- **`buildQueries`/`buildNodeQueries` themselves** — different topology access (caching vs inline), different receiver types\n- **Load* result-processing functions** — depend on package-specific types and fetch mechanisms\n\n## Verification\n\n1. `go build ./...` — compile check\n2. `go test ./pkg/metricstore/...` — existing + new scopequery tests\n3. `go test ./internal/metricstoreclient/...` — compile check\n4. `make test` — full test suite\n"}
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{"parentUuid":"f991a479-b5bd-40bf-9aee-9c147f709d46","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LaKRsqFSZMgmFNEZHfjkP4","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// Package metricstoreclient - Query Building\n 7→//\n 8→// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n 9→// It handles the complex mapping between requested metric scopes and native hardware topology,\n 10→// automatically aggregating or filtering metrics as needed.\n 11→//\n 12→// # Scope Transformations\n 13→//\n 14→// The buildScopeQueries function implements the core scope transformation algorithm.\n 15→// It handles 25+ different transformation cases, mapping between:\n 16→// - Accelerator (GPU) scope\n 17→// - HWThread (hardware thread/SMT) scope\n 18→// - Core (CPU core) scope\n 19→// - Socket (CPU package) scope\n 20→// - MemoryDomain (NUMA domain) scope\n 21→// - Node (full system) scope\n 22→//\n 23→// Transformations follow these rules:\n 24→// - Same scope: Return data as-is (e.g., Core → Core)\n 25→// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n 26→// - Finer scope: Error - cannot increase granularity\n 27→//\n 28→// # Query Building\n 29→//\n 30→// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n 31→// and node-specific query construction respectively. They:\n 32→// - Validate metric configurations\n 33→// - Handle subcluster-specific metric filtering\n 34→// - Detect and skip duplicate scope requests\n 35→// - Call buildScopeQueries for each metric/scope/host combination\n 36→package metricstoreclient\n 37→\n 38→import (\n 39→\t\"fmt\"\n 40→\t\"strconv\"\n 41→\n 42→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 43→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 44→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 45→)\n 46→\n 47→// Scope string constants used in API queries.\n 48→// Pre-converted to avoid repeated allocations during query building.\n 49→var (\n 50→\thwthreadString = string(schema.MetricScopeHWThread)\n 51→\tcoreString = string(schema.MetricScopeCore)\n 52→\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n 53→\tsocketString = string(schema.MetricScopeSocket)\n 54→\tacceleratorString = string(schema.MetricScopeAccelerator)\n 55→)\n 56→\n 57→// buildQueries constructs API queries for job-specific metric data.\n 58→// It iterates through metrics, scopes, and job resources to build the complete query set.\n 59→//\n 60→// The function handles:\n 61→// - Metric configuration validation and subcluster filtering\n 62→// - Scope deduplication to avoid redundant queries\n 63→// - Hardware thread list resolution (job-allocated vs full node)\n 64→// - Delegation to buildScopeQueries for scope transformations\n 65→//\n 66→// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\n 67→func (ccms *CCMetricStore) buildQueries(\n 68→\tjob *schema.Job,\n 69→\tmetrics []string,\n 70→\tscopes []schema.MetricScope,\n 71→\tresolution int,\n 72→) ([]APIQuery, []schema.MetricScope, error) {\n 73→\t// Initialize both slices together\n 74→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n 75→\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n 76→\n 77→\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n 78→\tif err != nil {\n 79→\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n 80→\t\treturn nil, nil, err\n 81→\t}\n 82→\n 83→\tfor _, metric := range metrics {\n 84→\t\tremoteName := metric\n 85→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 86→\t\tif mc == nil {\n 87→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n 88→\t\t\tcontinue\n 89→\t\t}\n 90→\n 91→\t\t// Skip if metric is removed for subcluster\n 92→\t\tif len(mc.SubClusters) != 0 {\n 93→\t\t\tisRemoved := false\n 94→\t\t\tfor _, scConfig := range mc.SubClusters {\n 95→\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n 96→\t\t\t\t\tisRemoved = true\n 97→\t\t\t\t\tbreak\n 98→\t\t\t\t}\n 99→\t\t\t}\n 100→\t\t\tif isRemoved {\n 101→\t\t\t\tcontinue\n 102→\t\t\t}\n 103→\t\t}\n 104→\n 105→\t\t// Avoid duplicates...\n 106→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 107→\n 108→\tscopesLoop:\n 109→\t\tfor _, requestedScope := range scopes {\n 110→\t\t\tnativeScope := mc.Scope\n 111→\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n 112→\t\t\t\tcontinue\n 113→\t\t\t}\n 114→\n 115→\t\t\tscope := nativeScope.Max(requestedScope)\n 116→\t\t\tfor _, s := range handledScopes {\n 117→\t\t\t\tif scope == s {\n 118→\t\t\t\t\tcontinue scopesLoop\n 119→\t\t\t\t}\n 120→\t\t\t}\n 121→\t\t\thandledScopes = append(handledScopes, scope)\n 122→\n 123→\t\t\tfor _, host := range job.Resources {\n 124→\t\t\t\thwthreads := host.HWThreads\n 125→\t\t\t\tif hwthreads == nil {\n 126→\t\t\t\t\thwthreads = topology.Node\n 127→\t\t\t\t}\n 128→\n 129→\t\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n 130→\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n 131→\t\t\t\t\tnativeScope, requestedScope,\n 132→\t\t\t\t\tremoteName, host.Hostname,\n 133→\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n 134→\t\t\t\t\tresolution,\n 135→\t\t\t\t)\n 136→\n 137→\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n 138→\t\t\t\tif hostQueries == nil && hostScopes == nil {\n 139→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 140→\t\t\t\t}\n 141→\n 142→\t\t\t\tqueries = append(queries, hostQueries...)\n 143→\t\t\t\tassignedScope = append(assignedScope, hostScopes...)\n 144→\t\t\t}\n 145→\t\t}\n 146→\t}\n 147→\n 148→\treturn queries, assignedScope, nil\n 149→}\n 150→\n 151→// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n 152→// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n 153→//\n 154→// The function handles:\n 155→// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n 156→// - Full node hardware thread lists (not job-specific subsets)\n 157→// - All accelerators on each node\n 158→// - Metric configuration validation with subcluster filtering\n 159→//\n 160→// Returns queries and their corresponding assigned scopes.\n 161→func (ccms *CCMetricStore) buildNodeQueries(\n 162→\tcluster string,\n 163→\tsubCluster string,\n 164→\tnodes []string,\n 165→\tmetrics []string,\n 166→\tscopes []schema.MetricScope,\n 167→\tresolution int,\n 168→) ([]APIQuery, []schema.MetricScope, error) {\n 169→\t// Initialize both slices together\n 170→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n 171→\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n 172→\n 173→\tfor _, metric := range metrics {\n 174→\t\tremoteName := metric\n 175→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 176→\t\tif mc == nil {\n 177→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n 178→\t\t\tcontinue\n 179→\t\t}\n 180→\n 181→\t\t// Skip if metric is removed for subcluster\n 182→\t\tif mc.SubClusters != nil {\n 183→\t\t\tisRemoved := false\n 184→\t\t\tfor _, scConfig := range mc.SubClusters {\n 185→\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n 186→\t\t\t\t\tisRemoved = true\n 187→\t\t\t\t\tbreak\n 188→\t\t\t\t}\n 189→\t\t\t}\n 190→\t\t\tif isRemoved {\n 191→\t\t\t\tcontinue\n 192→\t\t\t}\n 193→\t\t}\n 194→\n 195→\t\t// Avoid duplicates...\n 196→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 197→\n 198→\tscopesLoop:\n 199→\t\tfor _, requestedScope := range scopes {\n 200→\t\t\tnativeScope := mc.Scope\n 201→\n 202→\t\t\tscope := nativeScope.Max(requestedScope)\n 203→\t\t\tfor _, s := range handledScopes {\n 204→\t\t\t\tif scope == s {\n 205→\t\t\t\t\tcontinue scopesLoop\n 206→\t\t\t\t}\n 207→\t\t\t}\n 208→\t\t\thandledScopes = append(handledScopes, scope)\n 209→\n 210→\t\t\tfor _, hostname := range nodes {\n 211→\t\t\t\tvar topology *schema.Topology\n 212→\t\t\t\tvar err error\n 213→\n 214→\t\t\t\t// If no subCluster given, get it by node\n 215→\t\t\t\tif subCluster == \"\" {\n 216→\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n 217→\t\t\t\t} else {\n 218→\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n 219→\t\t\t\t}\n 220→\n 221→\t\t\t\tif err != nil {\n 222→\t\t\t\t\treturn nil, nil, err\n 223→\t\t\t\t}\n 224→\n 225→\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n 226→\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n 227→\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n 228→\n 229→\t\t\t\t// Moved check here if metric matches hardware specs\n 230→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n 231→\t\t\t\t\tcontinue scopesLoop\n 232→\t\t\t\t}\n 233→\n 234→\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n 235→\t\t\t\t\tnativeScope, requestedScope,\n 236→\t\t\t\t\tremoteName, hostname,\n 237→\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n 238→\t\t\t\t\tresolution,\n 239→\t\t\t\t)\n 240→\n 241→\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n 242→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 243→\t\t\t\t}\n 244→\n 245→\t\t\t\tqueries = append(queries, nodeQueries...)\n 246→\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n 247→\t\t\t}\n 248→\t\t}\n 249→\t}\n 250→\n 251→\treturn queries, assignedScope, nil\n 252→}\n 253→\n 254→// buildScopeQueries generates API queries for a given scope transformation.\n 255→// It returns a slice of queries and corresponding assigned scopes.\n 256→// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\n 257→func buildScopeQueries(\n 258→\tnativeScope, requestedScope schema.MetricScope,\n 259→\tmetric, hostname string,\n 260→\ttopology *schema.Topology,\n 261→\thwthreads []int,\n 262→\taccelerators []string,\n 263→\tresolution int,\n 264→) ([]APIQuery, []schema.MetricScope) {\n 265→\tscope := nativeScope.Max(requestedScope)\n 266→\tqueries := []APIQuery{}\n 267→\tscopes := []schema.MetricScope{}\n 268→\n 269→\thwthreadsStr := intToStringSlice(hwthreads)\n 270→\n 271→\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n 272→\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n 273→\t\tif scope != schema.MetricScopeAccelerator {\n 274→\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n 275→\t\t\treturn queries, scopes\n 276→\t\t}\n 277→\n 278→\t\tqueries = append(queries, APIQuery{\n 279→\t\t\tMetric: metric,\n 280→\t\t\tHostname: hostname,\n 281→\t\t\tAggregate: false,\n 282→\t\t\tType: &acceleratorString,\n 283→\t\t\tTypeIds: accelerators,\n 284→\t\t\tResolution: resolution,\n 285→\t\t})\n 286→\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n 287→\t\treturn queries, scopes\n 288→\t}\n 289→\n 290→\t// Accelerator -> Node\n 291→\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n 292→\t\tif len(accelerators) == 0 {\n 293→\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n 294→\t\t\treturn queries, scopes\n 295→\t\t}\n 296→\n 297→\t\tqueries = append(queries, APIQuery{\n 298→\t\t\tMetric: metric,\n 299→\t\t\tHostname: hostname,\n 300→\t\t\tAggregate: true,\n 301→\t\t\tType: &acceleratorString,\n 302→\t\t\tTypeIds: accelerators,\n 303→\t\t\tResolution: resolution,\n 304→\t\t})\n 305→\t\tscopes = append(scopes, scope)\n 306→\t\treturn queries, scopes\n 307→\t}\n 308→\n 309→\t// HWThread -> HWThread\n 310→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n 311→\t\tqueries = append(queries, APIQuery{\n 312→\t\t\tMetric: metric,\n 313→\t\t\tHostname: hostname,\n 314→\t\t\tAggregate: false,\n 315→\t\t\tType: &hwthreadString,\n 316→\t\t\tTypeIds: hwthreadsStr,\n 317→\t\t\tResolution: resolution,\n 318→\t\t})\n 319→\t\tscopes = append(scopes, scope)\n 320→\t\treturn queries, scopes\n 321→\t}\n 322→\n 323→\t// HWThread -> Core\n 324→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n 325→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 326→\t\tfor _, core := range cores {\n 327→\t\t\tqueries = append(queries, APIQuery{\n 328→\t\t\t\tMetric: metric,\n 329→\t\t\t\tHostname: hostname,\n 330→\t\t\t\tAggregate: true,\n 331→\t\t\t\tType: &hwthreadString,\n 332→\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n 333→\t\t\t\tResolution: resolution,\n 334→\t\t\t})\n 335→\t\t\tscopes = append(scopes, scope)\n 336→\t\t}\n 337→\t\treturn queries, scopes\n 338→\t}\n 339→\n 340→\t// HWThread -> Socket\n 341→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n 342→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 343→\t\tfor _, socket := range sockets {\n 344→\t\t\tqueries = append(queries, APIQuery{\n 345→\t\t\t\tMetric: metric,\n 346→\t\t\t\tHostname: hostname,\n 347→\t\t\t\tAggregate: true,\n 348→\t\t\t\tType: &hwthreadString,\n 349→\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 350→\t\t\t\tResolution: resolution,\n 351→\t\t\t})\n 352→\t\t\tscopes = append(scopes, scope)\n 353→\t\t}\n 354→\t\treturn queries, scopes\n 355→\t}\n 356→\n 357→\t// HWThread -> Node\n 358→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n 359→\t\tqueries = append(queries, APIQuery{\n 360→\t\t\tMetric: metric,\n 361→\t\t\tHostname: hostname,\n 362→\t\t\tAggregate: true,\n 363→\t\t\tType: &hwthreadString,\n 364→\t\t\tTypeIds: hwthreadsStr,\n 365→\t\t\tResolution: resolution,\n 366→\t\t})\n 367→\t\tscopes = append(scopes, scope)\n 368→\t\treturn queries, scopes\n 369→\t}\n 370→\n 371→\t// Core -> Core\n 372→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n 373→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 374→\t\tqueries = append(queries, APIQuery{\n 375→\t\t\tMetric: metric,\n 376→\t\t\tHostname: hostname,\n 377→\t\t\tAggregate: false,\n 378→\t\t\tType: &coreString,\n 379→\t\t\tTypeIds: intToStringSlice(cores),\n 380→\t\t\tResolution: resolution,\n 381→\t\t})\n 382→\t\tscopes = append(scopes, scope)\n 383→\t\treturn queries, scopes\n 384→\t}\n 385→\n 386→\t// Core -> Socket\n 387→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n 388→\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n 389→\t\tfor _, socket := range sockets {\n 390→\t\t\tqueries = append(queries, APIQuery{\n 391→\t\t\t\tMetric: metric,\n 392→\t\t\t\tHostname: hostname,\n 393→\t\t\t\tAggregate: true,\n 394→\t\t\t\tType: &coreString,\n 395→\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 396→\t\t\t\tResolution: resolution,\n 397→\t\t\t})\n 398→\t\t\tscopes = append(scopes, scope)\n 399→\t\t}\n 400→\t\treturn queries, scopes\n 401→\t}\n 402→\n 403→\t// Core -> Node\n 404→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n 405→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 406→\t\tqueries = append(queries, APIQuery{\n 407→\t\t\tMetric: metric,\n 408→\t\t\tHostname: hostname,\n 409→\t\t\tAggregate: true,\n 410→\t\t\tType: &coreString,\n 411→\t\t\tTypeIds: intToStringSlice(cores),\n 412→\t\t\tResolution: resolution,\n 413→\t\t})\n 414→\t\tscopes = append(scopes, scope)\n 415→\t\treturn queries, scopes\n 416→\t}\n 417→\n 418→\t// MemoryDomain -> MemoryDomain\n 419→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n 420→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 421→\t\tqueries = append(queries, APIQuery{\n 422→\t\t\tMetric: metric,\n 423→\t\t\tHostname: hostname,\n 424→\t\t\tAggregate: false,\n 425→\t\t\tType: &memoryDomainString,\n 426→\t\t\tTypeIds: intToStringSlice(memDomains),\n 427→\t\t\tResolution: resolution,\n 428→\t\t})\n 429→\t\tscopes = append(scopes, scope)\n 430→\t\treturn queries, scopes\n 431→\t}\n 432→\n 433→\t// MemoryDomain -> Node\n 434→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n 435→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 436→\t\tqueries = append(queries, APIQuery{\n 437→\t\t\tMetric: metric,\n 438→\t\t\tHostname: hostname,\n 439→\t\t\tAggregate: true,\n 440→\t\t\tType: &memoryDomainString,\n 441→\t\t\tTypeIds: intToStringSlice(memDomains),\n 442→\t\t\tResolution: resolution,\n 443→\t\t})\n 444→\t\tscopes = append(scopes, scope)\n 445→\t\treturn queries, scopes\n 446→\t}\n 447→\n 448→\t// MemoryDomain -> Socket\n 449→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n 450→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 451→\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n 452→\t\tif err != nil {\n 453→\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n 454→\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n 455→\t\t\treturn queries, scopes\n 456→\t\t}\n 457→\n 458→\t\t// Create a query for each socket\n 459→\t\tfor _, domains := range socketToDomains {\n 460→\t\t\tqueries = append(queries, APIQuery{\n 461→\t\t\t\tMetric: metric,\n 462→\t\t\t\tHostname: hostname,\n 463→\t\t\t\tAggregate: true,\n 464→\t\t\t\tType: &memoryDomainString,\n 465→\t\t\t\tTypeIds: intToStringSlice(domains),\n 466→\t\t\t\tResolution: resolution,\n 467→\t\t\t})\n 468→\t\t\t// Add scope for each query, not just once\n 469→\t\t\tscopes = append(scopes, scope)\n 470→\t\t}\n 471→\t\treturn queries, scopes\n 472→\t}\n 473→\n 474→\t// Socket -> Socket\n 475→\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n 476→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 477→\t\tqueries = append(queries, APIQuery{\n 478→\t\t\tMetric: metric,\n 479→\t\t\tHostname: hostname,\n 480→\t\t\tAggregate: false,\n 481→\t\t\tType: &socketString,\n 482→\t\t\tTypeIds: intToStringSlice(sockets),\n 483→\t\t\tResolution: resolution,\n 484→\t\t})\n 485→\t\tscopes = append(scopes, scope)\n 486→\t\treturn queries, scopes\n 487→\t}\n 488→\n 489→\t// Socket -> Node\n 490→\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n 491→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 492→\t\tqueries = append(queries, APIQuery{\n 493→\t\t\tMetric: metric,\n 494→\t\t\tHostname: hostname,\n 495→\t\t\tAggregate: true,\n 496→\t\t\tType: &socketString,\n 497→\t\t\tTypeIds: intToStringSlice(sockets),\n 498→\t\t\tResolution: resolution,\n 499→\t\t})\n 500→\t\tscopes = append(scopes, scope)\n 501→\t\treturn queries, scopes\n 502→\t}\n 503→\n 504→\t// Node -> Node\n 505→\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n 506→\t\tqueries = append(queries, APIQuery{\n 507→\t\t\tMetric: metric,\n 508→\t\t\tHostname: hostname,\n 509→\t\t\tResolution: resolution,\n 510→\t\t})\n 511→\t\tscopes = append(scopes, scope)\n 512→\t\treturn queries, scopes\n 513→\t}\n 514→\n 515→\t// Unhandled Case -> Error -> Return nils\n 516→\treturn nil, nil\n 517→}\n 518→\n 519→// intToStringSlice converts a slice of integers to a slice of strings.\n 520→// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\n 521→func intToStringSlice(is []int) []string {\n 522→\tss := make([]string, len(is))\n 523→\tfor i, x := range is {\n 524→\t\tss[i] = strconv.Itoa(x)\n 525→\t}\n 526→\treturn ss\n 527→}\n 528→"}]},"uuid":"b300b54a-c227-445b-aa9c-c9b4ff633bc2","timestamp":"2026-03-04T15:29:49.582Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\t\"strconv\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Scope string constants used in API queries.\n// Pre-converted to avoid repeated allocations during query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","numLines":528,"startLine":1,"totalLines":528}},"sourceToolAssistantUUID":"f991a479-b5bd-40bf-9aee-9c147f709d46"}
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{"parentUuid":"3b03e981-d2cc-48dd-b90d-a42e2a065bd4","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013RKvera1zE5WTk8Cut1cxk","type":"tool_result","content":"<persisted-output>\nOutput too large (50.6KB). Full output saved to: /Users/jan/.claude/projects/-Users-jan-prg-ClusterCockpit-cc-backend/5de2a23c-09cd-4d6c-a97c-fab8657d094c/tool-results/toolu_013RKvera1zE5WTk8Cut1cxk.txt\n\nPreview (first 2KB):\n 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// This file implements high-level query functions for loading job metric data\n 7→// with automatic scope transformation and aggregation.\n 8→//\n 9→// Key Concepts:\n 10→//\n 11→// Metric Scopes: Metrics are collected at different granularities (native scope):\n 12→// - HWThread: Per hardware thread\n 13→// - Core: Per CPU core\n 14→// - Socket: Per CPU socket\n 15→// - MemoryDomain: Per memory domain (NUMA)\n 16→// - Accelerator: Per GPU/accelerator\n 17→// - Node: Per compute node\n 18→//\n 19→// Scope Transformation: The buildQueries functions transform between native scope\n 20→// and requested scope by:\n 21→// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n 22→// - Rejecting requests for finer granularity than available\n 23→// - Handling special cases (e.g., Accelerator metrics)\n 24→//\n 25→// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n 26→// based on cluster topology and job resources.\n 27→package metricstore\n 28→\n 29→import (\n 30→\t\"context\"\n 31→\t\"fmt\"\n 32→\t\"strconv\"\n 33→\t\"strings\"\n 34→\t\"time\"\n 35→\n 36→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 37→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 38→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 39→)\n 40→\n 41→type InternalMetricStore struct{}\n 42→\n 43→var MetricStoreHandle *InternalMetricStore\n 44→\n 45→// HealthCheck delegates to the internal MemoryStore's HealthCheck.\n 46→func (ccms *InternalMetricStore) HealthCheck(cluster string,\n 47→\tnodes []string, metrics []string,\n 48→) (map[string]HealthCheckResult, error) {\n...\n</persisted-output>"}]},"uuid":"5b2742d6-e26f-4dd9-80f3-7e7ba692f4a0","timestamp":"2026-03-04T15:29:50.311Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strconv\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","numLines":1358,"startLine":1,"totalLines":1358}},"sourceToolAssistantUUID":"3b03e981-d2cc-48dd-b90d-a42e2a065bd4"}
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{"parentUuid":"ea3a8f6b-4b1e-40c3-be4f-7108bea58889","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DQyo1Mofg5wodzgGtgZKSh","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n 7→//\n 8→// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n 9→// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n 10→// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n 11→//\n 12→// # Architecture\n 13→//\n 14→// The package is split into two main components:\n 15→// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n 16→// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n 17→//\n 18→// # Basic Usage\n 19→//\n 20→//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n 21→//\n 22→//\t// Load job data\n 23→//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n 24→//\tif err != nil {\n 25→//\t log.Fatal(err)\n 26→//\t}\n 27→//\n 28→// # Metric Scopes\n 29→//\n 30→// The client supports hierarchical metric scopes that map to HPC hardware topology:\n 31→// - MetricScopeAccelerator: GPU/accelerator level metrics\n 32→// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n 33→// - MetricScopeCore: CPU core level metrics\n 34→// - MetricScopeSocket: CPU socket level metrics\n 35→// - MetricScopeMemoryDomain: NUMA domain level metrics\n 36→// - MetricScopeNode: Full node level metrics\n 37→//\n 38→// The client automatically handles scope transformations, aggregating finer-grained metrics\n 39→// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n 40→//\n 41→// # Error Handling\n 42→//\n 43→// The client supports partial errors - if some queries fail, it returns both the successful\n 44→// data and an error listing the failed queries. This allows processing partial results\n 45→// when some nodes or metrics are temporarily unavailable.\n 46→//\n 47→// # API Versioning\n 48→//\n 49→// The client uses cc-metric-store API v2, which includes support for:\n 50→// - Data resampling for bandwidth optimization\n 51→// - Multi-scope queries in a single request\n 52→// - Aggregation across hardware topology levels\n 53→package metricstoreclient\n 54→\n 55→import (\n 56→\t\"bufio\"\n 57→\t\"bytes\"\n 58→\t\"context\"\n 59→\t\"encoding/json\"\n 60→\t\"fmt\"\n 61→\t\"net/http\"\n 62→\t\"strings\"\n 63→\t\"time\"\n 64→\n 65→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 66→\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n 67→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 68→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 69→)\n 70→\n 71→// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n 72→// It manages connection details, authentication, and provides methods for querying metrics.\n 73→type CCMetricStore struct {\n 74→\tclient http.Client // HTTP client with 10-second timeout\n 75→\tjwt string // JWT Bearer token for authentication\n 76→\turl string // Base URL of cc-metric-store instance\n 77→\tqueryEndpoint string // Full URL to query API endpoint\n 78→\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n 79→}\n 80→\n 81→// APIQueryRequest represents a request to the cc-metric-store query API.\n 82→// It supports both explicit queries and \"for-all-nodes\" bulk queries.\n 83→type APIQueryRequest struct {\n 84→\tCluster string `json:\"cluster\"` // Target cluster name\n 85→\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n 86→\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n 87→\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n 88→\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n 89→\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n 90→\tWithData bool `json:\"with-data\"` // Include time series data points\n 91→}\n 92→\n 93→// APIQuery specifies a single metric query with optional scope filtering.\n 94→// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\n 95→type APIQuery struct {\n 96→\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n 97→\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n 98→\tMetric string `json:\"metric\"` // Metric name\n 99→\tHostname string `json:\"host\"` // Target hostname\n 100→\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n 101→\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n 102→\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n 103→\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n 104→}\n 105→\n 106→// APIQueryResponse contains the results from a cc-metric-store query.\n 107→// Results align with the Queries slice by index.\n 108→type APIQueryResponse struct {\n 109→\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n 110→\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n 111→}\n 112→\n 113→// APIMetricData represents time series data and statistics for a single metric series.\n 114→// Error is set if this particular series failed to load.\n 115→type APIMetricData struct {\n 116→\tError *string `json:\"error\"` // Error message if query failed\n 117→\tData []schema.Float `json:\"data\"` // Time series data points\n 118→\tFrom int64 `json:\"from\"` // Actual start time of data\n 119→\tTo int64 `json:\"to\"` // Actual end time of data\n 120→\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n 121→\tAvg schema.Float `json:\"avg\"` // Average value across time range\n 122→\tMin schema.Float `json:\"min\"` // Minimum value in time range\n 123→\tMax schema.Float `json:\"max\"` // Maximum value in time range\n 124→}\n 125→\n 126→// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n 127→// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n 128→// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\n 129→func NewCCMetricStore(url string, token string) *CCMetricStore {\n 130→\treturn &CCMetricStore{\n 131→\t\turl: url,\n 132→\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n 133→\t\tjwt: token,\n 134→\t\tclient: http.Client{\n 135→\t\t\tTimeout: 10 * time.Second,\n 136→\t\t},\n 137→\t\ttopologyCache: make(map[string]*schema.Topology),\n 138→\t}\n 139→}\n 140→\n 141→// doRequest executes an HTTP POST request to the cc-metric-store query API.\n 142→// It handles JSON encoding/decoding, authentication, and API versioning.\n 143→// The request body is automatically closed to prevent resource leaks.\n 144→func (ccms *CCMetricStore) doRequest(\n 145→\tctx context.Context,\n 146→\tbody *APIQueryRequest,\n 147→) (*APIQueryResponse, error) {\n 148→\tbuf := &bytes.Buffer{}\n 149→\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n 150→\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n 151→\t\treturn nil, err\n 152→\t}\n 153→\n 154→\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n 155→\tif err != nil {\n 156→\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n 157→\t\treturn nil, err\n 158→\t}\n 159→\tif ccms.jwt != \"\" {\n 160→\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n 161→\t}\n 162→\n 163→\t// versioning the cc-metric-store query API.\n 164→\t// v2 = data with resampling\n 165→\t// v1 = data without resampling\n 166→\tq := req.URL.Query()\n 167→\tq.Add(\"version\", \"v2\")\n 168→\treq.URL.RawQuery = q.Encode()\n 169→\n 170→\tres, err := ccms.client.Do(req)\n 171→\tif err != nil {\n 172→\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n 173→\t\treturn nil, err\n 174→\t}\n 175→\tdefer res.Body.Close()\n 176→\n 177→\tif res.StatusCode != http.StatusOK {\n 178→\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n 179→\t}\n 180→\n 181→\tvar resBody APIQueryResponse\n 182→\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n 183→\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n 184→\t\treturn nil, err\n 185→\t}\n 186→\n 187→\treturn &resBody, nil\n 188→}\n 189→\n 190→// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\n 191→func (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n 192→\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n 193→\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n 194→\t\treturn topology, nil\n 195→\t}\n 196→\n 197→\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n 198→\tif err != nil {\n 199→\t\treturn nil, err\n 200→\t}\n 201→\n 202→\tccms.topologyCache[cacheKey] = &subcluster.Topology\n 203→\treturn &subcluster.Topology, nil\n 204→}\n 205→\n 206→// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\n 207→func (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n 208→\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n 209→\tif err != nil {\n 210→\t\treturn nil, err\n 211→\t}\n 212→\n 213→\treturn ccms.getTopology(cluster, subCluster)\n 214→}\n 215→\n 216→// LoadData retrieves time series data and statistics for the specified job and metrics.\n 217→// It queries data for the job's time range and resources, handling scope transformations automatically.\n 218→//\n 219→// Parameters:\n 220→// - job: Job metadata including cluster, time range, and allocated resources\n 221→// - metrics: List of metric names to retrieve\n 222→// - scopes: Requested metric scopes (node, socket, core, etc.)\n 223→// - ctx: Context for cancellation and timeouts\n 224→// - resolution: Data resolution in seconds (0 for native resolution)\n 225→//\n 226→// Returns JobData organized as: metric -> scope -> series list.\n 227→// Supports partial errors: returns available data even if some queries fail.\n 228→func (ccms *CCMetricStore) LoadData(\n 229→\tjob *schema.Job,\n 230→\tmetrics []string,\n 231→\tscopes []schema.MetricScope,\n 232→\tctx context.Context,\n 233→\tresolution int,\n 234→) (schema.JobData, error) {\n 235→\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n 236→\tif err != nil {\n 237→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 238→\t\treturn nil, err\n 239→\t}\n 240→\n 241→\t// Verify assignment is correct - log any inconsistencies for debugging\n 242→\tif len(queries) != len(assignedScope) {\n 243→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n 244→\t\t\tlen(queries), len(assignedScope))\n 245→\t}\n 246→\n 247→\treq := APIQueryRequest{\n 248→\t\tCluster: job.Cluster,\n 249→\t\tFrom: job.StartTime,\n 250→\t\tTo: job.StartTime + int64(job.Duration),\n 251→\t\tQueries: queries,\n 252→\t\tWithStats: true,\n 253→\t\tWithData: true,\n 254→\t}\n 255→\n 256→\tresBody, err := ccms.doRequest(ctx, &req)\n 257→\tif err != nil {\n 258→\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n 259→\t\treturn nil, err\n 260→\t}\n 261→\n 262→\tvar errors []string\n 263→\tjobData := make(schema.JobData)\n 264→\n 265→\t// Add safety check for potential index out of range errors\n 266→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 267→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 268→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 269→\t\tif len(resBody.Results) > len(req.Queries) {\n 270→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 271→\t\t}\n 272→\t\tif len(assignedScope) > len(req.Queries) {\n 273→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 274→\t\t}\n 275→\t}\n 276→\n 277→\tfor i, row := range resBody.Results {\n 278→\t\t// Safety check to prevent index out of range errors\n 279→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 280→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 281→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 282→\t\t\tcontinue\n 283→\t\t}\n 284→\n 285→\t\tquery := req.Queries[i]\n 286→\t\tmetric := query.Metric\n 287→\t\tscope := assignedScope[i]\n 288→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 289→\n 290→\t\tif mc == nil {\n 291→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n 292→\t\t\tcontinue\n 293→\t\t}\n 294→\n 295→\t\tif _, ok := jobData[metric]; !ok {\n 296→\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n 297→\t\t}\n 298→\n 299→\t\tres := mc.Timestep\n 300→\t\tif len(row) > 0 {\n 301→\t\t\tres = row[0].Resolution\n 302→\t\t}\n 303→\n 304→\t\tjobMetric, ok := jobData[metric][scope]\n 305→\t\tif !ok {\n 306→\t\t\tjobMetric = &schema.JobMetric{\n 307→\t\t\t\tUnit: mc.Unit,\n 308→\t\t\t\tTimestep: res,\n 309→\t\t\t\tSeries: make([]schema.Series, 0),\n 310→\t\t\t}\n 311→\t\t\tjobData[metric][scope] = jobMetric\n 312→\t\t}\n 313→\n 314→\t\tfor ndx, res := range row {\n 315→\t\t\tif res.Error != nil {\n 316→\t\t\t\t/* Build list for \"partial errors\", if any */\n 317→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 318→\t\t\t\tcontinue\n 319→\t\t\t}\n 320→\n 321→\t\t\tid := (*string)(nil)\n 322→\t\t\tif query.Type != nil {\n 323→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 324→\t\t\t\tif ndx < len(query.TypeIds) {\n 325→\t\t\t\t\tid = new(string)\n 326→\t\t\t\t\t*id = query.TypeIds[ndx]\n 327→\t\t\t\t} else {\n 328→\t\t\t\t\t// Log the error but continue processing\n 329→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 330→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 331→\t\t\t\t}\n 332→\t\t\t}\n 333→\n 334→\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n 335→\n 336→\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n 337→\t\t\t\tHostname: query.Hostname,\n 338→\t\t\t\tID: id,\n 339→\t\t\t\tStatistics: schema.MetricStatistics{\n 340→\t\t\t\t\tAvg: float64(res.Avg),\n 341→\t\t\t\t\tMin: float64(res.Min),\n 342→\t\t\t\t\tMax: float64(res.Max),\n 343→\t\t\t\t},\n 344→\t\t\t\tData: res.Data,\n 345→\t\t\t})\n 346→\t\t}\n 347→\n 348→\t\t// So that one can later check len(jobData):\n 349→\t\tif len(jobMetric.Series) == 0 {\n 350→\t\t\tdelete(jobData[metric], scope)\n 351→\t\t\tif len(jobData[metric]) == 0 {\n 352→\t\t\t\tdelete(jobData, metric)\n 353→\t\t\t}\n 354→\t\t}\n 355→\t}\n 356→\n 357→\tif len(errors) != 0 {\n 358→\t\t/* Returns list for \"partial errors\" */\n 359→\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 360→\t}\n 361→\treturn jobData, nil\n 362→}\n 363→\n 364→// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n 365→// This is faster than LoadData when only statistical summaries are needed (no time series data).\n 366→//\n 367→// Returns statistics organized as: metric -> hostname -> statistics.\n 368→func (ccms *CCMetricStore) LoadStats(\n 369→\tjob *schema.Job,\n 370→\tmetrics []string,\n 371→\tctx context.Context,\n 372→) (map[string]map[string]schema.MetricStatistics, error) {\n 373→\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n 374→\tif err != nil {\n 375→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n 376→\t\treturn nil, err\n 377→\t}\n 378→\n 379→\treq := APIQueryRequest{\n 380→\t\tCluster: job.Cluster,\n 381→\t\tFrom: job.StartTime,\n 382→\t\tTo: job.StartTime + int64(job.Duration),\n 383→\t\tQueries: queries,\n 384→\t\tWithStats: true,\n 385→\t\tWithData: false,\n 386→\t}\n 387→\n 388→\tresBody, err := ccms.doRequest(ctx, &req)\n 389→\tif err != nil {\n 390→\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n 391→\t\treturn nil, err\n 392→\t}\n 393→\n 394→\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n 395→\tfor i, res := range resBody.Results {\n 396→\t\tif len(res) == 0 {\n 397→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 398→\t\t\tcontinue\n 399→\t\t}\n 400→\t\tquery := req.Queries[i]\n 401→\t\tmetric := query.Metric\n 402→\t\tdata := res[0]\n 403→\t\tif data.Error != nil {\n 404→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n 405→\t\t\tcontinue\n 406→\t\t}\n 407→\n 408→\t\tmetricdata, ok := stats[metric]\n 409→\t\tif !ok {\n 410→\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n 411→\t\t\tstats[metric] = metricdata\n 412→\t\t}\n 413→\n 414→\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n 415→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n 416→\t\t\tcontinue\n 417→\t\t}\n 418→\n 419→\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n 420→\t\t\tAvg: float64(data.Avg),\n 421→\t\t\tMin: float64(data.Min),\n 422→\t\t\tMax: float64(data.Max),\n 423→\t\t}\n 424→\t}\n 425→\n 426→\treturn stats, nil\n 427→}\n 428→\n 429→// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n 430→// Used for the Job-View Statistics Table to display per-scope breakdowns.\n 431→//\n 432→// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n 433→// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\n 434→func (ccms *CCMetricStore) LoadScopedStats(\n 435→\tjob *schema.Job,\n 436→\tmetrics []string,\n 437→\tscopes []schema.MetricScope,\n 438→\tctx context.Context,\n 439→) (schema.ScopedJobStats, error) {\n 440→\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n 441→\tif err != nil {\n 442→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 443→\t\treturn nil, err\n 444→\t}\n 445→\n 446→\treq := APIQueryRequest{\n 447→\t\tCluster: job.Cluster,\n 448→\t\tFrom: job.StartTime,\n 449→\t\tTo: job.StartTime + int64(job.Duration),\n 450→\t\tQueries: queries,\n 451→\t\tWithStats: true,\n 452→\t\tWithData: false,\n 453→\t}\n 454→\n 455→\tresBody, err := ccms.doRequest(ctx, &req)\n 456→\tif err != nil {\n 457→\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n 458→\t\treturn nil, err\n 459→\t}\n 460→\n 461→\tvar errors []string\n 462→\tscopedJobStats := make(schema.ScopedJobStats)\n 463→\n 464→\tfor i, row := range resBody.Results {\n 465→\t\tquery := req.Queries[i]\n 466→\t\tmetric := query.Metric\n 467→\t\tscope := assignedScope[i]\n 468→\n 469→\t\tif _, ok := scopedJobStats[metric]; !ok {\n 470→\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n 471→\t\t}\n 472→\n 473→\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n 474→\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n 475→\t\t}\n 476→\n 477→\t\tfor ndx, res := range row {\n 478→\t\t\tif res.Error != nil {\n 479→\t\t\t\t/* Build list for \"partial errors\", if any */\n 480→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 481→\t\t\t\tcontinue\n 482→\t\t\t}\n 483→\n 484→\t\t\tid := (*string)(nil)\n 485→\t\t\tif query.Type != nil {\n 486→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 487→\t\t\t\tif ndx < len(query.TypeIds) {\n 488→\t\t\t\t\tid = new(string)\n 489→\t\t\t\t\t*id = query.TypeIds[ndx]\n 490→\t\t\t\t} else {\n 491→\t\t\t\t\t// Log the error but continue processing\n 492→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 493→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 494→\t\t\t\t}\n 495→\t\t\t}\n 496→\n 497→\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n 498→\n 499→\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n 500→\t\t\t\tHostname: query.Hostname,\n 501→\t\t\t\tID: id,\n 502→\t\t\t\tData: &schema.MetricStatistics{\n 503→\t\t\t\t\tAvg: float64(res.Avg),\n 504→\t\t\t\t\tMin: float64(res.Min),\n 505→\t\t\t\t\tMax: float64(res.Max),\n 506→\t\t\t\t},\n 507→\t\t\t})\n 508→\t\t}\n 509→\n 510→\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n 511→\t\tif len(scopedJobStats[metric][scope]) == 0 {\n 512→\t\t\tdelete(scopedJobStats[metric], scope)\n 513→\t\t\tif len(scopedJobStats[metric]) == 0 {\n 514→\t\t\t\tdelete(scopedJobStats, metric)\n 515→\t\t\t}\n 516→\t\t}\n 517→\t}\n 518→\n 519→\tif len(errors) != 0 {\n 520→\t\t/* Returns list for \"partial errors\" */\n 521→\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 522→\t}\n 523→\treturn scopedJobStats, nil\n 524→}\n 525→\n 526→// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n 527→// Used for the Systems-View Node-Overview to display real-time node status.\n 528→//\n 529→// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n 530→// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\n 531→func (ccms *CCMetricStore) LoadNodeData(\n 532→\tcluster string,\n 533→\tmetrics, nodes []string,\n 534→\tscopes []schema.MetricScope,\n 535→\tfrom, to time.Time,\n 536→\tctx context.Context,\n 537→) (map[string]map[string][]*schema.JobMetric, error) {\n 538→\treq := APIQueryRequest{\n 539→\t\tCluster: cluster,\n 540→\t\tFrom: from.Unix(),\n 541→\t\tTo: to.Unix(),\n 542→\t\tWithStats: true,\n 543→\t\tWithData: true,\n 544→\t}\n 545→\n 546→\tif nodes == nil {\n 547→\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n 548→\t} else {\n 549→\t\tfor _, node := range nodes {\n 550→\t\t\tfor _, metric := range metrics {\n 551→\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n 552→\t\t\t\t\tHostname: node,\n 553→\t\t\t\t\tMetric: metric,\n 554→\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n 555→\t\t\t\t})\n 556→\t\t\t}\n 557→\t\t}\n 558→\t}\n 559→\n 560→\tresBody, err := ccms.doRequest(ctx, &req)\n 561→\tif err != nil {\n 562→\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n 563→\t\treturn nil, err\n 564→\t}\n 565→\n 566→\tvar errors []string\n 567→\tdata := make(map[string]map[string][]*schema.JobMetric)\n 568→\tfor i, res := range resBody.Results {\n 569→\t\tif len(res) == 0 {\n 570→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 571→\t\t\tcontinue\n 572→\t\t}\n 573→\n 574→\t\tvar query APIQuery\n 575→\t\tif resBody.Queries != nil {\n 576→\t\t\tquery = resBody.Queries[i]\n 577→\t\t} else {\n 578→\t\t\tquery = req.Queries[i]\n 579→\t\t}\n 580→\n 581→\t\tmetric := query.Metric\n 582→\t\tqdata := res[0]\n 583→\t\tif qdata.Error != nil {\n 584→\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n 585→\t\t}\n 586→\n 587→\t\tsanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n 588→\n 589→\t\thostdata, ok := data[query.Hostname]\n 590→\t\tif !ok {\n 591→\t\t\thostdata = make(map[string][]*schema.JobMetric)\n 592→\t\t\tdata[query.Hostname] = hostdata\n 593→\t\t}\n 594→\n 595→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 596→\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n 597→\t\t\tUnit: mc.Unit,\n 598→\t\t\tTimestep: mc.Timestep,\n 599→\t\t\tSeries: []schema.Series{\n 600→\t\t\t\t{\n 601→\t\t\t\t\tHostname: query.Hostname,\n 602→\t\t\t\t\tData: qdata.Data,\n 603→\t\t\t\t\tStatistics: schema.MetricStatistics{\n 604→\t\t\t\t\t\tAvg: float64(qdata.Avg),\n 605→\t\t\t\t\t\tMin: float64(qdata.Min),\n 606→\t\t\t\t\t\tMax: float64(qdata.Max),\n 607→\t\t\t\t\t},\n 608→\t\t\t\t},\n 609→\t\t\t},\n 610→\t\t})\n 611→\t}\n 612→\n 613→\tif len(errors) != 0 {\n 614→\t\t/* Returns list of \"partial errors\" */\n 615→\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 616→\t}\n 617→\n 618→\treturn data, nil\n 619→}\n 620→\n 621→// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n 622→//\n 623→// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n 624→// substring matching on hostnames.\n 625→//\n 626→// Returns:\n 627→// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n 628→// - Total node count (before pagination)\n 629→// - HasNextPage flag indicating if more pages are available\n 630→// - Error (may be partial error with some data returned)\n 631→func (ccms *CCMetricStore) LoadNodeListData(\n 632→\tcluster, subCluster string,\n 633→\tnodes []string,\n 634→\tmetrics []string,\n 635→\tscopes []schema.MetricScope,\n 636→\tresolution int,\n 637→\tfrom, to time.Time,\n 638→\tctx context.Context,\n 639→) (map[string]schema.JobData, error) {\n 640→\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n 641→\tif err != nil {\n 642→\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n 643→\t\treturn nil, err\n 644→\t}\n 645→\n 646→\t// Verify assignment is correct - log any inconsistencies for debugging\n 647→\tif len(queries) != len(assignedScope) {\n 648→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n 649→\t\t\tlen(queries), len(assignedScope))\n 650→\t}\n 651→\n 652→\treq := APIQueryRequest{\n 653→\t\tCluster: cluster,\n 654→\t\tQueries: queries,\n 655→\t\tFrom: from.Unix(),\n 656→\t\tTo: to.Unix(),\n 657→\t\tWithStats: true,\n 658→\t\tWithData: true,\n 659→\t}\n 660→\n 661→\tresBody, err := ccms.doRequest(ctx, &req)\n 662→\tif err != nil {\n 663→\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n 664→\t\treturn nil, err\n 665→\t}\n 666→\n 667→\tvar errors []string\n 668→\tdata := make(map[string]schema.JobData)\n 669→\n 670→\t// Add safety check for index out of range issues\n 671→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 672→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 673→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 674→\t\tif len(resBody.Results) > len(req.Queries) {\n 675→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 676→\t\t}\n 677→\t\tif len(assignedScope) > len(req.Queries) {\n 678→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 679→\t\t}\n 680→\t}\n 681→\n 682→\tfor i, row := range resBody.Results {\n 683→\t\t// Safety check to prevent index out of range errors\n 684→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 685→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 686→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 687→\t\t\tcontinue\n 688→\t\t}\n 689→\n 690→\t\tvar query APIQuery\n 691→\t\tif resBody.Queries != nil {\n 692→\t\t\tif i < len(resBody.Queries) {\n 693→\t\t\t\tquery = resBody.Queries[i]\n 694→\t\t\t} else {\n 695→\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n 696→\t\t\t\t\ti, len(resBody.Queries))\n 697→\t\t\t\tcontinue\n 698→\t\t\t}\n 699→\t\t} else {\n 700→\t\t\tquery = req.Queries[i]\n 701→\t\t}\n 702→\n 703→\t\tmetric := query.Metric\n 704→\t\tscope := assignedScope[i]\n 705→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 706→\t\tif mc == nil {\n 707→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n 708→\t\t\tcontinue\n 709→\t\t}\n 710→\n 711→\t\tres := mc.Timestep\n 712→\t\tif len(row) > 0 {\n 713→\t\t\tres = row[0].Resolution\n 714→\t\t}\n 715→\n 716→\t\t// Init Nested Map Data Structures If Not Found\n 717→\t\thostData, ok := data[query.Hostname]\n 718→\t\tif !ok {\n 719→\t\t\thostData = make(schema.JobData)\n 720→\t\t\tdata[query.Hostname] = hostData\n 721→\t\t}\n 722→\n 723→\t\tmetricData, ok := hostData[metric]\n 724→\t\tif !ok {\n 725→\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n 726→\t\t\tdata[query.Hostname][metric] = metricData\n 727→\t\t}\n 728→\n 729→\t\tscopeData, ok := metricData[scope]\n 730→\t\tif !ok {\n 731→\t\t\tscopeData = &schema.JobMetric{\n 732→\t\t\t\tUnit: mc.Unit,\n 733→\t\t\t\tTimestep: res,\n 734→\t\t\t\tSeries: make([]schema.Series, 0),\n 735→\t\t\t}\n 736→\t\t\tdata[query.Hostname][metric][scope] = scopeData\n 737→\t\t}\n 738→\n 739→\t\tfor ndx, res := range row {\n 740→\t\t\tif res.Error != nil {\n 741→\t\t\t\t/* Build list for \"partial errors\", if any */\n 742→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 743→\t\t\t\tcontinue\n 744→\t\t\t}\n 745→\n 746→\t\t\tid := (*string)(nil)\n 747→\t\t\tif query.Type != nil {\n 748→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 749→\t\t\t\tif ndx < len(query.TypeIds) {\n 750→\t\t\t\t\tid = new(string)\n 751→\t\t\t\t\t*id = query.TypeIds[ndx]\n 752→\t\t\t\t} else {\n 753→\t\t\t\t\t// Log the error but continue processing\n 754→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 755→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 756→\t\t\t\t}\n 757→\t\t\t}\n 758→\n 759→\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n 760→\n 761→\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n 762→\t\t\t\tHostname: query.Hostname,\n 763→\t\t\t\tID: id,\n 764→\t\t\t\tStatistics: schema.MetricStatistics{\n 765→\t\t\t\t\tAvg: float64(res.Avg),\n 766→\t\t\t\t\tMin: float64(res.Min),\n 767→\t\t\t\t\tMax: float64(res.Max),\n 768→\t\t\t\t},\n 769→\t\t\t\tData: res.Data,\n 770→\t\t\t})\n 771→\t\t}\n 772→\t}\n 773→\n 774→\tif len(errors) != 0 {\n 775→\t\t/* Returns list of \"partial errors\" */\n 776→\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 777→\t}\n 778→\n 779→\treturn data, nil\n 780→}\n 781→\n 782→// HealthCheck queries the external cc-metric-store's health check endpoint.\n 783→// It sends a HealthCheckReq as the request body to /api/healthcheck and\n 784→// returns the per-node health check results.\n 785→func (ccms *CCMetricStore) HealthCheck(cluster string,\n 786→\tnodes []string, metrics []string,\n 787→) (map[string]metricstore.HealthCheckResult, error) {\n 788→\treq := metricstore.HealthCheckReq{\n 789→\t\tCluster: cluster,\n 790→\t\tNodes: nodes,\n 791→\t\tMetricNames: metrics,\n 792→\t}\n 793→\n 794→\tbuf := &bytes.Buffer{}\n 795→\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n 796→\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n 797→\t\treturn nil, err\n 798→\t}\n 799→\n 800→\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n 801→\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n 802→\tif err != nil {\n 803→\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n 804→\t\treturn nil, err\n 805→\t}\n 806→\tif ccms.jwt != \"\" {\n 807→\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n 808→\t}\n 809→\n 810→\tres, err := ccms.client.Do(httpReq)\n 811→\tif err != nil {\n 812→\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n 813→\t\treturn nil, err\n 814→\t}\n 815→\tdefer res.Body.Close()\n 816→\n 817→\tif res.StatusCode != http.StatusOK {\n 818→\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n 819→\t}\n 820→\n 821→\tvar results map[string]metricstore.HealthCheckResult\n 822→\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n 823→\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n 824→\t\treturn nil, err\n 825→\t}\n 826→\n 827→\treturn results, nil\n 828→}\n 829→\n 830→// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n 831→// Regular float64 values cannot be JSONed when NaN.\n 832→func sanitizeStats(avg, min, max *schema.Float) {\n 833→\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n 834→\t\t*avg = schema.Float(0)\n 835→\t\t*min = schema.Float(0)\n 836→\t\t*max = schema.Float(0)\n 837→\t}\n 838→}\n 839→\n 840→// hasNaNStats returns true if any of the statistics contain NaN values.\n 841→func hasNaNStats(avg, min, max schema.Float) bool {\n 842→\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n 843→}\n 844→"}]},"uuid":"f9ec85f1-3aac-4db7-9cc2-2c5d5e15668c","timestamp":"2026-03-04T15:29:50.585Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n//\n// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n//\n// # Architecture\n//\n// The package is split into two main components:\n// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n//\n// # Basic Usage\n//\n//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n//\n//\t// Load job data\n//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n//\tif err != nil {\n//\t log.Fatal(err)\n//\t}\n//\n// # Metric Scopes\n//\n// The client supports hierarchical metric scopes that map to HPC hardware topology:\n// - MetricScopeAccelerator: GPU/accelerator level metrics\n// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n// - MetricScopeCore: CPU core level metrics\n// - MetricScopeSocket: CPU socket level metrics\n// - MetricScopeMemoryDomain: NUMA domain level metrics\n// - MetricScopeNode: Full node level metrics\n//\n// The client automatically handles scope transformations, aggregating finer-grained metrics\n// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n//\n// # Error Handling\n//\n// The client supports partial errors - if some queries fail, it returns both the successful\n// data and an error listing the failed queries. This allows processing partial results\n// when some nodes or metrics are temporarily unavailable.\n//\n// # API Versioning\n//\n// The client uses cc-metric-store API v2, which includes support for:\n// - Data resampling for bandwidth optimization\n// - Multi-scope queries in a single request\n// - Aggregation across hardware topology levels\npackage metricstoreclient\n\nimport (\n\t\"bufio\"\n\t\"bytes\"\n\t\"context\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"net/http\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n// It manages connection details, authentication, and provides methods for querying metrics.\ntype CCMetricStore struct {\n\tclient http.Client // HTTP client with 10-second timeout\n\tjwt string // JWT Bearer token for authentication\n\turl string // Base URL of cc-metric-store instance\n\tqueryEndpoint string // Full URL to query API endpoint\n\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n}\n\n// APIQueryRequest represents a request to the cc-metric-store query API.\n// It supports both explicit queries and \"for-all-nodes\" bulk queries.\ntype APIQueryRequest struct {\n\tCluster string `json:\"cluster\"` // Target cluster name\n\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n\tWithData bool `json:\"with-data\"` // Include time series data points\n}\n\n// APIQuery specifies a single metric query with optional scope filtering.\n// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\ntype APIQuery struct {\n\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n\tMetric string `json:\"metric\"` // Metric name\n\tHostname string `json:\"host\"` // Target hostname\n\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n}\n\n// APIQueryResponse contains the results from a cc-metric-store query.\n// Results align with the Queries slice by index.\ntype APIQueryResponse struct {\n\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n}\n\n// APIMetricData represents time series data and statistics for a single metric series.\n// Error is set if this particular series failed to load.\ntype APIMetricData struct {\n\tError *string `json:\"error\"` // Error message if query failed\n\tData []schema.Float `json:\"data\"` // Time series data points\n\tFrom int64 `json:\"from\"` // Actual start time of data\n\tTo int64 `json:\"to\"` // Actual end time of data\n\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n\tAvg schema.Float `json:\"avg\"` // Average value across time range\n\tMin schema.Float `json:\"min\"` // Minimum value in time range\n\tMax schema.Float `json:\"max\"` // Maximum value in time range\n}\n\n// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\nfunc NewCCMetricStore(url string, token string) *CCMetricStore {\n\treturn &CCMetricStore{\n\t\turl: url,\n\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n\t\tjwt: token,\n\t\tclient: http.Client{\n\t\t\tTimeout: 10 * time.Second,\n\t\t},\n\t\ttopologyCache: make(map[string]*schema.Topology),\n\t}\n}\n\n// doRequest executes an HTTP POST request to the cc-metric-store query API.\n// It handles JSON encoding/decoding, authentication, and API versioning.\n// The request body is automatically closed to prevent resource leaks.\nfunc (ccms *CCMetricStore) doRequest(\n\tctx context.Context,\n\tbody *APIQueryRequest,\n) (*APIQueryResponse, error) {\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\t// versioning the cc-metric-store query API.\n\t// v2 = data with resampling\n\t// v1 = data without resampling\n\tq := req.URL.Query()\n\tq.Add(\"version\", \"v2\")\n\treq.URL.RawQuery = q.Encode()\n\n\tres, err := ccms.client.Do(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n\t}\n\n\tvar resBody APIQueryResponse\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn &resBody, nil\n}\n\n// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\nfunc (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n\t\treturn topology, nil\n\t}\n\n\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tccms.topologyCache[cacheKey] = &subcluster.Topology\n\treturn &subcluster.Topology, nil\n}\n\n// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\nfunc (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn ccms.getTopology(cluster, subCluster)\n}\n\n// LoadData retrieves time series data and statistics for the specified job and metrics.\n// It queries data for the job's time range and resources, handling scope transformations automatically.\n//\n// Parameters:\n// - job: Job metadata including cluster, time range, and allocated resources\n// - metrics: List of metric names to retrieve\n// - scopes: Requested metric scopes (node, socket, core, etc.)\n// - ctx: Context for cancellation and timeouts\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns JobData organized as: metric -> scope -> series list.\n// Supports partial errors: returns available data even if some queries fail.\nfunc (ccms *CCMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n// This is faster than LoadData when only statistical summaries are needed (no time series data).\n//\n// Returns statistics organized as: metric -> hostname -> statistics.\nfunc (ccms *CCMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n// Used for the Job-View Statistics Table to display per-scope breakdowns.\n//\n// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\nfunc (ccms *CCMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n// Used for the Systems-View Node-Overview to display real-time node status.\n//\n// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\nfunc (ccms *CCMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n//\n// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n// substring matching on hostnames.\n//\n// Returns:\n// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n// - Total node count (before pagination)\n// - HasNextPage flag indicating if more pages are available\n// - Error (may be partial error with some data returned)\nfunc (ccms *CCMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// HealthCheck queries the external cc-metric-store's health check endpoint.\n// It sends a HealthCheckReq as the request body to /api/healthcheck and\n// returns the per-node health check results.\nfunc (ccms *CCMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]metricstore.HealthCheckResult, error) {\n\treq := metricstore.HealthCheckReq{\n\t\tCluster: cluster,\n\t\tNodes: nodes,\n\t\tMetricNames: metrics,\n\t}\n\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\tres, err := ccms.client.Do(httpReq)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n\t}\n\n\tvar results map[string]metricstore.HealthCheckResult\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn results, nil\n}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc sanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","numLines":844,"startLine":1,"totalLines":844}},"sourceToolAssistantUUID":"ea3a8f6b-4b1e-40c3-be4f-7108bea58889"}
{"parentUuid":"f9ec85f1-3aac-4db7-9cc2-2c5d5e15668c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_018h9USNcwNqk31d4QPRtM1B","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now let me read the relevant parts of the metricstore query.go file to understand the buildQueries and buildNodeQueries functions, as well as the sanitizeStats and other helpers.","signature":"EtsCCkYICxgCKkDsHPijYfEumVa+HSDAANAFHd6QdJGesZVI2xTW4/Kmmxl5w7L4b39CTuebYwPiOLSP22TkY4AtyVhVHwL2xgSeEgwnOiCgRG2OvP+MD8MaDLDa4PIEOmCJZ4j6/iIwek/6oWPxAPcyDY/VWL6fN896DQbCzwR1ZUGIriu2K1HhBaTE0mKTylQTpEd+vNxMKsIB4HZ68BFuUIiRfLrSjgH8s6dwo6fb5W+eaxH8NxoAiH2fg0tnhLsFzVV7+eNuDqA69nC3Kc9wd+XYvV76EQeMjqYACcnpUvsmft+yPtg3zDQpDG9z99dSTVdi6Uvsu+zEVPodOnmqwt2KiknzRlymgIGyjIVywWZQWJHGKnmceuty/wQLHFlcx5IO0JYGBnq92vVeIHHsAioSp7nN/nEuzOe1y+7yJ9C1Rs+KqcJqRrEhZKhuM6tCVv0AhZOdU57sgkMYAQ=="}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":19926,"cache_read_input_tokens":25501,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":19926},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiH7VKbf54tNEhaqHLDM","type":"assistant","uuid":"c07b0194-e154-4a3f-9988-bbde649dc559","timestamp":"2026-03-04T15:29:53.803Z"}
{"parentUuid":"c07b0194-e154-4a3f-9988-bbde649dc559","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_018h9USNcwNqk31d4QPRtM1B","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me read the key sections of the metricstore query.go file."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":19926,"cache_read_input_tokens":25501,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":19926},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiH7VKbf54tNEhaqHLDM","type":"assistant","uuid":"5dd70fbf-5eb5-4893-89ba-230cd74aa3bb","timestamp":"2026-03-04T15:29:54.313Z"}
{"parentUuid":"5dd70fbf-5eb5-4893-89ba-230cd74aa3bb","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_018h9USNcwNqk31d4QPRtM1B","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BtgCnfPYgcuBzJ2zPQPkNH","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","offset":280,"limit":300},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":19926,"cache_read_input_tokens":25501,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":19926},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiH7VKbf54tNEhaqHLDM","type":"assistant","uuid":"0ae0d1c3-5e55-44b5-92cc-39c08a4802e8","timestamp":"2026-03-04T15:29:55.668Z"}
{"parentUuid":"0ae0d1c3-5e55-44b5-92cc-39c08a4802e8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01BtgCnfPYgcuBzJ2zPQPkNH","toolUseID":"toolu_01BtgCnfPYgcuBzJ2zPQPkNH","timestamp":"2026-03-04T15:29:55.707Z","uuid":"00c1c0fa-777f-4275-8829-823ce7f663a2"}
{"parentUuid":"0ae0d1c3-5e55-44b5-92cc-39c08a4802e8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BtgCnfPYgcuBzJ2zPQPkNH","type":"tool_result","content":" 280→\t\t}\n 281→\n 282→\t\t// Skip if metric is removed for subcluster\n 283→\t\tif len(mc.SubClusters) != 0 {\n 284→\t\t\tisRemoved := false\n 285→\t\t\tfor _, scConfig := range mc.SubClusters {\n 286→\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n 287→\t\t\t\t\tisRemoved = true\n 288→\t\t\t\t\tbreak\n 289→\t\t\t\t}\n 290→\t\t\t}\n 291→\t\t\tif isRemoved {\n 292→\t\t\t\tcontinue\n 293→\t\t\t}\n 294→\t\t}\n 295→\n 296→\t\t// Avoid duplicates using map for O(1) lookup\n 297→\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n 298→\n 299→\t\tfor _, requestedScope := range scopes {\n 300→\t\t\tnativeScope := mc.Scope\n 301→\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n 302→\t\t\t\tcontinue\n 303→\t\t\t}\n 304→\n 305→\t\t\tscope := nativeScope.Max(requestedScope)\n 306→\t\t\tif handledScopes[scope] {\n 307→\t\t\t\tcontinue\n 308→\t\t\t}\n 309→\t\t\thandledScopes[scope] = true\n 310→\n 311→\t\t\tfor _, host := range job.Resources {\n 312→\t\t\t\thwthreads := host.HWThreads\n 313→\t\t\t\tif hwthreads == nil {\n 314→\t\t\t\t\thwthreads = topology.Node\n 315→\t\t\t\t}\n 316→\n 317→\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n 318→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n 319→\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n 320→\t\t\t\t\t\t// Skip all other catched cases\n 321→\t\t\t\t\t\tcontinue\n 322→\t\t\t\t\t}\n 323→\n 324→\t\t\t\t\tqueries = append(queries, APIQuery{\n 325→\t\t\t\t\t\tMetric: metric,\n 326→\t\t\t\t\t\tHostname: host.Hostname,\n 327→\t\t\t\t\t\tAggregate: false,\n 328→\t\t\t\t\t\tType: &acceleratorString,\n 329→\t\t\t\t\t\tTypeIds: host.Accelerators,\n 330→\t\t\t\t\t\tResolution: resolution,\n 331→\t\t\t\t\t})\n 332→\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n 333→\t\t\t\t\tcontinue\n 334→\t\t\t\t}\n 335→\n 336→\t\t\t\t// Accelerator -> Node\n 337→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n 338→\t\t\t\t\tif len(host.Accelerators) == 0 {\n 339→\t\t\t\t\t\tcontinue\n 340→\t\t\t\t\t}\n 341→\n 342→\t\t\t\t\tqueries = append(queries, APIQuery{\n 343→\t\t\t\t\t\tMetric: metric,\n 344→\t\t\t\t\t\tHostname: host.Hostname,\n 345→\t\t\t\t\t\tAggregate: true,\n 346→\t\t\t\t\t\tType: &acceleratorString,\n 347→\t\t\t\t\t\tTypeIds: host.Accelerators,\n 348→\t\t\t\t\t\tResolution: resolution,\n 349→\t\t\t\t\t})\n 350→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 351→\t\t\t\t\tcontinue\n 352→\t\t\t\t}\n 353→\n 354→\t\t\t\t// HWThread -> HWThread\n 355→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n 356→\t\t\t\t\tqueries = append(queries, APIQuery{\n 357→\t\t\t\t\t\tMetric: metric,\n 358→\t\t\t\t\t\tHostname: host.Hostname,\n 359→\t\t\t\t\t\tAggregate: false,\n 360→\t\t\t\t\t\tType: &hwthreadString,\n 361→\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n 362→\t\t\t\t\t\tResolution: resolution,\n 363→\t\t\t\t\t})\n 364→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 365→\t\t\t\t\tcontinue\n 366→\t\t\t\t}\n 367→\n 368→\t\t\t\t// HWThread -> Core\n 369→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n 370→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 371→\t\t\t\t\tfor _, core := range cores {\n 372→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 373→\t\t\t\t\t\t\tMetric: metric,\n 374→\t\t\t\t\t\t\tHostname: host.Hostname,\n 375→\t\t\t\t\t\t\tAggregate: true,\n 376→\t\t\t\t\t\t\tType: &hwthreadString,\n 377→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n 378→\t\t\t\t\t\t\tResolution: resolution,\n 379→\t\t\t\t\t\t})\n 380→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 381→\t\t\t\t\t}\n 382→\t\t\t\t\tcontinue\n 383→\t\t\t\t}\n 384→\n 385→\t\t\t\t// HWThread -> Socket\n 386→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n 387→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 388→\t\t\t\t\tfor _, socket := range sockets {\n 389→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 390→\t\t\t\t\t\t\tMetric: metric,\n 391→\t\t\t\t\t\t\tHostname: host.Hostname,\n 392→\t\t\t\t\t\t\tAggregate: true,\n 393→\t\t\t\t\t\t\tType: &hwthreadString,\n 394→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 395→\t\t\t\t\t\t\tResolution: resolution,\n 396→\t\t\t\t\t\t})\n 397→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 398→\t\t\t\t\t}\n 399→\t\t\t\t\tcontinue\n 400→\t\t\t\t}\n 401→\n 402→\t\t\t\t// HWThread -> Node\n 403→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n 404→\t\t\t\t\tqueries = append(queries, APIQuery{\n 405→\t\t\t\t\t\tMetric: metric,\n 406→\t\t\t\t\t\tHostname: host.Hostname,\n 407→\t\t\t\t\t\tAggregate: true,\n 408→\t\t\t\t\t\tType: &hwthreadString,\n 409→\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n 410→\t\t\t\t\t\tResolution: resolution,\n 411→\t\t\t\t\t})\n 412→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 413→\t\t\t\t\tcontinue\n 414→\t\t\t\t}\n 415→\n 416→\t\t\t\t// Core -> Core\n 417→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n 418→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 419→\t\t\t\t\tqueries = append(queries, APIQuery{\n 420→\t\t\t\t\t\tMetric: metric,\n 421→\t\t\t\t\t\tHostname: host.Hostname,\n 422→\t\t\t\t\t\tAggregate: false,\n 423→\t\t\t\t\t\tType: &coreString,\n 424→\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n 425→\t\t\t\t\t\tResolution: resolution,\n 426→\t\t\t\t\t})\n 427→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 428→\t\t\t\t\tcontinue\n 429→\t\t\t\t}\n 430→\n 431→\t\t\t\t// Core -> Socket\n 432→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n 433→\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n 434→\t\t\t\t\tfor _, socket := range sockets {\n 435→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 436→\t\t\t\t\t\t\tMetric: metric,\n 437→\t\t\t\t\t\t\tHostname: host.Hostname,\n 438→\t\t\t\t\t\t\tAggregate: true,\n 439→\t\t\t\t\t\t\tType: &coreString,\n 440→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 441→\t\t\t\t\t\t\tResolution: resolution,\n 442→\t\t\t\t\t\t})\n 443→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 444→\t\t\t\t\t}\n 445→\t\t\t\t\tcontinue\n 446→\t\t\t\t}\n 447→\n 448→\t\t\t\t// Core -> Node\n 449→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n 450→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 451→\t\t\t\t\tqueries = append(queries, APIQuery{\n 452→\t\t\t\t\t\tMetric: metric,\n 453→\t\t\t\t\t\tHostname: host.Hostname,\n 454→\t\t\t\t\t\tAggregate: true,\n 455→\t\t\t\t\t\tType: &coreString,\n 456→\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n 457→\t\t\t\t\t\tResolution: resolution,\n 458→\t\t\t\t\t})\n 459→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 460→\t\t\t\t\tcontinue\n 461→\t\t\t\t}\n 462→\n 463→\t\t\t\t// MemoryDomain -> MemoryDomain\n 464→\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n 465→\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 466→\t\t\t\t\tqueries = append(queries, APIQuery{\n 467→\t\t\t\t\t\tMetric: metric,\n 468→\t\t\t\t\t\tHostname: host.Hostname,\n 469→\t\t\t\t\t\tAggregate: false,\n 470→\t\t\t\t\t\tType: &memoryDomainString,\n 471→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 472→\t\t\t\t\t\tResolution: resolution,\n 473→\t\t\t\t\t})\n 474→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 475→\t\t\t\t\tcontinue\n 476→\t\t\t\t}\n 477→\n 478→\t\t\t\t// MemoryDomain -> Node\n 479→\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n 480→\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 481→\t\t\t\t\tqueries = append(queries, APIQuery{\n 482→\t\t\t\t\t\tMetric: metric,\n 483→\t\t\t\t\t\tHostname: host.Hostname,\n 484→\t\t\t\t\t\tAggregate: true,\n 485→\t\t\t\t\t\tType: &memoryDomainString,\n 486→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 487→\t\t\t\t\t\tResolution: resolution,\n 488→\t\t\t\t\t})\n 489→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 490→\t\t\t\t\tcontinue\n 491→\t\t\t\t}\n 492→\n 493→\t\t\t\t// Socket -> Socket\n 494→\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n 495→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 496→\t\t\t\t\tqueries = append(queries, APIQuery{\n 497→\t\t\t\t\t\tMetric: metric,\n 498→\t\t\t\t\t\tHostname: host.Hostname,\n 499→\t\t\t\t\t\tAggregate: false,\n 500→\t\t\t\t\t\tType: &socketString,\n 501→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 502→\t\t\t\t\t\tResolution: resolution,\n 503→\t\t\t\t\t})\n 504→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 505→\t\t\t\t\tcontinue\n 506→\t\t\t\t}\n 507→\n 508→\t\t\t\t// Socket -> Node\n 509→\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n 510→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 511→\t\t\t\t\tqueries = append(queries, APIQuery{\n 512→\t\t\t\t\t\tMetric: metric,\n 513→\t\t\t\t\t\tHostname: host.Hostname,\n 514→\t\t\t\t\t\tAggregate: true,\n 515→\t\t\t\t\t\tType: &socketString,\n 516→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 517→\t\t\t\t\t\tResolution: resolution,\n 518→\t\t\t\t\t})\n 519→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 520→\t\t\t\t\tcontinue\n 521→\t\t\t\t}\n 522→\n 523→\t\t\t\t// Node -> Node\n 524→\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n 525→\t\t\t\t\tqueries = append(queries, APIQuery{\n 526→\t\t\t\t\t\tMetric: metric,\n 527→\t\t\t\t\t\tHostname: host.Hostname,\n 528→\t\t\t\t\t\tResolution: resolution,\n 529→\t\t\t\t\t})\n 530→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 531→\t\t\t\t\tcontinue\n 532→\t\t\t\t}\n 533→\n 534→\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 535→\t\t\t}\n 536→\t\t}\n 537→\t}\n 538→\n 539→\treturn queries, assignedScope, nil\n 540→}\n 541→\n 542→// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n 543→//\n 544→// This is an optimized version of LoadData that fetches only statistics without\n 545→// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n 546→//\n 547→// Parameters:\n 548→// - job: Job metadata\n 549→// - metrics: List of metric names\n 550→// - ctx: Context (currently unused)\n 551→//\n 552→// Returns:\n 553→// - Map of metric → hostname → statistics\n 554→// - Error on query building or fetching failure\n 555→func (ccms *InternalMetricStore) LoadStats(\n 556→\tjob *schema.Job,\n 557→\tmetrics []string,\n 558→\tctx context.Context,\n 559→) (map[string]map[string]schema.MetricStatistics, error) {\n 560→\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n 561→\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n 562→\tif err != nil {\n 563→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n 564→\t\treturn nil, err\n 565→\t}\n 566→\n 567→\treq := APIQueryRequest{\n 568→\t\tCluster: job.Cluster,\n 569→\t\tFrom: job.StartTime,\n 570→\t\tTo: job.StartTime + int64(job.Duration),\n 571→\t\tQueries: queries,\n 572→\t\tWithStats: true,\n 573→\t\tWithData: false,\n 574→\t}\n 575→\n 576→\tresBody, err := FetchData(req)\n 577→\tif err != nil {\n 578→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 579→\t\treturn nil, err"}]},"uuid":"a0a0a848-9982-4a52-85ae-3c0ae7abfb51","timestamp":"2026-03-04T15:29:55.707Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err","numLines":300,"startLine":280,"totalLines":1358}},"sourceToolAssistantUUID":"0ae0d1c3-5e55-44b5-92cc-39c08a4802e8"}
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{"parentUuid":"2591a8b5-cf5a-4c84-b451-aa7a9d467ba8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JiLB67hDXBckzkBvaMJpeD","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// This file implements high-level query functions for loading job metric data\n 7→// with automatic scope transformation and aggregation.\n 8→//\n 9→// Key Concepts:\n 10→//\n 11→// Metric Scopes: Metrics are collected at different granularities (native scope):\n 12→// - HWThread: Per hardware thread\n 13→// - Core: Per CPU core\n 14→// - Socket: Per CPU socket\n 15→// - MemoryDomain: Per memory domain (NUMA)\n 16→// - Accelerator: Per GPU/accelerator\n 17→// - Node: Per compute node\n 18→//\n 19→// Scope Transformation: The buildQueries functions transform between native scope\n 20→// and requested scope by:\n 21→// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n 22→// - Rejecting requests for finer granularity than available\n 23→// - Handling special cases (e.g., Accelerator metrics)\n 24→//\n 25→// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n 26→// based on cluster topology and job resources.\n 27→package metricstore\n 28→\n 29→import (\n 30→\t\"context\"\n 31→\t\"fmt\"\n 32→\t\"strconv\"\n 33→\t\"strings\"\n 34→\t\"time\"\n 35→\n 36→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 37→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 38→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 39→)\n 40→\n 41→type InternalMetricStore struct{}\n 42→\n 43→var MetricStoreHandle *InternalMetricStore\n 44→\n 45→// HealthCheck delegates to the internal MemoryStore's HealthCheck.\n 46→func (ccms *InternalMetricStore) HealthCheck(cluster string,\n 47→\tnodes []string, metrics []string,\n 48→) (map[string]HealthCheckResult, error) {\n 49→\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n 50→}\n 51→\n 52→// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n 53→// When set to a non-nil function, LoadData will call this function instead of the default implementation.\n 54→var TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n 55→\n 56→// LoadData loads metric data for a specific job with automatic scope transformation.\n 57→//\n 58→// This is the primary function for retrieving job metric data. It handles:\n 59→// - Building queries with scope transformation via buildQueries\n 60→// - Fetching data from the metric store\n 61→// - Organizing results by metric and scope\n 62→// - Converting NaN statistics to 0 for JSON compatibility\n 63→// - Partial error handling (returns data for successful queries even if some fail)\n 64→//\n 65→// Parameters:\n 66→// - job: Job metadata including cluster, resources, and time range\n 67→// - metrics: List of metric names to load\n 68→// - scopes: Requested metric scopes (will be transformed to match native scopes)\n 69→// - ctx: Context for cancellation (currently unused but reserved for future use)\n 70→// - resolution: Data resolution in seconds (0 for native resolution)\n 71→//\n 72→// Returns:\n 73→// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n 74→// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n 75→//\n 76→// Example:\n 77→//\n 78→//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\n 79→func (ccms *InternalMetricStore) LoadData(\n 80→\tjob *schema.Job,\n 81→\tmetrics []string,\n 82→\tscopes []schema.MetricScope,\n 83→\tctx context.Context,\n 84→\tresolution int,\n 85→) (schema.JobData, error) {\n 86→\tif TestLoadDataCallback != nil {\n 87→\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n 88→\t}\n 89→\n 90→\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n 91→\tif err != nil {\n 92→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 93→\t\treturn nil, err\n 94→\t}\n 95→\n 96→\t// Verify assignment is correct - log any inconsistencies for debugging\n 97→\tif len(queries) != len(assignedScope) {\n 98→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n 99→\t\t\tlen(queries), len(assignedScope))\n 100→\t}"}]},"uuid":"f2047ea7-95c5-4fef-add2-981239d8bff9","timestamp":"2026-03-04T15:29:56.234Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strconv\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}","numLines":100,"startLine":1,"totalLines":1358}},"sourceToolAssistantUUID":"2591a8b5-cf5a-4c84-b451-aa7a9d467ba8"}
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{"parentUuid":"50efedb1-c5a9-45cb-a2ff-243484e9ffdd","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Bnu9yeuwPBximaszYZjCxP","type":"tool_result","content":" 100→\t}\n 101→\n 102→\treq := APIQueryRequest{\n 103→\t\tCluster: job.Cluster,\n 104→\t\tFrom: job.StartTime,\n 105→\t\tTo: job.StartTime + int64(job.Duration),\n 106→\t\tQueries: queries,\n 107→\t\tWithStats: true,\n 108→\t\tWithData: true,\n 109→\t}\n 110→\n 111→\tresBody, err := FetchData(req)\n 112→\tif err != nil {\n 113→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 114→\t\treturn nil, err\n 115→\t}\n 116→\n 117→\tvar errors []string\n 118→\tjobData := make(schema.JobData)\n 119→\n 120→\t// Add safety check for potential index out of range errors\n 121→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 122→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 123→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 124→\t\tif len(resBody.Results) > len(req.Queries) {\n 125→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 126→\t\t}\n 127→\t\tif len(assignedScope) > len(req.Queries) {\n 128→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 129→\t\t}\n 130→\t}\n 131→\n 132→\tfor i, row := range resBody.Results {\n 133→\t\t// Safety check to prevent index out of range errors\n 134→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 135→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 136→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 137→\t\t\tcontinue\n 138→\t\t}\n 139→\n 140→\t\tquery := req.Queries[i]\n 141→\t\tmetric := query.Metric\n 142→\t\tscope := assignedScope[i]\n 143→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 144→\n 145→\t\tif mc == nil {\n 146→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n 147→\t\t\tcontinue\n 148→\t\t}\n 149→\n 150→\t\tif _, ok := jobData[metric]; !ok {\n 151→\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n 152→\t\t}\n 153→\n 154→\t\tres := mc.Timestep\n 155→\t\tif len(row) > 0 {\n 156→\t\t\tres = int(row[0].Resolution)\n 157→\t\t}\n 158→\n 159→\t\tjobMetric, ok := jobData[metric][scope]\n 160→\t\tif !ok {\n 161→\t\t\tjobMetric = &schema.JobMetric{\n 162→\t\t\t\tUnit: mc.Unit,\n 163→\t\t\t\tTimestep: res,\n 164→\t\t\t\tSeries: make([]schema.Series, 0),\n 165→\t\t\t}\n 166→\t\t\tjobData[metric][scope] = jobMetric\n 167→\t\t}\n 168→\n 169→\t\tfor ndx, res := range row {\n 170→\t\t\tif res.Error != nil {\n 171→\t\t\t\t/* Build list for \"partial errors\", if any */\n 172→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 173→\t\t\t\tcontinue\n 174→\t\t\t}\n 175→\n 176→\t\t\tid := (*string)(nil)\n 177→\t\t\tif query.Type != nil {\n 178→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 179→\t\t\t\tif ndx < len(query.TypeIds) {\n 180→\t\t\t\t\tid = new(string)\n 181→\t\t\t\t\t*id = query.TypeIds[ndx]\n 182→\t\t\t\t} else {\n 183→\t\t\t\t\t// Log the error but continue processing\n 184→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 185→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 186→\t\t\t\t}\n 187→\t\t\t}\n 188→\n 189→\t\t\tsanitizeStats(&res)\n 190→\n 191→\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n 192→\t\t\t\tHostname: query.Hostname,\n 193→\t\t\t\tID: id,\n 194→\t\t\t\tStatistics: schema.MetricStatistics{\n 195→\t\t\t\t\tAvg: float64(res.Avg),\n 196→\t\t\t\t\tMin: float64(res.Min),\n 197→\t\t\t\t\tMax: float64(res.Max),\n 198→\t\t\t\t},\n 199→\t\t\t\tData: res.Data,\n 200→\t\t\t})\n 201→\t\t}\n 202→\n 203→\t\t// So that one can later check len(jobData):\n 204→\t\tif len(jobMetric.Series) == 0 {\n 205→\t\t\tdelete(jobData[metric], scope)\n 206→\t\t\tif len(jobData[metric]) == 0 {\n 207→\t\t\t\tdelete(jobData, metric)\n 208→\t\t\t}\n 209→\t\t}\n 210→\t}\n 211→\n 212→\tif len(errors) != 0 {\n 213→\t\t/* Returns list for \"partial errors\" */\n 214→\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 215→\t}\n 216→\treturn jobData, nil\n 217→}\n 218→\n 219→// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n 220→// query construction. These are used in APIQuery.Type field throughout buildQueries\n 221→// and buildNodeQueries functions. Converting once at package initialization improves\n 222→// performance for high-volume query building.\n 223→var (\n 224→\thwthreadString = string(schema.MetricScopeHWThread)\n 225→\tcoreString = string(schema.MetricScopeCore)\n 226→\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n 227→\tsocketString = string(schema.MetricScopeSocket)\n 228→\tacceleratorString = string(schema.MetricScopeAccelerator)\n 229→)\n 230→\n 231→// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n 232→//\n 233→// This function implements the core scope transformation logic, handling all combinations of\n 234→// native metric scopes and requested scopes. It uses the cluster topology to determine which\n 235→// hardware IDs to include in each query.\n 236→//\n 237→// Scope Transformation Rules:\n 238→// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n 239→// - If native scope < requested scope: Returns error (cannot increase granularity)\n 240→// - Special handling for Accelerator scope (independent of CPU hierarchy)\n 241→//\n 242→// The function generates one or more APIQuery per (metric, scope, host) combination:\n 243→// - For non-aggregated queries: One query with all relevant IDs\n 244→// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n 245→//\n 246→// Parameters:\n 247→// - job: Job metadata including cluster, subcluster, and resource allocation\n 248→// - metrics: List of metrics to query\n 249→// - scopes: Requested scopes for each metric\n 250→// - resolution: Data resolution in seconds\n 251→//\n 252→// Returns:\n 253→// - []APIQuery: List of queries to execute\n 254→// - []schema.MetricScope: Assigned scope for each query (after transformation)\n 255→// - error: Returns error if topology lookup fails or unhandled scope combination encountered\n 256→func buildQueries(\n 257→\tjob *schema.Job,\n 258→\tmetrics []string,\n 259→\tscopes []schema.MetricScope,\n 260→\tresolution int64,\n 261→) ([]APIQuery, []schema.MetricScope, error) {\n 262→\tif len(job.Resources) == 0 {\n 263→\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n 264→\t}\n 265→\n 266→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n 267→\tassignedScope := []schema.MetricScope{}\n 268→\n 269→\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n 270→\tif scerr != nil {\n 271→\t\treturn nil, nil, scerr\n 272→\t}\n 273→\ttopology := subcluster.Topology\n 274→\n 275→\tfor _, metric := range metrics {\n 276→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 277→\t\tif mc == nil {\n 278→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n 279→\t\t\tcontinue"}]},"uuid":"b0b8702c-fb20-426d-b14b-e3ea8bef9b22","timestamp":"2026-03-04T15:30:00.174Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue","numLines":180,"startLine":100,"totalLines":1358}},"sourceToolAssistantUUID":"50efedb1-c5a9-45cb-a2ff-243484e9ffdd"}
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{"parentUuid":"d669c2a3-8403-4c92-9015-eec0d313cf81","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AS4LSKHpCmJCakyPg6yNZB","type":"tool_result","content":" 580→\t}\n 581→\n 582→\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n 583→\tfor i, res := range resBody.Results {\n 584→\t\tif len(res) == 0 {\n 585→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 586→\t\t\tcontinue\n 587→\t\t}\n 588→\t\tquery := req.Queries[i]\n 589→\t\tmetric := query.Metric\n 590→\t\tdata := res[0]\n 591→\t\tif data.Error != nil {\n 592→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n 593→\t\t\tcontinue\n 594→\t\t}\n 595→\n 596→\t\tmetricdata, ok := stats[metric]\n 597→\t\tif !ok {\n 598→\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n 599→\t\t\tstats[metric] = metricdata\n 600→\t\t}\n 601→\n 602→\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n 603→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n 604→\t\t\tcontinue\n 605→\t\t}\n 606→\n 607→\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n 608→\t\t\tAvg: float64(data.Avg),\n 609→\t\t\tMin: float64(data.Min),\n 610→\t\t\tMax: float64(data.Max),\n 611→\t\t}\n 612→\t}\n 613→\n 614→\treturn stats, nil\n 615→}\n 616→\n 617→// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n 618→//\n 619→// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n 620→// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n 621→//\n 622→// Parameters:\n 623→// - job: Job metadata\n 624→// - metrics: List of metric names\n 625→// - scopes: Requested metric scopes\n 626→// - ctx: Context (currently unused)\n 627→//\n 628→// Returns:\n 629→// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n 630→// - Error or partial error listing failed queries\n 631→func (ccms *InternalMetricStore) LoadScopedStats(\n 632→\tjob *schema.Job,\n 633→\tmetrics []string,\n 634→\tscopes []schema.MetricScope,\n 635→\tctx context.Context,\n 636→) (schema.ScopedJobStats, error) {\n 637→\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n 638→\tif err != nil {\n 639→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 640→\t\treturn nil, err\n 641→\t}\n 642→\n 643→\treq := APIQueryRequest{\n 644→\t\tCluster: job.Cluster,\n 645→\t\tFrom: job.StartTime,\n 646→\t\tTo: job.StartTime + int64(job.Duration),\n 647→\t\tQueries: queries,\n 648→\t\tWithStats: true,\n 649→\t\tWithData: false,\n 650→\t}\n 651→\n 652→\tresBody, err := FetchData(req)\n 653→\tif err != nil {\n 654→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 655→\t\treturn nil, err\n 656→\t}\n 657→\n 658→\tvar errors []string\n 659→\tscopedJobStats := make(schema.ScopedJobStats)\n 660→\n 661→\tfor i, row := range resBody.Results {\n 662→\t\tif len(row) == 0 {\n 663→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 664→\t\t\tcontinue\n 665→\t\t}\n 666→\t\tquery := req.Queries[i]\n 667→\t\tmetric := query.Metric\n 668→\t\tscope := assignedScope[i]\n 669→\n 670→\t\tif _, ok := scopedJobStats[metric]; !ok {\n 671→\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n 672→\t\t}\n 673→\n 674→\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n 675→\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n 676→\t\t}\n 677→\n 678→\t\tfor ndx, res := range row {\n 679→\t\t\tif res.Error != nil {\n 680→\t\t\t\t/* Build list for \"partial errors\", if any */\n 681→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 682→\t\t\t\tcontinue\n 683→\t\t\t}\n 684→\n 685→\t\t\tid := (*string)(nil)\n 686→\t\t\tif query.Type != nil {\n 687→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 688→\t\t\t\tif ndx < len(query.TypeIds) {\n 689→\t\t\t\t\tid = new(string)\n 690→\t\t\t\t\t*id = query.TypeIds[ndx]\n 691→\t\t\t\t} else {\n 692→\t\t\t\t\t// Log the error but continue processing\n 693→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 694→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 695→\t\t\t\t}\n 696→\t\t\t}\n 697→\n 698→\t\t\tsanitizeStats(&res)\n 699→\n 700→\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n 701→\t\t\t\tHostname: query.Hostname,\n 702→\t\t\t\tID: id,\n 703→\t\t\t\tData: &schema.MetricStatistics{\n 704→\t\t\t\t\tAvg: float64(res.Avg),\n 705→\t\t\t\t\tMin: float64(res.Min),\n 706→\t\t\t\t\tMax: float64(res.Max),\n 707→\t\t\t\t},\n 708→\t\t\t})\n 709→\t\t}\n 710→\n 711→\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n 712→\t\tif len(scopedJobStats[metric][scope]) == 0 {\n 713→\t\t\tdelete(scopedJobStats[metric], scope)\n 714→\t\t\tif len(scopedJobStats[metric]) == 0 {\n 715→\t\t\t\tdelete(scopedJobStats, metric)\n 716→\t\t\t}\n 717→\t\t}\n 718→\t}\n 719→\n 720→\tif len(errors) != 0 {\n 721→\t\t/* Returns list for \"partial errors\" */\n 722→\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 723→\t}\n 724→\treturn scopedJobStats, nil\n 725→}\n 726→\n 727→// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n 728→//\n 729→// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n 730→// directly. Useful for system monitoring and node status views.\n 731→//\n 732→// Parameters:\n 733→// - cluster: Cluster name\n 734→// - metrics: List of metric names\n 735→// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n 736→// - scopes: Requested metric scopes (currently unused - always node scope)\n 737→// - from, to: Time range\n 738→// - ctx: Context (currently unused)\n 739→//\n 740→// Returns:\n 741→// - Map of hostname → metric → []JobMetric\n 742→// - Error or partial error listing failed queries\n 743→func (ccms *InternalMetricStore) LoadNodeData(\n 744→\tcluster string,\n 745→\tmetrics, nodes []string,\n 746→\tscopes []schema.MetricScope,\n 747→\tfrom, to time.Time,\n 748→\tctx context.Context,\n 749→) (map[string]map[string][]*schema.JobMetric, error) {\n 750→\treq := APIQueryRequest{\n 751→\t\tCluster: cluster,\n 752→\t\tFrom: from.Unix(),\n 753→\t\tTo: to.Unix(),\n 754→\t\tWithStats: true,\n 755→\t\tWithData: true,\n 756→\t}\n 757→\n 758→\tif nodes == nil {\n 759→\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n 760→\t} else {\n 761→\t\tfor _, node := range nodes {\n 762→\t\t\tfor _, metric := range metrics {\n 763→\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n 764→\t\t\t\t\tHostname: node,\n 765→\t\t\t\t\tMetric: metric,\n 766→\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n 767→\t\t\t\t})\n 768→\t\t\t}\n 769→\t\t}\n 770→\t}\n 771→\n 772→\tresBody, err := FetchData(req)\n 773→\tif err != nil {\n 774→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 775→\t\treturn nil, err\n 776→\t}\n 777→\n 778→\tvar errors []string\n 779→\tdata := make(map[string]map[string][]*schema.JobMetric)"}]},"uuid":"e7b7a98b-7760-4e50-94a4-473800b54a65","timestamp":"2026-03-04T15:30:00.664Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)","numLines":200,"startLine":580,"totalLines":1358}},"sourceToolAssistantUUID":"d669c2a3-8403-4c92-9015-eec0d313cf81"}
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{"parentUuid":"90b5186a-31a5-4528-a670-e58ae0507aba","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CRkwErby7cxdjB18qek5es","type":"tool_result","content":" 780→\tfor i, res := range resBody.Results {\n 781→\t\tif len(res) == 0 {\n 782→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 783→\t\t\tcontinue\n 784→\t\t}\n 785→\n 786→\t\tvar query APIQuery\n 787→\t\tif resBody.Queries != nil {\n 788→\t\t\tquery = resBody.Queries[i]\n 789→\t\t} else {\n 790→\t\t\tquery = req.Queries[i]\n 791→\t\t}\n 792→\n 793→\t\tmetric := query.Metric\n 794→\t\tqdata := res[0]\n 795→\t\tif qdata.Error != nil {\n 796→\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n 797→\t\t}\n 798→\n 799→\t\tsanitizeStats(&qdata)\n 800→\n 801→\t\thostdata, ok := data[query.Hostname]\n 802→\t\tif !ok {\n 803→\t\t\thostdata = make(map[string][]*schema.JobMetric)\n 804→\t\t\tdata[query.Hostname] = hostdata\n 805→\t\t}\n 806→\n 807→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 808→\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n 809→\t\t\tUnit: mc.Unit,\n 810→\t\t\tTimestep: mc.Timestep,\n 811→\t\t\tSeries: []schema.Series{\n 812→\t\t\t\t{\n 813→\t\t\t\t\tHostname: query.Hostname,\n 814→\t\t\t\t\tData: qdata.Data,\n 815→\t\t\t\t\tStatistics: schema.MetricStatistics{\n 816→\t\t\t\t\t\tAvg: float64(qdata.Avg),\n 817→\t\t\t\t\t\tMin: float64(qdata.Min),\n 818→\t\t\t\t\t\tMax: float64(qdata.Max),\n 819→\t\t\t\t\t},\n 820→\t\t\t\t},\n 821→\t\t\t},\n 822→\t\t})\n 823→\t}\n 824→\n 825→\tif len(errors) != 0 {\n 826→\t\t/* Returns list of \"partial errors\" */\n 827→\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 828→\t}\n 829→\n 830→\treturn data, nil\n 831→}\n 832→\n 833→// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n 834→//\n 835→// This is the most flexible node data loading function, supporting arbitrary scopes and\n 836→// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n 837→//\n 838→// Parameters:\n 839→// - cluster: Cluster name\n 840→// - subCluster: SubCluster name (empty string to infer from node names)\n 841→// - nodes: List of node hostnames\n 842→// - metrics: List of metric names\n 843→// - scopes: Requested metric scopes\n 844→// - resolution: Data resolution in seconds\n 845→// - from, to: Time range\n 846→// - ctx: Context (currently unused)\n 847→//\n 848→// Returns:\n 849→// - Map of hostname → JobData (metric → scope → JobMetric)\n 850→// - Error or partial error listing failed queries\n 851→func (ccms *InternalMetricStore) LoadNodeListData(\n 852→\tcluster, subCluster string,\n 853→\tnodes []string,\n 854→\tmetrics []string,\n 855→\tscopes []schema.MetricScope,\n 856→\tresolution int,\n 857→\tfrom, to time.Time,\n 858→\tctx context.Context,\n 859→) (map[string]schema.JobData, error) {\n 860→\t// Note: Order of node data is not guaranteed after this point\n 861→\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n 862→\tif err != nil {\n 863→\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n 864→\t\treturn nil, err\n 865→\t}\n 866→\n 867→\t// Verify assignment is correct - log any inconsistencies for debugging\n 868→\tif len(queries) != len(assignedScope) {\n 869→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n 870→\t\t\tlen(queries), len(assignedScope))\n 871→\t}\n 872→\n 873→\treq := APIQueryRequest{\n 874→\t\tCluster: cluster,\n 875→\t\tQueries: queries,\n 876→\t\tFrom: from.Unix(),\n 877→\t\tTo: to.Unix(),\n 878→\t\tWithStats: true,\n 879→\t\tWithData: true,\n 880→\t}\n 881→\n 882→\tresBody, err := FetchData(req)\n 883→\tif err != nil {\n 884→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 885→\t\treturn nil, err\n 886→\t}\n 887→\n 888→\tvar errors []string\n 889→\tdata := make(map[string]schema.JobData)\n 890→\n 891→\t// Add safety check for index out of range issues\n 892→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 893→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 894→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 895→\t\tif len(resBody.Results) > len(req.Queries) {\n 896→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 897→\t\t}\n 898→\t\tif len(assignedScope) > len(req.Queries) {\n 899→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 900→\t\t}\n 901→\t}\n 902→\n 903→\tfor i, row := range resBody.Results {\n 904→\t\t// Safety check to prevent index out of range errors\n 905→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 906→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 907→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 908→\t\t\tcontinue\n 909→\t\t}\n 910→\n 911→\t\tvar query APIQuery\n 912→\t\tif resBody.Queries != nil {\n 913→\t\t\tif i < len(resBody.Queries) {\n 914→\t\t\t\tquery = resBody.Queries[i]\n 915→\t\t\t} else {\n 916→\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n 917→\t\t\t\t\ti, len(resBody.Queries))\n 918→\t\t\t\tcontinue\n 919→\t\t\t}\n 920→\t\t} else {\n 921→\t\t\tquery = req.Queries[i]\n 922→\t\t}\n 923→\n 924→\t\tmetric := query.Metric\n 925→\t\tscope := assignedScope[i]\n 926→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 927→\t\tif mc == nil {\n 928→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n 929→\t\t\tcontinue\n 930→\t\t}\n 931→\n 932→\t\tres := mc.Timestep\n 933→\t\tif len(row) > 0 {\n 934→\t\t\tres = int(row[0].Resolution)\n 935→\t\t}\n 936→\n 937→\t\t// Init Nested Map Data Structures If Not Found\n 938→\t\thostData, ok := data[query.Hostname]\n 939→\t\tif !ok {\n 940→\t\t\thostData = make(schema.JobData)\n 941→\t\t\tdata[query.Hostname] = hostData\n 942→\t\t}\n 943→\n 944→\t\tmetricData, ok := hostData[metric]\n 945→\t\tif !ok {\n 946→\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n 947→\t\t\tdata[query.Hostname][metric] = metricData\n 948→\t\t}\n 949→\n 950→\t\tscopeData, ok := metricData[scope]\n 951→\t\tif !ok {\n 952→\t\t\tscopeData = &schema.JobMetric{\n 953→\t\t\t\tUnit: mc.Unit,\n 954→\t\t\t\tTimestep: res,\n 955→\t\t\t\tSeries: make([]schema.Series, 0),\n 956→\t\t\t}\n 957→\t\t\tdata[query.Hostname][metric][scope] = scopeData\n 958→\t\t}\n 959→\n 960→\t\tfor ndx, res := range row {\n 961→\t\t\tif res.Error != nil {\n 962→\t\t\t\t/* Build list for \"partial errors\", if any */\n 963→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 964→\t\t\t\tcontinue\n 965→\t\t\t}\n 966→\n 967→\t\t\tid := (*string)(nil)\n 968→\t\t\tif query.Type != nil {\n 969→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 970→\t\t\t\tif ndx < len(query.TypeIds) {\n 971→\t\t\t\t\tid = new(string)\n 972→\t\t\t\t\t*id = query.TypeIds[ndx]\n 973→\t\t\t\t} else {\n 974→\t\t\t\t\t// Log the error but continue processing\n 975→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 976→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 977→\t\t\t\t}\n 978→\t\t\t}\n 979→\n 980→\t\t\tsanitizeStats(&res)\n 981→\n 982→\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n 983→\t\t\t\tHostname: query.Hostname,\n 984→\t\t\t\tID: id,\n 985→\t\t\t\tStatistics: schema.MetricStatistics{\n 986→\t\t\t\t\tAvg: float64(res.Avg),\n 987→\t\t\t\t\tMin: float64(res.Min),\n 988→\t\t\t\t\tMax: float64(res.Max),\n 989→\t\t\t\t},\n 990→\t\t\t\tData: res.Data,\n 991→\t\t\t})\n 992→\t\t}\n 993→\t}\n 994→\n 995→\tif len(errors) != 0 {\n 996→\t\t/* Returns list of \"partial errors\" */\n 997→\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 998→\t}\n 999→\n 1000→\treturn data, nil\n 1001→}\n 1002→\n 1003→// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n 1004→//\n 1005→// Similar to buildQueries but operates on node lists rather than job resources.\n 1006→// Supports dynamic subcluster lookup when subCluster parameter is empty.\n 1007→//\n 1008→// Parameters:\n 1009→// - cluster: Cluster name\n 1010→// - subCluster: SubCluster name (empty = infer from node hostnames)\n 1011→// - nodes: List of node hostnames\n 1012→// - metrics: List of metric names\n 1013→// - scopes: Requested metric scopes\n 1014→// - resolution: Data resolution in seconds\n 1015→//\n 1016→// Returns:\n 1017→// - []APIQuery: List of queries to execute\n 1018→// - []schema.MetricScope: Assigned scope for each query\n 1019→// - error: Returns error if topology lookup fails or unhandled scope combination\n 1020→func buildNodeQueries(\n 1021→\tcluster string,\n 1022→\tsubCluster string,\n 1023→\tnodes []string,\n 1024→\tmetrics []string,\n 1025→\tscopes []schema.MetricScope,\n 1026→\tresolution int64,\n 1027→) ([]APIQuery, []schema.MetricScope, error) {\n 1028→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n 1029→\tassignedScope := []schema.MetricScope{}\n 1030→\n 1031→\t// Get Topol before loop if subCluster given\n 1032→\tvar subClusterTopol *schema.SubCluster\n 1033→\tvar scterr error\n 1034→\tif subCluster != \"\" {\n 1035→\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n 1036→\t\tif scterr != nil {\n 1037→\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n 1038→\t\t\treturn nil, nil, scterr\n 1039→\t\t}\n 1040→\t}\n 1041→\n 1042→\tfor _, metric := range metrics {\n 1043→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 1044→\t\tif mc == nil {\n 1045→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n 1046→\t\t\tcontinue\n 1047→\t\t}\n 1048→\n 1049→\t\t// Skip if metric is removed for subcluster\n 1050→\t\tif mc.SubClusters != nil {\n 1051→\t\t\tisRemoved := false\n 1052→\t\t\tfor _, scConfig := range mc.SubClusters {\n 1053→\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n 1054→\t\t\t\t\tisRemoved = true\n 1055→\t\t\t\t\tbreak\n 1056→\t\t\t\t}\n 1057→\t\t\t}\n 1058→\t\t\tif isRemoved {\n 1059→\t\t\t\tcontinue\n 1060→\t\t\t}\n 1061→\t\t}\n 1062→\n 1063→\t\t// Avoid duplicates using map for O(1) lookup\n 1064→\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n 1065→\n 1066→\t\tfor _, requestedScope := range scopes {\n 1067→\t\t\tnativeScope := mc.Scope\n 1068→\n 1069→\t\t\tscope := nativeScope.Max(requestedScope)\n 1070→\t\t\tif handledScopes[scope] {\n 1071→\t\t\t\tcontinue\n 1072→\t\t\t}\n 1073→\t\t\thandledScopes[scope] = true\n 1074→\n 1075→\t\t\tfor _, hostname := range nodes {\n 1076→\n 1077→\t\t\t\t// If no subCluster given, get it by node\n 1078→\t\t\t\tif subCluster == \"\" {\n 1079→\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n 1080→\t\t\t\t\tif scnerr != nil {\n 1081→\t\t\t\t\t\treturn nil, nil, scnerr\n 1082→\t\t\t\t\t}\n 1083→\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n 1084→\t\t\t\t\tif scterr != nil {\n 1085→\t\t\t\t\t\treturn nil, nil, scterr\n 1086→\t\t\t\t\t}\n 1087→\t\t\t\t}\n 1088→\n 1089→\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n 1090→\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n 1091→\t\t\t\ttopology := subClusterTopol.Topology\n 1092→\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n 1093→\n 1094→\t\t\t\t// Moved check here if metric matches hardware specs\n 1095→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n 1096→\t\t\t\t\tcontinue\n 1097→\t\t\t\t}\n 1098→\n 1099→\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n 1100→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n 1101→\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n 1102→\t\t\t\t\t\t// Skip all other catched cases\n 1103→\t\t\t\t\t\tcontinue\n 1104→\t\t\t\t\t}\n 1105→\n 1106→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1107→\t\t\t\t\t\tMetric: metric,\n 1108→\t\t\t\t\t\tHostname: hostname,\n 1109→\t\t\t\t\t\tAggregate: false,\n 1110→\t\t\t\t\t\tType: &acceleratorString,\n 1111→\t\t\t\t\t\tTypeIds: acceleratorIds,\n 1112→\t\t\t\t\t\tResolution: resolution,\n 1113→\t\t\t\t\t})\n 1114→\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n 1115→\t\t\t\t\tcontinue\n 1116→\t\t\t\t}\n 1117→\n 1118→\t\t\t\t// Accelerator -> Node\n 1119→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n 1120→\t\t\t\t\tif len(acceleratorIds) == 0 {\n 1121→\t\t\t\t\t\tcontinue\n 1122→\t\t\t\t\t}\n 1123→\n 1124→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1125→\t\t\t\t\t\tMetric: metric,\n 1126→\t\t\t\t\t\tHostname: hostname,\n 1127→\t\t\t\t\t\tAggregate: true,\n 1128→\t\t\t\t\t\tType: &acceleratorString,\n 1129→\t\t\t\t\t\tTypeIds: acceleratorIds,\n 1130→\t\t\t\t\t\tResolution: resolution,\n 1131→\t\t\t\t\t})\n 1132→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1133→\t\t\t\t\tcontinue\n 1134→\t\t\t\t}\n 1135→\n 1136→\t\t\t\t// HWThread -> HWThread\n 1137→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n 1138→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1139→\t\t\t\t\t\tMetric: metric,\n 1140→\t\t\t\t\t\tHostname: hostname,\n 1141→\t\t\t\t\t\tAggregate: false,\n 1142→\t\t\t\t\t\tType: &hwthreadString,\n 1143→\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n 1144→\t\t\t\t\t\tResolution: resolution,\n 1145→\t\t\t\t\t})\n 1146→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1147→\t\t\t\t\tcontinue\n 1148→\t\t\t\t}\n 1149→\n 1150→\t\t\t\t// HWThread -> Core\n 1151→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n 1152→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n 1153→\t\t\t\t\tfor _, core := range cores {\n 1154→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 1155→\t\t\t\t\t\t\tMetric: metric,\n 1156→\t\t\t\t\t\t\tHostname: hostname,\n 1157→\t\t\t\t\t\t\tAggregate: true,\n 1158→\t\t\t\t\t\t\tType: &hwthreadString,\n 1159→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n 1160→\t\t\t\t\t\t\tResolution: resolution,\n 1161→\t\t\t\t\t\t})\n 1162→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1163→\t\t\t\t\t}\n 1164→\t\t\t\t\tcontinue\n 1165→\t\t\t\t}\n 1166→\n 1167→\t\t\t\t// HWThread -> Socket\n 1168→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n 1169→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n 1170→\t\t\t\t\tfor _, socket := range sockets {\n 1171→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 1172→\t\t\t\t\t\t\tMetric: metric,\n 1173→\t\t\t\t\t\t\tHostname: hostname,\n 1174→\t\t\t\t\t\t\tAggregate: true,\n 1175→\t\t\t\t\t\t\tType: &hwthreadString,\n 1176→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 1177→\t\t\t\t\t\t\tResolution: resolution,\n 1178→\t\t\t\t\t\t})\n 1179→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1180→\t\t\t\t\t}\n 1181→\t\t\t\t\tcontinue\n 1182→\t\t\t\t}\n 1183→\n 1184→\t\t\t\t// HWThread -> Node\n 1185→\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n 1186→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1187→\t\t\t\t\t\tMetric: metric,\n 1188→\t\t\t\t\t\tHostname: hostname,\n 1189→\t\t\t\t\t\tAggregate: true,\n 1190→\t\t\t\t\t\tType: &hwthreadString,\n 1191→\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n 1192→\t\t\t\t\t\tResolution: resolution,\n 1193→\t\t\t\t\t})\n 1194→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1195→\t\t\t\t\tcontinue\n 1196→\t\t\t\t}\n 1197→\n 1198→\t\t\t\t// Core -> Core\n 1199→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n 1200→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n 1201→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1202→\t\t\t\t\t\tMetric: metric,\n 1203→\t\t\t\t\t\tHostname: hostname,\n 1204→\t\t\t\t\t\tAggregate: false,\n 1205→\t\t\t\t\t\tType: &coreString,\n 1206→\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n 1207→\t\t\t\t\t\tResolution: resolution,\n 1208→\t\t\t\t\t})\n 1209→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1210→\t\t\t\t\tcontinue\n 1211→\t\t\t\t}\n 1212→\n 1213→\t\t\t\t// Core -> Socket\n 1214→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n 1215→\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n 1216→\t\t\t\t\tfor _, socket := range sockets {\n 1217→\t\t\t\t\t\tqueries = append(queries, APIQuery{\n 1218→\t\t\t\t\t\t\tMetric: metric,\n 1219→\t\t\t\t\t\t\tHostname: hostname,\n 1220→\t\t\t\t\t\t\tAggregate: true,\n 1221→\t\t\t\t\t\t\tType: &coreString,\n 1222→\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n 1223→\t\t\t\t\t\t\tResolution: resolution,\n 1224→\t\t\t\t\t\t})\n 1225→\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1226→\t\t\t\t\t}\n 1227→\t\t\t\t\tcontinue\n 1228→\t\t\t\t}\n 1229→\n 1230→\t\t\t\t// Core -> Node\n 1231→\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n 1232→\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n 1233→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1234→\t\t\t\t\t\tMetric: metric,\n 1235→\t\t\t\t\t\tHostname: hostname,\n 1236→\t\t\t\t\t\tAggregate: true,\n 1237→\t\t\t\t\t\tType: &coreString,\n 1238→\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n 1239→\t\t\t\t\t\tResolution: resolution,\n 1240→\t\t\t\t\t})\n 1241→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1242→\t\t\t\t\tcontinue\n 1243→\t\t\t\t}\n 1244→\n 1245→\t\t\t\t// MemoryDomain -> MemoryDomain\n 1246→\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n 1247→\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n 1248→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1249→\t\t\t\t\t\tMetric: metric,\n 1250→\t\t\t\t\t\tHostname: hostname,\n 1251→\t\t\t\t\t\tAggregate: false,\n 1252→\t\t\t\t\t\tType: &memoryDomainString,\n 1253→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 1254→\t\t\t\t\t\tResolution: resolution,\n 1255→\t\t\t\t\t})\n 1256→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1257→\t\t\t\t\tcontinue\n 1258→\t\t\t\t}\n 1259→\n 1260→\t\t\t\t// MemoryDomain -> Node\n 1261→\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n 1262→\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n 1263→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1264→\t\t\t\t\t\tMetric: metric,\n 1265→\t\t\t\t\t\tHostname: hostname,\n 1266→\t\t\t\t\t\tAggregate: true,\n 1267→\t\t\t\t\t\tType: &memoryDomainString,\n 1268→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 1269→\t\t\t\t\t\tResolution: resolution,\n 1270→\t\t\t\t\t})\n 1271→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1272→\t\t\t\t\tcontinue\n 1273→\t\t\t\t}\n 1274→\n 1275→\t\t\t\t// Socket -> Socket\n 1276→\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n 1277→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n 1278→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1279→\t\t\t\t\t\tMetric: metric,\n 1280→\t\t\t\t\t\tHostname: hostname,\n 1281→\t\t\t\t\t\tAggregate: false,\n 1282→\t\t\t\t\t\tType: &socketString,\n 1283→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 1284→\t\t\t\t\t\tResolution: resolution,\n 1285→\t\t\t\t\t})\n 1286→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1287→\t\t\t\t\tcontinue\n 1288→\t\t\t\t}\n 1289→\n 1290→\t\t\t\t// Socket -> Node\n 1291→\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n 1292→\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n 1293→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1294→\t\t\t\t\t\tMetric: metric,\n 1295→\t\t\t\t\t\tHostname: hostname,\n 1296→\t\t\t\t\t\tAggregate: true,\n 1297→\t\t\t\t\t\tType: &socketString,\n 1298→\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n 1299→\t\t\t\t\t\tResolution: resolution,\n 1300→\t\t\t\t\t})\n 1301→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1302→\t\t\t\t\tcontinue\n 1303→\t\t\t\t}\n 1304→\n 1305→\t\t\t\t// Node -> Node\n 1306→\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n 1307→\t\t\t\t\tqueries = append(queries, APIQuery{\n 1308→\t\t\t\t\t\tMetric: metric,\n 1309→\t\t\t\t\t\tHostname: hostname,\n 1310→\t\t\t\t\t\tResolution: resolution,\n 1311→\t\t\t\t\t})\n 1312→\t\t\t\t\tassignedScope = append(assignedScope, scope)\n 1313→\t\t\t\t\tcontinue\n 1314→\t\t\t\t}\n 1315→\n 1316→\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 1317→\t\t\t}\n 1318→\t\t}\n 1319→\t}\n 1320→\n 1321→\treturn queries, assignedScope, nil\n 1322→}\n 1323→\n 1324→// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n 1325→//\n 1326→// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n 1327→// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n 1328→// but maintains API compatibility.\n 1329→func sanitizeStats(data *APIMetricData) {\n 1330→\tif data.Avg.IsNaN() {\n 1331→\t\tdata.Avg = schema.Float(0)\n 1332→\t}\n 1333→\tif data.Min.IsNaN() {\n 1334→\t\tdata.Min = schema.Float(0)\n 1335→\t}\n 1336→\tif data.Max.IsNaN() {\n 1337→\t\tdata.Max = schema.Float(0)\n 1338→\t}\n 1339→}\n 1340→\n 1341→// intToStringSlice converts a slice of integers to a slice of strings.\n 1342→// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n 1343→//\n 1344→// Optimized to reuse a byte buffer for string conversion, reducing allocations.\n 1345→func intToStringSlice(is []int) []string {\n 1346→\tif len(is) == 0 {\n 1347→\t\treturn nil\n 1348→\t}\n 1349→\n 1350→\tss := make([]string, len(is))\n 1351→\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n 1352→\tfor i, x := range is {\n 1353→\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n 1354→\t\tss[i] = string(buf)\n 1355→\t}\n 1356→\treturn ss\n 1357→}\n 1358→"}]},"uuid":"3b8ab33f-69fd-4223-bf7e-ce3840dc0718","timestamp":"2026-03-04T15:30:04.379Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","content":"\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","numLines":579,"startLine":780,"totalLines":1358}},"sourceToolAssistantUUID":"90b5186a-31a5-4528-a670-e58ae0507aba"}
{"parentUuid":"3b8ab33f-69fd-4223-bf7e-ce3840dc0718","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01QxfjFord1L4E4N8ELJzV8t","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a complete picture. Let me create the tasks and start implementing.\n\nKey observations:\n1. metricstore's `sanitizeStats` takes `*APIMetricData`, while metricstoreclient's takes `*schema.Float, *schema.Float, *schema.Float`\n2. metricstore's `sanitizeStats` zeros each field independently; metricstoreclient zeros ALL if ANY is NaN\n3. metricstore's `intToStringSlice` has the optimized buffer-reuse version\n4. metricstore is missing MemoryDomain → Socket transformation\n5. metricstore's `APIQuery.Resolution` is `int64`, metricstoreclient's is `int`\n\n\n6. Now I'm starting with the shared `scopequery.go` file to establish the common foundation.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7983,"cache_read_input_tokens":56379,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":7983},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiH8WNdSwGkNHAh6bkA2","type":"assistant","uuid":"fe624ff0-40b1-4d13-af12-c1c6a01898f5","timestamp":"2026-03-04T15:30:12.554Z"}
{"parentUuid":"fe624ff0-40b1-4d13-af12-c1c6a01898f5","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01QxfjFord1L4E4N8ELJzV8t","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have a full understanding of the code. Let me create task tracking and start implementing."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7983,"cache_read_input_tokens":56379,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":7983},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiH8WNdSwGkNHAh6bkA2","type":"assistant","uuid":"af72a1a9-3146-4b04-a579-9b67242c4831","timestamp":"2026-03-04T15:30:12.564Z"}
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It extracts the common algorithm for mapping\n// between native metric scopes and requested scopes based on cluster topology.\npackage metricstore\n\nimport (\n\t\"strconv\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations\n// during query construction. Used in ScopeQueryResult.Type field.\nvar (\n\tHWThreadString = string(schema.MetricScopeHWThread)\n\tCoreString = string(schema.MetricScopeCore)\n\tMemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tSocketString = string(schema.MetricScopeSocket)\n\tAcceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// ScopeQueryResult is a package-independent intermediate type returned by\n// BuildScopeQueries. Each consumer converts it to their own APIQuery type\n// (adding Resolution and any other package-specific fields).\ntype ScopeQueryResult struct {\n\tType *string\n\tMetric string\n\tHostname string\n\tTypeIds []string\n\tScope schema.MetricScope\n\tAggregate bool\n}\n\n// BuildScopeQueries generates scope query results for a given scope transformation.\n// It returns a slice of results and a boolean indicating success.\n// An empty slice means an expected exception (skip this combination).\n// ok=false means an unhandled case (caller should return an error).\nfunc BuildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n) ([]ScopeQueryResult, bool) {\n\tscope := nativeScope.Max(requestedScope)\n\tresults := []ScopeQueryResult{}\n\n\thwthreadsStr := IntToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &AcceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tScope: schema.MetricScopeAccelerator,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &AcceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &HWThreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &HWThreadString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Core[core]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &HWThreadString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &HWThreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &CoreString,\n\t\t\tTypeIds: IntToStringSlice(cores),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &CoreString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &CoreString,\n\t\t\tTypeIds: IntToStringSlice(cores),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &MemoryDomainString,\n\t\t\tTypeIds: IntToStringSlice(memDomains),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &MemoryDomainString,\n\t\t\t\tTypeIds: IntToStringSlice(domains),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &MemoryDomainString,\n\t\t\tTypeIds: IntToStringSlice(memDomains),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &SocketString,\n\t\t\tTypeIds: IntToStringSlice(sockets),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &SocketString,\n\t\t\tTypeIds: IntToStringSlice(sockets),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Unhandled 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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file contains shared scope transformation logic used by both the internal\n// metric store (pkg/metricstore) and the external cc-metric-store client\n// (internal/metricstoreclient). It extracts the common algorithm for mapping\n// between native metric scopes and requested scopes based on cluster topology.\npackage metricstore\n\nimport (\n\t\"strconv\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations\n// during query construction. Used in ScopeQueryResult.Type field.\nvar (\n\tHWThreadString = string(schema.MetricScopeHWThread)\n\tCoreString = string(schema.MetricScopeCore)\n\tMemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tSocketString = string(schema.MetricScopeSocket)\n\tAcceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// ScopeQueryResult is a package-independent intermediate type returned by\n// BuildScopeQueries. Each consumer converts it to their own APIQuery type\n// (adding Resolution and any other package-specific fields).\ntype ScopeQueryResult struct {\n\tType *string\n\tMetric string\n\tHostname string\n\tTypeIds []string\n\tScope schema.MetricScope\n\tAggregate bool\n}\n\n// BuildScopeQueries generates scope query results for a given scope transformation.\n// It returns a slice of results and a boolean indicating success.\n// An empty slice means an expected exception (skip this combination).\n// ok=false means an unhandled case (caller should return an error).\nfunc BuildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n) ([]ScopeQueryResult, bool) {\n\tscope := nativeScope.Max(requestedScope)\n\tresults := []ScopeQueryResult{}\n\n\thwthreadsStr := IntToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &AcceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tScope: schema.MetricScopeAccelerator,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &AcceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &HWThreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &HWThreadString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Core[core]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &HWThreadString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &HWThreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &CoreString,\n\t\t\tTypeIds: IntToStringSlice(cores),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &CoreString,\n\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &CoreString,\n\t\t\tTypeIds: IntToStringSlice(cores),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &MemoryDomainString,\n\t\t\tTypeIds: IntToStringSlice(memDomains),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slice\n\t\t\treturn results, true\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tresults = append(results, ScopeQueryResult{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &MemoryDomainString,\n\t\t\t\tTypeIds: IntToStringSlice(domains),\n\t\t\t\tScope: scope,\n\t\t\t})\n\t\t}\n\t\treturn results, true\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &MemoryDomainString,\n\t\t\tTypeIds: IntToStringSlice(memDomains),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &SocketString,\n\t\t\tTypeIds: IntToStringSlice(sockets),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &SocketString,\n\t\t\tTypeIds: IntToStringSlice(sockets),\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tresults = append(results, ScopeQueryResult{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tScope: scope,\n\t\t})\n\t\treturn results, true\n\t}\n\n\t// Unhandled Case\n\treturn nil, false\n}\n\n// IntToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to query TypeIds (string).\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc IntToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n\n// SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// If ANY of avg/min/max is NaN, ALL three are zeroed for consistency.\nfunc SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = 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{"parentUuid":"64f5a899-36f4-4081-bde7-7f804dda5d14","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GVXMBVVw8MsdsD7PVqbKN3","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"184261ca-aea4-4b8a-93c2-91d684274b71","timestamp":"2026-03-04T15:31:14.175Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"strconv\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)","newString":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strconv\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":29,"oldLines":7,"newStart":29,"newLines":6,"lines":[" import ("," \"context\""," \"fmt\"","- \"strconv\""," \"strings\""," \"time\""," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"64f5a899-36f4-4081-bde7-7f804dda5d14"}
{"parentUuid":"184261ca-aea4-4b8a-93c2-91d684274b71","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01CW3Xy1Z47qmrWXqf43xrFW","type":"message","role":"assistant","content":[{"type":"text","text":"Now replace the `sanitizeStats` calls in LoadData (takes `*APIMetricData`). I need to change them to use `SanitizeStats` with individual field pointers."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":416,"cache_read_input_tokens":68807,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":416},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHDei519ZWzYGBhyotm","type":"assistant","uuid":"ca1e402f-161d-4ee1-97bd-96ed4ec17075","timestamp":"2026-03-04T15:31:18.055Z"}
{"parentUuid":"ca1e402f-161d-4ee1-97bd-96ed4ec17075","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01CW3Xy1Z47qmrWXqf43xrFW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013andMWi2VUT9XuuiLgoZ8j","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","old_string":"\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)","new_string":"\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":416,"cache_read_input_tokens":68807,"output_tokens":847,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":416,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHDei519ZWzYGBhyotm","type":"assistant","uuid":"a39e1c86-1400-4d6c-b0a5-d20395687a9b","timestamp":"2026-03-04T15:31:27.264Z"}
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{"parentUuid":"a39e1c86-1400-4d6c-b0a5-d20395687a9b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013andMWi2VUT9XuuiLgoZ8j","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"374f6647-67f2-4ed6-8b05-f348f5289950","timestamp":"2026-03-04T15:31:27.295Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)","newString":"\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// Pre-converted scope strings avoid repeated string(MetricScope) allocations during\n// query construction. These are used in APIQuery.Type field throughout buildQueries\n// and buildNodeQueries functions. Converting once at package initialization improves\n// performance for high-volume query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":185,"oldLines":7,"newStart":185,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res)","+ SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," jobMetric.Series = append(jobMetric.Series, schema.Series{"," Hostname: query.Hostname,"]},{"oldStart":215,"oldLines":18,"newStart":215,"newLines":6,"lines":[" return jobData, nil"," }"," ","-// Pre-converted scope strings avoid repeated string(MetricScope) allocations during","-// query construction. These are used in APIQuery.Type field throughout buildQueries","-// and buildNodeQueries functions. Converting once at package initialization improves","-// performance for high-volume query building.","-var (","- hwthreadString = string(schema.MetricScopeHWThread)","- coreString = string(schema.MetricScopeCore)","- memoryDomainString = string(schema.MetricScopeMemoryDomain)","- socketString = string(schema.MetricScopeSocket)","- acceleratorString = string(schema.MetricScopeAccelerator)","-)","-"," // buildQueries constructs APIQuery structures with automatic scope transformation for a job."," //"," // This function implements the core scope transformation logic, handling all combinations of"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a39e1c86-1400-4d6c-b0a5-d20395687a9b"}
{"parentUuid":"374f6647-67f2-4ed6-8b05-f348f5289950","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_015njJKZABesJnWDkNohpSBW","type":"message","role":"assistant","content":[{"type":"text","text":"Now replace the entire `buildQueries` function body (the scope transformation part) with a call to `BuildScopeQueries`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":976,"cache_read_input_tokens":69223,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":976},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHEcoWFXoiLeQPBrjai","type":"assistant","uuid":"0a16a05d-6725-4f6a-aba7-37def2d3067e","timestamp":"2026-03-04T15:31:30.246Z"}
{"parentUuid":"0a16a05d-6725-4f6a-aba7-37def2d3067e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_015njJKZABesJnWDkNohpSBW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01T6AriGn3dLNufYR1jGGeWL","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","old_string":"\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}","new_string":"\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, 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{"parentUuid":"e0ab4422-533f-41f5-b7c3-daa8e6ea2b2a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01T6AriGn3dLNufYR1jGGeWL","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"a2a5fb0c-5de5-4793-b88e-ee2e65bed6c8","timestamp":"2026-03-04T15:31:56.199Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}","newString":"\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(host.Accelerators) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: host.Accelerators,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(hwthreads),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: host.Hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":280,"oldLines":9,"newStart":280,"newLines":10,"lines":[" }"," }"," ","- // Avoid duplicates using map for O(1) lookup","- handledScopes := make(map[schema.MetricScope]bool, 3)","+ // Avoid duplicates...","+ handledScopes := make([]schema.MetricScope, 0, 3)"," ","+ scopesLoop:"," for _, requestedScope := range scopes {"," nativeScope := mc.Scope"," if nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {"]},{"oldStart":290,"oldLines":10,"newStart":291,"newLines":12,"lines":[" }"," "," scope := nativeScope.Max(requestedScope)","- if handledScopes[scope] {","- continue","+ for _, s := range handledScopes {","+ if scope == s {","+ continue scopesLoop","+ }"," }","- handledScopes[scope] = true","+ handledScopes = append(handledScopes, scope)"," "," for _, host := range job.Resources {"," hwthreads := host.HWThreads"]},{"oldStart":301,"oldLines":224,"newStart":304,"newLines":27,"lines":[" hwthreads = topology.Node"," }"," ","- // Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)","- if nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {","- if scope != schema.MetricScopeAccelerator {","- // Skip all other catched cases","- continue","- }","+ scopeResults, ok := BuildScopeQueries(","+ nativeScope, requestedScope,","+ metric, host.Hostname,","+ &topology, hwthreads, host.Accelerators,","+ )"," ","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: false,","- Type: &acceleratorString,","- TypeIds: host.Accelerators,","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, schema.MetricScopeAccelerator)","- continue","+ if !ok {","+ return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," ","- // Accelerator -> Node","- if nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {","- if len(host.Accelerators) == 0 {","- continue","- }","-","+ for _, sr := range scopeResults {"," queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &acceleratorString,","- TypeIds: host.Accelerators,","+ Metric: sr.Metric,","+ Hostname: sr.Hostname,","+ Aggregate: sr.Aggregate,","+ Type: sr.Type,","+ TypeIds: sr.TypeIds,"," Resolution: resolution,"," })","- assignedScope = append(assignedScope, scope)","- continue","+ assignedScope = append(assignedScope, sr.Scope)"," }","-","- // HWThread -> HWThread","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: false,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(hwthreads),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // HWThread -> Core","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- for _, core := range cores {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Core[core]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // HWThread -> Socket","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // HWThread -> Node","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(hwthreads),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Core -> Core","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: false,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Core -> Socket","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromCores(hwthreads)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // Core -> Node","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // MemoryDomain -> MemoryDomain","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {","- sockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: false,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // MemoryDomain -> Node","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {","- sockets, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Socket -> Socket","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: false,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Socket -> Node","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Aggregate: true,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Node -> Node","- if nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: host.Hostname,","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," }"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"e0ab4422-533f-41f5-b7c3-daa8e6ea2b2a"}
{"parentUuid":"a2a5fb0c-5de5-4793-b88e-ee2e65bed6c8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01JkDN3EqRfxwNSXX7QJs9ug","type":"message","role":"assistant","content":[{"type":"text","text":"Good, those errors are from `buildNodeQueries` which still uses the old constants. Now replace `buildNodeQueries`'s inline if-chain similarly. Let me also update the `sanitizeStats` calls in `LoadStats`, `LoadScopedStats`, `LoadNodeData`, and `LoadNodeListData`."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3331,"cache_read_input_tokens":70199,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3331},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHGkQx5rnXBtoAQXpVQ","type":"assistant","uuid":"e197c8f5-bb02-4eac-bcbd-f091af4cc804","timestamp":"2026-03-04T15:32:03.414Z"}
{"parentUuid":"e197c8f5-bb02-4eac-bcbd-f091af4cc804","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01JkDN3EqRfxwNSXX7QJs9ug","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01STVMsEY7SdxDH4bZ9QRKHz","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","old_string":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {","new_string":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3331,"cache_read_input_tokens":70199,"output_tokens":273,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3331,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHGkQx5rnXBtoAQXpVQ","type":"assistant","uuid":"84f2ff38-114b-4ffd-b437-6289be782ba5","timestamp":"2026-03-04T15:32:04.008Z"}
{"parentUuid":"84f2ff38-114b-4ffd-b437-6289be782ba5","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01STVMsEY7SdxDH4bZ9QRKHz","toolUseID":"toolu_01STVMsEY7SdxDH4bZ9QRKHz","timestamp":"2026-03-04T15:32:04.077Z","uuid":"38cc1c02-2ae4-4664-ae6f-c6249a8f9140"}
{"parentUuid":"84f2ff38-114b-4ffd-b437-6289be782ba5","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01STVMsEY7SdxDH4bZ9QRKHz","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"87cc1603-c073-49ee-af46-d47d0050d070","timestamp":"2026-03-04T15:32:04.076Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {","newString":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":392,"oldLines":7,"newStart":392,"newLines":7,"lines":[" stats[metric] = metricdata"," }"," ","- if data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {","+ if data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic"," cclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)"," continue"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"84f2ff38-114b-4ffd-b437-6289be782ba5"}
{"parentUuid":"87cc1603-c073-49ee-af46-d47d0050d070","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01NcQVHkbPrfjXqVCYHHwPje","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me replace the sanitizeStats calls in LoadScopedStats (takes `*APIMetricData`):"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":645,"cache_read_input_tokens":73530,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":645},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHHL7zVJcKP6rukMv2U","type":"assistant","uuid":"3fd76523-88f1-47f4-8f69-176d2fd1cb50","timestamp":"2026-03-04T15:32:06.917Z"}
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{"parentUuid":"a24730f2-fbb3-4709-8873-659ffa7c66bc","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WgGNSbrgb9zGddNetMRumh","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"c076b260-f201-4388-85f3-b1a1c3a53ab3","timestamp":"2026-03-04T15:32:09.265Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{","newString":"\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":488,"oldLines":7,"newStart":488,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res)","+ SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," scopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{"," Hostname: query.Hostname,"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a24730f2-fbb3-4709-8873-659ffa7c66bc"}
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{"parentUuid":"6d6d5a30-1d48-4e29-ba03-820d1366c001","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HD5ez7L3NKbGQnuSv5Xm6e","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"36f45b88-132a-46b1-8fe4-eb412e392e5a","timestamp":"2026-03-04T15:32:13.956Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]","newString":"\t\tSanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":589,"oldLines":7,"newStart":589,"newLines":7,"lines":[" errors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))"," }"," ","- sanitizeStats(&qdata)","+ SanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)"," "," hostdata, ok := data[query.Hostname]"," if !ok {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"6d6d5a30-1d48-4e29-ba03-820d1366c001"}
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{"parentUuid":"45f8d8be-0a9a-4a40-b1ac-f6853732b4fb","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VgKwD3w8pcB7CgWSDUFsne","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"8b9f6a22-7079-49ae-8702-c8d75e02024c","timestamp":"2026-03-04T15:32:17.802Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{","newString":"\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tSanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":770,"oldLines":7,"newStart":770,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res)","+ SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," scopeData.Series = append(scopeData.Series, schema.Series{"," Hostname: query.Hostname,"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"45f8d8be-0a9a-4a40-b1ac-f6853732b4fb"}
{"parentUuid":"8b9f6a22-7079-49ae-8702-c8d75e02024c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01THqgcYURm8wTqg7LVUYWoG","type":"message","role":"assistant","content":[{"type":"text","text":"Now replace the entire `buildNodeQueries` inline if-chain with `BuildScopeQueries`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":263,"cache_read_input_tokens":75074,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":263},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHJLwstRFqA4mmYJ1qh","type":"assistant","uuid":"ea45881d-e141-4fd6-a9f6-47dee7517bd4","timestamp":"2026-03-04T15:32:21.303Z"}
{"parentUuid":"ea45881d-e141-4fd6-a9f6-47dee7517bd4","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01THqgcYURm8wTqg7LVUYWoG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AJrwNFftQo12e7tRDEAUkV","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","old_string":"\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}","new_string":"\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tnodeScopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue nodeScopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, hostname,\n\t\t\t\t\t&topology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":263,"cache_read_input_tokens":75074,"output_tokens":3556,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":263,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHJLwstRFqA4mmYJ1qh","type":"assistant","uuid":"5b6360af-e3f4-48cd-ad7b-8fdc6b762d45","timestamp":"2026-03-04T15:32:54.713Z"}
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{\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}","newString":"\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tnodeScopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue nodeScopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, hostname,\n\t\t\t\t\t&topology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tSanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates using map for O(1) lookup\n\t\thandledScopes := make(map[schema.MetricScope]bool, 3)\n\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tif handledScopes[scope] {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\thandledScopes[scope] = true\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\t\t\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t\t\t\t// Skip all other catched cases\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, schema.MetricScopeAccelerator)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Accelerator -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\t\t\t\tif len(acceleratorIds) == 0 {\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &acceleratorString,\n\t\t\t\t\t\tTypeIds: acceleratorIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> HWThread\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, core := range cores {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// HWThread -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &hwthreadString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Node),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Core\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromCores(topology.Node)\n\t\t\t\t\tfor _, socket := range sockets {\n\t\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t\t})\n\t\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\t}\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Core -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\t\t\t\tcores, _ := topology.GetCoresFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &coreString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> MemoryDomain\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// MemoryDomain -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &memoryDomainString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Socket\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: false,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Socket -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\t\t\t\tsockets, _ := topology.GetSocketsFromHWThreads(topology.Node)\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tAggregate: true,\n\t\t\t\t\t\tType: &socketString,\n\t\t\t\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\t// Node -> Node\n\t\t\t\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: metric,\n\t\t\t\t\t\tHostname: hostname,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, scope)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// sanitizeStats converts NaN statistics to zero for JSON compatibility.\n//\n// schema.Float with NaN values cannot be properly JSON-encoded, so we convert\n// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",\n// but maintains API compatibility.\nfunc sanitizeStats(data *APIMetricData) {\n\tif data.Avg.IsNaN() {\n\t\tdata.Avg = schema.Float(0)\n\t}\n\tif data.Min.IsNaN() {\n\t\tdata.Min = schema.Float(0)\n\t}\n\tif data.Max.IsNaN() {\n\t\tdata.Max = schema.Float(0)\n\t}\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).\n//\n// Optimized to reuse a byte buffer for string conversion, reducing allocations.\nfunc intToStringSlice(is []int) []string {\n\tif len(is) == 0 {\n\t\treturn nil\n\t}\n\n\tss := make([]string, len(is))\n\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n\tfor i, x := range is {\n\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n\t\tss[i] = string(buf)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":853,"oldLines":17,"newStart":853,"newLines":20,"lines":[" }"," }"," ","- // Avoid duplicates using map for O(1) lookup","- handledScopes := make(map[schema.MetricScope]bool, 3)","+ // Avoid duplicates...","+ handledScopes := make([]schema.MetricScope, 0, 3)"," ","+ nodeScopesLoop:"," for _, requestedScope := range scopes {"," nativeScope := mc.Scope"," "," scope := nativeScope.Max(requestedScope)","- if handledScopes[scope] {","- continue","+ for _, s := range handledScopes {","+ if scope == s {","+ continue nodeScopesLoop","+ }"," }","- handledScopes[scope] = true","+ handledScopes = append(handledScopes, scope)"," "," for _, hostname := range nodes {"," "]},{"oldStart":879,"oldLines":8,"newStart":882,"newLines":7,"lines":[" }"," }"," ","- // Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable","- // Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable","+ // Always full node hwthread id list, no partial queries expected"," topology := subClusterTopol.Topology"," acceleratorIds := topology.GetAcceleratorIDs()"," "]},{"oldStart":889,"oldLines":262,"newStart":891,"newLines":30,"lines":[" continue"," }"," ","- // Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)","- if nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {","- if scope != schema.MetricScopeAccelerator {","- // Skip all other catched cases","- continue","- }","+ scopeResults, ok := BuildScopeQueries(","+ nativeScope, requestedScope,","+ metric, hostname,","+ &topology, topology.Node, acceleratorIds,","+ )"," ","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &acceleratorString,","- TypeIds: acceleratorIds,","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, schema.MetricScopeAccelerator)","- continue","+ if !ok {","+ return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," ","- // Accelerator -> Node","- if nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {","- if len(acceleratorIds) == 0 {","- continue","- }","-","+ for _, sr := range scopeResults {"," queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &acceleratorString,","- TypeIds: acceleratorIds,","+ Metric: sr.Metric,","+ Hostname: sr.Hostname,","+ Aggregate: sr.Aggregate,","+ Type: sr.Type,","+ TypeIds: sr.TypeIds,"," Resolution: resolution,"," })","- assignedScope = append(assignedScope, scope)","- continue","+ assignedScope = append(assignedScope, sr.Scope)"," }","-","- // HWThread -> HWThread","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Node),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // HWThread -> Core","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(topology.Node)","- for _, core := range cores {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Core[core]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // HWThread -> Socket","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(topology.Node)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // HWThread -> Node","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Node),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Core -> Core","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Core -> Socket","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromCores(topology.Node)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- }","- continue","- }","-","- // Core -> Node","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {","- cores, _ := topology.GetCoresFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // MemoryDomain -> MemoryDomain","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {","- sockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // MemoryDomain -> Node","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {","- sockets, _ := topology.GetMemoryDomainsFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Socket -> Socket","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Socket -> Node","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {","- sockets, _ := topology.GetSocketsFromHWThreads(topology.Node)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- // Node -> Node","- if nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Resolution: resolution,","- })","- assignedScope = append(assignedScope, scope)","- continue","- }","-","- return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," }"," }"," "," return queries, assignedScope, nil"," }","-","-// sanitizeStats converts NaN statistics to zero for JSON compatibility.","-//","-// schema.Float with NaN values cannot be properly JSON-encoded, so we convert","-// NaN to 0. This loses the distinction between \"no data\" and \"zero value\",","-// but maintains API compatibility.","-func sanitizeStats(data *APIMetricData) {","- if data.Avg.IsNaN() {","- data.Avg = schema.Float(0)","- }","- if data.Min.IsNaN() {","- data.Min = schema.Float(0)","- }","- if data.Max.IsNaN() {","- data.Max = schema.Float(0)","- }","-}","-","-// intToStringSlice converts a slice of integers to a slice of strings.","-// Used to convert hardware thread/core/socket IDs from topology (int) to APIQuery TypeIds (string).","-//","-// Optimized to reuse a byte buffer for string conversion, reducing allocations.","-func intToStringSlice(is []int) []string {","- if len(is) == 0 {","- return nil","- }","-","- ss := make([]string, len(is))","- buf := make([]byte, 0, 16) // Reusable buffer for integer conversion","- for i, x := range is {","- buf = strconv.AppendInt(buf[:0], int64(x), 10)","- ss[i] = string(buf)","- }","- return ss","-}"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"5b6360af-e3f4-48cd-ad7b-8fdc6b762d45"}
{"parentUuid":"1b1f9b67-0ca9-40da-a00a-fdefa9348197","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01L5n7VyBvqmY8Ts1Lf3RzFP","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me also undo the nolint comment I added — that was in LoadStats where it checks NaN inline (not using sanitizeStats). Let me check:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3601,"cache_read_input_tokens":75337,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3601},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHM54UzxfbUvdedVqPq","type":"assistant","uuid":"a5ff9b08-3c4a-4d5d-94a7-81c61877a21e","timestamp":"2026-03-04T15:32:58.349Z"}
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{"parentUuid":"f1927ef4-f49f-4919-af65-b59b895f1498","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01JLqg67447srj4WjhxYX7ZF","toolUseID":"toolu_01JLqg67447srj4WjhxYX7ZF","timestamp":"2026-03-04T15:33:00.024Z","uuid":"2a26216e-f4aa-492a-8897-938902c95bed"}
{"parentUuid":"f1927ef4-f49f-4919-af65-b59b895f1498","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JLqg67447srj4WjhxYX7ZF","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"648b82fc-8380-4669-ab12-f5b2f4667a1b","timestamp":"2026-03-04T15:33:00.023Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic","newString":"\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file implements high-level query functions for loading job metric data\n// with automatic scope transformation and aggregation.\n//\n// Key Concepts:\n//\n// Metric Scopes: Metrics are collected at different granularities (native scope):\n// - HWThread: Per hardware thread\n// - Core: Per CPU core\n// - Socket: Per CPU socket\n// - MemoryDomain: Per memory domain (NUMA)\n// - Accelerator: Per GPU/accelerator\n// - Node: Per compute node\n//\n// Scope Transformation: The buildQueries functions transform between native scope\n// and requested scope by:\n// - Aggregating finer-grained data (e.g., HWThread → Core → Socket → Node)\n// - Rejecting requests for finer granularity than available\n// - Handling special cases (e.g., Accelerator metrics)\n//\n// Query Building: Constructs APIQuery structures with proper selectors (Type, TypeIds)\n// based on cluster topology and job resources.\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\ntype InternalMetricStore struct{}\n\nvar MetricStoreHandle *InternalMetricStore\n\n// HealthCheck delegates to the internal MemoryStore's HealthCheck.\nfunc (ccms *InternalMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]HealthCheckResult, error) {\n\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n}\n\n// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n// When set to a non-nil function, LoadData will call this function instead of the default implementation.\nvar TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n\n// LoadData loads metric data for a specific job with automatic scope transformation.\n//\n// This is the primary function for retrieving job metric data. It handles:\n// - Building queries with scope transformation via buildQueries\n// - Fetching data from the metric store\n// - Organizing results by metric and scope\n// - Converting NaN statistics to 0 for JSON compatibility\n// - Partial error handling (returns data for successful queries even if some fail)\n//\n// Parameters:\n// - job: Job metadata including cluster, resources, and time range\n// - metrics: List of metric names to load\n// - scopes: Requested metric scopes (will be transformed to match native scopes)\n// - ctx: Context for cancellation (currently unused but reserved for future use)\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns:\n// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n//\n// Example:\n//\n//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\nfunc (ccms *InternalMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tif TestLoadDataCallback != nil {\n\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n\t}\n\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n//\n// This function implements the core scope transformation logic, handling all combinations of\n// native metric scopes and requested scopes. It uses the cluster topology to determine which\n// hardware IDs to include in each query.\n//\n// Scope Transformation Rules:\n// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n// - If native scope < requested scope: Returns error (cannot increase granularity)\n// - Special handling for Accelerator scope (independent of CPU hierarchy)\n//\n// The function generates one or more APIQuery per (metric, scope, host) combination:\n// - For non-aggregated queries: One query with all relevant IDs\n// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n//\n// Parameters:\n// - job: Job metadata including cluster, subcluster, and resource allocation\n// - metrics: List of metrics to query\n// - scopes: Requested scopes for each metric\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query (after transformation)\n// - error: Returns error if topology lookup fails or unhandled scope combination encountered\nfunc buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tif len(job.Resources) == 0 {\n\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n\t}\n\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := []schema.MetricScope{}\n\n\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n\tif scerr != nil {\n\t\treturn nil, nil, scerr\n\t}\n\ttopology := subcluster.Topology\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, host.Hostname,\n\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n//\n// This is an optimized version of LoadData that fetches only statistics without\n// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of metric → hostname → statistics\n// - Error on query building or fetching failure\nfunc (ccms *InternalMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n//\n// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n//\n// Parameters:\n// - job: Job metadata\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tif len(row) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n//\n// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n// directly. Useful for system monitoring and node status views.\n//\n// Parameters:\n// - cluster: Cluster name\n// - metrics: List of metric names\n// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n// - scopes: Requested metric scopes (currently unused - always node scope)\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → metric → []JobMetric\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tSanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n//\n// This is the most flexible node data loading function, supporting arbitrary scopes and\n// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty string to infer from node names)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n// - from, to: Time range\n// - ctx: Context (currently unused)\n//\n// Returns:\n// - Map of hostname → JobData (metric → scope → JobMetric)\n// - Error or partial error listing failed queries\nfunc (ccms *InternalMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\t// Note: Order of node data is not guaranteed after this point\n\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCLuster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := FetchData(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = int(row[0].Resolution)\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n//\n// Similar to buildQueries but operates on node lists rather than job resources.\n// Supports dynamic subcluster lookup when subCluster parameter is empty.\n//\n// Parameters:\n// - cluster: Cluster name\n// - subCluster: SubCluster name (empty = infer from node hostnames)\n// - nodes: List of node hostnames\n// - metrics: List of metric names\n// - scopes: Requested metric scopes\n// - resolution: Data resolution in seconds\n//\n// Returns:\n// - []APIQuery: List of queries to execute\n// - []schema.MetricScope: Assigned scope for each query\n// - error: Returns error if topology lookup fails or unhandled scope combination\nfunc buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int64,\n) ([]APIQuery, []schema.MetricScope, error) {\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := []schema.MetricScope{}\n\n\t// Get Topol before loop if subCluster given\n\tvar subClusterTopol *schema.SubCluster\n\tvar scterr error\n\tif subCluster != \"\" {\n\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n\t\tif scterr != nil {\n\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n\t\t\treturn nil, nil, scterr\n\t\t}\n\t}\n\n\tfor _, metric := range metrics {\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tnodeScopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue nodeScopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n\t\t\t\t\tif scnerr != nil {\n\t\t\t\t\t\treturn nil, nil, scnerr\n\t\t\t\t\t}\n\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n\t\t\t\t\tif scterr != nil {\n\t\t\t\t\t\treturn nil, nil, scterr\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected\n\t\t\t\ttopology := subClusterTopol.Topology\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tmetric, hostname,\n\t\t\t\t\t&topology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n","structuredPatch":[{"oldStart":392,"oldLines":7,"newStart":392,"newLines":7,"lines":[" stats[metric] = metricdata"," }"," ","- if data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() { //nolint:gocritic","+ if data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {"," cclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)"," continue"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"f1927ef4-f49f-4919-af65-b59b895f1498"}
{"parentUuid":"648b82fc-8380-4669-ab12-f5b2f4667a1b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01JvmchByA2vATqhFUCEb5xm","type":"message","role":"assistant","content":[{"type":"text","text":"Let me verify the file compiles:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":284,"cache_read_input_tokens":78938,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":284},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHMTdJ2vjv97hpGeidg","type":"assistant","uuid":"4ce4dc32-6159-4306-825e-1917e80e7adf","timestamp":"2026-03-04T15:33:02.582Z"}
{"parentUuid":"4ce4dc32-6159-4306-825e-1917e80e7adf","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01JvmchByA2vATqhFUCEb5xm","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_014FsMzyxDDB2ESJdHrWRLse","name":"Bash","input":{"command":"go build ./pkg/metricstore/... 2>&1","description":"Build metricstore package"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":284,"cache_read_input_tokens":78938,"output_tokens":114,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":284,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHMTdJ2vjv97hpGeidg","type":"assistant","uuid":"f8451a69-8af1-4173-a8aa-676e096c9ada","timestamp":"2026-03-04T15:33:03.302Z"}
{"parentUuid":"f8451a69-8af1-4173-a8aa-676e096c9ada","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014FsMzyxDDB2ESJdHrWRLse","type":"tool_result","content":"","is_error":false}]},"uuid":"a4ae8a22-fd6e-4744-a53d-522fa6f12b84","timestamp":"2026-03-04T15:33:03.829Z","toolUseResult":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"f8451a69-8af1-4173-a8aa-676e096c9ada"}
{"parentUuid":"a4ae8a22-fd6e-4744-a53d-522fa6f12b84","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01P4HbfE7zgRWsgYSAeRaq9x","type":"message","role":"assistant","content":[{"type":"text","text":"Clean build. Now update metricstoreclient."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":299,"cache_read_input_tokens":79222,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":299},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHMjq813C34yKSqFViR","type":"assistant","uuid":"a5229016-8ebd-4e9c-98de-9997b7a0f346","timestamp":"2026-03-04T15:33:06.378Z"}
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{"parentUuid":"af1037a3-0be9-4f6e-a645-69d437471682","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DN62TwwecwCkAfzXUbKN9q","type":"tool_result","content":"Updated task #2 status"}]},"uuid":"a45b2c27-0324-409b-85dc-30f37ec76682","timestamp":"2026-03-04T15:33:06.968Z","toolUseResult":{"success":true,"taskId":"2","updatedFields":["status"],"statusChange":{"from":"in_progress","to":"completed"}},"sourceToolAssistantUUID":"af1037a3-0be9-4f6e-a645-69d437471682"}
{"parentUuid":"a45b2c27-0324-409b-85dc-30f37ec76682","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01P4HbfE7zgRWsgYSAeRaq9x","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016smZMG2bFDcMPia3UCXc8F","name":"TaskUpdate","input":{"taskId":"3","status":"in_progress"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":299,"cache_read_input_tokens":79222,"output_tokens":138,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":299,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHMjq813C34yKSqFViR","type":"assistant","uuid":"49a19c77-414e-46be-a102-990462c4babd","timestamp":"2026-03-04T15:33:07.647Z"}
{"parentUuid":"49a19c77-414e-46be-a102-990462c4babd","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016smZMG2bFDcMPia3UCXc8F","type":"tool_result","content":"Updated task #3 status"}]},"uuid":"17c94f52-780b-46f8-b645-eed61898477c","timestamp":"2026-03-04T15:33:07.756Z","toolUseResult":{"success":true,"taskId":"3","updatedFields":["status"],"statusChange":{"from":"pending","to":"in_progress"}},"sourceToolAssistantUUID":"49a19c77-414e-46be-a102-990462c4babd"}
{"parentUuid":"17c94f52-780b-46f8-b645-eed61898477c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01HpHT9zH2iAEogis5FX57KZ","type":"message","role":"assistant","content":[{"type":"text","text":"Now update `internal/metricstoreclient/cc-metric-store-queries.go` — replace `buildScopeQueries` with `BuildScopeQueries`, remove local helpers:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":211,"cache_read_input_tokens":79521,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":211},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHN2UEec63n7up4Rqee","type":"assistant","uuid":"5d6620c0-2396-4d77-8d8f-90c57d2b17d2","timestamp":"2026-03-04T15:33:11.176Z"}
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{"parentUuid":"8f84b03b-dbc9-458d-84b8-76dd35d9a96e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0118A7ztKxW5TV8s3qSJrcC1","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"c5dba356-702c-4e4f-9cbf-f83dcb3209f0","timestamp":"2026-03-04T15:33:13.715Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"import (\n\t\"fmt\"\n\t\"strconv\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)","newString":"import (\n\t\"fmt\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\t\"strconv\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Scope string constants used in API queries.\n// Pre-converted to avoid repeated allocations during query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":37,"oldLines":9,"newStart":37,"newLines":9,"lines":[" "," import ("," \"fmt\"","- \"strconv\""," "," \"github.com/ClusterCockpit/cc-backend/pkg/archive\"","+ \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\""," cclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\""," \"github.com/ClusterCockpit/cc-lib/v2/schema\""," )"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"8f84b03b-dbc9-458d-84b8-76dd35d9a96e"}
{"parentUuid":"c5dba356-702c-4e4f-9cbf-f83dcb3209f0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01Vy9nmYj58qVAn2vtWfPanL","type":"message","role":"assistant","content":[{"type":"text","text":"Remove local scope string constants:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":424,"cache_read_input_tokens":79732,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":424},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHNTyQWsG4dCJEi1Nsq","type":"assistant","uuid":"e0f44779-7af8-4e55-b89e-078a40ad8e4c","timestamp":"2026-03-04T15:33:16.353Z"}
{"parentUuid":"e0f44779-7af8-4e55-b89e-078a40ad8e4c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01Vy9nmYj58qVAn2vtWfPanL","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KtQiMn8vn3MF86xcbisoho","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","old_string":"// Scope string constants used in API queries.\n// Pre-converted to avoid repeated allocations during query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries","new_string":"// buildQueries"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":424,"cache_read_input_tokens":79732,"output_tokens":287,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":424,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHNTyQWsG4dCJEi1Nsq","type":"assistant","uuid":"46135af1-857d-4da9-bf7b-9b170d19afc7","timestamp":"2026-03-04T15:33:19.081Z"}
{"parentUuid":"46135af1-857d-4da9-bf7b-9b170d19afc7","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01KtQiMn8vn3MF86xcbisoho","toolUseID":"toolu_01KtQiMn8vn3MF86xcbisoho","timestamp":"2026-03-04T15:33:19.097Z","uuid":"bdbeb639-7c89-49bd-857f-9d1a85c06285"}
{"parentUuid":"46135af1-857d-4da9-bf7b-9b170d19afc7","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KtQiMn8vn3MF86xcbisoho","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"d5deaa18-8272-4547-9224-83fe3971a3af","timestamp":"2026-03-04T15:33:19.096Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"// Scope string constants used in API queries.\n// Pre-converted to avoid repeated allocations during query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries","newString":"// buildQueries","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Scope string constants used in API queries.\n// Pre-converted to avoid repeated allocations during query building.\nvar (\n\thwthreadString = string(schema.MetricScopeHWThread)\n\tcoreString = string(schema.MetricScopeCore)\n\tmemoryDomainString = string(schema.MetricScopeMemoryDomain)\n\tsocketString = string(schema.MetricScopeSocket)\n\tacceleratorString = string(schema.MetricScopeAccelerator)\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":44,"oldLines":16,"newStart":44,"newLines":6,"lines":[" \"github.com/ClusterCockpit/cc-lib/v2/schema\""," )"," ","-// Scope string constants used in API queries.","-// Pre-converted to avoid repeated allocations during query building.","-var (","- hwthreadString = string(schema.MetricScopeHWThread)","- coreString = string(schema.MetricScopeCore)","- memoryDomainString = string(schema.MetricScopeMemoryDomain)","- socketString = string(schema.MetricScopeSocket)","- acceleratorString = string(schema.MetricScopeAccelerator)","-)","-"," // buildQueries constructs API queries for job-specific metric data."," // It iterates through metrics, scopes, and job resources to build the complete query set."," //"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"46135af1-857d-4da9-bf7b-9b170d19afc7"}
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{"parentUuid":"f501e7ed-0b0a-4a48-a5b7-d787cadd982e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01LPbmf8UnqZGPygfE4DLgYG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VW9FyLgTjfWK12SPamB76w","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","old_string":"\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)","new_string":"\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":459,"cache_read_input_tokens":80156,"output_tokens":585,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":459,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHNsG8Aun6WoSfMbTTf","type":"assistant","uuid":"7dbb54ac-8ecb-4864-b2b6-990663590082","timestamp":"2026-03-04T15:33:29.484Z"}
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{"parentUuid":"7dbb54ac-8ecb-4864-b2b6-990663590082","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VW9FyLgTjfWK12SPamB76w","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"0df6e17f-3b3a-446c-8232-9583ccd6bd8f","timestamp":"2026-03-04T15:33:29.598Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)","newString":"\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\t// Note: Expected exceptions will return as empty slices -> Continue\n\t\t\t\thostQueries, hostScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\t// Note: Unexpected errors, such as unhandled cases, will return as nils -> Error\n\t\t\t\tif hostQueries == nil && hostScopes == nil {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, hostQueries...)\n\t\t\t\tassignedScope = append(assignedScope, hostScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":116,"oldLines":21,"newStart":116,"newLines":27,"lines":[" hwthreads = topology.Node"," }"," ","- // Note: Expected exceptions will return as empty slices -> Continue","- hostQueries, hostScopes := buildScopeQueries(","+ scopeResults, ok := metricstore.BuildScopeQueries("," nativeScope, requestedScope,"," remoteName, host.Hostname,"," topology, hwthreads, host.Accelerators,","- resolution,"," )"," ","- // Note: Unexpected errors, such as unhandled cases, will return as nils -> Error","- if hostQueries == nil && hostScopes == nil {","+ if !ok {"," return nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," ","- queries = append(queries, hostQueries...)","- assignedScope = append(assignedScope, hostScopes...)","+ for _, sr := range scopeResults {","+ queries = append(queries, APIQuery{","+ Metric: sr.Metric,","+ Hostname: sr.Hostname,","+ Aggregate: sr.Aggregate,","+ Type: sr.Type,","+ TypeIds: sr.TypeIds,","+ Resolution: resolution,","+ })","+ assignedScope = append(assignedScope, sr.Scope)","+ }"," }"," }"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"7dbb54ac-8ecb-4864-b2b6-990663590082"}
{"parentUuid":"0df6e17f-3b3a-446c-8232-9583ccd6bd8f","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01QXJFtG2hjEPbpdXvdWjtB8","type":"message","role":"assistant","content":[{"type":"text","text":"Now do the same for `buildNodeQueries`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":969,"cache_read_input_tokens":80615,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":969},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHPdvyKNf3LR2DtZTA5","type":"assistant","uuid":"8650f56e-cdcb-4866-a313-01bed5d5f41b","timestamp":"2026-03-04T15:33:32.345Z"}
{"parentUuid":"8650f56e-cdcb-4866-a313-01bed5d5f41b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01QXJFtG2hjEPbpdXvdWjtB8","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01EoGHMD3jAbsScmhd92WVez","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","old_string":"\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)","new_string":"\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":969,"cache_read_input_tokens":80615,"output_tokens":529,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":969,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHPdvyKNf3LR2DtZTA5","type":"assistant","uuid":"537595a2-aaea-4efb-81cf-ae82cca56c45","timestamp":"2026-03-04T15:33:35.923Z"}
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{"parentUuid":"537595a2-aaea-4efb-81cf-ae82cca56c45","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01EoGHMD3jAbsScmhd92WVez","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"a08faade-a915-4639-8b3e-7d56789ac2f6","timestamp":"2026-03-04T15:33:35.987Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)","newString":"\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tnodeQueries, nodeScopes := buildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t\tresolution,\n\t\t\t\t)\n\n\t\t\t\tif len(nodeQueries) == 0 && len(nodeScopes) == 0 {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tqueries = append(queries, nodeQueries...)\n\t\t\t\tassignedScope = append(assignedScope, nodeScopes...)\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":227,"oldLines":19,"newStart":227,"newLines":27,"lines":[" continue scopesLoop"," }"," ","- nodeQueries, nodeScopes := buildScopeQueries(","+ scopeResults, ok := metricstore.BuildScopeQueries("," nativeScope, requestedScope,"," remoteName, hostname,"," topology, topology.Node, acceleratorIds,","- resolution,"," )"," ","- if len(nodeQueries) == 0 && len(nodeScopes) == 0 {","+ if !ok {"," return nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," ","- queries = append(queries, nodeQueries...)","- assignedScope = append(assignedScope, nodeScopes...)","+ for _, sr := range scopeResults {","+ queries = append(queries, APIQuery{","+ Metric: sr.Metric,","+ Hostname: sr.Hostname,","+ Aggregate: sr.Aggregate,","+ Type: sr.Type,","+ TypeIds: sr.TypeIds,","+ Resolution: resolution,","+ })","+ assignedScope = append(assignedScope, sr.Scope)","+ }"," }"," }"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"537595a2-aaea-4efb-81cf-ae82cca56c45"}
{"parentUuid":"a08faade-a915-4639-8b3e-7d56789ac2f6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01AeRJCm3t2PDPqUyR2PSCP7","type":"message","role":"assistant","content":[{"type":"text","text":"Good — those errors are from the old `buildScopeQueries` function that still exists. Now delete it and `intToStringSlice`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":913,"cache_read_input_tokens":81584,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":913},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHQ6yf6tuiyCgcYVUp4","type":"assistant","uuid":"312c0487-cab2-4c19-bebb-b40f868eccff","timestamp":"2026-03-04T15:33:39.442Z"}
{"parentUuid":"312c0487-cab2-4c19-bebb-b40f868eccff","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01AeRJCm3t2PDPqUyR2PSCP7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Bn3djAYPcNXVkUHEZEDnuf","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","old_string":"// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}","new_string":""},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":913,"cache_read_input_tokens":81584,"output_tokens":2877,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":913,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHQ6yf6tuiyCgcYVUp4","type":"assistant","uuid":"ccc57f11-4eb5-4fbb-b17f-37fa70d76765","timestamp":"2026-03-04T15:34:06.820Z"}
{"parentUuid":"ccc57f11-4eb5-4fbb-b17f-37fa70d76765","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01Bn3djAYPcNXVkUHEZEDnuf","toolUseID":"toolu_01Bn3djAYPcNXVkUHEZEDnuf","timestamp":"2026-03-04T15:34:06.940Z","uuid":"e49b65a9-abcc-48b3-b0cc-f5931092e083"}
{"parentUuid":"ccc57f11-4eb5-4fbb-b17f-37fa70d76765","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Bn3djAYPcNXVkUHEZEDnuf","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"41da93ec-e279-4e0e-bc4f-6c875c2402c7","timestamp":"2026-03-04T15:34:06.939Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}","newString":"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient - Query Building\n//\n// This file contains the query construction and scope transformation logic for cc-metric-store queries.\n// It handles the complex mapping between requested metric scopes and native hardware topology,\n// automatically aggregating or filtering metrics as needed.\n//\n// # Scope Transformations\n//\n// The buildScopeQueries function implements the core scope transformation algorithm.\n// It handles 25+ different transformation cases, mapping between:\n// - Accelerator (GPU) scope\n// - HWThread (hardware thread/SMT) scope\n// - Core (CPU core) scope\n// - Socket (CPU package) scope\n// - MemoryDomain (NUMA domain) scope\n// - Node (full system) scope\n//\n// Transformations follow these rules:\n// - Same scope: Return data as-is (e.g., Core → Core)\n// - Coarser scope: Aggregate data (e.g., Core → Socket with Aggregate=true)\n// - Finer scope: Error - cannot increase granularity\n//\n// # Query Building\n//\n// buildQueries and buildNodeQueries are the main entry points, handling job-specific\n// and node-specific query construction respectively. They:\n// - Validate metric configurations\n// - Handle subcluster-specific metric filtering\n// - Detect and skip duplicate scope requests\n// - Call buildScopeQueries for each metric/scope/host combination\npackage metricstoreclient\n\nimport (\n\t\"fmt\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// buildQueries constructs API queries for job-specific metric data.\n// It iterates through metrics, scopes, and job resources to build the complete query set.\n//\n// The function handles:\n// - Metric configuration validation and subcluster filtering\n// - Scope deduplication to avoid redundant queries\n// - Hardware thread list resolution (job-allocated vs full node)\n// - Delegation to buildScopeQueries for scope transformations\n//\n// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\nfunc (ccms *CCMetricStore) buildQueries(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n\n\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n\t\treturn nil, nil, err\n\t}\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, host := range job.Resources {\n\t\t\t\thwthreads := host.HWThreads\n\t\t\t\tif hwthreads == nil {\n\t\t\t\t\thwthreads = topology.Node\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, host.Hostname,\n\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n//\n// The function handles:\n// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n// - Full node hardware thread lists (not job-specific subsets)\n// - All accelerators on each node\n// - Metric configuration validation with subcluster filtering\n//\n// Returns queries and their corresponding assigned scopes.\nfunc (ccms *CCMetricStore) buildNodeQueries(\n\tcluster string,\n\tsubCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope, error) {\n\t// Initialize both slices together\n\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n\n\tfor _, metric := range metrics {\n\t\tremoteName := metric\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Skip if metric is removed for subcluster\n\t\tif mc.SubClusters != nil {\n\t\t\tisRemoved := false\n\t\t\tfor _, scConfig := range mc.SubClusters {\n\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\t\t\tisRemoved = true\n\t\t\t\t\tbreak\n\t\t\t\t}\n\t\t\t}\n\t\t\tif isRemoved {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t}\n\n\t\t// Avoid duplicates...\n\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n\n\tscopesLoop:\n\t\tfor _, requestedScope := range scopes {\n\t\t\tnativeScope := mc.Scope\n\n\t\t\tscope := nativeScope.Max(requestedScope)\n\t\t\tfor _, s := range handledScopes {\n\t\t\t\tif scope == s {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\t\t\t}\n\t\t\thandledScopes = append(handledScopes, scope)\n\n\t\t\tfor _, hostname := range nodes {\n\t\t\t\tvar topology *schema.Topology\n\t\t\t\tvar err error\n\n\t\t\t\t// If no subCluster given, get it by node\n\t\t\t\tif subCluster == \"\" {\n\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n\t\t\t\t} else {\n\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n\t\t\t\t}\n\n\t\t\t\tif err != nil {\n\t\t\t\t\treturn nil, nil, err\n\t\t\t\t}\n\n\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n\n\t\t\t\t// Moved check here if metric matches hardware specs\n\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n\t\t\t\t\tcontinue scopesLoop\n\t\t\t\t}\n\n\t\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n\t\t\t\t\tnativeScope, requestedScope,\n\t\t\t\t\tremoteName, hostname,\n\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n\t\t\t\t)\n\n\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}\n\n\t\t\t\tfor _, sr := range scopeResults {\n\t\t\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\t\t\tMetric: sr.Metric,\n\t\t\t\t\t\tHostname: sr.Hostname,\n\t\t\t\t\t\tAggregate: sr.Aggregate,\n\t\t\t\t\t\tType: sr.Type,\n\t\t\t\t\t\tTypeIds: sr.TypeIds,\n\t\t\t\t\t\tResolution: resolution,\n\t\t\t\t\t})\n\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn queries, assignedScope, nil\n}\n\n// buildScopeQueries generates API queries for a given scope transformation.\n// It returns a slice of queries and corresponding assigned scopes.\n// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.\nfunc buildScopeQueries(\n\tnativeScope, requestedScope schema.MetricScope,\n\tmetric, hostname string,\n\ttopology *schema.Topology,\n\thwthreads []int,\n\taccelerators []string,\n\tresolution int,\n) ([]APIQuery, []schema.MetricScope) {\n\tscope := nativeScope.Max(requestedScope)\n\tqueries := []APIQuery{}\n\tscopes := []schema.MetricScope{}\n\n\thwthreadsStr := intToStringSlice(hwthreads)\n\n\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n\t\tif scope != schema.MetricScopeAccelerator {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, schema.MetricScopeAccelerator)\n\t\treturn queries, scopes\n\t}\n\n\t// Accelerator -> Node\n\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n\t\tif len(accelerators) == 0 {\n\t\t\t// Expected Exception -> Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &acceleratorString,\n\t\t\tTypeIds: accelerators,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> HWThread\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Core\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tfor _, core := range cores {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Core[core]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Socket\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &hwthreadString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// HWThread -> Node\n\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &hwthreadString,\n\t\t\tTypeIds: hwthreadsStr,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Core\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Socket\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n\t\tfor _, socket := range sockets {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &coreString,\n\t\t\t\tTypeIds: intToStringSlice(topology.Socket[socket]),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Core -> Node\n\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &coreString,\n\t\t\tTypeIds: intToStringSlice(cores),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> MemoryDomain\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Node\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &memoryDomainString,\n\t\t\tTypeIds: intToStringSlice(memDomains),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// MemoryDomain -> Socket\n\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n\t\tif err != nil {\n\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slices\n\t\t\treturn queries, scopes\n\t\t}\n\n\t\t// Create a query for each socket\n\t\tfor _, domains := range socketToDomains {\n\t\t\tqueries = append(queries, APIQuery{\n\t\t\t\tMetric: metric,\n\t\t\t\tHostname: hostname,\n\t\t\t\tAggregate: true,\n\t\t\t\tType: &memoryDomainString,\n\t\t\t\tTypeIds: intToStringSlice(domains),\n\t\t\t\tResolution: resolution,\n\t\t\t})\n\t\t\t// Add scope for each query, not just once\n\t\t\tscopes = append(scopes, scope)\n\t\t}\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Socket\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: false,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Socket -> Node\n\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tAggregate: true,\n\t\t\tType: &socketString,\n\t\t\tTypeIds: intToStringSlice(sockets),\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Node -> Node\n\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n\t\tqueries = append(queries, APIQuery{\n\t\t\tMetric: metric,\n\t\t\tHostname: hostname,\n\t\t\tResolution: resolution,\n\t\t})\n\t\tscopes = append(scopes, scope)\n\t\treturn queries, scopes\n\t}\n\n\t// Unhandled Case -> Error -> Return nils\n\treturn nil, nil\n}\n\n// intToStringSlice converts a slice of integers to a slice of strings.\n// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.\nfunc intToStringSlice(is []int) []string {\n\tss := make([]string, len(is))\n\tfor i, x := range is {\n\t\tss[i] = strconv.Itoa(x)\n\t}\n\treturn ss\n}\n","structuredPatch":[{"oldStart":255,"oldLines":277,"newStart":255,"newLines":3,"lines":[" return queries, assignedScope, nil"," }"," ","-// buildScopeQueries generates API queries for a given scope transformation.","-// It returns a slice of queries and corresponding assigned scopes.","-// Some transformations (e.g., HWThread -> Core/Socket) may generate multiple queries.","-func buildScopeQueries(","- nativeScope, requestedScope schema.MetricScope,","- metric, hostname string,","- topology *schema.Topology,","- hwthreads []int,","- accelerators []string,","- resolution int,","-) ([]APIQuery, []schema.MetricScope) {","- scope := nativeScope.Max(requestedScope)","- queries := []APIQuery{}","- scopes := []schema.MetricScope{}","-","- hwthreadsStr := intToStringSlice(hwthreads)","-","- // Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)","- if nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {","- if scope != schema.MetricScopeAccelerator {","- // Expected Exception -> Continue -> Return Empty Slices","- return queries, scopes","- }","-","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &acceleratorString,","- TypeIds: accelerators,","- Resolution: resolution,","- })","- scopes = append(scopes, schema.MetricScopeAccelerator)","- return queries, scopes","- }","-","- // Accelerator -> Node","- if nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {","- if len(accelerators) == 0 {","- // Expected Exception -> Continue -> Return Empty Slices","- return queries, scopes","- }","-","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &acceleratorString,","- TypeIds: accelerators,","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // HWThread -> HWThread","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &hwthreadString,","- TypeIds: hwthreadsStr,","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // HWThread -> Core","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- for _, core := range cores {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Core[core]),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- }","- return queries, scopes","- }","-","- // HWThread -> Socket","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- }","- return queries, scopes","- }","-","- // HWThread -> Node","- if nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &hwthreadString,","- TypeIds: hwthreadsStr,","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // Core -> Core","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // Core -> Socket","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromCores(hwthreads)","- for _, socket := range sockets {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(topology.Socket[socket]),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- }","- return queries, scopes","- }","-","- // Core -> Node","- if nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {","- cores, _ := topology.GetCoresFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &coreString,","- TypeIds: intToStringSlice(cores),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // MemoryDomain -> MemoryDomain","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {","- memDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(memDomains),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // MemoryDomain -> Node","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {","- memDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(memDomains),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // MemoryDomain -> Socket","- if nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {","- memDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)","- socketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)","- if err != nil {","- cclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)","- // Rare Error Case -> Still Continue -> Return Empty Slices","- return queries, scopes","- }","-","- // Create a query for each socket","- for _, domains := range socketToDomains {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &memoryDomainString,","- TypeIds: intToStringSlice(domains),","- Resolution: resolution,","- })","- // Add scope for each query, not just once","- scopes = append(scopes, scope)","- }","- return queries, scopes","- }","-","- // Socket -> Socket","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: false,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // Socket -> Node","- if nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {","- sockets, _ := topology.GetSocketsFromHWThreads(hwthreads)","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Aggregate: true,","- Type: &socketString,","- TypeIds: intToStringSlice(sockets),","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // Node -> Node","- if nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {","- queries = append(queries, APIQuery{","- Metric: metric,","- Hostname: hostname,","- Resolution: resolution,","- })","- scopes = append(scopes, scope)","- return queries, scopes","- }","-","- // Unhandled Case -> Error -> Return nils","- return nil, nil","-}","-","-// intToStringSlice converts a slice of integers to a slice of strings.","-// Used to convert hardware IDs (core IDs, socket IDs, etc.) to the string format required by the API.","-func intToStringSlice(is []int) []string {","- ss := make([]string, len(is))","- for i, x := range is {","- ss[i] = strconv.Itoa(x)","- }","- return ss","-}"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"ccc57f11-4eb5-4fbb-b17f-37fa70d76765"}
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{"parentUuid":"341e6d23-7f11-45f7-9bf5-71ce3e40f249","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XFFhbbuycPtDdXPq5pBKmj","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"026e4af2-e966-4070-8979-6d3c5c163731","timestamp":"2026-03-04T15:34:13.181Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"","newString":"\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tms \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n//\n// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n//\n// # Architecture\n//\n// The package is split into two main components:\n// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n//\n// # Basic Usage\n//\n//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n//\n//\t// Load job data\n//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n//\tif err != nil {\n//\t log.Fatal(err)\n//\t}\n//\n// # Metric Scopes\n//\n// The client supports hierarchical metric scopes that map to HPC hardware topology:\n// - MetricScopeAccelerator: GPU/accelerator level metrics\n// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n// - MetricScopeCore: CPU core level metrics\n// - MetricScopeSocket: CPU socket level metrics\n// - MetricScopeMemoryDomain: NUMA domain level metrics\n// - MetricScopeNode: Full node level metrics\n//\n// The client automatically handles scope transformations, aggregating finer-grained metrics\n// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n//\n// # Error Handling\n//\n// The client supports partial errors - if some queries fail, it returns both the successful\n// data and an error listing the failed queries. This allows processing partial results\n// when some nodes or metrics are temporarily unavailable.\n//\n// # API Versioning\n//\n// The client uses cc-metric-store API v2, which includes support for:\n// - Data resampling for bandwidth optimization\n// - Multi-scope queries in a single request\n// - Aggregation across hardware topology levels\npackage metricstoreclient\n\nimport (\n\t\"bufio\"\n\t\"bytes\"\n\t\"context\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"net/http\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n// It manages connection details, authentication, and provides methods for querying metrics.\ntype CCMetricStore struct {\n\tclient http.Client // HTTP client with 10-second timeout\n\tjwt string // JWT Bearer token for authentication\n\turl string // Base URL of cc-metric-store instance\n\tqueryEndpoint string // Full URL to query API endpoint\n\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n}\n\n// APIQueryRequest represents a request to the cc-metric-store query API.\n// It supports both explicit queries and \"for-all-nodes\" bulk queries.\ntype APIQueryRequest struct {\n\tCluster string `json:\"cluster\"` // Target cluster name\n\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n\tWithData bool `json:\"with-data\"` // Include time series data points\n}\n\n// APIQuery specifies a single metric query with optional scope filtering.\n// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\ntype APIQuery struct {\n\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n\tMetric string `json:\"metric\"` // Metric name\n\tHostname string `json:\"host\"` // Target hostname\n\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n}\n\n// APIQueryResponse contains the results from a cc-metric-store query.\n// Results align with the Queries slice by index.\ntype APIQueryResponse struct {\n\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n}\n\n// APIMetricData represents time series data and statistics for a single metric series.\n// Error is set if this particular series failed to load.\ntype APIMetricData struct {\n\tError *string `json:\"error\"` // Error message if query failed\n\tData []schema.Float `json:\"data\"` // Time series data points\n\tFrom int64 `json:\"from\"` // Actual start time of data\n\tTo int64 `json:\"to\"` // Actual end time of data\n\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n\tAvg schema.Float `json:\"avg\"` // Average value across time range\n\tMin schema.Float `json:\"min\"` // Minimum value in time range\n\tMax schema.Float `json:\"max\"` // Maximum value in time range\n}\n\n// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\nfunc NewCCMetricStore(url string, token string) *CCMetricStore {\n\treturn &CCMetricStore{\n\t\turl: url,\n\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n\t\tjwt: token,\n\t\tclient: http.Client{\n\t\t\tTimeout: 10 * time.Second,\n\t\t},\n\t\ttopologyCache: make(map[string]*schema.Topology),\n\t}\n}\n\n// doRequest executes an HTTP POST request to the cc-metric-store query API.\n// It handles JSON encoding/decoding, authentication, and API versioning.\n// The request body is automatically closed to prevent resource leaks.\nfunc (ccms *CCMetricStore) doRequest(\n\tctx context.Context,\n\tbody *APIQueryRequest,\n) (*APIQueryResponse, error) {\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\t// versioning the cc-metric-store query API.\n\t// v2 = data with resampling\n\t// v1 = data without resampling\n\tq := req.URL.Query()\n\tq.Add(\"version\", \"v2\")\n\treq.URL.RawQuery = q.Encode()\n\n\tres, err := ccms.client.Do(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n\t}\n\n\tvar resBody APIQueryResponse\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn &resBody, nil\n}\n\n// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\nfunc (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n\t\treturn topology, nil\n\t}\n\n\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tccms.topologyCache[cacheKey] = &subcluster.Topology\n\treturn &subcluster.Topology, nil\n}\n\n// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\nfunc (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn ccms.getTopology(cluster, subCluster)\n}\n\n// LoadData retrieves time series data and statistics for the specified job and metrics.\n// It queries data for the job's time range and resources, handling scope transformations automatically.\n//\n// Parameters:\n// - job: Job metadata including cluster, time range, and allocated resources\n// - metrics: List of metric names to retrieve\n// - scopes: Requested metric scopes (node, socket, core, etc.)\n// - ctx: Context for cancellation and timeouts\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns JobData organized as: metric -> scope -> series list.\n// Supports partial errors: returns available data even if some queries fail.\nfunc (ccms *CCMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n// This is faster than LoadData when only statistical summaries are needed (no time series data).\n//\n// Returns statistics organized as: metric -> hostname -> statistics.\nfunc (ccms *CCMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n// Used for the Job-View Statistics Table to display per-scope breakdowns.\n//\n// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\nfunc (ccms *CCMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n// Used for the Systems-View Node-Overview to display real-time node status.\n//\n// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\nfunc (ccms *CCMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n//\n// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n// substring matching on hostnames.\n//\n// Returns:\n// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n// - Total node count (before pagination)\n// - HasNextPage flag indicating if more pages are available\n// - Error (may be partial error with some data returned)\nfunc (ccms *CCMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// HealthCheck queries the external cc-metric-store's health check endpoint.\n// It sends a HealthCheckReq as the request body to /api/healthcheck and\n// returns the per-node health check results.\nfunc (ccms *CCMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]metricstore.HealthCheckResult, error) {\n\treq := metricstore.HealthCheckReq{\n\t\tCluster: cluster,\n\t\tNodes: nodes,\n\t\tMetricNames: metrics,\n\t}\n\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\tres, err := ccms.client.Do(httpReq)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n\t}\n\n\tvar results map[string]metricstore.HealthCheckResult\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn results, nil\n}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc sanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","structuredPatch":[{"oldStart":63,"oldLines":7,"newStart":63,"newLines":7,"lines":[" \"time\""," "," \"github.com/ClusterCockpit/cc-backend/pkg/archive\"","- \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"","+ ms \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\""," cclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\""," \"github.com/ClusterCockpit/cc-lib/v2/schema\""," )"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"341e6d23-7f11-45f7-9bf5-71ce3e40f249"}
{"parentUuid":"026e4af2-e966-4070-8979-6d3c5c163731","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01VbA63TUhW6eLNNcYyWdTW2","type":"message","role":"assistant","content":[{"type":"text","text":"Now I need to update all `metricstore.` references to `ms.` and `sanitizeStats` calls. Let me check what uses `metricstore.` in this file:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":395,"cache_read_input_tokens":85953,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":395},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHSr2Ksgh4CDfrG9zcU","type":"assistant","uuid":"980e033a-51b0-40f9-ad2a-a9cbb2580ab8","timestamp":"2026-03-04T15:34:17.400Z"}
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{"parentUuid":"c1ce6f73-dece-4fe5-a890-9fd16658c737","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Eu1ba4UiuPfej9Yjrqmcsg","type":"tool_result","content":"787:) (map[string]metricstore.HealthCheckResult, error) {\n788:\treq := metricstore.HealthCheckReq{\n821:\tvar results map[string]metricstore.HealthCheckResult"}]},"uuid":"56575c68-5d5d-4888-8eae-079525668e24","timestamp":"2026-03-04T15:34:18.472Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"787:) (map[string]metricstore.HealthCheckResult, error) {\n788:\treq := metricstore.HealthCheckReq{\n821:\tvar results map[string]metricstore.HealthCheckResult","numLines":3},"sourceToolAssistantUUID":"c1ce6f73-dece-4fe5-a890-9fd16658c737"}
{"parentUuid":"56575c68-5d5d-4888-8eae-079525668e24","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01RxnbixVYcMgEux5VuvggKV","type":"message","role":"assistant","content":[{"type":"text","text":"I need to update `metricstore.` to `ms.`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":566,"cache_read_input_tokens":86348,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":566},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHTEeMuHi2XvP5v1LBP","type":"assistant","uuid":"628afd02-350a-4f09-a196-17b3780d0a6c","timestamp":"2026-03-04T15:34:21.279Z"}
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{"parentUuid":"f86fa1fe-f38f-4d00-8ba1-705d9810097a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01T94vcnaNbaCpcDZDtt1nPV","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated. All occurrences of 'metricstore.' were successfully replaced with 'ms.'."}]},"uuid":"931dd2c8-1641-4a02-ab68-87b82225a9ce","timestamp":"2026-03-04T15:34:22.162Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"metricstore.","newString":"ms.","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n//\n// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n//\n// # Architecture\n//\n// The package is split into two main components:\n// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n//\n// # Basic Usage\n//\n//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n//\n//\t// Load job data\n//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n//\tif err != nil {\n//\t log.Fatal(err)\n//\t}\n//\n// # Metric Scopes\n//\n// The client supports hierarchical metric scopes that map to HPC hardware topology:\n// - MetricScopeAccelerator: GPU/accelerator level metrics\n// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n// - MetricScopeCore: CPU core level metrics\n// - MetricScopeSocket: CPU socket level metrics\n// - MetricScopeMemoryDomain: NUMA domain level metrics\n// - MetricScopeNode: Full node level metrics\n//\n// The client automatically handles scope transformations, aggregating finer-grained metrics\n// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n//\n// # Error Handling\n//\n// The client supports partial errors - if some queries fail, it returns both the successful\n// data and an error listing the failed queries. This allows processing partial results\n// when some nodes or metrics are temporarily unavailable.\n//\n// # API Versioning\n//\n// The client uses cc-metric-store API v2, which includes support for:\n// - Data resampling for bandwidth optimization\n// - Multi-scope queries in a single request\n// - Aggregation across hardware topology levels\npackage metricstoreclient\n\nimport (\n\t\"bufio\"\n\t\"bytes\"\n\t\"context\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"net/http\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tms \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n// It manages connection details, authentication, and provides methods for querying metrics.\ntype CCMetricStore struct {\n\tclient http.Client // HTTP client with 10-second timeout\n\tjwt string // JWT Bearer token for authentication\n\turl string // Base URL of cc-metric-store instance\n\tqueryEndpoint string // Full URL to query API endpoint\n\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n}\n\n// APIQueryRequest represents a request to the cc-metric-store query API.\n// It supports both explicit queries and \"for-all-nodes\" bulk queries.\ntype APIQueryRequest struct {\n\tCluster string `json:\"cluster\"` // Target cluster name\n\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n\tWithData bool `json:\"with-data\"` // Include time series data points\n}\n\n// APIQuery specifies a single metric query with optional scope filtering.\n// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\ntype APIQuery struct {\n\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n\tMetric string `json:\"metric\"` // Metric name\n\tHostname string `json:\"host\"` // Target hostname\n\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n}\n\n// APIQueryResponse contains the results from a cc-metric-store query.\n// Results align with the Queries slice by index.\ntype APIQueryResponse struct {\n\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n}\n\n// APIMetricData represents time series data and statistics for a single metric series.\n// Error is set if this particular series failed to load.\ntype APIMetricData struct {\n\tError *string `json:\"error\"` // Error message if query failed\n\tData []schema.Float `json:\"data\"` // Time series data points\n\tFrom int64 `json:\"from\"` // Actual start time of data\n\tTo int64 `json:\"to\"` // Actual end time of data\n\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n\tAvg schema.Float `json:\"avg\"` // Average value across time range\n\tMin schema.Float `json:\"min\"` // Minimum value in time range\n\tMax schema.Float `json:\"max\"` // Maximum value in time range\n}\n\n// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\nfunc NewCCMetricStore(url string, token string) *CCMetricStore {\n\treturn &CCMetricStore{\n\t\turl: url,\n\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n\t\tjwt: token,\n\t\tclient: http.Client{\n\t\t\tTimeout: 10 * time.Second,\n\t\t},\n\t\ttopologyCache: make(map[string]*schema.Topology),\n\t}\n}\n\n// doRequest executes an HTTP POST request to the cc-metric-store query API.\n// It handles JSON encoding/decoding, authentication, and API versioning.\n// The request body is automatically closed to prevent resource leaks.\nfunc (ccms *CCMetricStore) doRequest(\n\tctx context.Context,\n\tbody *APIQueryRequest,\n) (*APIQueryResponse, error) {\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\t// versioning the cc-metric-store query API.\n\t// v2 = data with resampling\n\t// v1 = data without resampling\n\tq := req.URL.Query()\n\tq.Add(\"version\", \"v2\")\n\treq.URL.RawQuery = q.Encode()\n\n\tres, err := ccms.client.Do(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n\t}\n\n\tvar resBody APIQueryResponse\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn &resBody, nil\n}\n\n// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\nfunc (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n\t\treturn topology, nil\n\t}\n\n\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tccms.topologyCache[cacheKey] = &subcluster.Topology\n\treturn &subcluster.Topology, nil\n}\n\n// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\nfunc (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn ccms.getTopology(cluster, subCluster)\n}\n\n// LoadData retrieves time series data and statistics for the specified job and metrics.\n// It queries data for the job's time range and resources, handling scope transformations automatically.\n//\n// Parameters:\n// - job: Job metadata including cluster, time range, and allocated resources\n// - metrics: List of metric names to retrieve\n// - scopes: Requested metric scopes (node, socket, core, etc.)\n// - ctx: Context for cancellation and timeouts\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns JobData organized as: metric -> scope -> series list.\n// Supports partial errors: returns available data even if some queries fail.\nfunc (ccms *CCMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n// This is faster than LoadData when only statistical summaries are needed (no time series data).\n//\n// Returns statistics organized as: metric -> hostname -> statistics.\nfunc (ccms *CCMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n// Used for the Job-View Statistics Table to display per-scope breakdowns.\n//\n// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\nfunc (ccms *CCMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n// Used for the Systems-View Node-Overview to display real-time node status.\n//\n// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\nfunc (ccms *CCMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n//\n// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n// substring matching on hostnames.\n//\n// Returns:\n// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n// - Total node count (before pagination)\n// - HasNextPage flag indicating if more pages are available\n// - Error (may be partial error with some data returned)\nfunc (ccms *CCMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// HealthCheck queries the external cc-metric-store's health check endpoint.\n// It sends a HealthCheckReq as the request body to /api/healthcheck and\n// returns the per-node health check results.\nfunc (ccms *CCMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]metricstore.HealthCheckResult, error) {\n\treq := metricstore.HealthCheckReq{\n\t\tCluster: cluster,\n\t\tNodes: nodes,\n\t\tMetricNames: metrics,\n\t}\n\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\tres, err := ccms.client.Do(httpReq)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n\t}\n\n\tvar results map[string]metricstore.HealthCheckResult\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn results, nil\n}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc sanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","structuredPatch":[{"oldStart":784,"oldLines":8,"newStart":784,"newLines":8,"lines":[" // returns the per-node health check results."," func (ccms *CCMetricStore) HealthCheck(cluster string,"," nodes []string, metrics []string,","-) (map[string]metricstore.HealthCheckResult, error) {","- req := metricstore.HealthCheckReq{","+) (map[string]ms.HealthCheckResult, error) {","+ req := ms.HealthCheckReq{"," Cluster: cluster,"," Nodes: nodes,"," MetricNames: metrics,"]},{"oldStart":818,"oldLines":7,"newStart":818,"newLines":7,"lines":[" return nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)"," }"," ","- var results map[string]metricstore.HealthCheckResult","+ var results 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{"parentUuid":"eb8a94f2-7ad3-4eca-8f96-d65eeadc1008","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UngLeY3mA2iRTmdVWBdrNU","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated. All occurrences of 'sanitizeStats(' were successfully replaced with 'ms.SanitizeStats('."}]},"uuid":"950b8637-87bb-454d-86f0-72497f0b237d","timestamp":"2026-03-04T15:34:29.806Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"sanitizeStats(","newString":"ms.SanitizeStats(","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n//\n// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n//\n// # Architecture\n//\n// The package is split into two main components:\n// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n//\n// # Basic Usage\n//\n//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n//\n//\t// Load job data\n//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n//\tif err != nil {\n//\t log.Fatal(err)\n//\t}\n//\n// # Metric Scopes\n//\n// The client supports hierarchical metric scopes that map to HPC hardware topology:\n// - MetricScopeAccelerator: GPU/accelerator level metrics\n// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n// - MetricScopeCore: CPU core level metrics\n// - MetricScopeSocket: CPU socket level metrics\n// - MetricScopeMemoryDomain: NUMA domain level metrics\n// - MetricScopeNode: Full node level metrics\n//\n// The client automatically handles scope transformations, aggregating finer-grained metrics\n// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n//\n// # Error Handling\n//\n// The client supports partial errors - if some queries fail, it returns both the successful\n// data and an error listing the failed queries. This allows processing partial results\n// when some nodes or metrics are temporarily unavailable.\n//\n// # API Versioning\n//\n// The client uses cc-metric-store API v2, which includes support for:\n// - Data resampling for bandwidth optimization\n// - Multi-scope queries in a single request\n// - Aggregation across hardware topology levels\npackage metricstoreclient\n\nimport (\n\t\"bufio\"\n\t\"bytes\"\n\t\"context\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"net/http\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tms \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n// It manages connection details, authentication, and provides methods for querying metrics.\ntype CCMetricStore struct {\n\tclient http.Client // HTTP client with 10-second timeout\n\tjwt string // JWT Bearer token for authentication\n\turl string // Base URL of cc-metric-store instance\n\tqueryEndpoint string // Full URL to query API endpoint\n\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n}\n\n// APIQueryRequest represents a request to the cc-metric-store query API.\n// It supports both explicit queries and \"for-all-nodes\" bulk queries.\ntype APIQueryRequest struct {\n\tCluster string `json:\"cluster\"` // Target cluster name\n\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n\tWithData bool `json:\"with-data\"` // Include time series data points\n}\n\n// APIQuery specifies a single metric query with optional scope filtering.\n// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\ntype APIQuery struct {\n\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n\tMetric string `json:\"metric\"` // Metric name\n\tHostname string `json:\"host\"` // Target hostname\n\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n}\n\n// APIQueryResponse contains the results from a cc-metric-store query.\n// Results align with the Queries slice by index.\ntype APIQueryResponse struct {\n\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n}\n\n// APIMetricData represents time series data and statistics for a single metric series.\n// Error is set if this particular series failed to load.\ntype APIMetricData struct {\n\tError *string `json:\"error\"` // Error message if query failed\n\tData []schema.Float `json:\"data\"` // Time series data points\n\tFrom int64 `json:\"from\"` // Actual start time of data\n\tTo int64 `json:\"to\"` // Actual end time of data\n\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n\tAvg schema.Float `json:\"avg\"` // Average value across time range\n\tMin schema.Float `json:\"min\"` // Minimum value in time range\n\tMax schema.Float `json:\"max\"` // Maximum value in time range\n}\n\n// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\nfunc NewCCMetricStore(url string, token string) *CCMetricStore {\n\treturn &CCMetricStore{\n\t\turl: url,\n\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n\t\tjwt: token,\n\t\tclient: http.Client{\n\t\t\tTimeout: 10 * time.Second,\n\t\t},\n\t\ttopologyCache: make(map[string]*schema.Topology),\n\t}\n}\n\n// doRequest executes an HTTP POST request to the cc-metric-store query API.\n// It handles JSON encoding/decoding, authentication, and API versioning.\n// The request body is automatically closed to prevent resource leaks.\nfunc (ccms *CCMetricStore) doRequest(\n\tctx context.Context,\n\tbody *APIQueryRequest,\n) (*APIQueryResponse, error) {\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\t// versioning the cc-metric-store query API.\n\t// v2 = data with resampling\n\t// v1 = data without resampling\n\tq := req.URL.Query()\n\tq.Add(\"version\", \"v2\")\n\treq.URL.RawQuery = q.Encode()\n\n\tres, err := ccms.client.Do(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n\t}\n\n\tvar resBody APIQueryResponse\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn &resBody, nil\n}\n\n// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\nfunc (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n\t\treturn topology, nil\n\t}\n\n\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tccms.topologyCache[cacheKey] = &subcluster.Topology\n\treturn &subcluster.Topology, nil\n}\n\n// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\nfunc (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn ccms.getTopology(cluster, subCluster)\n}\n\n// LoadData retrieves time series data and statistics for the specified job and metrics.\n// It queries data for the job's time range and resources, handling scope transformations automatically.\n//\n// Parameters:\n// - job: Job metadata including cluster, time range, and allocated resources\n// - metrics: List of metric names to retrieve\n// - scopes: Requested metric scopes (node, socket, core, etc.)\n// - ctx: Context for cancellation and timeouts\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns JobData organized as: metric -> scope -> series list.\n// Supports partial errors: returns available data even if some queries fail.\nfunc (ccms *CCMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n// This is faster than LoadData when only statistical summaries are needed (no time series data).\n//\n// Returns statistics organized as: metric -> hostname -> statistics.\nfunc (ccms *CCMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n// Used for the Job-View Statistics Table to display per-scope breakdowns.\n//\n// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\nfunc (ccms *CCMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n// Used for the Systems-View Node-Overview to display real-time node status.\n//\n// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\nfunc (ccms *CCMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tsanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n//\n// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n// substring matching on hostnames.\n//\n// Returns:\n// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n// - Total node count (before pagination)\n// - HasNextPage flag indicating if more pages are available\n// - Error (may be partial error with some data returned)\nfunc (ccms *CCMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tsanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// HealthCheck queries the external cc-metric-store's health check endpoint.\n// It sends a HealthCheckReq as the request body to /api/healthcheck and\n// returns the per-node health check results.\nfunc (ccms *CCMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]ms.HealthCheckResult, error) {\n\treq := ms.HealthCheckReq{\n\t\tCluster: cluster,\n\t\tNodes: nodes,\n\t\tMetricNames: metrics,\n\t}\n\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\tres, err := ccms.client.Do(httpReq)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n\t}\n\n\tvar results map[string]ms.HealthCheckResult\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn results, nil\n}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc sanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","structuredPatch":[{"oldStart":331,"oldLines":7,"newStart":331,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res.Avg, &res.Min, &res.Max)","+ ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," jobMetric.Series = append(jobMetric.Series, schema.Series{"," Hostname: query.Hostname,"]},{"oldStart":494,"oldLines":7,"newStart":494,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res.Avg, &res.Min, &res.Max)","+ ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," scopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{"," Hostname: query.Hostname,"]},{"oldStart":584,"oldLines":7,"newStart":584,"newLines":7,"lines":[" errors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))"," }"," ","- sanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)","+ ms.SanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)"," "," hostdata, ok := data[query.Hostname]"," if !ok {"]},{"oldStart":756,"oldLines":7,"newStart":756,"newLines":7,"lines":[" }"," }"," ","- sanitizeStats(&res.Avg, &res.Min, &res.Max)","+ ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "," scopeData.Series = append(scopeData.Series, schema.Series{"," Hostname: query.Hostname,"]},{"oldStart":829,"oldLines":7,"newStart":829,"newLines":7,"lines":[" "," // sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling."," // Regular float64 values cannot be JSONed when NaN.","-func sanitizeStats(avg, min, max *schema.Float) {","+func ms.SanitizeStats(avg, min, max *schema.Float) {"," if avg.IsNaN() || min.IsNaN() || max.IsNaN() {"," *avg = schema.Float(0)"," *min = schema.Float(0)"]}],"userModified":false,"replaceAll":true},"sourceToolAssistantUUID":"eb8a94f2-7ad3-4eca-8f96-d65eeadc1008"}
{"parentUuid":"950b8637-87bb-454d-86f0-72497f0b237d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_014rYkUeSMNzuPC5Wu5bB2hr","type":"message","role":"assistant","content":[{"type":"text","text":"Now delete the local `sanitizeStats` and `hasNaNStats` functions:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":230,"cache_read_input_tokens":87441,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":230},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHU57uMxNaY86WMr1su","type":"assistant","uuid":"5382ff05-13ad-4fd5-9b7c-8eeee23d09c4","timestamp":"2026-03-04T15:34:33.036Z"}
{"parentUuid":"5382ff05-13ad-4fd5-9b7c-8eeee23d09c4","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_014rYkUeSMNzuPC5Wu5bB2hr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01DorrWsgJ28Ro2n8fSedRKo","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","old_string":"// ms.SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}","new_string":"// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":230,"cache_read_input_tokens":87441,"output_tokens":402,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":230,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHU57uMxNaY86WMr1su","type":"assistant","uuid":"4f3f39ae-22a3-4d00-a158-5a3a6a32bac9","timestamp":"2026-03-04T15:34:36.085Z"}
{"parentUuid":"4f3f39ae-22a3-4d00-a158-5a3a6a32bac9","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"type":"tool_result","content":"<tool_use_error>String to replace not found in file.\nString: // ms.SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}</tool_use_error>","is_error":true,"tool_use_id":"toolu_01DorrWsgJ28Ro2n8fSedRKo"}]},"uuid":"c5045c89-2a0c-4a20-9755-f7925b984c34","timestamp":"2026-03-04T15:34:36.166Z","toolUseResult":"Error: String to replace not found in file.\nString: // ms.SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}","sourceToolAssistantUUID":"4f3f39ae-22a3-4d00-a158-5a3a6a32bac9"}
{"parentUuid":"c5045c89-2a0c-4a20-9755-f7925b984c34","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_019Y1pc8F6GPu9nU2FoNmQue","type":"message","role":"assistant","content":[{"type":"text","text":"The replace_all also hit the function definition. Let me read the current state:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":887,"cache_read_input_tokens":87671,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":887},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHUYbdbNJfsPjqVjrr9","type":"assistant","uuid":"59de1cd2-ec2b-4a0a-bda2-b7a92510c6f2","timestamp":"2026-03-04T15:34:39.586Z"}
{"parentUuid":"59de1cd2-ec2b-4a0a-bda2-b7a92510c6f2","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_019Y1pc8F6GPu9nU2FoNmQue","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KFzgX13jPZnxwqck1S1koP","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","offset":828,"limit":20},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":887,"cache_read_input_tokens":87671,"output_tokens":138,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":887,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHUYbdbNJfsPjqVjrr9","type":"assistant","uuid":"de2a06c5-62a4-4d84-bc99-ad496f216980","timestamp":"2026-03-04T15:34:40.179Z"}
{"parentUuid":"de2a06c5-62a4-4d84-bc99-ad496f216980","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01KFzgX13jPZnxwqck1S1koP","toolUseID":"toolu_01KFzgX13jPZnxwqck1S1koP","timestamp":"2026-03-04T15:34:40.357Z","uuid":"4deaad01-4525-4aed-9d41-163316806ae6"}
{"parentUuid":"de2a06c5-62a4-4d84-bc99-ad496f216980","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KFzgX13jPZnxwqck1S1koP","type":"tool_result","content":" 828→}\n 829→\n 830→// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n 831→// Regular float64 values cannot be JSONed when NaN.\n 832→func ms.SanitizeStats(avg, min, max *schema.Float) {\n 833→\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n 834→\t\t*avg = schema.Float(0)\n 835→\t\t*min = schema.Float(0)\n 836→\t\t*max = schema.Float(0)\n 837→\t}\n 838→}\n 839→\n 840→// hasNaNStats returns true if any of the statistics contain NaN values.\n 841→func hasNaNStats(avg, min, max schema.Float) bool {\n 842→\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n 843→}\n 844→"}]},"uuid":"9386b0f6-a07f-4654-82ac-ad6bfe6c69b0","timestamp":"2026-03-04T15:34:40.357Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","content":"}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","numLines":17,"startLine":828,"totalLines":844}},"sourceToolAssistantUUID":"de2a06c5-62a4-4d84-bc99-ad496f216980"}
{"parentUuid":"9386b0f6-a07f-4654-82ac-ad6bfe6c69b0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_018RcTKmg4MeVMRZNwQBNBMM","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Gpxz8ckQBXeyCm2mGwU9CR","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","old_string":"// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}","new_string":"// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":386,"cache_read_input_tokens":88558,"output_tokens":379,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":386,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHUrUfZNYgW59qCDmim","type":"assistant","uuid":"22843440-cecc-48fa-8a6c-96b3c2b32660","timestamp":"2026-03-04T15:34:45.793Z"}
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{"parentUuid":"22843440-cecc-48fa-8a6c-96b3c2b32660","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Gpxz8ckQBXeyCm2mGwU9CR","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"07ed1346-95f3-47d8-ab78-f507a0561e65","timestamp":"2026-03-04T15:34:45.880Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}","newString":"// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package metricstoreclient provides a client for querying the cc-metric-store time series database.\n//\n// The cc-metric-store is a high-performance time series database optimized for HPC metric data.\n// This client handles HTTP communication, query construction, scope transformations, and data retrieval\n// for job and node metrics across different metric scopes (node, socket, core, hwthread, accelerator).\n//\n// # Architecture\n//\n// The package is split into two main components:\n// - Client Operations (cc-metric-store.go): HTTP client, request handling, data loading methods\n// - Query Building (cc-metric-store-queries.go): Query construction and scope transformation logic\n//\n// # Basic Usage\n//\n//\tstore := NewCCMetricStore(\"http://localhost:8080\", \"jwt-token\")\n//\n//\t// Load job data\n//\tjobData, err := store.LoadData(job, metrics, scopes, ctx, resolution)\n//\tif err != nil {\n//\t log.Fatal(err)\n//\t}\n//\n// # Metric Scopes\n//\n// The client supports hierarchical metric scopes that map to HPC hardware topology:\n// - MetricScopeAccelerator: GPU/accelerator level metrics\n// - MetricScopeHWThread: Hardware thread (SMT) level metrics\n// - MetricScopeCore: CPU core level metrics\n// - MetricScopeSocket: CPU socket level metrics\n// - MetricScopeMemoryDomain: NUMA domain level metrics\n// - MetricScopeNode: Full node level metrics\n//\n// The client automatically handles scope transformations, aggregating finer-grained metrics\n// to coarser scopes when needed (e.g., aggregating core metrics to socket level).\n//\n// # Error Handling\n//\n// The client supports partial errors - if some queries fail, it returns both the successful\n// data and an error listing the failed queries. This allows processing partial results\n// when some nodes or metrics are temporarily unavailable.\n//\n// # API Versioning\n//\n// The client uses cc-metric-store API v2, which includes support for:\n// - Data resampling for bandwidth optimization\n// - Multi-scope queries in a single request\n// - Aggregation across hardware topology levels\npackage metricstoreclient\n\nimport (\n\t\"bufio\"\n\t\"bytes\"\n\t\"context\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"net/http\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tms \"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// CCMetricStore is the HTTP client for communicating with cc-metric-store.\n// It manages connection details, authentication, and provides methods for querying metrics.\ntype CCMetricStore struct {\n\tclient http.Client // HTTP client with 10-second timeout\n\tjwt string // JWT Bearer token for authentication\n\turl string // Base URL of cc-metric-store instance\n\tqueryEndpoint string // Full URL to query API endpoint\n\ttopologyCache map[string]*schema.Topology // cluster -> topology cache\n}\n\n// APIQueryRequest represents a request to the cc-metric-store query API.\n// It supports both explicit queries and \"for-all-nodes\" bulk queries.\ntype APIQueryRequest struct {\n\tCluster string `json:\"cluster\"` // Target cluster name\n\tQueries []APIQuery `json:\"queries\"` // Explicit list of metric queries\n\tForAllNodes []string `json:\"for-all-nodes\"` // Metrics to query for all nodes\n\tFrom int64 `json:\"from\"` // Start time (Unix timestamp)\n\tTo int64 `json:\"to\"` // End time (Unix timestamp)\n\tWithStats bool `json:\"with-stats\"` // Include min/avg/max statistics\n\tWithData bool `json:\"with-data\"` // Include time series data points\n}\n\n// APIQuery specifies a single metric query with optional scope filtering.\n// Type and TypeIds define the hardware scope (core, socket, accelerator, etc.).\ntype APIQuery struct {\n\tType *string `json:\"type,omitempty\"` // Scope type (e.g., \"core\", \"socket\")\n\tSubType *string `json:\"subtype,omitempty\"` // Sub-scope type (reserved for future use)\n\tMetric string `json:\"metric\"` // Metric name\n\tHostname string `json:\"host\"` // Target hostname\n\tResolution int `json:\"resolution\"` // Data resolution in seconds (0 = native)\n\tTypeIds []string `json:\"type-ids,omitempty\"` // IDs for the scope type (e.g., core IDs)\n\tSubTypeIds []string `json:\"subtype-ids,omitempty\"` // IDs for sub-scope (reserved)\n\tAggregate bool `json:\"aggreg\"` // Aggregate across TypeIds\n}\n\n// APIQueryResponse contains the results from a cc-metric-store query.\n// Results align with the Queries slice by index.\ntype APIQueryResponse struct {\n\tQueries []APIQuery `json:\"queries,omitempty\"` // Echoed queries (for bulk requests)\n\tResults [][]APIMetricData `json:\"results\"` // Result data, indexed by query\n}\n\n// APIMetricData represents time series data and statistics for a single metric series.\n// Error is set if this particular series failed to load.\ntype APIMetricData struct {\n\tError *string `json:\"error\"` // Error message if query failed\n\tData []schema.Float `json:\"data\"` // Time series data points\n\tFrom int64 `json:\"from\"` // Actual start time of data\n\tTo int64 `json:\"to\"` // Actual end time of data\n\tResolution int `json:\"resolution\"` // Actual resolution of data in seconds\n\tAvg schema.Float `json:\"avg\"` // Average value across time range\n\tMin schema.Float `json:\"min\"` // Minimum value in time range\n\tMax schema.Float `json:\"max\"` // Maximum value in time range\n}\n\n// NewCCMetricStore creates and initializes a new (external) CCMetricStore client.\n// The url parameter should include the protocol and port (e.g., \"http://localhost:8080\").\n// The token parameter is a JWT used for Bearer authentication; pass empty string if auth is disabled.\nfunc NewCCMetricStore(url string, token string) *CCMetricStore {\n\treturn &CCMetricStore{\n\t\turl: url,\n\t\tqueryEndpoint: fmt.Sprintf(\"%s/api/query\", url),\n\t\tjwt: token,\n\t\tclient: http.Client{\n\t\t\tTimeout: 10 * time.Second,\n\t\t},\n\t\ttopologyCache: make(map[string]*schema.Topology),\n\t}\n}\n\n// doRequest executes an HTTP POST request to the cc-metric-store query API.\n// It handles JSON encoding/decoding, authentication, and API versioning.\n// The request body is automatically closed to prevent resource leaks.\nfunc (ccms *CCMetricStore) doRequest(\n\tctx context.Context,\n\tbody *APIQueryRequest,\n) (*APIQueryResponse, error) {\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(body); err != nil {\n\t\tcclog.Errorf(\"Error while encoding request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treq, err := http.NewRequestWithContext(ctx, http.MethodGet, ccms.queryEndpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\treq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\t// versioning the cc-metric-store query API.\n\t// v2 = data with resampling\n\t// v1 = data without resampling\n\tq := req.URL.Query()\n\tq.Add(\"version\", \"v2\")\n\treq.URL.RawQuery = q.Encode()\n\n\tres, err := ccms.client.Do(req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", ccms.queryEndpoint, res.Status)\n\t}\n\n\tvar resBody APIQueryResponse\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&resBody); err != nil {\n\t\tcclog.Errorf(\"Error while decoding result body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn &resBody, nil\n}\n\n// getTopology returns the topology for a given cluster and subcluster, caching it if not already present\nfunc (ccms *CCMetricStore) getTopology(cluster, subCluster string) (*schema.Topology, error) {\n\tcacheKey := fmt.Sprintf(\"%s:%s\", cluster, subCluster)\n\tif topology, ok := ccms.topologyCache[cacheKey]; ok {\n\t\treturn topology, nil\n\t}\n\n\tsubcluster, err := archive.GetSubCluster(cluster, subCluster)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tccms.topologyCache[cacheKey] = &subcluster.Topology\n\treturn &subcluster.Topology, nil\n}\n\n// getTopologyByNode returns the topology for a given cluster and node, caching it if not already present\nfunc (ccms *CCMetricStore) getTopologyByNode(cluster, node string) (*schema.Topology, error) {\n\tsubCluster, err := archive.GetSubClusterByNode(cluster, node)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn ccms.getTopology(cluster, subCluster)\n}\n\n// LoadData retrieves time series data and statistics for the specified job and metrics.\n// It queries data for the job's time range and resources, handling scope transformations automatically.\n//\n// Parameters:\n// - job: Job metadata including cluster, time range, and allocated resources\n// - metrics: List of metric names to retrieve\n// - scopes: Requested metric scopes (node, socket, core, etc.)\n// - ctx: Context for cancellation and timeouts\n// - resolution: Data resolution in seconds (0 for native resolution)\n//\n// Returns JobData organized as: metric -> scope -> series list.\n// Supports partial errors: returns available data even if some queries fail.\nfunc (ccms *CCMetricStore) LoadData(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n\tresolution int,\n) (schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tjobData := make(schema.JobData)\n\n\t// Add safety check for potential index out of range errors\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := jobData[metric]; !ok {\n\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\tjobMetric, ok := jobData[metric][scope]\n\t\tif !ok {\n\t\t\tjobMetric = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tjobData[metric][scope] = jobMetric\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tms.SanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(jobData):\n\t\tif len(jobMetric.Series) == 0 {\n\t\t\tdelete(jobData[metric], scope)\n\t\t\tif len(jobData[metric]) == 0 {\n\t\t\t\tdelete(jobData, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn jobData, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn jobData, nil\n}\n\n// LoadStats retrieves min/avg/max statistics for job metrics at node scope.\n// This is faster than LoadData when only statistical summaries are needed (no time series data).\n//\n// Returns statistics organized as: metric -> hostname -> statistics.\nfunc (ccms *CCMetricStore) LoadStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tctx context.Context,\n) (map[string]map[string]schema.MetricStatistics, error) {\n\tqueries, _, err := ccms.buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0) // #166 Add scope shere for analysis view accelerator normalization?\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tdata := res[0]\n\t\tif data.Error != nil {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata, ok := stats[metric]\n\t\tif !ok {\n\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n\t\t\tstats[metric] = metricdata\n\t\t}\n\n\t\tif hasNaNStats(data.Avg, data.Min, data.Max) {\n\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n\t\t\tcontinue\n\t\t}\n\n\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n\t\t\tAvg: float64(data.Avg),\n\t\t\tMin: float64(data.Min),\n\t\t\tMax: float64(data.Max),\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// LoadScopedStats retrieves statistics for job metrics across multiple scopes.\n// Used for the Job-View Statistics Table to display per-scope breakdowns.\n//\n// Returns statistics organized as: metric -> scope -> list of scoped statistics.\n// Each scoped statistic includes hostname, hardware ID (if applicable), and min/avg/max values.\nfunc (ccms *CCMetricStore) LoadScopedStats(\n\tjob *schema.Job,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tctx context.Context,\n) (schema.ScopedJobStats, error) {\n\tqueries, assignedScope, err := ccms.buildQueries(job, metrics, scopes, 0)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: job.Cluster,\n\t\tFrom: job.StartTime,\n\t\tTo: job.StartTime + int64(job.Duration),\n\t\tQueries: queries,\n\t\tWithStats: true,\n\t\tWithData: false,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for job %d: %s\", job.JobID, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tscopedJobStats := make(schema.ScopedJobStats)\n\n\tfor i, row := range resBody.Results {\n\t\tquery := req.Queries[i]\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\n\t\tif _, ok := scopedJobStats[metric]; !ok {\n\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n\t\t}\n\n\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tms.SanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tData: &schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t})\n\t\t}\n\n\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n\t\tif len(scopedJobStats[metric][scope]) == 0 {\n\t\t\tdelete(scopedJobStats[metric], scope)\n\t\t\tif len(scopedJobStats[metric]) == 0 {\n\t\t\t\tdelete(scopedJobStats, metric)\n\t\t\t}\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list for \"partial errors\" */\n\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\treturn scopedJobStats, nil\n}\n\n// LoadNodeData retrieves current metric data for specified nodes in a cluster.\n// Used for the Systems-View Node-Overview to display real-time node status.\n//\n// If nodes is nil, queries all metrics for all nodes in the cluster (bulk query).\n// Returns data organized as: hostname -> metric -> list of JobMetric (with time series and stats).\nfunc (ccms *CCMetricStore) LoadNodeData(\n\tcluster string,\n\tmetrics, nodes []string,\n\tscopes []schema.MetricScope,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]map[string][]*schema.JobMetric, error) {\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tif nodes == nil {\n\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n\t} else {\n\t\tfor _, node := range nodes {\n\t\t\tfor _, metric := range metrics {\n\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n\t\t\t\t\tHostname: node,\n\t\t\t\t\tMetric: metric,\n\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]map[string][]*schema.JobMetric)\n\tfor i, res := range resBody.Results {\n\t\tif len(res) == 0 {\n\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tquery = resBody.Queries[i]\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tqdata := res[0]\n\t\tif qdata.Error != nil {\n\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n\t\t}\n\n\t\tms.SanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n\n\t\thostdata, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostdata = make(map[string][]*schema.JobMetric)\n\t\t\tdata[query.Hostname] = hostdata\n\t\t}\n\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,\n\t\t\tSeries: []schema.Series{\n\t\t\t\t{\n\t\t\t\t\tHostname: query.Hostname,\n\t\t\t\t\tData: qdata.Data,\n\t\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\t\tAvg: float64(qdata.Avg),\n\t\t\t\t\t\tMin: float64(qdata.Min),\n\t\t\t\t\t\tMax: float64(qdata.Max),\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// LoadNodeListData retrieves paginated node metrics for the Systems-View Node-List.\n//\n// Supports filtering by subcluster and node name pattern. The nodeFilter performs\n// substring matching on hostnames.\n//\n// Returns:\n// - Node data organized as: hostname -> JobData (metric -> scope -> series)\n// - Total node count (before pagination)\n// - HasNextPage flag indicating if more pages are available\n// - Error (may be partial error with some data returned)\nfunc (ccms *CCMetricStore) LoadNodeListData(\n\tcluster, subCluster string,\n\tnodes []string,\n\tmetrics []string,\n\tscopes []schema.MetricScope,\n\tresolution int,\n\tfrom, to time.Time,\n\tctx context.Context,\n) (map[string]schema.JobData, error) {\n\tqueries, assignedScope, err := ccms.buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, resolution)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building node queries for Cluster %s, SubCluster %s, Metrics %v, Scopes %v: %s\", cluster, subCluster, metrics, scopes, err.Error())\n\t\treturn nil, err\n\t}\n\n\t// Verify assignment is correct - log any inconsistencies for debugging\n\tif len(queries) != len(assignedScope) {\n\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n\t\t\tlen(queries), len(assignedScope))\n\t}\n\n\treq := APIQueryRequest{\n\t\tCluster: cluster,\n\t\tQueries: queries,\n\t\tFrom: from.Unix(),\n\t\tTo: to.Unix(),\n\t\tWithStats: true,\n\t\tWithData: true,\n\t}\n\n\tresBody, err := ccms.doRequest(ctx, &req)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing request for cluster %s: %s\", cluster, err.Error())\n\t\treturn nil, err\n\t}\n\n\tvar errors []string\n\tdata := make(map[string]schema.JobData)\n\n\t// Add safety check for index out of range issues\n\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n\t\tif len(resBody.Results) > len(req.Queries) {\n\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n\t\t}\n\t\tif len(assignedScope) > len(req.Queries) {\n\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n\t\t}\n\t}\n\n\tfor i, row := range resBody.Results {\n\t\t// Safety check to prevent index out of range errors\n\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n\t\t\t\ti, len(req.Queries), len(assignedScope))\n\t\t\tcontinue\n\t\t}\n\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {\n\t\t\tif i < len(resBody.Queries) {\n\t\t\t\tquery = resBody.Queries[i]\n\t\t\t} else {\n\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n\t\t\t\t\ti, len(resBody.Queries))\n\t\t\t\tcontinue\n\t\t\t}\n\t\t} else {\n\t\t\tquery = req.Queries[i]\n\t\t}\n\n\t\tmetric := query.Metric\n\t\tscope := assignedScope[i]\n\t\tmc := archive.GetMetricConfig(cluster, metric)\n\t\tif mc == nil {\n\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tres := mc.Timestep\n\t\tif len(row) > 0 {\n\t\t\tres = row[0].Resolution\n\t\t}\n\n\t\t// Init Nested Map Data Structures If Not Found\n\t\thostData, ok := data[query.Hostname]\n\t\tif !ok {\n\t\t\thostData = make(schema.JobData)\n\t\t\tdata[query.Hostname] = hostData\n\t\t}\n\n\t\tmetricData, ok := hostData[metric]\n\t\tif !ok {\n\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n\t\t\tdata[query.Hostname][metric] = metricData\n\t\t}\n\n\t\tscopeData, ok := metricData[scope]\n\t\tif !ok {\n\t\t\tscopeData = &schema.JobMetric{\n\t\t\t\tUnit: mc.Unit,\n\t\t\t\tTimestep: res,\n\t\t\t\tSeries: make([]schema.Series, 0),\n\t\t\t}\n\t\t\tdata[query.Hostname][metric][scope] = scopeData\n\t\t}\n\n\t\tfor ndx, res := range row {\n\t\t\tif res.Error != nil {\n\t\t\t\t/* Build list for \"partial errors\", if any */\n\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n\t\t\t\tcontinue\n\t\t\t}\n\n\t\t\tid := (*string)(nil)\n\t\t\tif query.Type != nil {\n\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n\t\t\t\tif ndx < len(query.TypeIds) {\n\t\t\t\t\tid = new(string)\n\t\t\t\t\t*id = query.TypeIds[ndx]\n\t\t\t\t} else {\n\t\t\t\t\t// Log the error but continue processing\n\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tms.SanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n\t\t\t\tHostname: query.Hostname,\n\t\t\t\tID: id,\n\t\t\t\tStatistics: schema.MetricStatistics{\n\t\t\t\t\tAvg: float64(res.Avg),\n\t\t\t\t\tMin: float64(res.Min),\n\t\t\t\t\tMax: float64(res.Max),\n\t\t\t\t},\n\t\t\t\tData: res.Data,\n\t\t\t})\n\t\t}\n\t}\n\n\tif len(errors) != 0 {\n\t\t/* Returns list of \"partial errors\" */\n\t\treturn data, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n\t}\n\n\treturn data, nil\n}\n\n// HealthCheck queries the external cc-metric-store's health check endpoint.\n// It sends a HealthCheckReq as the request body to /api/healthcheck and\n// returns the per-node health check results.\nfunc (ccms *CCMetricStore) HealthCheck(cluster string,\n\tnodes []string, metrics []string,\n) (map[string]ms.HealthCheckResult, error) {\n\treq := ms.HealthCheckReq{\n\t\tCluster: cluster,\n\t\tNodes: nodes,\n\t\tMetricNames: metrics,\n\t}\n\n\tbuf := &bytes.Buffer{}\n\tif err := json.NewEncoder(buf).Encode(req); err != nil {\n\t\tcclog.Errorf(\"Error while encoding health check request body: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\tendpoint := fmt.Sprintf(\"%s/api/healthcheck\", ccms.url)\n\thttpReq, err := http.NewRequest(http.MethodGet, endpoint, buf)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while building health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tif ccms.jwt != \"\" {\n\t\thttpReq.Header.Add(\"Authorization\", fmt.Sprintf(\"Bearer %s\", ccms.jwt))\n\t}\n\n\tres, err := ccms.client.Do(httpReq)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while performing health check request: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\tdefer res.Body.Close()\n\n\tif res.StatusCode != http.StatusOK {\n\t\treturn nil, fmt.Errorf(\"'%s': HTTP Status: %s\", endpoint, res.Status)\n\t}\n\n\tvar results map[string]ms.HealthCheckResult\n\tif err := json.NewDecoder(bufio.NewReader(res.Body)).Decode(&results); err != nil {\n\t\tcclog.Errorf(\"Error while decoding health check response: %s\", err.Error())\n\t\treturn nil, err\n\t}\n\n\treturn results, nil\n}\n\n// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n// Regular float64 values cannot be JSONed when NaN.\nfunc ms.SanitizeStats(avg, min, max *schema.Float) {\n\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n\t\t*avg = schema.Float(0)\n\t\t*min = schema.Float(0)\n\t\t*max = schema.Float(0)\n\t}\n}\n\n// hasNaNStats returns true if any of the statistics contain NaN values.\nfunc hasNaNStats(avg, min, max schema.Float) bool {\n\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n}\n","structuredPatch":[{"oldStart":827,"oldLines":16,"newStart":827,"newLines":6,"lines":[" return results, nil"," }"," ","-// sanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.","-// Regular float64 values cannot be JSONed when NaN.","-func ms.SanitizeStats(avg, min, max *schema.Float) {","- if avg.IsNaN() || min.IsNaN() || max.IsNaN() {","- *avg = schema.Float(0)","- *min = schema.Float(0)","- *max = schema.Float(0)","- }","-}","-"," // hasNaNStats returns true if any of the statistics contain NaN values."," func hasNaNStats(avg, min, max schema.Float) bool {"," return avg.IsNaN() || min.IsNaN() || max.IsNaN()"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"22843440-cecc-48fa-8a6c-96b3c2b32660"}
{"parentUuid":"07ed1346-95f3-47d8-ab78-f507a0561e65","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_011MsCvwCJQr5rNAtUd98t9A","type":"message","role":"assistant","content":[{"type":"text","text":"Now also need to update the import in `cc-metric-store-queries.go` — the `cclog` import may no longer be needed since we removed `buildScopeQueries`. Let me check:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":431,"cache_read_input_tokens":88944,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":431},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHVG9TaZwds2ot6USA7","type":"assistant","uuid":"7edf3288-726f-48b2-b2d1-190b45d610b5","timestamp":"2026-03-04T15:34:49.656Z"}
{"parentUuid":"7edf3288-726f-48b2-b2d1-190b45d610b5","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_011MsCvwCJQr5rNAtUd98t9A","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01ACDAKFZK4BTydHt1WDqoBM","name":"Grep","input":{"pattern":"cclog\\.","path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","output_mode":"content"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":431,"cache_read_input_tokens":88944,"output_tokens":172,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":431,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHVG9TaZwds2ot6USA7","type":"assistant","uuid":"12f6a698-a4a9-4bd3-a2eb-6ef0544e019d","timestamp":"2026-03-04T15:34:50.424Z"}
{"parentUuid":"12f6a698-a4a9-4bd3-a2eb-6ef0544e019d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Grep","command":"callback"},"parentToolUseID":"toolu_01ACDAKFZK4BTydHt1WDqoBM","toolUseID":"toolu_01ACDAKFZK4BTydHt1WDqoBM","timestamp":"2026-03-04T15:34:50.714Z","uuid":"883f37da-9c0e-476e-9f66-16d6e33b5dcd"}
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{"parentUuid":"2044d774-c5b6-4e03-8290-44f2a143ecff","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_0186pGto7Cx1Wa3L6rd7Z5MB","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01TE2kBZbXYwLbbgAk9PAmuZ","name":"Bash","input":{"command":"go doc github.com/ClusterCockpit/cc-lib/v2/schema Topology 2>&1 | head -40","description":"Get Topology type docs"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":162,"cache_read_input_tokens":90390,"output_tokens":103,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":162,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHfzRxcUUfzRCJqAhF6","type":"assistant","uuid":"403291be-12df-4a86-b5ed-897819aeaa03","timestamp":"2026-03-04T15:37:14.695Z"}
{"parentUuid":"403291be-12df-4a86-b5ed-897819aeaa03","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TE2kBZbXYwLbbgAk9PAmuZ","type":"tool_result","content":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\ntype Topology struct {\n\tNode []int `json:\"node\"` // All hardware thread IDs on this node\n\tSocket [][]int `json:\"socket\"` // Hardware threads grouped by socket\n\tMemoryDomain [][]int `json:\"memoryDomain\"` // Hardware threads grouped by NUMA domain\n\tDie [][]*int `json:\"die,omitempty\"` // Hardware threads grouped by die (optional)\n\tCore [][]int `json:\"core\"` // Hardware threads grouped by core\n\tAccelerators []*Accelerator `json:\"accelerators,omitempty\"` // Attached accelerators (GPUs, etc.)\n\n\t// Has unexported fields.\n}\n Topology defines the hardware topology of a compute node, mapping the\n hierarchical relationships between hardware threads, cores, sockets,\n memory domains, and accelerators.\n\n The topology is represented as nested arrays where indices represent\n hardware IDs:\n - Node: Flat list of all hardware thread IDs on the node\n - Socket: Hardware threads grouped by physical CPU socket\n - Core: Hardware threads grouped by physical core\n - MemoryDomain: Hardware threads grouped by NUMA domain\n - Die: Optional grouping by CPU die within sockets\n - Accelerators: List of attached hardware accelerators\n\nfunc (topo *Topology) EnsureTopologyMaps()\nfunc (topo *Topology) GetAcceleratorID(id int) (string, error)\nfunc (topo *Topology) GetAcceleratorIDs() []string\nfunc (topo *Topology) GetAcceleratorIDsAsInt() ([]int, error)\nfunc (topo *Topology) GetCoresFromHWThreads(hwthreads []int) (cores []int, exclusive bool)\nfunc (topo *Topology) GetMemoryDomainsBySocket(domainIDs []int) (map[int][]int, error)\nfunc (topo *Topology) GetMemoryDomainsFromHWThreads(hwthreads []int) (memDoms []int, exclusive bool)\nfunc (topo *Topology) GetSocketsFromCores(cores []int) (sockets []int, exclusive bool)\nfunc (topo *Topology) GetSocketsFromHWThreads(hwthreads []int) (sockets []int, exclusive bool)\nfunc (topo *Topology) InitTopologyMaps()","is_error":false}]},"uuid":"e8c1450b-b4cd-4268-b51f-b0116aacdb11","timestamp":"2026-03-04T15:37:15.049Z","toolUseResult":{"stdout":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\ntype Topology struct {\n\tNode []int `json:\"node\"` // All hardware thread IDs on this node\n\tSocket [][]int `json:\"socket\"` // Hardware threads grouped by socket\n\tMemoryDomain [][]int `json:\"memoryDomain\"` // Hardware threads grouped by NUMA domain\n\tDie [][]*int `json:\"die,omitempty\"` // Hardware threads grouped by die (optional)\n\tCore [][]int `json:\"core\"` // Hardware threads grouped by core\n\tAccelerators []*Accelerator `json:\"accelerators,omitempty\"` // Attached accelerators (GPUs, etc.)\n\n\t// Has unexported fields.\n}\n Topology defines the hardware topology of a compute node, mapping the\n hierarchical relationships between hardware threads, cores, sockets,\n memory domains, and accelerators.\n\n The topology is represented as nested arrays where indices represent\n hardware IDs:\n - Node: Flat list of all hardware thread IDs on the node\n - Socket: Hardware threads grouped by physical CPU socket\n - Core: Hardware threads grouped by physical core\n - MemoryDomain: Hardware threads grouped by NUMA domain\n - Die: Optional grouping by CPU die within sockets\n - Accelerators: List of attached hardware accelerators\n\nfunc (topo *Topology) EnsureTopologyMaps()\nfunc (topo *Topology) GetAcceleratorID(id int) (string, error)\nfunc (topo *Topology) GetAcceleratorIDs() []string\nfunc (topo *Topology) GetAcceleratorIDsAsInt() ([]int, error)\nfunc (topo *Topology) GetCoresFromHWThreads(hwthreads []int) (cores []int, exclusive bool)\nfunc (topo *Topology) GetMemoryDomainsBySocket(domainIDs []int) (map[int][]int, error)\nfunc (topo *Topology) GetMemoryDomainsFromHWThreads(hwthreads []int) (memDoms []int, exclusive bool)\nfunc (topo *Topology) GetSocketsFromCores(cores []int) (sockets []int, exclusive bool)\nfunc (topo *Topology) GetSocketsFromHWThreads(hwthreads []int) (sockets []int, exclusive bool)\nfunc (topo *Topology) InitTopologyMaps()","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"403291be-12df-4a86-b5ed-897819aeaa03"}
{"parentUuid":"e8c1450b-b4cd-4268-b51f-b0116aacdb11","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_015yM1B8nM7rm3edUHfDuVvC","type":"message","role":"assistant","content":[{"type":"text","text":"Now I can create the test file:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":713,"cache_read_input_tokens":90552,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":713},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHgFu8dWUa6m82HjSRc","type":"assistant","uuid":"97f44dfa-238d-4c2d-85d0-865a5165e0f3","timestamp":"2026-03-04T15:37:18.717Z"}
{"parentUuid":"97f44dfa-238d-4c2d-85d0-865a5165e0f3","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_015yM1B8nM7rm3edUHfDuVvC","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GPfnTTghYb8ndty5c9BAav","name":"Write","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery_test.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\npackage metricstore\n\nimport (\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// makeTopology creates a simple 2-socket, 4-core, 8-hwthread topology for testing.\n// Socket 0: cores 0,1 with hwthreads 0,1,2,3\n// Socket 1: cores 2,3 with hwthreads 4,5,6,7\n// MemoryDomain 0: hwthreads 0,1,2,3 (socket 0)\n// MemoryDomain 1: hwthreads 4,5,6,7 (socket 1)\nfunc makeTopology() schema.Topology {\n\ttopo := schema.Topology{\n\t\tNode: []int{0, 1, 2, 3, 4, 5, 6, 7},\n\t\tSocket: [][]int{{0, 1, 2, 3}, {4, 5, 6, 7}},\n\t\tMemoryDomain: [][]int{{0, 1, 2, 3}, {4, 5, 6, 7}},\n\t\tCore: [][]int{{0, 1}, {2, 3}, {4, 5}, {6, 7}},\n\t\tAccelerators: []*schema.Accelerator{\n\t\t\t{ID: \"gpu0\"},\n\t\t\t{ID: \"gpu1\"},\n\t\t},\n\t}\n\treturn topo\n}\n\nfunc TestBuildScopeQueries(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\taccIds := topo.GetAcceleratorIDs()\n\n\ttests := []struct {\n\t\tname string\n\t\tnativeScope schema.MetricScope\n\t\trequestedScope schema.MetricScope\n\t\texpectOk bool\n\t\texpectLen int // expected number of results\n\t\texpectAgg bool\n\t\texpectScope schema.MetricScope\n\t}{\n\t\t// Same-scope cases\n\t\t{\n\t\t\tname: \"HWThread->HWThread\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeHWThread, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeHWThread,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Core\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeCore,\n\t\t},\n\t\t{\n\t\t\tname: \"Socket->Socket\", nativeScope: schema.MetricScopeSocket,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->MemoryDomain\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeMemoryDomain, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeMemoryDomain,\n\t\t},\n\t\t{\n\t\t\tname: \"Node->Node\", nativeScope: schema.MetricScopeNode,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Accelerator->Accelerator\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeAccelerator, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeAccelerator,\n\t\t},\n\t\t// Aggregation cases\n\t\t{\n\t\t\tname: \"HWThread->Core\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 4, // 4 cores\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeCore,\n\t\t},\n\t\t{\n\t\t\tname: \"HWThread->Socket\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"HWThread->Node\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Socket\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Node\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Socket->Node\", nativeScope: schema.MetricScopeSocket,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->Node\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->Socket\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"Accelerator->Node\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t// Expected exception: Accelerator scope requested but non-accelerator scope in between\n\t\t{\n\t\t\tname: \"Accelerator->Core (exception)\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 0,\n\t\t},\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tresults, ok := BuildScopeQueries(\n\t\t\t\ttt.nativeScope, tt.requestedScope,\n\t\t\t\t\"test_metric\", \"node001\",\n\t\t\t\t&topo, topo.Node, accIds,\n\t\t\t)\n\n\t\t\tif ok != tt.expectOk {\n\t\t\t\tt.Fatalf(\"expected ok=%v, got ok=%v\", tt.expectOk, ok)\n\t\t\t}\n\n\t\t\tif len(results) != tt.expectLen {\n\t\t\t\tt.Fatalf(\"expected %d results, got %d\", tt.expectLen, len(results))\n\t\t\t}\n\n\t\t\tif tt.expectLen > 0 {\n\t\t\t\tfor _, r := range results {\n\t\t\t\t\tif r.Scope != tt.expectScope {\n\t\t\t\t\t\tt.Errorf(\"expected scope %s, got %s\", tt.expectScope, r.Scope)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Aggregate != tt.expectAgg {\n\t\t\t\t\t\tt.Errorf(\"expected aggregate=%v, got %v\", tt.expectAgg, r.Aggregate)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Metric != \"test_metric\" {\n\t\t\t\t\t\tt.Errorf(\"expected metric 'test_metric', got '%s'\", r.Metric)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Hostname != \"node001\" {\n\t\t\t\t\t\tt.Errorf(\"expected hostname 'node001', got '%s'\", r.Hostname)\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestBuildScopeQueries_UnhandledCase(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\n\t// Node native with HWThread requested => scope.Max = Node, but let's try an invalid combination\n\t// Actually all valid combinations are handled. An unhandled case would be something like\n\t// a scope that doesn't exist in the if-chain. Since all real scopes are covered,\n\t// we test with a synthetic unhandled combination by checking the bool return.\n\t// The function should return ok=false for truly unhandled cases.\n\n\t// For now, verify all known combinations return ok=true\n\tscopes := []schema.MetricScope{\n\t\tschema.MetricScopeHWThread, schema.MetricScopeCore,\n\t\tschema.MetricScopeSocket, schema.MetricScopeNode,\n\t}\n\n\tfor _, native := range scopes {\n\t\tfor _, requested := range scopes {\n\t\t\tresults, ok := BuildScopeQueries(\n\t\t\t\tnative, requested,\n\t\t\t\t\"m\", \"h\", &topo, topo.Node, nil,\n\t\t\t)\n\t\t\tif !ok {\n\t\t\t\tt.Errorf(\"unexpected unhandled case: native=%s, requested=%s\", native, requested)\n\t\t\t}\n\t\t\tif results == nil {\n\t\t\t\tt.Errorf(\"results should not be nil for native=%s, requested=%s\", native, requested)\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunc TestIntToStringSlice(t *testing.T) {\n\ttests := []struct {\n\t\tinput []int\n\t\texpected []string\n\t}{\n\t\t{nil, nil},\n\t\t{[]int{}, nil},\n\t\t{[]int{0}, []string{\"0\"}},\n\t\t{[]int{1, 2, 3}, []string{\"1\", \"2\", \"3\"}},\n\t\t{[]int{10, 100, 1000}, []string{\"10\", \"100\", \"1000\"}},\n\t}\n\n\tfor _, tt := range tests {\n\t\tresult := IntToStringSlice(tt.input)\n\t\tif len(result) != len(tt.expected) {\n\t\t\tt.Errorf(\"IntToStringSlice(%v): expected len %d, got %d\", tt.input, len(tt.expected), len(result))\n\t\t\tcontinue\n\t\t}\n\t\tfor i := range result {\n\t\t\tif result[i] != tt.expected[i] {\n\t\t\t\tt.Errorf(\"IntToStringSlice(%v)[%d]: expected %s, got %s\", tt.input, i, tt.expected[i], result[i])\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunc TestSanitizeStats(t *testing.T) {\n\t// Test: all valid - should remain unchanged\n\tavg, min, max := schema.Float(1.0), schema.Float(0.5), schema.Float(2.0)\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 1.0 || min != 0.5 || max != 2.0 {\n\t\tt.Errorf(\"SanitizeStats should not change valid values\")\n\t}\n\n\t// Test: one NaN - all should be zeroed\n\tavg, min, max = schema.Float(1.0), schema.Float(0.5), schema.NaN\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 0 || min != 0 || max != 0 {\n\t\tt.Errorf(\"SanitizeStats should zero all when any is NaN, got avg=%v min=%v max=%v\", avg, min, max)\n\t}\n\n\t// Test: all NaN\n\tavg, min, max = schema.NaN, schema.NaN, schema.NaN\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 0 || min != 0 || max != 0 {\n\t\tt.Errorf(\"SanitizeStats should zero all NaN values\")\n\t}\n}\n\nfunc TestNodeToNodeQuery(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\n\tresults, ok := BuildScopeQueries(\n\t\tschema.MetricScopeNode, schema.MetricScopeNode,\n\t\t\"cpu_load\", \"node001\",\n\t\t&topo, topo.Node, nil,\n\t)\n\n\tif !ok {\n\t\tt.Fatal(\"expected ok=true for Node->Node\")\n\t}\n\tif len(results) != 1 {\n\t\tt.Fatalf(\"expected 1 result, got %d\", len(results))\n\t}\n\tr := results[0]\n\tif r.Type != nil {\n\t\tt.Error(\"Node->Node should have nil Type\")\n\t}\n\tif r.TypeIds != nil {\n\t\tt.Error(\"Node->Node should have nil TypeIds\")\n\t}\n\tif r.Aggregate {\n\t\tt.Error(\"Node->Node should not aggregate\")\n\t}\n}\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":713,"cache_read_input_tokens":90552,"output_tokens":3568,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":713,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHgFu8dWUa6m82HjSRc","type":"assistant","uuid":"068a0cd8-83e9-4890-bece-283acfe24feb","timestamp":"2026-03-04T15:37:56.774Z"}
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{"parentUuid":"068a0cd8-83e9-4890-bece-283acfe24feb","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GPfnTTghYb8ndty5c9BAav","type":"tool_result","content":"File created successfully at: /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery_test.go"}]},"uuid":"602a40b0-f2c7-445d-b020-ac3f53d13df6","timestamp":"2026-03-04T15:37:56.947Z","toolUseResult":{"type":"create","filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery_test.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\npackage metricstore\n\nimport (\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// makeTopology creates a simple 2-socket, 4-core, 8-hwthread topology for testing.\n// Socket 0: cores 0,1 with hwthreads 0,1,2,3\n// Socket 1: cores 2,3 with hwthreads 4,5,6,7\n// MemoryDomain 0: hwthreads 0,1,2,3 (socket 0)\n// MemoryDomain 1: hwthreads 4,5,6,7 (socket 1)\nfunc makeTopology() schema.Topology {\n\ttopo := schema.Topology{\n\t\tNode: []int{0, 1, 2, 3, 4, 5, 6, 7},\n\t\tSocket: [][]int{{0, 1, 2, 3}, {4, 5, 6, 7}},\n\t\tMemoryDomain: [][]int{{0, 1, 2, 3}, {4, 5, 6, 7}},\n\t\tCore: [][]int{{0, 1}, {2, 3}, {4, 5}, {6, 7}},\n\t\tAccelerators: []*schema.Accelerator{\n\t\t\t{ID: \"gpu0\"},\n\t\t\t{ID: \"gpu1\"},\n\t\t},\n\t}\n\treturn topo\n}\n\nfunc TestBuildScopeQueries(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\taccIds := topo.GetAcceleratorIDs()\n\n\ttests := []struct {\n\t\tname string\n\t\tnativeScope schema.MetricScope\n\t\trequestedScope schema.MetricScope\n\t\texpectOk bool\n\t\texpectLen int // expected number of results\n\t\texpectAgg bool\n\t\texpectScope schema.MetricScope\n\t}{\n\t\t// Same-scope cases\n\t\t{\n\t\t\tname: \"HWThread->HWThread\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeHWThread, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeHWThread,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Core\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeCore,\n\t\t},\n\t\t{\n\t\t\tname: \"Socket->Socket\", nativeScope: schema.MetricScopeSocket,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->MemoryDomain\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeMemoryDomain, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeMemoryDomain,\n\t\t},\n\t\t{\n\t\t\tname: \"Node->Node\", nativeScope: schema.MetricScopeNode,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Accelerator->Accelerator\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeAccelerator, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: false, expectScope: schema.MetricScopeAccelerator,\n\t\t},\n\t\t// Aggregation cases\n\t\t{\n\t\t\tname: \"HWThread->Core\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 4, // 4 cores\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeCore,\n\t\t},\n\t\t{\n\t\t\tname: \"HWThread->Socket\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"HWThread->Node\", nativeScope: schema.MetricScopeHWThread,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Socket\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"Core->Node\", nativeScope: schema.MetricScopeCore,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"Socket->Node\", nativeScope: schema.MetricScopeSocket,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->Node\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t{\n\t\t\tname: \"MemoryDomain->Socket\", nativeScope: schema.MetricScopeMemoryDomain,\n\t\t\trequestedScope: schema.MetricScopeSocket, expectOk: true, expectLen: 2, // 2 sockets\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeSocket,\n\t\t},\n\t\t{\n\t\t\tname: \"Accelerator->Node\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeNode, expectOk: true, expectLen: 1,\n\t\t\texpectAgg: true, expectScope: schema.MetricScopeNode,\n\t\t},\n\t\t// Expected exception: Accelerator scope requested but non-accelerator scope in between\n\t\t{\n\t\t\tname: \"Accelerator->Core (exception)\", nativeScope: schema.MetricScopeAccelerator,\n\t\t\trequestedScope: schema.MetricScopeCore, expectOk: true, expectLen: 0,\n\t\t},\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tresults, ok := BuildScopeQueries(\n\t\t\t\ttt.nativeScope, tt.requestedScope,\n\t\t\t\t\"test_metric\", \"node001\",\n\t\t\t\t&topo, topo.Node, accIds,\n\t\t\t)\n\n\t\t\tif ok != tt.expectOk {\n\t\t\t\tt.Fatalf(\"expected ok=%v, got ok=%v\", tt.expectOk, ok)\n\t\t\t}\n\n\t\t\tif len(results) != tt.expectLen {\n\t\t\t\tt.Fatalf(\"expected %d results, got %d\", tt.expectLen, len(results))\n\t\t\t}\n\n\t\t\tif tt.expectLen > 0 {\n\t\t\t\tfor _, r := range results {\n\t\t\t\t\tif r.Scope != tt.expectScope {\n\t\t\t\t\t\tt.Errorf(\"expected scope %s, got %s\", tt.expectScope, r.Scope)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Aggregate != tt.expectAgg {\n\t\t\t\t\t\tt.Errorf(\"expected aggregate=%v, got %v\", tt.expectAgg, r.Aggregate)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Metric != \"test_metric\" {\n\t\t\t\t\t\tt.Errorf(\"expected metric 'test_metric', got '%s'\", r.Metric)\n\t\t\t\t\t}\n\t\t\t\t\tif r.Hostname != \"node001\" {\n\t\t\t\t\t\tt.Errorf(\"expected hostname 'node001', got '%s'\", r.Hostname)\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestBuildScopeQueries_UnhandledCase(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\n\t// Node native with HWThread requested => scope.Max = Node, but let's try an invalid combination\n\t// Actually all valid combinations are handled. An unhandled case would be something like\n\t// a scope that doesn't exist in the if-chain. Since all real scopes are covered,\n\t// we test with a synthetic unhandled combination by checking the bool return.\n\t// The function should return ok=false for truly unhandled cases.\n\n\t// For now, verify all known combinations return ok=true\n\tscopes := []schema.MetricScope{\n\t\tschema.MetricScopeHWThread, schema.MetricScopeCore,\n\t\tschema.MetricScopeSocket, schema.MetricScopeNode,\n\t}\n\n\tfor _, native := range scopes {\n\t\tfor _, requested := range scopes {\n\t\t\tresults, ok := BuildScopeQueries(\n\t\t\t\tnative, requested,\n\t\t\t\t\"m\", \"h\", &topo, topo.Node, nil,\n\t\t\t)\n\t\t\tif !ok {\n\t\t\t\tt.Errorf(\"unexpected unhandled case: native=%s, requested=%s\", native, requested)\n\t\t\t}\n\t\t\tif results == nil {\n\t\t\t\tt.Errorf(\"results should not be nil for native=%s, requested=%s\", native, requested)\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunc TestIntToStringSlice(t *testing.T) {\n\ttests := []struct {\n\t\tinput []int\n\t\texpected []string\n\t}{\n\t\t{nil, nil},\n\t\t{[]int{}, nil},\n\t\t{[]int{0}, []string{\"0\"}},\n\t\t{[]int{1, 2, 3}, []string{\"1\", \"2\", \"3\"}},\n\t\t{[]int{10, 100, 1000}, []string{\"10\", \"100\", \"1000\"}},\n\t}\n\n\tfor _, tt := range tests {\n\t\tresult := IntToStringSlice(tt.input)\n\t\tif len(result) != len(tt.expected) {\n\t\t\tt.Errorf(\"IntToStringSlice(%v): expected len %d, got %d\", tt.input, len(tt.expected), len(result))\n\t\t\tcontinue\n\t\t}\n\t\tfor i := range result {\n\t\t\tif result[i] != tt.expected[i] {\n\t\t\t\tt.Errorf(\"IntToStringSlice(%v)[%d]: expected %s, got %s\", tt.input, i, tt.expected[i], result[i])\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunc TestSanitizeStats(t *testing.T) {\n\t// Test: all valid - should remain unchanged\n\tavg, min, max := schema.Float(1.0), schema.Float(0.5), schema.Float(2.0)\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 1.0 || min != 0.5 || max != 2.0 {\n\t\tt.Errorf(\"SanitizeStats should not change valid values\")\n\t}\n\n\t// Test: one NaN - all should be zeroed\n\tavg, min, max = schema.Float(1.0), schema.Float(0.5), schema.NaN\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 0 || min != 0 || max != 0 {\n\t\tt.Errorf(\"SanitizeStats should zero all when any is NaN, got avg=%v min=%v max=%v\", avg, min, max)\n\t}\n\n\t// Test: all NaN\n\tavg, min, max = schema.NaN, schema.NaN, schema.NaN\n\tSanitizeStats(&avg, &min, &max)\n\tif avg != 0 || min != 0 || max != 0 {\n\t\tt.Errorf(\"SanitizeStats should zero all NaN values\")\n\t}\n}\n\nfunc TestNodeToNodeQuery(t *testing.T) {\n\ttopo := makeTopology()\n\ttopo.InitTopologyMaps()\n\n\tresults, ok := BuildScopeQueries(\n\t\tschema.MetricScopeNode, schema.MetricScopeNode,\n\t\t\"cpu_load\", \"node001\",\n\t\t&topo, topo.Node, nil,\n\t)\n\n\tif !ok {\n\t\tt.Fatal(\"expected ok=true for Node->Node\")\n\t}\n\tif len(results) != 1 {\n\t\tt.Fatalf(\"expected 1 result, got %d\", len(results))\n\t}\n\tr := results[0]\n\tif r.Type != nil {\n\t\tt.Error(\"Node->Node should have nil Type\")\n\t}\n\tif r.TypeIds != nil {\n\t\tt.Error(\"Node->Node should have nil TypeIds\")\n\t}\n\tif r.Aggregate {\n\t\tt.Error(\"Node->Node should not aggregate\")\n\t}\n}\n","structuredPatch":[],"originalFile":null},"sourceToolAssistantUUID":"068a0cd8-83e9-4890-bece-283acfe24feb"}
{"parentUuid":"602a40b0-f2c7-445d-b020-ac3f53d13df6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01HMHyj5GXRVwYwRgegHPXBh","type":"message","role":"assistant","content":[{"type":"text","text":"I need to check if `schema.NaN` exists:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3616,"cache_read_input_tokens":91265,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3616},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHjLjRW5mJM1Rrr7Adg","type":"assistant","uuid":"b779e34a-1db2-42dd-b4ed-c6c3c2481ce7","timestamp":"2026-03-04T15:38:00.178Z"}
{"parentUuid":"b779e34a-1db2-42dd-b4ed-c6c3c2481ce7","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01HMHyj5GXRVwYwRgegHPXBh","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017SV3nDrVHb4FykqwR5Lz4y","name":"Bash","input":{"command":"go doc github.com/ClusterCockpit/cc-lib/v2/schema Float 2>&1 | head -20","description":"Check schema.Float type"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3616,"cache_read_input_tokens":91265,"output_tokens":116,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3616,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHjLjRW5mJM1Rrr7Adg","type":"assistant","uuid":"82b7572f-2ec7-44d2-bd54-45c3ce4b4020","timestamp":"2026-03-04T15:38:00.801Z"}
{"parentUuid":"82b7572f-2ec7-44d2-bd54-45c3ce4b4020","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017SV3nDrVHb4FykqwR5Lz4y","type":"tool_result","content":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\ntype Float float64\n Float is a custom float64 type with special handling for NaN values in JSON\n and GraphQL serialization.\n\n Standard Go encoding/json treats NaN as an error, but in metric data it's\n common to have missing or invalid measurements that should be represented as\n null in JSON. This type allows NaN values to be serialized as JSON null and\n vice versa, while avoiding the memory overhead of using *float64 pointers\n for every nullable metric value.\n\n Key behaviors:\n - NaN values marshal to JSON null\n - JSON null unmarshals to NaN\n - Regular float values marshal/unmarshal normally\n - GraphQL marshaling follows the same null handling\n\n This is particularly important for time series metric data where missing\n data points are common and need efficient representation.","is_error":false}]},"uuid":"0ba2e16e-056d-468b-84bf-835911a02f40","timestamp":"2026-03-04T15:38:01.028Z","toolUseResult":{"stdout":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\ntype Float float64\n Float is a custom float64 type with special handling for NaN values in JSON\n and GraphQL serialization.\n\n Standard Go encoding/json treats NaN as an error, but in metric data it's\n common to have missing or invalid measurements that should be represented as\n null in JSON. This type allows NaN values to be serialized as JSON null and\n vice versa, while avoiding the memory overhead of using *float64 pointers\n for every nullable metric value.\n\n Key behaviors:\n - NaN values marshal to JSON null\n - JSON null unmarshals to NaN\n - Regular float values marshal/unmarshal normally\n - GraphQL marshaling follows the same null handling\n\n This is particularly important for time series metric data where missing\n data points are common and need efficient representation.","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"82b7572f-2ec7-44d2-bd54-45c3ce4b4020"}
{"parentUuid":"0ba2e16e-056d-468b-84bf-835911a02f40","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_013hiXuDhuxD3G1Bs78zedGZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AzKCo6DuSX2vaHyW3PQKRq","name":"Bash","input":{"command":"go doc github.com/ClusterCockpit/cc-lib/v2/schema.NaN 2>&1","description":"Check if NaN constant exists"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":338,"cache_read_input_tokens":94881,"output_tokens":100,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":338,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHjeUWxGx66rpBm5zFU","type":"assistant","uuid":"393fd334-ea5b-4035-b0cd-d84811733d27","timestamp":"2026-03-04T15:38:04.714Z"}
{"parentUuid":"393fd334-ea5b-4035-b0cd-d84811733d27","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AzKCo6DuSX2vaHyW3PQKRq","type":"tool_result","content":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\nvar (\n\tNaN Float = Float(math.NaN())\n)","is_error":false}]},"uuid":"27f19bf6-5eae-4cf0-992e-823e2ca25b5f","timestamp":"2026-03-04T15:38:04.987Z","toolUseResult":{"stdout":"package schema // import \"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\nvar (\n\tNaN Float = Float(math.NaN())\n)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"393fd334-ea5b-4035-b0cd-d84811733d27"}
{"parentUuid":"27f19bf6-5eae-4cf0-992e-823e2ca25b5f","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_0128JzsX8FphiWcjn9Kcfs9W","type":"message","role":"assistant","content":[{"type":"text","text":"Good, `schema.NaN` exists. Now run the tests:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":348,"cache_read_input_tokens":95219,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":348},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHjw7dsY1Pyc4zajZtt","type":"assistant","uuid":"c46c480c-42d6-4c97-88a7-730ea811e963","timestamp":"2026-03-04T15:38:07.841Z"}
{"parentUuid":"c46c480c-42d6-4c97-88a7-730ea811e963","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_0128JzsX8FphiWcjn9Kcfs9W","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01H4M2oACWo8R74uv3J3LQRv","name":"Bash","input":{"command":"go test ./pkg/metricstore/... -run TestBuildScopeQueries -v 2>&1","description":"Run scopequery tests"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":348,"cache_read_input_tokens":95219,"output_tokens":133,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":348,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHjw7dsY1Pyc4zajZtt","type":"assistant","uuid":"088003ef-38d5-4b6a-b671-0132107c04ca","timestamp":"2026-03-04T15:38:08.799Z"}
{"parentUuid":"088003ef-38d5-4b6a-b671-0132107c04ca","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01H4M2oACWo8R74uv3J3LQRv","type":"tool_result","content":"=== RUN TestBuildScopeQueries\n=== RUN TestBuildScopeQueries/HWThread->HWThread\n=== RUN TestBuildScopeQueries/Core->Core\n=== RUN TestBuildScopeQueries/Socket->Socket\n=== RUN TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN TestBuildScopeQueries/Node->Node\n=== RUN TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN TestBuildScopeQueries/HWThread->Core\n=== RUN TestBuildScopeQueries/HWThread->Socket\n=== RUN TestBuildScopeQueries/HWThread->Node\n=== RUN TestBuildScopeQueries/Core->Socket\n=== RUN TestBuildScopeQueries/Core->Node\n=== RUN TestBuildScopeQueries/Socket->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN TestBuildScopeQueries/Accelerator->Node\n=== RUN TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\nPASS\nok \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.488s","is_error":false}]},"uuid":"eb6b21ba-f8d4-4ef6-a908-041f893084d2","timestamp":"2026-03-04T15:38:10.353Z","toolUseResult":{"stdout":"=== RUN TestBuildScopeQueries\n=== RUN TestBuildScopeQueries/HWThread->HWThread\n=== RUN TestBuildScopeQueries/Core->Core\n=== RUN TestBuildScopeQueries/Socket->Socket\n=== RUN TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN TestBuildScopeQueries/Node->Node\n=== RUN TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN TestBuildScopeQueries/HWThread->Core\n=== RUN TestBuildScopeQueries/HWThread->Socket\n=== RUN TestBuildScopeQueries/HWThread->Node\n=== RUN TestBuildScopeQueries/Core->Socket\n=== RUN TestBuildScopeQueries/Core->Node\n=== RUN TestBuildScopeQueries/Socket->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN TestBuildScopeQueries/Accelerator->Node\n=== RUN TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\nPASS\nok \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.488s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"088003ef-38d5-4b6a-b671-0132107c04ca"}
{"parentUuid":"eb6b21ba-f8d4-4ef6-a908-041f893084d2","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_014nB2NgcxTh8VNY5jmqPR9P","type":"message","role":"assistant","content":[{"type":"text","text":"All tests pass. Let me run all the scopequery tests:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":977,"cache_read_input_tokens":95567,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":977},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHkLSLoUnLGERKw4y89","type":"assistant","uuid":"bc6171f8-d5c8-4d39-9d32-82431a7ed01a","timestamp":"2026-03-04T15:38:13.690Z"}
{"parentUuid":"bc6171f8-d5c8-4d39-9d32-82431a7ed01a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_014nB2NgcxTh8VNY5jmqPR9P","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SufKQAD9of2rif45ao5gYZ","name":"Bash","input":{"command":"go test ./pkg/metricstore/... -run \"TestBuildScope|TestIntToString|TestSanitize|TestNodeToNode\" -v 2>&1","description":"Run all new tests"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":977,"cache_read_input_tokens":95567,"output_tokens":126,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":977,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHkLSLoUnLGERKw4y89","type":"assistant","uuid":"3119ba2b-41f5-4c08-9450-a206c7d7a14a","timestamp":"2026-03-04T15:38:14.281Z"}
{"parentUuid":"3119ba2b-41f5-4c08-9450-a206c7d7a14a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SufKQAD9of2rif45ao5gYZ","type":"tool_result","content":"=== RUN TestBuildScopeQueries\n=== RUN TestBuildScopeQueries/HWThread->HWThread\n=== RUN TestBuildScopeQueries/Core->Core\n=== RUN TestBuildScopeQueries/Socket->Socket\n=== RUN TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN TestBuildScopeQueries/Node->Node\n=== RUN TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN TestBuildScopeQueries/HWThread->Core\n=== RUN TestBuildScopeQueries/HWThread->Socket\n=== RUN TestBuildScopeQueries/HWThread->Node\n=== RUN TestBuildScopeQueries/Core->Socket\n=== RUN TestBuildScopeQueries/Core->Node\n=== RUN TestBuildScopeQueries/Socket->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN TestBuildScopeQueries/Accelerator->Node\n=== RUN TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.313s","is_error":false}]},"uuid":"8357e02e-6b68-475d-8095-d8e399731e90","timestamp":"2026-03-04T15:38:15.512Z","toolUseResult":{"stdout":"=== RUN TestBuildScopeQueries\n=== RUN TestBuildScopeQueries/HWThread->HWThread\n=== RUN TestBuildScopeQueries/Core->Core\n=== RUN TestBuildScopeQueries/Socket->Socket\n=== RUN TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN TestBuildScopeQueries/Node->Node\n=== RUN TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN TestBuildScopeQueries/HWThread->Core\n=== RUN TestBuildScopeQueries/HWThread->Socket\n=== RUN TestBuildScopeQueries/HWThread->Node\n=== RUN TestBuildScopeQueries/Core->Socket\n=== RUN TestBuildScopeQueries/Core->Node\n=== RUN TestBuildScopeQueries/Socket->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Node\n=== RUN TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN TestBuildScopeQueries/Accelerator->Node\n=== RUN TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.313s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"3119ba2b-41f5-4c08-9450-a206c7d7a14a"}
{"parentUuid":"8357e02e-6b68-475d-8095-d8e399731e90","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_012KS2LJ9g4Sn7p9LvJ3kHGV","type":"message","role":"assistant","content":[{"type":"text","text":"All passing. Now run the full test suite:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1074,"cache_read_input_tokens":96544,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1074},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiHkiRgN8Bhc4bjyEJf3","type":"assistant","uuid":"bea762aa-862d-4a1a-ae00-d44f28654113","timestamp":"2026-03-04T15:38:18.856Z"}
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{"parentUuid":"2b4d72f3-62d0-4f60-9907-2a3c21cf2815","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"5de2a23c-09cd-4d6c-a97c-fab8657d094c","version":"2.1.66","gitBranch":"dev","slug":"curious-dancing-nebula","message":{"model":"claude-opus-4-6","id":"msg_01TvYGHfr3inqrb7i2ZNXHZC","type":"message","role":"assistant","content":[{"type":"text","text":"All done. Here's a summary of what was implemented:\n\n**New file: `pkg/metricstore/scopequery.go`**\n- `ScopeQueryResult` — package-independent intermediate type (no Resolution field)\n- `BuildScopeQueries()` — shared scope transformation logic ported from metricstoreclient, covering all 16+ cases including the **MemoryDomain → Socket** transformation that was missing from metricstore\n- `IntToStringSlice()` — exported, using the optimized buffer-reuse version\n- `SanitizeStats()` — exported, zeros ALL stats if ANY is NaN (consistent behavior)\n- Exported scope string constants (`HWThreadString`, `CoreString`, etc.)\n\n**New file: `pkg/metricstore/scopequery_test.go`**\n- Table-driven tests for all scope transformations (same-scope, aggregation, accelerator, memory domain)\n- Tests for `IntToStringSlice` and `SanitizeStats`\n\n**Modified: `pkg/metricstore/query.go`**\n- `buildQueries()` and `buildNodeQueries()` now call `BuildScopeQueries()` and convert results to local `APIQuery`\n- Removed local `sanitizeStats`, `intToStringSlice`, scope string constants\n- Switched scope dedup from `map[schema.MetricScope]bool` to labeled-loop + slice\n- Gains the **MemoryDomain → Socket** transformation that was previously missing\n\n**Modified: `internal/metricstoreclient/cc-metric-store-queries.go`**\n- Replaced local `buildScopeQueries()` with `metricstore.BuildScopeQueries()`\n- Removed local `intToStringSlice` and scope string constants\n\n**Modified: `internal/metricstoreclient/cc-metric-store.go`**\n- Replaced local `sanitizeStats` with `ms.SanitizeStats()`"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":100,"cache_read_input_tokens":98383,"output_tokens":465,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":100,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiHn19XhLpuJ9uu4bgun","type":"assistant","uuid":"0f6f3c54-5779-4913-bcff-93f1eb7add15","timestamp":"2026-03-04T15:38:44.625Z"}
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