From 616b02a90fda4162d450627495a7e303dc4e789d Mon Sep 17 00:00:00 2001 From: Jan Eitzinger Date: Wed, 4 Mar 2026 17:31:37 +0100 Subject: [PATCH] Checkpoint: d10e6221ee4f Entire-Session: 2c26c946-1def-45ad-aac8-f65c4765658b Entire-Strategy: manual-commit Entire-Agent: Claude Code Ephemeral-branch: entire/2698208-e3b0c4 --- d1/0e6221ee4f/0/content_hash.txt | 1 + d1/0e6221ee4f/0/context.md | 18 ++++ d1/0e6221ee4f/0/full.jsonl | 147 +++++++++++++++++++++++++++++++ d1/0e6221ee4f/0/metadata.json | 33 +++++++ d1/0e6221ee4f/0/prompt.txt | 113 ++++++++++++++++++++++++ d1/0e6221ee4f/metadata.json | 29 ++++++ 6 files changed, 341 insertions(+) create mode 100644 d1/0e6221ee4f/0/content_hash.txt create mode 100644 d1/0e6221ee4f/0/context.md create mode 100644 d1/0e6221ee4f/0/full.jsonl create mode 100644 d1/0e6221ee4f/0/metadata.json create mode 100644 d1/0e6221ee4f/0/prompt.txt create mode 100644 d1/0e6221ee4f/metadata.json diff --git a/d1/0e6221ee4f/0/content_hash.txt b/d1/0e6221ee4f/0/content_hash.txt new file mode 100644 index 00000000..ce72ad29 --- /dev/null +++ b/d1/0e6221ee4f/0/content_hash.txt @@ -0,0 +1 @@ +sha256:ad59838443958f38904843251dcc7aa0b67210074fb8697ff3136cd088c540d1 \ No newline at end of file diff --git a/d1/0e6221ee4f/0/context.md b/d1/0e6221ee4f/0/context.md new file mode 100644 index 00000000..e1aee7cc --- /dev/null +++ b/d1/0e6221ee4f/0/context.md @@ -0,0 +1,18 @@ +# Session Context + +## User Prompts + +### Prompt 1 + +Implement the following plan: + +# Plan: Improve buildQuery implementation and related code + +## Context + +The `buildQueries`/`buildNodeQueries` functions and `Load*` methods exist in two packages with near-identical logic: +- `pkg/metricstore/query.go` (internal, in-memory store) +- `internal/metricstoreclient/cc-metric-store.go` + `cc-metric-store-queries.go` (external, HTTP client) + +Both share `BuildScopeQueries` and `SanitizeStats` from `pkg/metricstore/scopequery.go`. The review identified bug... + diff --git a/d1/0e6221ee4f/0/full.jsonl b/d1/0e6221ee4f/0/full.jsonl new file mode 100644 index 00000000..f84c0bde --- /dev/null +++ b/d1/0e6221ee4f/0/full.jsonl @@ -0,0 +1,147 @@ +{"type":"file-history-snapshot","messageId":"1b4af328-8505-4c6a-b2d4-9c102454705c","snapshot":{"messageId":"1b4af328-8505-4c6a-b2d4-9c102454705c","trackedFileBackups":{},"timestamp":"2026-03-04T16:21:24.341Z"},"isSnapshotUpdate":false} +{"parentUuid":null,"isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"1acfae29-e5cc-4dd0-a6e2-7f11167368b8","toolUseID":"1acfae29-e5cc-4dd0-a6e2-7f11167368b8","timestamp":"2026-03-04T16:21:24.286Z","uuid":"221c23c0-659b-4ece-a489-72d0a5020ef8"} +{"parentUuid":"221c23c0-659b-4ece-a489-72d0a5020ef8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Plan: Improve buildQuery implementation and related code\n\n## Context\n\nThe `buildQueries`/`buildNodeQueries` functions and `Load*` methods exist in two packages with near-identical logic:\n- `pkg/metricstore/query.go` (internal, in-memory store)\n- `internal/metricstoreclient/cc-metric-store.go` + `cc-metric-store-queries.go` (external, HTTP client)\n\nBoth share `BuildScopeQueries` and `SanitizeStats` from `pkg/metricstore/scopequery.go`. The review identified bugs, dead code, duplicated patterns, and inconsistencies across both packages.\n\n## Changes\n\n### 1. Bug fix: `LoadNodeData` nil metric config panic (both packages)\n\n`archive.GetMetricConfig()` can return nil, but `LoadNodeData` dereferences `mc.Unit`/`mc.Timestep` without checking. Every other Load function checks.\n\n**Files:**\n- `pkg/metricstore/query.go:600` — add nil check + `continue`\n- `internal/metricstoreclient/cc-metric-store.go:595` — add nil check + `continue`\n\n### 2. Bug fix: `LoadNodeData` missing `continue` after error (both packages)\n\nWhen `qdata.Error != nil`, the error is appended but execution falls through to append invalid data. Should `continue`.\n\n**Files:**\n- `pkg/metricstore/query.go:589-590`\n- `internal/metricstoreclient/cc-metric-store.go:583-585`\n\n### 3. Extract `ExtractTypeID` helper to `scopequery.go`\n\nThe ID-extraction block is copy-pasted 6 times (3x in each package). Extract to shared helper in `pkg/metricstore/scopequery.go`.\n\n```go\nfunc ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string {\n if queryType == nil {\n return nil\n }\n if ndx < len(typeIds) {\n id := typeIds[ndx]\n return &id\n }\n cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n ndx, len(typeIds), metric, hostname)\n return nil\n}\n```\n\n**Files to update:**\n- `pkg/metricstore/scopequery.go` — add function\n- `pkg/metricstore/query.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData`\n- `internal/metricstoreclient/cc-metric-store.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData`\n\n### 4. Extract `IsMetricRemovedForSubCluster` helper to `scopequery.go`\n\nThe subcluster-removal check is duplicated 4 times (2x in each package). Extract to shared helper.\n\n```go\nfunc IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool {\n for _, scConfig := range mc.SubClusters {\n if scConfig.Name == subCluster && scConfig.Remove {\n return true\n }\n }\n return false\n}\n```\n\n**Files to update:**\n- `pkg/metricstore/scopequery.go` — add function\n- `pkg/metricstore/query.go` — replace in `buildQueries` and `buildNodeQueries`\n- `internal/metricstoreclient/cc-metric-store-queries.go` — replace in `buildQueries` and `buildNodeQueries`\n\n### 5. Fix TODO in production error messages\n\nReplace `\"TODO: unhandled case\"` with proper error text in all 4 occurrences.\n\n**Files:**\n- `pkg/metricstore/query.go:314,901`\n- `internal/metricstoreclient/cc-metric-store-queries.go:126,237`\n\n### 6. Remove redundant inner bounds checks in `LoadData` and `LoadNodeListData`\n\nThe outer truncation (e.g., lines 120-129 in internal `LoadData`) already ensures bounds safety, making the inner `if i >= len(...)` check dead code. Remove the inner checks.\n\n**Files (4 occurrences — 2 in each package):**\n- `pkg/metricstore/query.go` — `LoadData` (lines 131-137), `LoadNodeListData` (lines 696-702)\n- `internal/metricstoreclient/cc-metric-store.go` — `LoadData` (lines 278-283), `LoadNodeListData` (lines 682-688)\n\n### 7. Add capacity hint for `assignedScope` in internal `buildQueries`/`buildNodeQueries`\n\n**File:** `pkg/metricstore/query.go:254,822`\n\nChange `assignedScope := []schema.MetricScope{}` to use `make()` with matching capacity.\n\n### 8. Add bounds check to `LoadStats` for consistency (both packages)\n\n`LoadStats` indexes `req.Queries[i]` without checking bounds, unlike all other Load functions. Add a check.\n\n**Files:**\n- `pkg/metricstore/query.go:376`\n- `internal/metricstoreclient/cc-metric-store.go:395`\n\n## Verification\n\n1. `go build ./...` — ensure compilation succeeds\n2. `go test ./pkg/metricstore/...` — run metricstore tests\n3. `go test ./internal/metricstoreclient/...` — run client tests\n4. `go vet ./pkg/metricstore/... ./internal/metricstoreclient/...` — check for issues\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/f0763fe7-f9bf-47b1-85f7-b16c2b9bffe1.jsonl"},"uuid":"1b4af328-8505-4c6a-b2d4-9c102454705c","timestamp":"2026-03-04T16:21:24.123Z","planContent":"# Plan: Improve buildQuery implementation and related code\n\n## Context\n\nThe `buildQueries`/`buildNodeQueries` functions and `Load*` methods exist in two packages with near-identical logic:\n- `pkg/metricstore/query.go` (internal, in-memory store)\n- `internal/metricstoreclient/cc-metric-store.go` + `cc-metric-store-queries.go` (external, HTTP client)\n\nBoth share `BuildScopeQueries` and `SanitizeStats` from `pkg/metricstore/scopequery.go`. The review identified bugs, dead code, duplicated patterns, and inconsistencies across both packages.\n\n## Changes\n\n### 1. Bug fix: `LoadNodeData` nil metric config panic (both packages)\n\n`archive.GetMetricConfig()` can return nil, but `LoadNodeData` dereferences `mc.Unit`/`mc.Timestep` without checking. Every other Load function checks.\n\n**Files:**\n- `pkg/metricstore/query.go:600` — add nil check + `continue`\n- `internal/metricstoreclient/cc-metric-store.go:595` — add nil check + `continue`\n\n### 2. Bug fix: `LoadNodeData` missing `continue` after error (both packages)\n\nWhen `qdata.Error != nil`, the error is appended but execution falls through to append invalid data. Should `continue`.\n\n**Files:**\n- `pkg/metricstore/query.go:589-590`\n- `internal/metricstoreclient/cc-metric-store.go:583-585`\n\n### 3. Extract `ExtractTypeID` helper to `scopequery.go`\n\nThe ID-extraction block is copy-pasted 6 times (3x in each package). Extract to shared helper in `pkg/metricstore/scopequery.go`.\n\n```go\nfunc ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string {\n if queryType == nil {\n return nil\n }\n if ndx < len(typeIds) {\n id := typeIds[ndx]\n return &id\n }\n cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n ndx, len(typeIds), metric, hostname)\n return nil\n}\n```\n\n**Files to update:**\n- `pkg/metricstore/scopequery.go` — add function\n- `pkg/metricstore/query.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData`\n- `internal/metricstoreclient/cc-metric-store.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData`\n\n### 4. Extract `IsMetricRemovedForSubCluster` helper to `scopequery.go`\n\nThe subcluster-removal check is duplicated 4 times (2x in each package). Extract to shared helper.\n\n```go\nfunc IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool {\n for _, scConfig := range mc.SubClusters {\n if scConfig.Name == subCluster && scConfig.Remove {\n return true\n }\n }\n return false\n}\n```\n\n**Files to update:**\n- `pkg/metricstore/scopequery.go` — add function\n- `pkg/metricstore/query.go` — replace in `buildQueries` and `buildNodeQueries`\n- `internal/metricstoreclient/cc-metric-store-queries.go` — replace in `buildQueries` and `buildNodeQueries`\n\n### 5. Fix TODO in production error messages\n\nReplace `\"TODO: unhandled case\"` with proper error text in all 4 occurrences.\n\n**Files:**\n- `pkg/metricstore/query.go:314,901`\n- `internal/metricstoreclient/cc-metric-store-queries.go:126,237`\n\n### 6. Remove redundant inner bounds checks in `LoadData` and `LoadNodeListData`\n\nThe outer truncation (e.g., lines 120-129 in internal `LoadData`) already ensures bounds safety, making the inner `if i >= len(...)` check dead code. Remove the inner checks.\n\n**Files (4 occurrences — 2 in each package):**\n- `pkg/metricstore/query.go` — `LoadData` (lines 131-137), `LoadNodeListData` (lines 696-702)\n- `internal/metricstoreclient/cc-metric-store.go` — `LoadData` (lines 278-283), `LoadNodeListData` (lines 682-688)\n\n### 7. Add capacity hint for `assignedScope` in internal `buildQueries`/`buildNodeQueries`\n\n**File:** `pkg/metricstore/query.go:254,822`\n\nChange `assignedScope := []schema.MetricScope{}` to use `make()` with matching capacity.\n\n### 8. Add bounds check to `LoadStats` for consistency (both packages)\n\n`LoadStats` indexes `req.Queries[i]` without checking bounds, unlike all other Load functions. Add a check.\n\n**Files:**\n- `pkg/metricstore/query.go:376`\n- `internal/metricstoreclient/cc-metric-store.go:395`\n\n## Verification\n\n1. `go build ./...` — ensure compilation succeeds\n2. `go test ./pkg/metricstore/...` — run metricstore tests\n3. `go test ./internal/metricstoreclient/...` — run client tests\n4. `go vet ./pkg/metricstore/... ./internal/metricstoreclient/...` — check for issues\n"} +{"parentUuid":"1b4af328-8505-4c6a-b2d4-9c102454705c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_011g9AfQBbpziMeRAKPETsBo","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me start by reading the relevant files to understand the current code before making changes.","signature":"EogCCkYICxgCKkBW59RCY6tGSB56nAGA//z3lRvJEDn5iJLOClMZGjxNRiWuAGiCmaIgNTdta1Sy/TNzx1kW0Sge7rGR/PxRSRnzEgzVWMKKRnGC7F5gVQ8aDB6IRgIGLUck+mUAMiIwPXSOdENPofnHH9C37ntJ46QPY4BzS6csCErH0oBdUdwdHWREsXjnRxmDPUwveX44KnBZq7rE/ucs/NLtbve7FsWyZDGfGNx4ZjUMDIu8FXayWkk/mgTVUREaEua4Wq+iLifqOh7XyOWmdPdP6hWeqLgZok0w5xWaXSdVlPcdSNOa45s5wW+0+MiAPlM5CVjU7eU9PEMAJ4lRdjI1NYPgS1GxGAE="}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":5219,"cache_read_input_tokens":20208,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5219},"output_tokens":10,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM3Z8ehPsB12AQ62uTR","type":"assistant","uuid":"d7ac8dff-17df-4dda-a199-64a0acff57ff","timestamp":"2026-03-04T16:21:27.002Z"} +{"parentUuid":"d7ac8dff-17df-4dda-a199-64a0acff57ff","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_011g9AfQBbpziMeRAKPETsBo","type":"message","role":"assistant","content":[{"type":"text","text":"I'll start by reading the key files to understand the current code."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":5219,"cache_read_input_tokens":20208,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5219},"output_tokens":10,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM3Z8ehPsB12AQ62uTR","type":"assistant","uuid":"9d93b803-a9c4-4b1f-8066-2aa3a3ce854d","timestamp":"2026-03-04T16:21:27.552Z"} +{"parentUuid":"9d93b803-a9c4-4b1f-8066-2aa3a3ce854d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_011g9AfQBbpziMeRAKPETsBo","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KoYLbsxdKoLzHRtxpeDnCJ","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":5219,"cache_read_input_tokens":20208,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5219},"output_tokens":10,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM3Z8ehPsB12AQ62uTR","type":"assistant","uuid":"5a8d3ec0-23f6-42ad-9bf7-dc28fd089d24","timestamp":"2026-03-04T16:21:28.585Z"} +{"parentUuid":"5a8d3ec0-23f6-42ad-9bf7-dc28fd089d24","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01KoYLbsxdKoLzHRtxpeDnCJ","toolUseID":"toolu_01KoYLbsxdKoLzHRtxpeDnCJ","timestamp":"2026-03-04T16:21:28.771Z","uuid":"2739bf37-bec1-4dbf-9591-e5de067de986"} +{"parentUuid":"5a8d3ec0-23f6-42ad-9bf7-dc28fd089d24","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KoYLbsxdKoLzHRtxpeDnCJ","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\"strings\"\n 33→\t\"time\"\n 34→\n 35→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 36→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 37→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 38→)\n 39→\n 40→type InternalMetricStore struct{}\n 41→\n 42→var MetricStoreHandle *InternalMetricStore\n 43→\n 44→// HealthCheck delegates to the internal MemoryStore's HealthCheck.\n 45→func (ccms *InternalMetricStore) HealthCheck(cluster string,\n 46→\tnodes []string, metrics []string,\n 47→) (map[string]HealthCheckResult, error) {\n 48→\treturn GetMemoryStore().HealthCheck(cluster, nodes, metrics)\n 49→}\n 50→\n 51→// TestLoadDataCallback allows tests to override LoadData behavior for testing purposes.\n 52→// When set to a non-nil function, LoadData will call this function instead of the default implementation.\n 53→var TestLoadDataCallback func(job *schema.Job, metrics []string, scopes []schema.MetricScope, ctx context.Context, resolution int) (schema.JobData, error)\n 54→\n 55→// LoadData loads metric data for a specific job with automatic scope transformation.\n 56→//\n 57→// This is the primary function for retrieving job metric data. It handles:\n 58→// - Building queries with scope transformation via buildQueries\n 59→// - Fetching data from the metric store\n 60→// - Organizing results by metric and scope\n 61→// - Converting NaN statistics to 0 for JSON compatibility\n 62→// - Partial error handling (returns data for successful queries even if some fail)\n 63→//\n 64→// Parameters:\n 65→// - job: Job metadata including cluster, resources, and time range\n 66→// - metrics: List of metric names to load\n 67→// - scopes: Requested metric scopes (will be transformed to match native scopes)\n 68→// - ctx: Context for cancellation (currently unused but reserved for future use)\n 69→// - resolution: Data resolution in seconds (0 for native resolution)\n 70→//\n 71→// Returns:\n 72→// - JobData: Map of metric → scope → JobMetric with time-series data and statistics\n 73→// - Error: Returns error if query building or fetching fails, or partial error listing failed hosts\n 74→//\n 75→// Example:\n 76→//\n 77→//\tjobData, err := LoadData(job, []string{\"cpu_load\", \"mem_used\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 60)\n 78→func (ccms *InternalMetricStore) LoadData(\n 79→\tjob *schema.Job,\n 80→\tmetrics []string,\n 81→\tscopes []schema.MetricScope,\n 82→\tctx context.Context,\n 83→\tresolution int,\n 84→) (schema.JobData, error) {\n 85→\tif TestLoadDataCallback != nil {\n 86→\t\treturn TestLoadDataCallback(job, metrics, scopes, ctx, resolution)\n 87→\t}\n 88→\n 89→\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, int64(resolution))\n 90→\tif err != nil {\n 91→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 92→\t\treturn nil, err\n 93→\t}\n 94→\n 95→\t// Verify assignment is correct - log any inconsistencies for debugging\n 96→\tif len(queries) != len(assignedScope) {\n 97→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildQueries: %d vs %d\",\n 98→\t\t\tlen(queries), len(assignedScope))\n 99→\t}\n 100→\n 101→\treq := APIQueryRequest{\n 102→\t\tCluster: job.Cluster,\n 103→\t\tFrom: job.StartTime,\n 104→\t\tTo: job.StartTime + int64(job.Duration),\n 105→\t\tQueries: queries,\n 106→\t\tWithStats: true,\n 107→\t\tWithData: true,\n 108→\t}\n 109→\n 110→\tresBody, err := FetchData(req)\n 111→\tif err != nil {\n 112→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 113→\t\treturn nil, err\n 114→\t}\n 115→\n 116→\tvar errors []string\n 117→\tjobData := make(schema.JobData)\n 118→\n 119→\t// Add safety check for potential index out of range errors\n 120→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 121→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 122→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 123→\t\tif len(resBody.Results) > len(req.Queries) {\n 124→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 125→\t\t}\n 126→\t\tif len(assignedScope) > len(req.Queries) {\n 127→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 128→\t\t}\n 129→\t}\n 130→\n 131→\tfor i, row := range resBody.Results {\n 132→\t\t// Safety check to prevent index out of range errors\n 133→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 134→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 135→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 136→\t\t\tcontinue\n 137→\t\t}\n 138→\n 139→\t\tquery := req.Queries[i]\n 140→\t\tmetric := query.Metric\n 141→\t\tscope := assignedScope[i]\n 142→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 143→\n 144→\t\tif mc == nil {\n 145→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, job.Cluster)\n 146→\t\t\tcontinue\n 147→\t\t}\n 148→\n 149→\t\tif _, ok := jobData[metric]; !ok {\n 150→\t\t\tjobData[metric] = make(map[schema.MetricScope]*schema.JobMetric)\n 151→\t\t}\n 152→\n 153→\t\tres := mc.Timestep\n 154→\t\tif len(row) > 0 {\n 155→\t\t\tres = int(row[0].Resolution)\n 156→\t\t}\n 157→\n 158→\t\tjobMetric, ok := jobData[metric][scope]\n 159→\t\tif !ok {\n 160→\t\t\tjobMetric = &schema.JobMetric{\n 161→\t\t\t\tUnit: mc.Unit,\n 162→\t\t\t\tTimestep: res,\n 163→\t\t\t\tSeries: make([]schema.Series, 0),\n 164→\t\t\t}\n 165→\t\t\tjobData[metric][scope] = jobMetric\n 166→\t\t}\n 167→\n 168→\t\tfor ndx, res := range row {\n 169→\t\t\tif res.Error != nil {\n 170→\t\t\t\t/* Build list for \"partial errors\", if any */\n 171→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 172→\t\t\t\tcontinue\n 173→\t\t\t}\n 174→\n 175→\t\t\tid := (*string)(nil)\n 176→\t\t\tif query.Type != nil {\n 177→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 178→\t\t\t\tif ndx < len(query.TypeIds) {\n 179→\t\t\t\t\tid = new(string)\n 180→\t\t\t\t\t*id = query.TypeIds[ndx]\n 181→\t\t\t\t} else {\n 182→\t\t\t\t\t// Log the error but continue processing\n 183→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 184→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 185→\t\t\t\t}\n 186→\t\t\t}\n 187→\n 188→\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n 189→\n 190→\t\t\tjobMetric.Series = append(jobMetric.Series, schema.Series{\n 191→\t\t\t\tHostname: query.Hostname,\n 192→\t\t\t\tID: id,\n 193→\t\t\t\tStatistics: schema.MetricStatistics{\n 194→\t\t\t\t\tAvg: float64(res.Avg),\n 195→\t\t\t\t\tMin: float64(res.Min),\n 196→\t\t\t\t\tMax: float64(res.Max),\n 197→\t\t\t\t},\n 198→\t\t\t\tData: res.Data,\n 199→\t\t\t})\n 200→\t\t}\n 201→\n 202→\t\t// So that one can later check len(jobData):\n 203→\t\tif len(jobMetric.Series) == 0 {\n 204→\t\t\tdelete(jobData[metric], scope)\n 205→\t\t\tif len(jobData[metric]) == 0 {\n 206→\t\t\t\tdelete(jobData, metric)\n 207→\t\t\t}\n 208→\t\t}\n 209→\t}\n 210→\n 211→\tif len(errors) != 0 {\n 212→\t\t/* Returns list for \"partial errors\" */\n 213→\t\treturn jobData, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 214→\t}\n 215→\treturn jobData, nil\n 216→}\n 217→\n 218→// buildQueries constructs APIQuery structures with automatic scope transformation for a job.\n 219→//\n 220→// This function implements the core scope transformation logic, handling all combinations of\n 221→// native metric scopes and requested scopes. It uses the cluster topology to determine which\n 222→// hardware IDs to include in each query.\n 223→//\n 224→// Scope Transformation Rules:\n 225→// - If native scope >= requested scope: Aggregates data (Aggregate=true in APIQuery)\n 226→// - If native scope < requested scope: Returns error (cannot increase granularity)\n 227→// - Special handling for Accelerator scope (independent of CPU hierarchy)\n 228→//\n 229→// The function generates one or more APIQuery per (metric, scope, host) combination:\n 230→// - For non-aggregated queries: One query with all relevant IDs\n 231→// - For aggregated queries: May generate multiple queries (e.g., one per socket/core)\n 232→//\n 233→// Parameters:\n 234→// - job: Job metadata including cluster, subcluster, and resource allocation\n 235→// - metrics: List of metrics to query\n 236→// - scopes: Requested scopes for each metric\n 237→// - resolution: Data resolution in seconds\n 238→//\n 239→// Returns:\n 240→// - []APIQuery: List of queries to execute\n 241→// - []schema.MetricScope: Assigned scope for each query (after transformation)\n 242→// - error: Returns error if topology lookup fails or unhandled scope combination encountered\n 243→func buildQueries(\n 244→\tjob *schema.Job,\n 245→\tmetrics []string,\n 246→\tscopes []schema.MetricScope,\n 247→\tresolution int64,\n 248→) ([]APIQuery, []schema.MetricScope, error) {\n 249→\tif len(job.Resources) == 0 {\n 250→\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > no resources allocated for job %d\", job.JobID)\n 251→\t}\n 252→\n 253→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n 254→\tassignedScope := []schema.MetricScope{}\n 255→\n 256→\tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n 257→\tif scerr != nil {\n 258→\t\treturn nil, nil, scerr\n 259→\t}\n 260→\ttopology := subcluster.Topology\n 261→\n 262→\tfor _, metric := range metrics {\n 263→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 264→\t\tif mc == nil {\n 265→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, job.Cluster)\n 266→\t\t\tcontinue\n 267→\t\t}\n 268→\n 269→\t\t// Skip if metric is removed for subcluster\n 270→\t\tif len(mc.SubClusters) != 0 {\n 271→\t\t\tisRemoved := false\n 272→\t\t\tfor _, scConfig := range mc.SubClusters {\n 273→\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n 274→\t\t\t\t\tisRemoved = true\n 275→\t\t\t\t\tbreak\n 276→\t\t\t\t}\n 277→\t\t\t}\n 278→\t\t\tif isRemoved {\n 279→\t\t\t\tcontinue\n 280→\t\t\t}\n 281→\t\t}\n 282→\n 283→\t\t// Avoid duplicates...\n 284→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 285→\n 286→\tscopesLoop:\n 287→\t\tfor _, requestedScope := range scopes {\n 288→\t\t\tnativeScope := mc.Scope\n 289→\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n 290→\t\t\t\tcontinue\n 291→\t\t\t}\n 292→\n 293→\t\t\tscope := nativeScope.Max(requestedScope)\n 294→\t\t\tfor _, s := range handledScopes {\n 295→\t\t\t\tif scope == s {\n 296→\t\t\t\t\tcontinue scopesLoop\n 297→\t\t\t\t}\n 298→\t\t\t}\n 299→\t\t\thandledScopes = append(handledScopes, scope)\n 300→\n 301→\t\t\tfor _, host := range job.Resources {\n 302→\t\t\t\thwthreads := host.HWThreads\n 303→\t\t\t\tif hwthreads == nil {\n 304→\t\t\t\t\thwthreads = topology.Node\n 305→\t\t\t\t}\n 306→\n 307→\t\t\t\tscopeResults, ok := BuildScopeQueries(\n 308→\t\t\t\t\tnativeScope, requestedScope,\n 309→\t\t\t\t\tmetric, host.Hostname,\n 310→\t\t\t\t\t&topology, hwthreads, host.Accelerators,\n 311→\t\t\t\t)\n 312→\n 313→\t\t\t\tif !ok {\n 314→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 315→\t\t\t\t}\n 316→\n 317→\t\t\t\tfor _, sr := range scopeResults {\n 318→\t\t\t\t\tqueries = append(queries, APIQuery{\n 319→\t\t\t\t\t\tMetric: sr.Metric,\n 320→\t\t\t\t\t\tHostname: sr.Hostname,\n 321→\t\t\t\t\t\tAggregate: sr.Aggregate,\n 322→\t\t\t\t\t\tType: sr.Type,\n 323→\t\t\t\t\t\tTypeIds: sr.TypeIds,\n 324→\t\t\t\t\t\tResolution: resolution,\n 325→\t\t\t\t\t})\n 326→\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n 327→\t\t\t\t}\n 328→\t\t\t}\n 329→\t\t}\n 330→\t}\n 331→\n 332→\treturn queries, assignedScope, nil\n 333→}\n 334→\n 335→// LoadStats loads only metric statistics (avg/min/max) for a job at node scope.\n 336→//\n 337→// This is an optimized version of LoadData that fetches only statistics without\n 338→// time-series data, reducing bandwidth and memory usage. Always queries at node scope.\n 339→//\n 340→// Parameters:\n 341→// - job: Job metadata\n 342→// - metrics: List of metric names\n 343→// - ctx: Context (currently unused)\n 344→//\n 345→// Returns:\n 346→// - Map of metric → hostname → statistics\n 347→// - Error on query building or fetching failure\n 348→func (ccms *InternalMetricStore) LoadStats(\n 349→\tjob *schema.Job,\n 350→\tmetrics []string,\n 351→\tctx context.Context,\n 352→) (map[string]map[string]schema.MetricStatistics, error) {\n 353→\t// TODO(#166): Add scope parameter for analysis view accelerator normalization\n 354→\tqueries, _, err := buildQueries(job, metrics, []schema.MetricScope{schema.MetricScopeNode}, 0)\n 355→\tif err != nil {\n 356→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v: %s\", job.JobID, metrics, err.Error())\n 357→\t\treturn nil, err\n 358→\t}\n 359→\n 360→\treq := APIQueryRequest{\n 361→\t\tCluster: job.Cluster,\n 362→\t\tFrom: job.StartTime,\n 363→\t\tTo: job.StartTime + int64(job.Duration),\n 364→\t\tQueries: queries,\n 365→\t\tWithStats: true,\n 366→\t\tWithData: false,\n 367→\t}\n 368→\n 369→\tresBody, err := FetchData(req)\n 370→\tif err != nil {\n 371→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 372→\t\treturn nil, err\n 373→\t}\n 374→\n 375→\tstats := make(map[string]map[string]schema.MetricStatistics, len(metrics))\n 376→\tfor i, res := range resBody.Results {\n 377→\t\tif len(res) == 0 {\n 378→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 379→\t\t\tcontinue\n 380→\t\t}\n 381→\t\tquery := req.Queries[i]\n 382→\t\tmetric := query.Metric\n 383→\t\tdata := res[0]\n 384→\t\tif data.Error != nil {\n 385→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *data.Error)\n 386→\t\t\tcontinue\n 387→\t\t}\n 388→\n 389→\t\tmetricdata, ok := stats[metric]\n 390→\t\tif !ok {\n 391→\t\t\tmetricdata = make(map[string]schema.MetricStatistics, job.NumNodes)\n 392→\t\t\tstats[metric] = metricdata\n 393→\t\t}\n 394→\n 395→\t\tif data.Avg.IsNaN() || data.Min.IsNaN() || data.Max.IsNaN() {\n 396→\t\t\tcclog.Warnf(\"fetching %s for node %s failed: one of avg/min/max is NaN\", metric, query.Hostname)\n 397→\t\t\tcontinue\n 398→\t\t}\n 399→\n 400→\t\tmetricdata[query.Hostname] = schema.MetricStatistics{\n 401→\t\t\tAvg: float64(data.Avg),\n 402→\t\t\tMin: float64(data.Min),\n 403→\t\t\tMax: float64(data.Max),\n 404→\t\t}\n 405→\t}\n 406→\n 407→\treturn stats, nil\n 408→}\n 409→\n 410→// LoadScopedStats loads metric statistics for a job with scope-aware grouping.\n 411→//\n 412→// Similar to LoadStats but supports multiple scopes and returns statistics grouped\n 413→// by scope with hardware IDs (e.g., per-core, per-socket statistics).\n 414→//\n 415→// Parameters:\n 416→// - job: Job metadata\n 417→// - metrics: List of metric names\n 418→// - scopes: Requested metric scopes\n 419→// - ctx: Context (currently unused)\n 420→//\n 421→// Returns:\n 422→// - ScopedJobStats: Map of metric → scope → []ScopedStats (with hostname and ID)\n 423→// - Error or partial error listing failed queries\n 424→func (ccms *InternalMetricStore) LoadScopedStats(\n 425→\tjob *schema.Job,\n 426→\tmetrics []string,\n 427→\tscopes []schema.MetricScope,\n 428→\tctx context.Context,\n 429→) (schema.ScopedJobStats, error) {\n 430→\tqueries, assignedScope, err := buildQueries(job, metrics, scopes, 0)\n 431→\tif err != nil {\n 432→\t\tcclog.Errorf(\"Error while building queries for jobId %d, Metrics %v, Scopes %v: %s\", job.JobID, metrics, scopes, err.Error())\n 433→\t\treturn nil, err\n 434→\t}\n 435→\n 436→\treq := APIQueryRequest{\n 437→\t\tCluster: job.Cluster,\n 438→\t\tFrom: job.StartTime,\n 439→\t\tTo: job.StartTime + int64(job.Duration),\n 440→\t\tQueries: queries,\n 441→\t\tWithStats: true,\n 442→\t\tWithData: false,\n 443→\t}\n 444→\n 445→\tresBody, err := FetchData(req)\n 446→\tif err != nil {\n 447→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 448→\t\treturn nil, err\n 449→\t}\n 450→\n 451→\tvar errors []string\n 452→\tscopedJobStats := make(schema.ScopedJobStats)\n 453→\n 454→\tfor i, row := range resBody.Results {\n 455→\t\tif len(row) == 0 {\n 456→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 457→\t\t\tcontinue\n 458→\t\t}\n 459→\t\tquery := req.Queries[i]\n 460→\t\tmetric := query.Metric\n 461→\t\tscope := assignedScope[i]\n 462→\n 463→\t\tif _, ok := scopedJobStats[metric]; !ok {\n 464→\t\t\tscopedJobStats[metric] = make(map[schema.MetricScope][]*schema.ScopedStats)\n 465→\t\t}\n 466→\n 467→\t\tif _, ok := scopedJobStats[metric][scope]; !ok {\n 468→\t\t\tscopedJobStats[metric][scope] = make([]*schema.ScopedStats, 0)\n 469→\t\t}\n 470→\n 471→\t\tfor ndx, res := range row {\n 472→\t\t\tif res.Error != nil {\n 473→\t\t\t\t/* Build list for \"partial errors\", if any */\n 474→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 475→\t\t\t\tcontinue\n 476→\t\t\t}\n 477→\n 478→\t\t\tid := (*string)(nil)\n 479→\t\t\tif query.Type != nil {\n 480→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 481→\t\t\t\tif ndx < len(query.TypeIds) {\n 482→\t\t\t\t\tid = new(string)\n 483→\t\t\t\t\t*id = query.TypeIds[ndx]\n 484→\t\t\t\t} else {\n 485→\t\t\t\t\t// Log the error but continue processing\n 486→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 487→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 488→\t\t\t\t}\n 489→\t\t\t}\n 490→\n 491→\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n 492→\n 493→\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{\n 494→\t\t\t\tHostname: query.Hostname,\n 495→\t\t\t\tID: id,\n 496→\t\t\t\tData: &schema.MetricStatistics{\n 497→\t\t\t\t\tAvg: float64(res.Avg),\n 498→\t\t\t\t\tMin: float64(res.Min),\n 499→\t\t\t\t\tMax: float64(res.Max),\n 500→\t\t\t\t},\n 501→\t\t\t})\n 502→\t\t}\n 503→\n 504→\t\t// So that one can later check len(scopedJobStats[metric][scope]): Remove from map if empty\n 505→\t\tif len(scopedJobStats[metric][scope]) == 0 {\n 506→\t\t\tdelete(scopedJobStats[metric], scope)\n 507→\t\t\tif len(scopedJobStats[metric]) == 0 {\n 508→\t\t\t\tdelete(scopedJobStats, metric)\n 509→\t\t\t}\n 510→\t\t}\n 511→\t}\n 512→\n 513→\tif len(errors) != 0 {\n 514→\t\t/* Returns list for \"partial errors\" */\n 515→\t\treturn scopedJobStats, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 516→\t}\n 517→\treturn scopedJobStats, nil\n 518→}\n 519→\n 520→// LoadNodeData loads metric data for specific nodes in a cluster over a time range.\n 521→//\n 522→// Unlike LoadData which operates on job resources, this function queries arbitrary nodes\n 523→// directly. Useful for system monitoring and node status views.\n 524→//\n 525→// Parameters:\n 526→// - cluster: Cluster name\n 527→// - metrics: List of metric names\n 528→// - nodes: List of node hostnames (nil = all nodes in cluster via ForAllNodes)\n 529→// - scopes: Requested metric scopes (currently unused - always node scope)\n 530→// - from, to: Time range\n 531→// - ctx: Context (currently unused)\n 532→//\n 533→// Returns:\n 534→// - Map of hostname → metric → []JobMetric\n 535→// - Error or partial error listing failed queries\n 536→func (ccms *InternalMetricStore) LoadNodeData(\n 537→\tcluster string,\n 538→\tmetrics, nodes []string,\n 539→\tscopes []schema.MetricScope,\n 540→\tfrom, to time.Time,\n 541→\tctx context.Context,\n 542→) (map[string]map[string][]*schema.JobMetric, error) {\n 543→\treq := APIQueryRequest{\n 544→\t\tCluster: cluster,\n 545→\t\tFrom: from.Unix(),\n 546→\t\tTo: to.Unix(),\n 547→\t\tWithStats: true,\n 548→\t\tWithData: true,\n 549→\t}\n 550→\n 551→\tif nodes == nil {\n 552→\t\treq.ForAllNodes = append(req.ForAllNodes, metrics...)\n 553→\t} else {\n 554→\t\tfor _, node := range nodes {\n 555→\t\t\tfor _, metric := range metrics {\n 556→\t\t\t\treq.Queries = append(req.Queries, APIQuery{\n 557→\t\t\t\t\tHostname: node,\n 558→\t\t\t\t\tMetric: metric,\n 559→\t\t\t\t\tResolution: 0, // Default for Node Queries: Will return metric $Timestep Resolution\n 560→\t\t\t\t})\n 561→\t\t\t}\n 562→\t\t}\n 563→\t}\n 564→\n 565→\tresBody, err := FetchData(req)\n 566→\tif err != nil {\n 567→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 568→\t\treturn nil, err\n 569→\t}\n 570→\n 571→\tvar errors []string\n 572→\tdata := make(map[string]map[string][]*schema.JobMetric)\n 573→\tfor i, res := range resBody.Results {\n 574→\t\tif len(res) == 0 {\n 575→\t\t\t// No Data Found For Metric, Logged in FetchData to Warn\n 576→\t\t\tcontinue\n 577→\t\t}\n 578→\n 579→\t\tvar query APIQuery\n 580→\t\tif resBody.Queries != nil {\n 581→\t\t\tquery = resBody.Queries[i]\n 582→\t\t} else {\n 583→\t\t\tquery = req.Queries[i]\n 584→\t\t}\n 585→\n 586→\t\tmetric := query.Metric\n 587→\t\tqdata := res[0]\n 588→\t\tif qdata.Error != nil {\n 589→\t\t\terrors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))\n 590→\t\t}\n 591→\n 592→\t\tSanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)\n 593→\n 594→\t\thostdata, ok := data[query.Hostname]\n 595→\t\tif !ok {\n 596→\t\t\thostdata = make(map[string][]*schema.JobMetric)\n 597→\t\t\tdata[query.Hostname] = hostdata\n 598→\t\t}\n 599→\n 600→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 601→\t\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n 602→\t\t\tUnit: mc.Unit,\n 603→\t\t\tTimestep: mc.Timestep,\n 604→\t\t\tSeries: []schema.Series{\n 605→\t\t\t\t{\n 606→\t\t\t\t\tHostname: query.Hostname,\n 607→\t\t\t\t\tData: qdata.Data,\n 608→\t\t\t\t\tStatistics: schema.MetricStatistics{\n 609→\t\t\t\t\t\tAvg: float64(qdata.Avg),\n 610→\t\t\t\t\t\tMin: float64(qdata.Min),\n 611→\t\t\t\t\t\tMax: float64(qdata.Max),\n 612→\t\t\t\t\t},\n 613→\t\t\t\t},\n 614→\t\t\t},\n 615→\t\t})\n 616→\t}\n 617→\n 618→\tif len(errors) != 0 {\n 619→\t\t/* Returns list of \"partial errors\" */\n 620→\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 621→\t}\n 622→\n 623→\treturn data, nil\n 624→}\n 625→\n 626→// LoadNodeListData loads metric data for a list of nodes with full scope transformation support.\n 627→//\n 628→// This is the most flexible node data loading function, supporting arbitrary scopes and\n 629→// resolution. Uses buildNodeQueries for proper scope transformation based on topology.\n 630→//\n 631→// Parameters:\n 632→// - cluster: Cluster name\n 633→// - subCluster: SubCluster name (empty string to infer from node names)\n 634→// - nodes: List of node hostnames\n 635→// - metrics: List of metric names\n 636→// - scopes: Requested metric scopes\n 637→// - resolution: Data resolution in seconds\n 638→// - from, to: Time range\n 639→// - ctx: Context (currently unused)\n 640→//\n 641→// Returns:\n 642→// - Map of hostname → JobData (metric → scope → JobMetric)\n 643→// - Error or partial error listing failed queries\n 644→func (ccms *InternalMetricStore) LoadNodeListData(\n 645→\tcluster, subCluster string,\n 646→\tnodes []string,\n 647→\tmetrics []string,\n 648→\tscopes []schema.MetricScope,\n 649→\tresolution int,\n 650→\tfrom, to time.Time,\n 651→\tctx context.Context,\n 652→) (map[string]schema.JobData, error) {\n 653→\t// Note: Order of node data is not guaranteed after this point\n 654→\tqueries, assignedScope, err := buildNodeQueries(cluster, subCluster, nodes, metrics, scopes, int64(resolution))\n 655→\tif err != nil {\n 656→\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 657→\t\treturn nil, err\n 658→\t}\n 659→\n 660→\t// Verify assignment is correct - log any inconsistencies for debugging\n 661→\tif len(queries) != len(assignedScope) {\n 662→\t\tcclog.Errorf(\"Critical error: queries and assignedScope have different lengths after buildNodeQueries: %d vs %d\",\n 663→\t\t\tlen(queries), len(assignedScope))\n 664→\t}\n 665→\n 666→\treq := APIQueryRequest{\n 667→\t\tCluster: cluster,\n 668→\t\tQueries: queries,\n 669→\t\tFrom: from.Unix(),\n 670→\t\tTo: to.Unix(),\n 671→\t\tWithStats: true,\n 672→\t\tWithData: true,\n 673→\t}\n 674→\n 675→\tresBody, err := FetchData(req)\n 676→\tif err != nil {\n 677→\t\tcclog.Errorf(\"Error while fetching data : %s\", err.Error())\n 678→\t\treturn nil, err\n 679→\t}\n 680→\n 681→\tvar errors []string\n 682→\tdata := make(map[string]schema.JobData)\n 683→\n 684→\t// Add safety check for index out of range issues\n 685→\tif len(resBody.Results) != len(req.Queries) || len(assignedScope) != len(req.Queries) {\n 686→\t\tcclog.Warnf(\"Mismatch in query results count: queries=%d, results=%d, assignedScope=%d\",\n 687→\t\t\tlen(req.Queries), len(resBody.Results), len(assignedScope))\n 688→\t\tif len(resBody.Results) > len(req.Queries) {\n 689→\t\t\tresBody.Results = resBody.Results[:len(req.Queries)]\n 690→\t\t}\n 691→\t\tif len(assignedScope) > len(req.Queries) {\n 692→\t\t\tassignedScope = assignedScope[:len(req.Queries)]\n 693→\t\t}\n 694→\t}\n 695→\n 696→\tfor i, row := range resBody.Results {\n 697→\t\t// Safety check to prevent index out of range errors\n 698→\t\tif i >= len(req.Queries) || i >= len(assignedScope) {\n 699→\t\t\tcclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",\n 700→\t\t\t\ti, len(req.Queries), len(assignedScope))\n 701→\t\t\tcontinue\n 702→\t\t}\n 703→\n 704→\t\tvar query APIQuery\n 705→\t\tif resBody.Queries != nil {\n 706→\t\t\tif i < len(resBody.Queries) {\n 707→\t\t\t\tquery = resBody.Queries[i]\n 708→\t\t\t} else {\n 709→\t\t\t\tcclog.Warnf(\"Index out of range prevented for resBody.Queries: i=%d, len=%d\",\n 710→\t\t\t\t\ti, len(resBody.Queries))\n 711→\t\t\t\tcontinue\n 712→\t\t\t}\n 713→\t\t} else {\n 714→\t\t\tquery = req.Queries[i]\n 715→\t\t}\n 716→\n 717→\t\tmetric := query.Metric\n 718→\t\tscope := assignedScope[i]\n 719→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 720→\t\tif mc == nil {\n 721→\t\t\tcclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)\n 722→\t\t\tcontinue\n 723→\t\t}\n 724→\n 725→\t\tres := mc.Timestep\n 726→\t\tif len(row) > 0 {\n 727→\t\t\tres = int(row[0].Resolution)\n 728→\t\t}\n 729→\n 730→\t\t// Init Nested Map Data Structures If Not Found\n 731→\t\thostData, ok := data[query.Hostname]\n 732→\t\tif !ok {\n 733→\t\t\thostData = make(schema.JobData)\n 734→\t\t\tdata[query.Hostname] = hostData\n 735→\t\t}\n 736→\n 737→\t\tmetricData, ok := hostData[metric]\n 738→\t\tif !ok {\n 739→\t\t\tmetricData = make(map[schema.MetricScope]*schema.JobMetric)\n 740→\t\t\tdata[query.Hostname][metric] = metricData\n 741→\t\t}\n 742→\n 743→\t\tscopeData, ok := metricData[scope]\n 744→\t\tif !ok {\n 745→\t\t\tscopeData = &schema.JobMetric{\n 746→\t\t\t\tUnit: mc.Unit,\n 747→\t\t\t\tTimestep: res,\n 748→\t\t\t\tSeries: make([]schema.Series, 0),\n 749→\t\t\t}\n 750→\t\t\tdata[query.Hostname][metric][scope] = scopeData\n 751→\t\t}\n 752→\n 753→\t\tfor ndx, res := range row {\n 754→\t\t\tif res.Error != nil {\n 755→\t\t\t\t/* Build list for \"partial errors\", if any */\n 756→\t\t\t\terrors = append(errors, fmt.Sprintf(\"failed to fetch '%s' from host '%s': %s\", query.Metric, query.Hostname, *res.Error))\n 757→\t\t\t\tcontinue\n 758→\t\t\t}\n 759→\n 760→\t\t\tid := (*string)(nil)\n 761→\t\t\tif query.Type != nil {\n 762→\t\t\t\t// Check if ndx is within the bounds of TypeIds slice\n 763→\t\t\t\tif ndx < len(query.TypeIds) {\n 764→\t\t\t\t\tid = new(string)\n 765→\t\t\t\t\t*id = query.TypeIds[ndx]\n 766→\t\t\t\t} else {\n 767→\t\t\t\t\t// Log the error but continue processing\n 768→\t\t\t\t\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n 769→\t\t\t\t\t\tndx, len(query.TypeIds), query.Metric, query.Hostname)\n 770→\t\t\t\t}\n 771→\t\t\t}\n 772→\n 773→\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n 774→\n 775→\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{\n 776→\t\t\t\tHostname: query.Hostname,\n 777→\t\t\t\tID: id,\n 778→\t\t\t\tStatistics: schema.MetricStatistics{\n 779→\t\t\t\t\tAvg: float64(res.Avg),\n 780→\t\t\t\t\tMin: float64(res.Min),\n 781→\t\t\t\t\tMax: float64(res.Max),\n 782→\t\t\t\t},\n 783→\t\t\t\tData: res.Data,\n 784→\t\t\t})\n 785→\t\t}\n 786→\t}\n 787→\n 788→\tif len(errors) != 0 {\n 789→\t\t/* Returns list of \"partial errors\" */\n 790→\t\treturn data, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > Errors: %s\", strings.Join(errors, \", \"))\n 791→\t}\n 792→\n 793→\treturn data, nil\n 794→}\n 795→\n 796→// buildNodeQueries constructs APIQuery structures for node-based queries with scope transformation.\n 797→//\n 798→// Similar to buildQueries but operates on node lists rather than job resources.\n 799→// Supports dynamic subcluster lookup when subCluster parameter is empty.\n 800→//\n 801→// Parameters:\n 802→// - cluster: Cluster name\n 803→// - subCluster: SubCluster name (empty = infer from node hostnames)\n 804→// - nodes: List of node hostnames\n 805→// - metrics: List of metric names\n 806→// - scopes: Requested metric scopes\n 807→// - resolution: Data resolution in seconds\n 808→//\n 809→// Returns:\n 810→// - []APIQuery: List of queries to execute\n 811→// - []schema.MetricScope: Assigned scope for each query\n 812→// - error: Returns error if topology lookup fails or unhandled scope combination\n 813→func buildNodeQueries(\n 814→\tcluster string,\n 815→\tsubCluster string,\n 816→\tnodes []string,\n 817→\tmetrics []string,\n 818→\tscopes []schema.MetricScope,\n 819→\tresolution int64,\n 820→) ([]APIQuery, []schema.MetricScope, error) {\n 821→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n 822→\tassignedScope := []schema.MetricScope{}\n 823→\n 824→\t// Get Topol before loop if subCluster given\n 825→\tvar subClusterTopol *schema.SubCluster\n 826→\tvar scterr error\n 827→\tif subCluster != \"\" {\n 828→\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subCluster)\n 829→\t\tif scterr != nil {\n 830→\t\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", cluster, subCluster, scterr.Error())\n 831→\t\t\treturn nil, nil, scterr\n 832→\t\t}\n 833→\t}\n 834→\n 835→\tfor _, metric := range metrics {\n 836→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 837→\t\tif mc == nil {\n 838→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n 839→\t\t\tcontinue\n 840→\t\t}\n 841→\n 842→\t\t// Skip if metric is removed for subcluster\n 843→\t\tif mc.SubClusters != nil {\n 844→\t\t\tisRemoved := false\n 845→\t\t\tfor _, scConfig := range mc.SubClusters {\n 846→\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n 847→\t\t\t\t\tisRemoved = true\n 848→\t\t\t\t\tbreak\n 849→\t\t\t\t}\n 850→\t\t\t}\n 851→\t\t\tif isRemoved {\n 852→\t\t\t\tcontinue\n 853→\t\t\t}\n 854→\t\t}\n 855→\n 856→\t\t// Avoid duplicates...\n 857→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 858→\n 859→\tnodeScopesLoop:\n 860→\t\tfor _, requestedScope := range scopes {\n 861→\t\t\tnativeScope := mc.Scope\n 862→\n 863→\t\t\tscope := nativeScope.Max(requestedScope)\n 864→\t\t\tfor _, s := range handledScopes {\n 865→\t\t\t\tif scope == s {\n 866→\t\t\t\t\tcontinue nodeScopesLoop\n 867→\t\t\t\t}\n 868→\t\t\t}\n 869→\t\t\thandledScopes = append(handledScopes, scope)\n 870→\n 871→\t\t\tfor _, hostname := range nodes {\n 872→\n 873→\t\t\t\t// If no subCluster given, get it by node\n 874→\t\t\t\tif subCluster == \"\" {\n 875→\t\t\t\t\tsubClusterName, scnerr := archive.GetSubClusterByNode(cluster, hostname)\n 876→\t\t\t\t\tif scnerr != nil {\n 877→\t\t\t\t\t\treturn nil, nil, scnerr\n 878→\t\t\t\t\t}\n 879→\t\t\t\t\tsubClusterTopol, scterr = archive.GetSubCluster(cluster, subClusterName)\n 880→\t\t\t\t\tif scterr != nil {\n 881→\t\t\t\t\t\treturn nil, nil, scterr\n 882→\t\t\t\t\t}\n 883→\t\t\t\t}\n 884→\n 885→\t\t\t\t// Always full node hwthread id list, no partial queries expected\n 886→\t\t\t\ttopology := subClusterTopol.Topology\n 887→\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n 888→\n 889→\t\t\t\t// Moved check here if metric matches hardware specs\n 890→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n 891→\t\t\t\t\tcontinue\n 892→\t\t\t\t}\n 893→\n 894→\t\t\t\tscopeResults, ok := BuildScopeQueries(\n 895→\t\t\t\t\tnativeScope, requestedScope,\n 896→\t\t\t\t\tmetric, hostname,\n 897→\t\t\t\t\t&topology, topology.Node, acceleratorIds,\n 898→\t\t\t\t)\n 899→\n 900→\t\t\t\tif !ok {\n 901→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 902→\t\t\t\t}\n 903→\n 904→\t\t\t\tfor _, sr := range scopeResults {\n 905→\t\t\t\t\tqueries = append(queries, APIQuery{\n 906→\t\t\t\t\t\tMetric: sr.Metric,\n 907→\t\t\t\t\t\tHostname: sr.Hostname,\n 908→\t\t\t\t\t\tAggregate: sr.Aggregate,\n 909→\t\t\t\t\t\tType: sr.Type,\n 910→\t\t\t\t\t\tTypeIds: sr.TypeIds,\n 911→\t\t\t\t\t\tResolution: resolution,\n 912→\t\t\t\t\t})\n 913→\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n 914→\t\t\t\t}\n 915→\t\t\t}\n 916→\t\t}\n 917→\t}\n 918→\n 919→\treturn queries, assignedScope, nil\n 920→}\n 921→"}]},"uuid":"50504edf-493a-40cd-9b16-7a181d4c5921","timestamp":"2026-03-04T16:21:28.770Z","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\"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.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","numLines":921,"startLine":1,"totalLines":921}},"sourceToolAssistantUUID":"5a8d3ec0-23f6-42ad-9bf7-dc28fd089d24"} 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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→\tms \"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\tms.SanitizeStats(&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\tms.SanitizeStats(&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\tms.SanitizeStats(&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\tms.SanitizeStats(&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]ms.HealthCheckResult, error) {\n 788→\treq := ms.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]ms.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→// hasNaNStats returns true if any of the statistics contain NaN values.\n 831→func hasNaNStats(avg, min, max schema.Float) bool {\n 832→\treturn avg.IsNaN() || min.IsNaN() || max.IsNaN()\n 833→}\n 834→"}]},"uuid":"8d88412e-c92c-4159-9695-153829520c10","timestamp":"2026-03-04T16:21:29.332Z","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\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// 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() || 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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 contains shared scope transformation logic used by both the internal\n 7→// metric store (pkg/metricstore) and the external cc-metric-store client\n 8→// (internal/metricstoreclient). It extracts the common algorithm for mapping\n 9→// between native metric scopes and requested scopes based on cluster topology.\n 10→package metricstore\n 11→\n 12→import (\n 13→\t\"strconv\"\n 14→\n 15→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 16→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 17→)\n 18→\n 19→// Pre-converted scope strings avoid repeated string(MetricScope) allocations\n 20→// during query construction. Used in ScopeQueryResult.Type field.\n 21→var (\n 22→\tHWThreadString = string(schema.MetricScopeHWThread)\n 23→\tCoreString = string(schema.MetricScopeCore)\n 24→\tMemoryDomainString = string(schema.MetricScopeMemoryDomain)\n 25→\tSocketString = string(schema.MetricScopeSocket)\n 26→\tAcceleratorString = string(schema.MetricScopeAccelerator)\n 27→)\n 28→\n 29→// ScopeQueryResult is a package-independent intermediate type returned by\n 30→// BuildScopeQueries. Each consumer converts it to their own APIQuery type\n 31→// (adding Resolution and any other package-specific fields).\n 32→type ScopeQueryResult struct {\n 33→\tType *string\n 34→\tMetric string\n 35→\tHostname string\n 36→\tTypeIds []string\n 37→\tScope schema.MetricScope\n 38→\tAggregate bool\n 39→}\n 40→\n 41→// BuildScopeQueries generates scope query results for a given scope transformation.\n 42→// It returns a slice of results and a boolean indicating success.\n 43→// An empty slice means an expected exception (skip this combination).\n 44→// ok=false means an unhandled case (caller should return an error).\n 45→func BuildScopeQueries(\n 46→\tnativeScope, requestedScope schema.MetricScope,\n 47→\tmetric, hostname string,\n 48→\ttopology *schema.Topology,\n 49→\thwthreads []int,\n 50→\taccelerators []string,\n 51→) ([]ScopeQueryResult, bool) {\n 52→\tscope := nativeScope.Max(requestedScope)\n 53→\tresults := []ScopeQueryResult{}\n 54→\n 55→\thwthreadsStr := IntToStringSlice(hwthreads)\n 56→\n 57→\t// Accelerator -> Accelerator (Use \"accelerator\" scope if requested scope is lower than node)\n 58→\tif nativeScope == schema.MetricScopeAccelerator && scope.LT(schema.MetricScopeNode) {\n 59→\t\tif scope != schema.MetricScopeAccelerator {\n 60→\t\t\t// Expected Exception -> Return Empty Slice\n 61→\t\t\treturn results, true\n 62→\t\t}\n 63→\n 64→\t\tresults = append(results, ScopeQueryResult{\n 65→\t\t\tMetric: metric,\n 66→\t\t\tHostname: hostname,\n 67→\t\t\tAggregate: false,\n 68→\t\t\tType: &AcceleratorString,\n 69→\t\t\tTypeIds: accelerators,\n 70→\t\t\tScope: schema.MetricScopeAccelerator,\n 71→\t\t})\n 72→\t\treturn results, true\n 73→\t}\n 74→\n 75→\t// Accelerator -> Node\n 76→\tif nativeScope == schema.MetricScopeAccelerator && scope == schema.MetricScopeNode {\n 77→\t\tif len(accelerators) == 0 {\n 78→\t\t\t// Expected Exception -> Return Empty Slice\n 79→\t\t\treturn results, true\n 80→\t\t}\n 81→\n 82→\t\tresults = append(results, ScopeQueryResult{\n 83→\t\t\tMetric: metric,\n 84→\t\t\tHostname: hostname,\n 85→\t\t\tAggregate: true,\n 86→\t\t\tType: &AcceleratorString,\n 87→\t\t\tTypeIds: accelerators,\n 88→\t\t\tScope: scope,\n 89→\t\t})\n 90→\t\treturn results, true\n 91→\t}\n 92→\n 93→\t// HWThread -> HWThread\n 94→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeHWThread {\n 95→\t\tresults = append(results, ScopeQueryResult{\n 96→\t\t\tMetric: metric,\n 97→\t\t\tHostname: hostname,\n 98→\t\t\tAggregate: false,\n 99→\t\t\tType: &HWThreadString,\n 100→\t\t\tTypeIds: hwthreadsStr,\n 101→\t\t\tScope: scope,\n 102→\t\t})\n 103→\t\treturn results, true\n 104→\t}\n 105→\n 106→\t// HWThread -> Core\n 107→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeCore {\n 108→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 109→\t\tfor _, core := range cores {\n 110→\t\t\tresults = append(results, ScopeQueryResult{\n 111→\t\t\t\tMetric: metric,\n 112→\t\t\t\tHostname: hostname,\n 113→\t\t\t\tAggregate: true,\n 114→\t\t\t\tType: &HWThreadString,\n 115→\t\t\t\tTypeIds: IntToStringSlice(topology.Core[core]),\n 116→\t\t\t\tScope: scope,\n 117→\t\t\t})\n 118→\t\t}\n 119→\t\treturn results, true\n 120→\t}\n 121→\n 122→\t// HWThread -> Socket\n 123→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeSocket {\n 124→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 125→\t\tfor _, socket := range sockets {\n 126→\t\t\tresults = append(results, ScopeQueryResult{\n 127→\t\t\t\tMetric: metric,\n 128→\t\t\t\tHostname: hostname,\n 129→\t\t\t\tAggregate: true,\n 130→\t\t\t\tType: &HWThreadString,\n 131→\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n 132→\t\t\t\tScope: scope,\n 133→\t\t\t})\n 134→\t\t}\n 135→\t\treturn results, true\n 136→\t}\n 137→\n 138→\t// HWThread -> Node\n 139→\tif nativeScope == schema.MetricScopeHWThread && scope == schema.MetricScopeNode {\n 140→\t\tresults = append(results, ScopeQueryResult{\n 141→\t\t\tMetric: metric,\n 142→\t\t\tHostname: hostname,\n 143→\t\t\tAggregate: true,\n 144→\t\t\tType: &HWThreadString,\n 145→\t\t\tTypeIds: hwthreadsStr,\n 146→\t\t\tScope: scope,\n 147→\t\t})\n 148→\t\treturn results, true\n 149→\t}\n 150→\n 151→\t// Core -> Core\n 152→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeCore {\n 153→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 154→\t\tresults = append(results, ScopeQueryResult{\n 155→\t\t\tMetric: metric,\n 156→\t\t\tHostname: hostname,\n 157→\t\t\tAggregate: false,\n 158→\t\t\tType: &CoreString,\n 159→\t\t\tTypeIds: IntToStringSlice(cores),\n 160→\t\t\tScope: scope,\n 161→\t\t})\n 162→\t\treturn results, true\n 163→\t}\n 164→\n 165→\t// Core -> Socket\n 166→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeSocket {\n 167→\t\tsockets, _ := topology.GetSocketsFromCores(hwthreads)\n 168→\t\tfor _, socket := range sockets {\n 169→\t\t\tresults = append(results, ScopeQueryResult{\n 170→\t\t\t\tMetric: metric,\n 171→\t\t\t\tHostname: hostname,\n 172→\t\t\t\tAggregate: true,\n 173→\t\t\t\tType: &CoreString,\n 174→\t\t\t\tTypeIds: IntToStringSlice(topology.Socket[socket]),\n 175→\t\t\t\tScope: scope,\n 176→\t\t\t})\n 177→\t\t}\n 178→\t\treturn results, true\n 179→\t}\n 180→\n 181→\t// Core -> Node\n 182→\tif nativeScope == schema.MetricScopeCore && scope == schema.MetricScopeNode {\n 183→\t\tcores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 184→\t\tresults = append(results, ScopeQueryResult{\n 185→\t\t\tMetric: metric,\n 186→\t\t\tHostname: hostname,\n 187→\t\t\tAggregate: true,\n 188→\t\t\tType: &CoreString,\n 189→\t\t\tTypeIds: IntToStringSlice(cores),\n 190→\t\t\tScope: scope,\n 191→\t\t})\n 192→\t\treturn results, true\n 193→\t}\n 194→\n 195→\t// MemoryDomain -> MemoryDomain\n 196→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeMemoryDomain {\n 197→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 198→\t\tresults = append(results, ScopeQueryResult{\n 199→\t\t\tMetric: metric,\n 200→\t\t\tHostname: hostname,\n 201→\t\t\tAggregate: false,\n 202→\t\t\tType: &MemoryDomainString,\n 203→\t\t\tTypeIds: IntToStringSlice(memDomains),\n 204→\t\t\tScope: scope,\n 205→\t\t})\n 206→\t\treturn results, true\n 207→\t}\n 208→\n 209→\t// MemoryDomain -> Socket\n 210→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeSocket {\n 211→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 212→\t\tsocketToDomains, err := topology.GetMemoryDomainsBySocket(memDomains)\n 213→\t\tif err != nil {\n 214→\t\t\tcclog.Errorf(\"Error mapping memory domains to sockets, return unchanged: %v\", err)\n 215→\t\t\t// Rare Error Case -> Still Continue -> Return Empty Slice\n 216→\t\t\treturn results, true\n 217→\t\t}\n 218→\n 219→\t\t// Create a query for each socket\n 220→\t\tfor _, domains := range socketToDomains {\n 221→\t\t\tresults = append(results, ScopeQueryResult{\n 222→\t\t\t\tMetric: metric,\n 223→\t\t\t\tHostname: hostname,\n 224→\t\t\t\tAggregate: true,\n 225→\t\t\t\tType: &MemoryDomainString,\n 226→\t\t\t\tTypeIds: IntToStringSlice(domains),\n 227→\t\t\t\tScope: scope,\n 228→\t\t\t})\n 229→\t\t}\n 230→\t\treturn results, true\n 231→\t}\n 232→\n 233→\t// MemoryDomain -> Node\n 234→\tif nativeScope == schema.MetricScopeMemoryDomain && scope == schema.MetricScopeNode {\n 235→\t\tmemDomains, _ := topology.GetMemoryDomainsFromHWThreads(hwthreads)\n 236→\t\tresults = append(results, ScopeQueryResult{\n 237→\t\t\tMetric: metric,\n 238→\t\t\tHostname: hostname,\n 239→\t\t\tAggregate: true,\n 240→\t\t\tType: &MemoryDomainString,\n 241→\t\t\tTypeIds: IntToStringSlice(memDomains),\n 242→\t\t\tScope: scope,\n 243→\t\t})\n 244→\t\treturn results, true\n 245→\t}\n 246→\n 247→\t// Socket -> Socket\n 248→\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeSocket {\n 249→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 250→\t\tresults = append(results, ScopeQueryResult{\n 251→\t\t\tMetric: metric,\n 252→\t\t\tHostname: hostname,\n 253→\t\t\tAggregate: false,\n 254→\t\t\tType: &SocketString,\n 255→\t\t\tTypeIds: IntToStringSlice(sockets),\n 256→\t\t\tScope: scope,\n 257→\t\t})\n 258→\t\treturn results, true\n 259→\t}\n 260→\n 261→\t// Socket -> Node\n 262→\tif nativeScope == schema.MetricScopeSocket && scope == schema.MetricScopeNode {\n 263→\t\tsockets, _ := topology.GetSocketsFromHWThreads(hwthreads)\n 264→\t\tresults = append(results, ScopeQueryResult{\n 265→\t\t\tMetric: metric,\n 266→\t\t\tHostname: hostname,\n 267→\t\t\tAggregate: true,\n 268→\t\t\tType: &SocketString,\n 269→\t\t\tTypeIds: IntToStringSlice(sockets),\n 270→\t\t\tScope: scope,\n 271→\t\t})\n 272→\t\treturn results, true\n 273→\t}\n 274→\n 275→\t// Node -> Node\n 276→\tif nativeScope == schema.MetricScopeNode && scope == schema.MetricScopeNode {\n 277→\t\tresults = append(results, ScopeQueryResult{\n 278→\t\t\tMetric: metric,\n 279→\t\t\tHostname: hostname,\n 280→\t\t\tScope: scope,\n 281→\t\t})\n 282→\t\treturn results, true\n 283→\t}\n 284→\n 285→\t// Unhandled Case\n 286→\treturn nil, false\n 287→}\n 288→\n 289→// IntToStringSlice converts a slice of integers to a slice of strings.\n 290→// Used to convert hardware thread/core/socket IDs from topology (int) to query TypeIds (string).\n 291→// Optimized to reuse a byte buffer for string conversion, reducing allocations.\n 292→func IntToStringSlice(is []int) []string {\n 293→\tif len(is) == 0 {\n 294→\t\treturn nil\n 295→\t}\n 296→\n 297→\tss := make([]string, len(is))\n 298→\tbuf := make([]byte, 0, 16) // Reusable buffer for integer conversion\n 299→\tfor i, x := range is {\n 300→\t\tbuf = strconv.AppendInt(buf[:0], int64(x), 10)\n 301→\t\tss[i] = string(buf)\n 302→\t}\n 303→\treturn ss\n 304→}\n 305→\n 306→// SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling.\n 307→// If ANY of avg/min/max is NaN, ALL three are zeroed for consistency.\n 308→func SanitizeStats(avg, min, max *schema.Float) {\n 309→\tif avg.IsNaN() || min.IsNaN() || max.IsNaN() {\n 310→\t\t*avg = schema.Float(0)\n 311→\t\t*min = schema.Float(0)\n 312→\t\t*max = schema.Float(0)\n 313→\t}\n 314→}\n 315→"}]},"uuid":"d3f4d094-7482-4aab-af2b-0fe09c1e0457","timestamp":"2026-03-04T16:21:29.416Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery.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 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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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→\n 41→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 42→\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\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→// buildQueries constructs API queries for job-specific metric data.\n 48→// It iterates through metrics, scopes, and job resources to build the complete query set.\n 49→//\n 50→// The function handles:\n 51→// - Metric configuration validation and subcluster filtering\n 52→// - Scope deduplication to avoid redundant queries\n 53→// - Hardware thread list resolution (job-allocated vs full node)\n 54→// - Delegation to buildScopeQueries for scope transformations\n 55→//\n 56→// Returns queries and their corresponding assigned scopes (which may differ from requested scopes).\n 57→func (ccms *CCMetricStore) buildQueries(\n 58→\tjob *schema.Job,\n 59→\tmetrics []string,\n 60→\tscopes []schema.MetricScope,\n 61→\tresolution int,\n 62→) ([]APIQuery, []schema.MetricScope, error) {\n 63→\t// Initialize both slices together\n 64→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))\n 65→\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\n 66→\n 67→\ttopology, err := ccms.getTopology(job.Cluster, job.SubCluster)\n 68→\tif err != nil {\n 69→\t\tcclog.Errorf(\"could not load cluster %s subCluster %s topology: %s\", job.Cluster, job.SubCluster, err.Error())\n 70→\t\treturn nil, nil, err\n 71→\t}\n 72→\n 73→\tfor _, metric := range metrics {\n 74→\t\tremoteName := metric\n 75→\t\tmc := archive.GetMetricConfig(job.Cluster, metric)\n 76→\t\tif mc == nil {\n 77→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s' - skipping\", metric, job.Cluster)\n 78→\t\t\tcontinue\n 79→\t\t}\n 80→\n 81→\t\t// Skip if metric is removed for subcluster\n 82→\t\tif len(mc.SubClusters) != 0 {\n 83→\t\t\tisRemoved := false\n 84→\t\t\tfor _, scConfig := range mc.SubClusters {\n 85→\t\t\t\tif scConfig.Name == job.SubCluster && scConfig.Remove {\n 86→\t\t\t\t\tisRemoved = true\n 87→\t\t\t\t\tbreak\n 88→\t\t\t\t}\n 89→\t\t\t}\n 90→\t\t\tif isRemoved {\n 91→\t\t\t\tcontinue\n 92→\t\t\t}\n 93→\t\t}\n 94→\n 95→\t\t// Avoid duplicates...\n 96→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 97→\n 98→\tscopesLoop:\n 99→\t\tfor _, requestedScope := range scopes {\n 100→\t\t\tnativeScope := mc.Scope\n 101→\t\t\tif nativeScope == schema.MetricScopeAccelerator && job.NumAcc == 0 {\n 102→\t\t\t\tcontinue\n 103→\t\t\t}\n 104→\n 105→\t\t\tscope := nativeScope.Max(requestedScope)\n 106→\t\t\tfor _, s := range handledScopes {\n 107→\t\t\t\tif scope == s {\n 108→\t\t\t\t\tcontinue scopesLoop\n 109→\t\t\t\t}\n 110→\t\t\t}\n 111→\t\t\thandledScopes = append(handledScopes, scope)\n 112→\n 113→\t\t\tfor _, host := range job.Resources {\n 114→\t\t\t\thwthreads := host.HWThreads\n 115→\t\t\t\tif hwthreads == nil {\n 116→\t\t\t\t\thwthreads = topology.Node\n 117→\t\t\t\t}\n 118→\n 119→\t\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n 120→\t\t\t\t\tnativeScope, requestedScope,\n 121→\t\t\t\t\tremoteName, host.Hostname,\n 122→\t\t\t\t\ttopology, hwthreads, host.Accelerators,\n 123→\t\t\t\t)\n 124→\n 125→\t\t\t\tif !ok {\n 126→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 127→\t\t\t\t}\n 128→\n 129→\t\t\t\tfor _, sr := range scopeResults {\n 130→\t\t\t\t\tqueries = append(queries, APIQuery{\n 131→\t\t\t\t\t\tMetric: sr.Metric,\n 132→\t\t\t\t\t\tHostname: sr.Hostname,\n 133→\t\t\t\t\t\tAggregate: sr.Aggregate,\n 134→\t\t\t\t\t\tType: sr.Type,\n 135→\t\t\t\t\t\tTypeIds: sr.TypeIds,\n 136→\t\t\t\t\t\tResolution: resolution,\n 137→\t\t\t\t\t})\n 138→\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n 139→\t\t\t\t}\n 140→\t\t\t}\n 141→\t\t}\n 142→\t}\n 143→\n 144→\treturn queries, assignedScope, nil\n 145→}\n 146→\n 147→// buildNodeQueries constructs API queries for node-specific metric data (Systems View).\n 148→// Similar to buildQueries but uses full node topology instead of job-allocated resources.\n 149→//\n 150→// The function handles:\n 151→// - SubCluster topology resolution (either pre-loaded or per-node lookup)\n 152→// - Full node hardware thread lists (not job-specific subsets)\n 153→// - All accelerators on each node\n 154→// - Metric configuration validation with subcluster filtering\n 155→//\n 156→// Returns queries and their corresponding assigned scopes.\n 157→func (ccms *CCMetricStore) buildNodeQueries(\n 158→\tcluster string,\n 159→\tsubCluster string,\n 160→\tnodes []string,\n 161→\tmetrics []string,\n 162→\tscopes []schema.MetricScope,\n 163→\tresolution int,\n 164→) ([]APIQuery, []schema.MetricScope, error) {\n 165→\t// Initialize both slices together\n 166→\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n 167→\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\n 168→\n 169→\tfor _, metric := range metrics {\n 170→\t\tremoteName := metric\n 171→\t\tmc := archive.GetMetricConfig(cluster, metric)\n 172→\t\tif mc == nil {\n 173→\t\t\tcclog.Warnf(\"metric '%s' is not specified for cluster '%s'\", metric, cluster)\n 174→\t\t\tcontinue\n 175→\t\t}\n 176→\n 177→\t\t// Skip if metric is removed for subcluster\n 178→\t\tif mc.SubClusters != nil {\n 179→\t\t\tisRemoved := false\n 180→\t\t\tfor _, scConfig := range mc.SubClusters {\n 181→\t\t\t\tif scConfig.Name == subCluster && scConfig.Remove {\n 182→\t\t\t\t\tisRemoved = true\n 183→\t\t\t\t\tbreak\n 184→\t\t\t\t}\n 185→\t\t\t}\n 186→\t\t\tif isRemoved {\n 187→\t\t\t\tcontinue\n 188→\t\t\t}\n 189→\t\t}\n 190→\n 191→\t\t// Avoid duplicates...\n 192→\t\thandledScopes := make([]schema.MetricScope, 0, 3)\n 193→\n 194→\tscopesLoop:\n 195→\t\tfor _, requestedScope := range scopes {\n 196→\t\t\tnativeScope := mc.Scope\n 197→\n 198→\t\t\tscope := nativeScope.Max(requestedScope)\n 199→\t\t\tfor _, s := range handledScopes {\n 200→\t\t\t\tif scope == s {\n 201→\t\t\t\t\tcontinue scopesLoop\n 202→\t\t\t\t}\n 203→\t\t\t}\n 204→\t\t\thandledScopes = append(handledScopes, scope)\n 205→\n 206→\t\t\tfor _, hostname := range nodes {\n 207→\t\t\t\tvar topology *schema.Topology\n 208→\t\t\t\tvar err error\n 209→\n 210→\t\t\t\t// If no subCluster given, get it by node\n 211→\t\t\t\tif subCluster == \"\" {\n 212→\t\t\t\t\ttopology, err = ccms.getTopologyByNode(cluster, hostname)\n 213→\t\t\t\t} else {\n 214→\t\t\t\t\ttopology, err = ccms.getTopology(cluster, subCluster)\n 215→\t\t\t\t}\n 216→\n 217→\t\t\t\tif err != nil {\n 218→\t\t\t\t\treturn nil, nil, err\n 219→\t\t\t\t}\n 220→\n 221→\t\t\t\t// Always full node hwthread id list, no partial queries expected -> Use \"topology.Node\" directly where applicable\n 222→\t\t\t\t// Always full accelerator id list, no partial queries expected -> Use \"acceleratorIds\" directly where applicable\n 223→\t\t\t\tacceleratorIds := topology.GetAcceleratorIDs()\n 224→\n 225→\t\t\t\t// Moved check here if metric matches hardware specs\n 226→\t\t\t\tif nativeScope == schema.MetricScopeAccelerator && len(acceleratorIds) == 0 {\n 227→\t\t\t\t\tcontinue scopesLoop\n 228→\t\t\t\t}\n 229→\n 230→\t\t\t\tscopeResults, ok := metricstore.BuildScopeQueries(\n 231→\t\t\t\t\tnativeScope, requestedScope,\n 232→\t\t\t\t\tremoteName, hostname,\n 233→\t\t\t\t\ttopology, topology.Node, acceleratorIds,\n 234→\t\t\t\t)\n 235→\n 236→\t\t\t\tif !ok {\n 237→\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n 238→\t\t\t\t}\n 239→\n 240→\t\t\t\tfor _, sr := range scopeResults {\n 241→\t\t\t\t\tqueries = append(queries, APIQuery{\n 242→\t\t\t\t\t\tMetric: sr.Metric,\n 243→\t\t\t\t\t\tHostname: sr.Hostname,\n 244→\t\t\t\t\t\tAggregate: sr.Aggregate,\n 245→\t\t\t\t\t\tType: sr.Type,\n 246→\t\t\t\t\t\tTypeIds: sr.TypeIds,\n 247→\t\t\t\t\t\tResolution: resolution,\n 248→\t\t\t\t\t})\n 249→\t\t\t\t\tassignedScope = append(assignedScope, sr.Scope)\n 250→\t\t\t\t}\n 251→\t\t\t}\n 252→\t\t}\n 253→\t}\n 254→\n 255→\treturn queries, assignedScope, nil\n 256→}\n 257→\n 258→"}]},"uuid":"1cf847ce-5e84-4387-b78f-bde8b7d6805b","timestamp":"2026-03-04T16:21:29.638Z","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\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","numLines":258,"startLine":1,"totalLines":258}},"sourceToolAssistantUUID":"894586f3-1edc-4d60-8e01-e8be80bd12e0"} +{"parentUuid":"1cf847ce-5e84-4387-b78f-bde8b7d6805b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01NehUtggEZszWBkiLPCdB2n","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a good understanding of all the files. Let me create the task list and start implementing the changes.\n\nLet me plan the edits:\n\n1. **Bug fix: `LoadNodeData` nil metric config** - both packages need nil check before `mc.Unit`/`mc.Timestep`\n2. **Bug fix: `LoadNodeData` missing `continue` after error** - both packages\n3. **Extract `ExtractTypeID` helper** - add to scopequery.go, replace 6 occurrences\n4. **Extract `IsMetricRemovedForSubCluster` helper** - add to scopequery.go, replace 4 occurrences\n\n\n5. **Fix TODO error messages** - 4 occurrences\n6. **Remove redundant inner bounds checks** - 4 occurrences\n7. **Add capacity hint for `assignedScope`** - 2 occurrences in internal query.go\n8. **Add bounds check to `LoadStats`** - 2 occurrences\n\nNow I'll start working through these fixes systematically.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":31802,"cache_read_input_tokens":25427,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":31802},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM3w7zAWxne15YM1bWU","type":"assistant","uuid":"fbd08388-172f-4eaf-89ba-93f94b7634d0","timestamp":"2026-03-04T16:21:38.136Z"} +{"parentUuid":"fbd08388-172f-4eaf-89ba-93f94b7634d0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01NehUtggEZszWBkiLPCdB2n","type":"message","role":"assistant","content":[{"type":"text","text":"I'll implement all 8 changes. Let me start with the shared helper functions in `scopequery.go`, then update both packages."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":31802,"cache_read_input_tokens":25427,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":31802},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM3w7zAWxne15YM1bWU","type":"assistant","uuid":"a1485cde-8e87-4f76-8a4a-79275bd6df72","timestamp":"2026-03-04T16:21:38.338Z"} 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Build and test"}]},"uuid":"e4fbd0a2-29cc-4c1b-a805-fe0dee90d55a","timestamp":"2026-03-04T16:21:48.893Z","toolUseResult":{"task":{"id":"4","subject":"Build and test"}},"sourceToolAssistantUUID":"5dc203e5-1b2a-4265-a91a-6f5dd27e4c0a"} 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+{"parentUuid":"2801585e-e9d9-4434-b612-edca5e2bbf0d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016FSqLtKC4X3q2usonKQYtF","type":"tool_result","content":"Updated task #1 status"}]},"uuid":"abddf838-8718-44a6-a491-e8097528044e","timestamp":"2026-03-04T16:21:51.415Z","toolUseResult":{"success":true,"taskId":"1","updatedFields":["status"],"statusChange":{"from":"pending","to":"in_progress"}},"sourceToolAssistantUUID":"2801585e-e9d9-4434-b612-edca5e2bbf0d"} +{"parentUuid":"abddf838-8718-44a6-a491-e8097528044e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01SWwWfm25JqU6SAj2anjvgz","type":"message","role":"assistant","content":[{"type":"text","text":"### Step 1: Add helper functions to `scopequery.go`"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":90,"cache_read_input_tokens":58142,"cache_creation":{"ephemeral_5m_input_tokens":90,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM5YDtaxZ3fGY8k7W8m","type":"assistant","uuid":"27bceb17-86de-45f0-a01e-41e9b7b38b3d","timestamp":"2026-03-04T16:21:54.039Z"} 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Logs a warning and returns nil\n// if the index is out of range.\nfunc ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string {\n\tif queryType == nil {\n\t\treturn nil\n\t}\n\tif ndx < len(typeIds) {\n\t\tid := typeIds[ndx]\n\t\treturn &id\n\t}\n\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\tndx, len(typeIds), metric, hostname)\n\treturn nil\n}\n\n// IsMetricRemovedForSubCluster checks whether a metric is marked as removed\n// for the given subcluster in its per-subcluster configuration.\nfunc IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool {\n\tfor _, scConfig := range mc.SubClusters {\n\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\treturn true\n\t\t}\n\t}\n\treturn false\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) {"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":90,"cache_read_input_tokens":58142,"output_tokens":554,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":90},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiM5YDtaxZ3fGY8k7W8m","type":"assistant","uuid":"7749d1f6-173a-4a7d-8f6d-63644adb255a","timestamp":"2026-03-04T16:22:02.586Z"} +{"type":"file-history-snapshot","messageId":"7749d1f6-173a-4a7d-8f6d-63644adb255a","snapshot":{"messageId":"1b4af328-8505-4c6a-b2d4-9c102454705c","trackedFileBackups":{"pkg/metricstore/scopequery.go":{"backupFileName":"268c5efa680c9247@v1","version":1,"backupTime":"2026-03-04T16:22:02.604Z"}},"timestamp":"2026-03-04T16:21:24.341Z"},"isSnapshotUpdate":true} +{"parentUuid":"7749d1f6-173a-4a7d-8f6d-63644adb255a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01WXB3JfFAuKbKvGneXbqmPC","toolUseID":"toolu_01WXB3JfFAuKbKvGneXbqmPC","timestamp":"2026-03-04T16:22:02.606Z","uuid":"b4d27a28-7645-4cb4-bff8-46ca8ad00524"} +{"parentUuid":"7749d1f6-173a-4a7d-8f6d-63644adb255a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WXB3JfFAuKbKvGneXbqmPC","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery.go has been updated successfully."}]},"uuid":"201d7577-c743-4547-98cb-949b82dfbbe4","timestamp":"2026-03-04T16:22:02.606Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/scopequery.go","oldString":"// 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) {","newString":"// ExtractTypeID returns the type ID at the given index from a query's TypeIds slice.\n// Returns nil if queryType is nil (no type filtering). Logs a warning and returns nil\n// if the index is out of range.\nfunc ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string {\n\tif queryType == nil {\n\t\treturn nil\n\t}\n\tif ndx < len(typeIds) {\n\t\tid := typeIds[ndx]\n\t\treturn &id\n\t}\n\tcclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",\n\t\tndx, len(typeIds), metric, hostname)\n\treturn nil\n}\n\n// IsMetricRemovedForSubCluster checks whether a metric is marked as removed\n// for the given subcluster in its per-subcluster configuration.\nfunc IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool {\n\tfor _, scConfig := range mc.SubClusters {\n\t\tif scConfig.Name == subCluster && scConfig.Remove {\n\t\t\treturn true\n\t\t}\n\t}\n\treturn false\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) {","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 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 = schema.Float(0)\n\t}\n}\n","structuredPatch":[{"oldStart":303,"oldLines":6,"newStart":303,"newLines":33,"lines":[" return ss"," }"," ","+// ExtractTypeID returns the type ID at the given index from a query's TypeIds slice.","+// Returns nil if queryType is nil (no type filtering). Logs a warning and returns nil","+// if the index is out of range.","+func ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string {","+ if queryType == nil {","+ return nil","+ }","+ if ndx < len(typeIds) {","+ id := typeIds[ndx]","+ return &id","+ }","+ cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","+ ndx, len(typeIds), metric, hostname)","+ return nil","+}","+","+// IsMetricRemovedForSubCluster checks whether a metric is marked as removed","+// for the given subcluster in its per-subcluster configuration.","+func IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool {","+ for _, scConfig := range mc.SubClusters {","+ if scConfig.Name == subCluster && scConfig.Remove {","+ return true","+ }","+ }","+ return false","+}","+"," // SanitizeStats replaces NaN values in statistics with 0 to enable JSON marshaling."," // If ANY of avg/min/max is NaN, ALL three are zeroed for consistency."," func SanitizeStats(avg, min, max *schema.Float) {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"7749d1f6-173a-4a7d-8f6d-63644adb255a"} 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+{"parentUuid":"eb21f006-d17d-4eee-af46-413c770ebccb","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01RVNfkhcWpcoQhcsKiuVj7X","type":"message","role":"assistant","content":[{"type":"text","text":"### Step 2: Fix `pkg/metricstore/query.go`"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":88,"cache_read_input_tokens":58852,"cache_creation":{"ephemeral_5m_input_tokens":88,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM6XyY5K1LqB5tr8bxw","type":"assistant","uuid":"13f0baa3-9bae-4248-ac2b-1e389cdc8dc3","timestamp":"2026-03-04T16:22:07.161Z"} 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+{"parentUuid":"a2b294b9-ee9d-4a1a-aa8b-216af7ddc25f","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SRgpUBThBKp7LgDTh81cMt","type":"tool_result","content":"Updated task #2 status"}]},"uuid":"5cdd2c10-aa4c-46f2-8efa-980d6d8a5061","timestamp":"2026-03-04T16:22:07.597Z","toolUseResult":{"success":true,"taskId":"2","updatedFields":["status"],"statusChange":{"from":"pending","to":"in_progress"}},"sourceToolAssistantUUID":"a2b294b9-ee9d-4a1a-aa8b-216af7ddc25f"} +{"parentUuid":"5cdd2c10-aa4c-46f2-8efa-980d6d8a5061","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_016Hg43tBzWLfHV3BV4My2Gs","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 6: Remove redundant inner bounds check in `LoadData`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":108,"cache_read_input_tokens":58940,"cache_creation":{"ephemeral_5m_input_tokens":108,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiM6jN97T8gR3E6QZufp","type":"assistant","uuid":"d92f10cd-63ea-4969-badd-e8cc560c98d0","timestamp":"2026-03-04T16:22:09.894Z"} 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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}","new_string":"\tfor i, row := range resBody.Results {\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":108,"cache_read_input_tokens":58940,"output_tokens":1621,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":108},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiM6jN97T8gR3E6QZufp","type":"assistant","uuid":"86f73ee8-f88e-4c3e-b544-05868286528f","timestamp":"2026-03-04T16:22:27.532Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"c22d06d7-d874-4ccc-bec5-2fa3492cc1b7","timestamp":"2026-03-04T16:22:27.558Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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}","newString":"\tfor i, row := range resBody.Results {\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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}","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.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":129,"oldLines":13,"newStart":129,"newLines":6,"lines":[" }"," "," for i, row := range resBody.Results {","- // Safety check to prevent index out of range errors","- if i >= len(req.Queries) || i >= len(assignedScope) {","- cclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",","- i, len(req.Queries), len(assignedScope))","- continue","- }","-"," query := req.Queries[i]"," metric := query.Metric"," scope := assignedScope[i]"]},{"oldStart":172,"oldLines":18,"newStart":165,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id = query.TypeIds[ndx]","- } else {","- // Log the error but continue processing","- cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","- ndx, len(query.TypeIds), query.Metric, query.Hostname)","- }","- }","+ id := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)"," "," SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"86f73ee8-f88e-4c3e-b544-05868286528f"} 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{\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}","new_string":"\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\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\n\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1685,"cache_read_input_tokens":59048,"output_tokens":688,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1685},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiM8Cv7TtSieDcS4RxSb","type":"assistant","uuid":"28d45d95-a288-46ce-93f2-0f05dd567e5c","timestamp":"2026-03-04T16:22:37.446Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"48374131-7421-4a6b-8bea-2ce795f7721c","timestamp":"2026-03-04T16:22:37.485Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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}","newString":"\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\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\n\t\t}","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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.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":233,"oldLines":7,"newStart":233,"newLines":7,"lines":[" }"," "," queries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(job.Resources))","- assignedScope := []schema.MetricScope{}","+ assignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))"," "," subcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)"," if scerr != nil {"]},{"oldStart":249,"oldLines":17,"newStart":249,"newLines":8,"lines":[" }"," "," // Skip if metric is removed for subcluster","- if len(mc.SubClusters) != 0 {","- isRemoved := false","- for _, scConfig := range mc.SubClusters {","- if scConfig.Name == job.SubCluster && scConfig.Remove {","- isRemoved = true","- break","- }","- }","- if isRemoved {","- continue","- }","+ if len(mc.SubClusters) != 0 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {","+ continue"," }"," "," // Avoid duplicates..."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"28d45d95-a288-46ce-93f2-0f05dd567e5c"} 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+{"parentUuid":"71623392-1e4f-4289-ae14-7de13088ab07","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_018LxK4WrJmuV2xBPq1GTvPi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018fxSBBX92FrF41LUz8Bdj9","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","old_string":"\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","new_string":"\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > unsupported scope transformation: 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"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":733,"cache_read_input_tokens":60733,"output_tokens":520,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":733},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiM8wGJfQdGXrXbVo9TV","type":"assistant","uuid":"0ab8d7d9-cf1f-41e3-910b-a4abb38a0dab","timestamp":"2026-03-04T16:22:44.465Z"} +{"parentUuid":"0ab8d7d9-cf1f-41e3-910b-a4abb38a0dab","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_018fxSBBX92FrF41LUz8Bdj9","toolUseID":"toolu_018fxSBBX92FrF41LUz8Bdj9","timestamp":"2026-03-04T16:22:44.504Z","uuid":"abd3ced3-4cd6-4483-9623-8b15e02e46ef"} +{"parentUuid":"0ab8d7d9-cf1f-41e3-910b-a4abb38a0dab","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018fxSBBX92FrF41LUz8Bdj9","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"31ad577e-2be5-4a93-881b-6b4dffbcb573","timestamp":"2026-03-04T16:22:44.503Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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","newString":"\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > unsupported scope transformation: 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","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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.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":284,"oldLines":7,"newStart":284,"newLines":7,"lines":[" )"," "," if !ok {","- return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)","+ return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > unsupported scope transformation: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," "," for _, sr := range scopeResults 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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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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.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":347,"oldLines":6,"newStart":347,"newLines":10,"lines":[" "," stats := make(map[string]map[string]schema.MetricStatistics, len(metrics))"," for i, res := range resBody.Results {","+ if i >= len(req.Queries) {","+ cclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))","+ break","+ }"," if len(res) == 0 {"," // No Data Found For Metric, Logged in FetchData to Warn"," 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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{","new_string":"\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopedJobStats[metric][scope] = append(scopedJobStats[metric][scope], &schema.ScopedStats{"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":414,"cache_read_input_tokens":62031,"output_tokens":592,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":414},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiM9tarT2c3F3KcssUEG","type":"assistant","uuid":"2f128ff8-ef26-430a-ab75-11d78fb651d0","timestamp":"2026-03-04T16:23:00.205Z"} +{"parentUuid":"2f128ff8-ef26-430a-ab75-11d78fb651d0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01BEkeNjggekSnobMwuZCe2Q","toolUseID":"toolu_01BEkeNjggekSnobMwuZCe2Q","timestamp":"2026-03-04T16:23:00.240Z","uuid":"ba7ce09c-29ca-4663-b64e-a6ec72d10c93"} +{"parentUuid":"2f128ff8-ef26-430a-ab75-11d78fb651d0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BEkeNjggekSnobMwuZCe2Q","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"590cfd45-2ac1-498f-8019-1c645dfb2bda","timestamp":"2026-03-04T16:23:00.240Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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{","newString":"\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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.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":452,"oldLines":18,"newStart":452,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id = query.TypeIds[ndx]","- } else {","- // Log the error but continue processing","- cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","- ndx, len(query.TypeIds), query.Metric, query.Hostname)","- }","- }","+ id := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)"," "," SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"2f128ff8-ef26-430a-ab75-11d78fb651d0"} +{"parentUuid":"590cfd45-2ac1-498f-8019-1c645dfb2bda","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01A288fHZbfkMzxoFsDcvC2B","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 1+2: `LoadNodeData` — nil check for mc and `continue` after error:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":836,"cache_read_input_tokens":62445,"cache_creation":{"ephemeral_5m_input_tokens":836,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMAcXEmopiigvwsjno3","type":"assistant","uuid":"5a087d72-b274-4551-ab90-e3b6e6d0be52","timestamp":"2026-03-04T16:23:03.324Z"} 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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,","new_string":"\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\tcontinue\n\t\t}\n\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\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\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":836,"cache_read_input_tokens":62445,"output_tokens":611,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":836},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMAcXEmopiigvwsjno3","type":"assistant","uuid":"a545f783-2c84-4fb9-bf88-90ad7f1cdfd5","timestamp":"2026-03-04T16:23:08.477Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"0d4d9b47-445e-46df-ba60-bde4a67c3b00","timestamp":"2026-03-04T16:23:08.536Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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,","newString":"\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\tcontinue\n\t\t}\n\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\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\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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":553,"oldLines":8,"newStart":553,"newLines":15,"lines":[" qdata := res[0]"," if qdata.Error != nil {"," errors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))","+ continue"," }"," ","+ mc := archive.GetMetricConfig(cluster, metric)","+ if mc == nil {","+ cclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)","+ continue","+ }","+"," 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"00562317-afee-4993-bcf9-5d7ae06a0690","timestamp":"2026-03-04T16:23:14.329Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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 {","newString":"\tfor i, row := range resBody.Results {\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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":666,"oldLines":13,"newStart":666,"newLines":6,"lines":[" }"," "," for i, row := range resBody.Results {","- // Safety check to prevent index out of range errors","- if i >= len(req.Queries) || i >= len(assignedScope) {","- cclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",","- i, len(req.Queries), len(assignedScope))","- continue","- }","-"," var query APIQuery"," if resBody.Queries != nil {"," if i < 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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{","new_string":"\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\t\t\tSanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"7f96e6db-d828-43b2-9e63-bd2625e8210a","timestamp":"2026-03-04T16:23:23.822Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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{","newString":"\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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\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":722,"oldLines":18,"newStart":722,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id = query.TypeIds[ndx]","- } else {","- // Log the error but continue processing","- cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","- ndx, len(query.TypeIds), query.Metric, query.Hostname)","- }","- }","+ id := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)"," "," SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a01fa7e2-743e-49ef-8d41-472883d667de"} +{"parentUuid":"7f96e6db-d828-43b2-9e63-bd2625e8210a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01Qzzqu3PqTQzeVwp7hgcCPr","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 4+5+7: `buildNodeQueries` — use helper, fix TODO, add capacity hint:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":614,"cache_read_input_tokens":64279,"cache_creation":{"ephemeral_5m_input_tokens":614,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMCMGmexVL3imKLT9WE","type":"assistant","uuid":"64fccec2-74be-415e-a2eb-2c6af3a23718","timestamp":"2026-03-04T16:23:26.957Z"} 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%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}","new_string":"\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\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 && IsMetricRemovedForSubCluster(mc, subCluster) {\n\t\t\tcontinue\n\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":614,"cache_read_input_tokens":64279,"output_tokens":785,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":614},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMCMGmexVL3imKLT9WE","type":"assistant","uuid":"6bc38d8d-eb39-480a-b07d-216df599cf3d","timestamp":"2026-03-04T16:23:34.932Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"fbc3d6b5-4661-4a64-a836-3f6cf1339fa1","timestamp":"2026-03-04T16:23:34.988Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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}","newString":"\tqueries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))\n\tassignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\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 && IsMetricRemovedForSubCluster(mc, subCluster) {\n\t\t\tcontinue\n\t\t}","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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":773,"oldLines":7,"newStart":773,"newLines":7,"lines":[" resolution int64,"," ) ([]APIQuery, []schema.MetricScope, error) {"," queries := make([]APIQuery, 0, len(metrics)*len(scopes)*len(nodes))","- assignedScope := []schema.MetricScope{}","+ assignedScope := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))"," "," // Get Topol before loop if subCluster given"," var subClusterTopol *schema.SubCluster"]},{"oldStart":794,"oldLines":17,"newStart":794,"newLines":8,"lines":[" }"," "," // Skip if metric is removed for subcluster","- if mc.SubClusters != nil {","- isRemoved := false","- for _, scConfig := range mc.SubClusters {","- if scConfig.Name == subCluster && scConfig.Remove {","- isRemoved = true","- break","- }","- }","- if isRemoved {","- continue","- }","+ if mc.SubClusters != nil && IsMetricRemovedForSubCluster(mc, subCluster) {","+ continue"," }"," "," // Avoid duplicates..."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"6bc38d8d-eb39-480a-b07d-216df599cf3d"} 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/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go has been updated successfully."}]},"uuid":"e5d9fb3a-cd3e-4009-86dd-09f5c6e33ecf","timestamp":"2026-03-04T16:23:40.160Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/query.go","oldString":"\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}","newString":"\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > unsupported scope transformation: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\n\t\t\t\t}","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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(job.Resources))\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 && IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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\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 := ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 := make([]schema.MetricScope, 0, len(metrics)*len(scopes)*len(nodes))\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 && IsMetricRemovedForSubCluster(mc, subCluster) {\n\t\t\tcontinue\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":843,"oldLines":7,"newStart":843,"newLines":7,"lines":[" )"," "," if !ok {","- return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)","+ return nil, nil, fmt.Errorf(\"METRICDATA/INTERNAL-CCMS > unsupported scope transformation: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," "," for _, sr := range scopeResults {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"ada9f7b5-45c0-4ce3-bdc2-1399afd92564"} 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+{"parentUuid":"61de309f-cb29-4334-b7c7-ca614a836789","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_012i6SAH3sgn9fZ1K6e1yL1f","type":"message","role":"assistant","content":[{"type":"text","text":"### Step 3: Fix external metricstoreclient files"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":88,"cache_read_input_tokens":66228,"cache_creation":{"ephemeral_5m_input_tokens":88,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMDhQ1rGMCjxpmxyeh9","type":"assistant","uuid":"cf93cc96-85ca-4f64-a183-3f7d904039f1","timestamp":"2026-03-04T16:23:44.395Z"} 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+{"parentUuid":"3ce0e6d0-8f7c-48c2-a6cc-a7fcf3534a1b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VZmEBUa1jmRhSnG9G6A8VP","type":"tool_result","content":"Updated task #3 status"}]},"uuid":"98f8489f-93b2-4d6b-84c7-a95d7d43f675","timestamp":"2026-03-04T16:23:44.763Z","toolUseResult":{"success":true,"taskId":"3","updatedFields":["status"],"statusChange":{"from":"pending","to":"in_progress"}},"sourceToolAssistantUUID":"3ce0e6d0-8f7c-48c2-a6cc-a7fcf3534a1b"} +{"parentUuid":"98f8489f-93b2-4d6b-84c7-a95d7d43f675","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01QGXdvKPF8UXXw9wjhBLCw4","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 6: Remove redundant inner bounds check in `LoadData`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":105,"cache_read_input_tokens":66316,"cache_creation":{"ephemeral_5m_input_tokens":105,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMDu3kNeTbr4Chj1dj1","type":"assistant","uuid":"a8b6eb62-ca08-48c5-904f-52bdc863a0ce","timestamp":"2026-03-04T16:23:47.071Z"} 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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}","new_string":"\tfor i, row := range resBody.Results {\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":105,"cache_read_input_tokens":66316,"output_tokens":1647,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":105},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMDu3kNeTbr4Chj1dj1","type":"assistant","uuid":"5f1c383c-b4bc-4e12-bc05-0c692e1853b3","timestamp":"2026-03-04T16:24:05.543Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"bb63ed50-143a-464a-9f26-93aec6787d87","timestamp":"2026-03-04T16:24:05.581Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\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}","newString":"\tfor i, row := range resBody.Results {\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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}","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// 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":275,"oldLines":13,"newStart":275,"newLines":6,"lines":[" }"," "," for i, row := range resBody.Results {","- // Safety check to prevent index out of range errors","- if i >= len(req.Queries) || i >= len(assignedScope) {","- cclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",","- i, len(req.Queries), len(assignedScope))","- continue","- }","-"," query := req.Queries[i]"," metric := query.Metric"," scope := assignedScope[i]"]},{"oldStart":318,"oldLines":18,"newStart":311,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id = query.TypeIds[ndx]","- } else {","- // Log the error but continue processing","- cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","- ndx, len(query.TypeIds), query.Metric, query.Hostname)","- }","- }","+ id := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)"," "," ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"5f1c383c-b4bc-4e12-bc05-0c692e1853b3"} +{"parentUuid":"bb63ed50-143a-464a-9f26-93aec6787d87","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01RTQCBr8NbY7YJtkwnK58FA","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 8: Add bounds check to 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:= req.Queries[i]","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\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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// 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":375,"oldLines":6,"newStart":375,"newLines":10,"lines":[" "," stats := make(map[string]map[string]schema.MetricStatistics, len(metrics))"," for i, res := range resBody.Results {","+ if i >= len(req.Queries) {","+ cclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))","+ break","+ }"," if len(res) == 0 {"," // No Data Found For Metric, Logged in FetchData to Warn"," continue"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"ebd50b0e-989c-4b03-a954-0bcb32220337"} +{"parentUuid":"fa4da924-7c8e-46cf-bb6a-018a8dbba7dc","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_016srAaDZV9coPWCTWSFP6n2","type":"message","role":"assistant","content":[{"type":"text","text":"Fix 3: Replace TypeID extraction in `LoadScopedStats`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":428,"cache_read_input_tokens":68120,"cache_creation":{"ephemeral_5m_input_tokens":428,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMFumDJqWxjJAfh6RJX","type":"assistant","uuid":"963d3907-b313-49fe-b0a0-a3bd528e1f0c","timestamp":"2026-03-04T16:24:15.112Z"} 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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{","new_string":"\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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{"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":428,"cache_read_input_tokens":68120,"output_tokens":605,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":428},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMFumDJqWxjJAfh6RJX","type":"assistant","uuid":"87b38381-5b6c-4fb4-b6f0-d9757edb59e6","timestamp":"2026-03-04T16:24:20.376Z"} +{"parentUuid":"87b38381-5b6c-4fb4-b6f0-d9757edb59e6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_016RY9ttb9MRrtYy8u5Ha8Ay","toolUseID":"toolu_016RY9ttb9MRrtYy8u5Ha8Ay","timestamp":"2026-03-04T16:24:20.421Z","uuid":"824871a8-4567-4e20-83f7-925ba58d4ef2"} +{"parentUuid":"87b38381-5b6c-4fb4-b6f0-d9757edb59e6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016RY9ttb9MRrtYy8u5Ha8Ay","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"62c9c0b6-a899-454a-8e9d-69b1733d680e","timestamp":"2026-03-04T16:24:20.421Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\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{","newString":"\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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{","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\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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// 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":467,"oldLines":18,"newStart":467,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id = query.TypeIds[ndx]","- } else {","- // Log the error but continue processing","- cclog.Warnf(\"TypeIds index out of range: %d with length %d for metric %s on host %s\",","- ndx, len(query.TypeIds), query.Metric, query.Hostname)","- }","- }","+ id := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)"," "," ms.SanitizeStats(&res.Avg, &res.Min, &res.Max)"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"87b38381-5b6c-4fb4-b6f0-d9757edb59e6"} 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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,","new_string":"\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\tcontinue\n\t\t}\n\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\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\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":657,"cache_read_input_tokens":68548,"output_tokens":622,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":657},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMGXazUqBu6hMvAT5DD","type":"assistant","uuid":"a0bff37c-b537-47a8-a7af-7d4d91fca640","timestamp":"2026-03-04T16:24:28.808Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"3e89bc46-6f07-45d0-ab24-f18ec1c368dc","timestamp":"2026-03-04T16:24:28.874Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\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,","newString":"\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\tcontinue\n\t\t}\n\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\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\thostdata[metric] = append(hostdata[metric], &schema.JobMetric{\n\t\t\tUnit: mc.Unit,\n\t\t\tTimestep: mc.Timestep,","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\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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// 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":557,"oldLines":8,"newStart":557,"newLines":15,"lines":[" qdata := res[0]"," if qdata.Error != nil {"," errors = append(errors, fmt.Sprintf(\"fetching %s for node %s failed: %s\", metric, query.Hostname, *qdata.Error))","+ continue"," }"," ","+ mc := archive.GetMetricConfig(cluster, metric)","+ if mc == nil {","+ cclog.Warnf(\"Metric config not found for %s on cluster %s\", metric, cluster)","+ continue","+ }","+"," ms.SanitizeStats(&qdata.Avg, &qdata.Min, &qdata.Max)"," "," hostdata, ok := data[query.Hostname]"]},{"oldStart":567,"oldLines":7,"newStart":574,"newLines":6,"lines":[" data[query.Hostname] = hostdata"," }"," ","- mc := archive.GetMetricConfig(cluster, metric)"," hostdata[metric] = append(hostdata[metric], &schema.JobMetric{"," Unit: mc.Unit,"," Timestep: mc.Timestep,"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a0bff37c-b537-47a8-a7af-7d4d91fca640"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"12cc6b83-b38b-4b1f-b369-ce21084b4d9d","timestamp":"2026-03-04T16:24:34.091Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\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 {","newString":"\tfor i, row := range resBody.Results {\n\t\tvar query APIQuery\n\t\tif resBody.Queries != nil {","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\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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// 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":661,"oldLines":13,"newStart":661,"newLines":6,"lines":[" }"," "," for i, row := range resBody.Results {","- // Safety check to prevent index out of range errors","- if i >= len(req.Queries) || i >= len(assignedScope) {","- cclog.Warnf(\"Index out of range prevented: i=%d, queries=%d, assignedScope=%d\",","- i, len(req.Queries), len(assignedScope))","- continue","- }","-"," var query APIQuery"," if resBody.Queries != nil {"," if i < len(resBody.Queries) {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"9c09a996-1e4e-4a97-a3a1-487f83fd45e0"} 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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{","new_string":"\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\t\t\tms.SanitizeStats(&res.Avg, &res.Min, &res.Max)\n\n\t\t\tscopeData.Series = append(scopeData.Series, schema.Series{"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":555,"cache_read_input_tokens":69879,"output_tokens":582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":555},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMHXjx2jd8KfDGB4h8d","type":"assistant","uuid":"66e42176-a084-4b99-9838-079f60e3727b","timestamp":"2026-03-04T16:24:43.648Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go has been updated successfully."}]},"uuid":"a92f1fc0-31f4-435d-9da6-ac89f5a1144b","timestamp":"2026-03-04T16:24:43.740Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store.go","oldString":"\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{","newString":"\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\n\n\t\t\tms.SanitizeStats(&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.\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\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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 i >= len(req.Queries) {\n\t\t\tcclog.Warnf(\"LoadStats: result index %d exceeds queries length %d\", i, len(req.Queries))\n\t\t\tbreak\n\t\t}\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 := ms.ExtractTypeID(query.Type, query.TypeIds, ndx, query.Metric, query.Hostname)\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\tcontinue\n\t\t}\n\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\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\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\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// 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":717,"oldLines":18,"newStart":717,"newLines":7,"lines":[" continue"," }"," ","- id := (*string)(nil)","- if query.Type != nil {","- // Check if ndx is within the bounds of TypeIds slice","- if ndx < len(query.TypeIds) {","- id = new(string)","- *id 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subcluster\n\t\tif len(mc.SubClusters) != 0 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\n\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":634,"cache_read_input_tokens":70434,"output_tokens":336,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":634},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMJF5sU3s1bFLsoDGKC","type":"assistant","uuid":"a4a71d0e-8bdb-4510-91c8-0e7fbe1d87fe","timestamp":"2026-03-04T16:24:50.843Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"7fe42a30-6ea9-4728-aebf-f9818fcf9068","timestamp":"2026-03-04T16:24:50.915Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"\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}","newString":"\t\t// Skip if metric is removed for subcluster\n\t\tif len(mc.SubClusters) != 0 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\n\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\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","structuredPatch":[{"oldStart":79,"oldLines":17,"newStart":79,"newLines":8,"lines":[" }"," "," // Skip if metric is removed for subcluster","- if len(mc.SubClusters) != 0 {","- isRemoved := false","- for _, scConfig := range mc.SubClusters {","- if scConfig.Name == job.SubCluster && scConfig.Remove {","- isRemoved = true","- break","- }","- }","- if isRemoved {","- continue","- }","+ if len(mc.SubClusters) != 0 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {","+ continue"," }"," "," // Avoid duplicates..."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a4a71d0e-8bdb-4510-91c8-0e7fbe1d87fe"} +{"parentUuid":"7fe42a30-6ea9-4728-aebf-f9818fcf9068","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01NwA5rnh6ELCFRoEb7wrGpZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XmkKmv7SFmnyBEqHW7eWuH","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\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","new_string":"\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > unsupported scope transformation: 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"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":390,"cache_read_input_tokens":71068,"output_tokens":524,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":390},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMJmdeXtCcTPLKLxPzB","type":"assistant","uuid":"7b4134b4-31cf-4dd9-98fa-e1fe71cede51","timestamp":"2026-03-04T16:24:58.154Z"} +{"parentUuid":"7b4134b4-31cf-4dd9-98fa-e1fe71cede51","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01XmkKmv7SFmnyBEqHW7eWuH","toolUseID":"toolu_01XmkKmv7SFmnyBEqHW7eWuH","timestamp":"2026-03-04T16:24:58.214Z","uuid":"d91f7fa4-54ab-4630-ad69-158e02aa4544"} +{"parentUuid":"7b4134b4-31cf-4dd9-98fa-e1fe71cede51","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XmkKmv7SFmnyBEqHW7eWuH","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"a890eee4-d46c-4383-83ff-334e592cc243","timestamp":"2026-03-04T16:24:58.213Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"\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","newString":"\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > unsupported scope transformation: 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","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 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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","structuredPatch":[{"oldStart":114,"oldLines":7,"newStart":114,"newLines":7,"lines":[" )"," "," if !ok {","- return nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > TODO: unhandled case: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)","+ return nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > unsupported scope transformation: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)"," }"," "," for _, sr := range scopeResults {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"7b4134b4-31cf-4dd9-98fa-e1fe71cede51"} 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subcluster\n\t\tif mc.SubClusters != nil && metricstore.IsMetricRemovedForSubCluster(mc, subCluster) {\n\t\t\tcontinue\n\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":578,"cache_read_input_tokens":71458,"output_tokens":286,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":578},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMKJq7qboRzc9277Vuw","type":"assistant","uuid":"a9312bbe-5407-4fa0-b651-c0f2544fd8da","timestamp":"2026-03-04T16:25:02.582Z"} 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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 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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","structuredPatch":[{"oldStart":166,"oldLines":17,"newStart":166,"newLines":8,"lines":[" }"," "," // Skip if metric is removed for subcluster","- if mc.SubClusters != nil {","- isRemoved := false","- for _, scConfig := range mc.SubClusters {","- if scConfig.Name == subCluster && scConfig.Remove {","- isRemoved = true","- break","- }","- }","- if isRemoved {","- continue","- }","+ if mc.SubClusters != nil && metricstore.IsMetricRemovedForSubCluster(mc, subCluster) {","+ continue"," }"," "," // Avoid duplicates..."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a9312bbe-5407-4fa0-b651-c0f2544fd8da"} 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requestedScope)\n\t\t\t\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":340,"cache_read_input_tokens":72036,"output_tokens":272,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":340},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMKduaiyMmPaZJMAhMY","type":"assistant","uuid":"8cf9c709-7d1c-4446-bbac-4247039b824f","timestamp":"2026-03-04T16:25:06.028Z"} 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/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go has been updated successfully."}]},"uuid":"183f4b68-e5f0-48c9-985c-6936432abbc6","timestamp":"2026-03-04T16:25:06.104Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/metricstoreclient/cc-metric-store-queries.go","oldString":"\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}","newString":"\t\t\t\tif !ok {\n\t\t\t\t\treturn nil, nil, fmt.Errorf(\"METRICDATA/EXTERNAL-CCMS > unsupported scope transformation: native-scope=%s, requested-scope=%s\", nativeScope, requestedScope)\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 && metricstore.IsMetricRemovedForSubCluster(mc, job.SubCluster) {\n\t\t\tcontinue\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 > unsupported scope transformation: 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 && metricstore.IsMetricRemovedForSubCluster(mc, subCluster) {\n\t\t\tcontinue\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: 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Let me also check the unused import situation — `cclog` was used in `LoadScopedStats` of `cc-metric-store.go` and now the inline TypeID code is removed, but `cclog` is still used elsewhere so it should be fine."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":422,"cache_read_input_tokens":73006,"cache_creation":{"ephemeral_5m_input_tokens":422,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYiMMzKUX8GPyuhi529CA","type":"assistant","uuid":"38d84270-3430-4a99-b281-3bec2e64514e","timestamp":"2026-03-04T16:25:38.603Z"} +{"parentUuid":"38d84270-3430-4a99-b281-3bec2e64514e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01SsaXYUMMqTUmZqTbuPVoan","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016gh6mVXF5eWQ1GbW8pa5SJ","name":"TaskUpdate","input":{"taskId":"4","status":"completed"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":422,"cache_read_input_tokens":73006,"output_tokens":132,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":422},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMMzKUX8GPyuhi529CA","type":"assistant","uuid":"d1eb36b7-20bd-46a8-9807-8c865626afb0","timestamp":"2026-03-04T16:25:38.893Z"} +{"parentUuid":"d1eb36b7-20bd-46a8-9807-8c865626afb0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016gh6mVXF5eWQ1GbW8pa5SJ","type":"tool_result","content":"Updated task #4 status"}]},"uuid":"15937656-9ebc-45a8-a781-45d8b5724f03","timestamp":"2026-03-04T16:25:38.943Z","toolUseResult":{"success":true,"taskId":"4","updatedFields":["status"],"statusChange":{"from":"in_progress","to":"completed"}},"sourceToolAssistantUUID":"d1eb36b7-20bd-46a8-9807-8c865626afb0"} +{"parentUuid":"15937656-9ebc-45a8-a781-45d8b5724f03","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","message":{"model":"claude-opus-4-6","id":"msg_01UvvrRTFDaBMyVK9RXcWZgn","type":"message","role":"assistant","content":[{"type":"text","text":"All changes implemented and verified. Here's a summary:\n\n1. **Bug fix: `LoadNodeData` nil metric config** — Added nil check for `mc` before dereferencing in both packages\n2. **Bug fix: `LoadNodeData` missing `continue` after error** — Added `continue` after appending error in both packages\n3. **Extracted `ExtractTypeID` helper** — Added to `scopequery.go`, replaced 6 inline occurrences (3 per package)\n4. **Extracted `IsMetricRemovedForSubCluster` helper** — Added to `scopequery.go`, replaced 4 inline occurrences (2 per package)\n5. **Fixed TODO error messages** — Replaced \"TODO: unhandled case\" with \"unsupported scope transformation\" in all 4 occurrences\n6. **Removed redundant inner bounds checks** — Removed 4 dead-code safety checks that were already guarded by outer truncation\n7. **Added capacity hint for `assignedScope`** — Changed from `[]schema.MetricScope{}` to `make(...)` with matching capacity in internal `buildQueries`/`buildNodeQueries`\n8. **Added bounds check to `LoadStats`** — Added `i >= len(req.Queries)` check in both packages\n\nBuild, vet, and tests all pass."}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":150,"cache_read_input_tokens":73428,"output_tokens":316,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":150},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYiMNK65jFV1yhXpqx48o","type":"assistant","uuid":"b2a82d09-9aac-42d2-bff9-437dcb545572","timestamp":"2026-03-04T16:25:49.744Z"} +{"parentUuid":"b2a82d09-9aac-42d2-bff9-437dcb545572","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"2c26c946-1def-45ad-aac8-f65c4765658b","version":"2.1.68","gitBranch":"dev","slug":"warm-floating-scone","type":"progress","data":{"type":"hook_progress","hookEvent":"Stop","hookName":"Stop","command":"entire hooks claude-code stop"},"parentToolUseID":"31cfba45-91c2-4d3c-ac97-0e874028e929","toolUseID":"31cfba45-91c2-4d3c-ac97-0e874028e929","timestamp":"2026-03-04T16:25:49.763Z","uuid":"0347ac93-7b4a-41fb-a7f7-954808decd90"} diff --git a/d1/0e6221ee4f/0/metadata.json b/d1/0e6221ee4f/0/metadata.json new file mode 100644 index 00000000..c981759d --- /dev/null +++ b/d1/0e6221ee4f/0/metadata.json @@ -0,0 +1,33 @@ +{ + "cli_version": "0.4.9", + "checkpoint_id": "d10e6221ee4f", + "session_id": "2c26c946-1def-45ad-aac8-f65c4765658b", + "strategy": "manual-commit", + "created_at": "2026-03-04T16:31:37.217581Z", + "branch": "dev", + "checkpoints_count": 1, + "files_touched": [ + "internal/metricstoreclient/cc-metric-store-queries.go", + "internal/metricstoreclient/cc-metric-store.go", + "pkg/metricstore/query.go", + "pkg/metricstore/scopequery.go" + ], + "agent": "Claude Code", + "turn_id": "d9170bb2f081", + "token_usage": { + "input_tokens": 39, + "cache_creation_tokens": 53370, + "cache_read_tokens": 2335326, + "output_tokens": 14970, + "api_call_count": 37 + }, + "initial_attribution": { + "calculated_at": "2026-03-04T16:31:36.921624Z", + "agent_lines": 69, + "human_added": 0, + "human_modified": 0, + "human_removed": 0, + "total_committed": 69, + "agent_percentage": 100 + } +} diff --git a/d1/0e6221ee4f/0/prompt.txt b/d1/0e6221ee4f/0/prompt.txt new file mode 100644 index 00000000..6145cade --- /dev/null +++ b/d1/0e6221ee4f/0/prompt.txt @@ -0,0 +1,113 @@ +Implement the following plan: + +# Plan: Improve buildQuery implementation and related code + +## Context + +The `buildQueries`/`buildNodeQueries` functions and `Load*` methods exist in two packages with near-identical logic: +- `pkg/metricstore/query.go` (internal, in-memory store) +- `internal/metricstoreclient/cc-metric-store.go` + `cc-metric-store-queries.go` (external, HTTP client) + +Both share `BuildScopeQueries` and `SanitizeStats` from `pkg/metricstore/scopequery.go`. The review identified bugs, dead code, duplicated patterns, and inconsistencies across both packages. + +## Changes + +### 1. Bug fix: `LoadNodeData` nil metric config panic (both packages) + +`archive.GetMetricConfig()` can return nil, but `LoadNodeData` dereferences `mc.Unit`/`mc.Timestep` without checking. Every other Load function checks. + +**Files:** +- `pkg/metricstore/query.go:600` — add nil check + `continue` +- `internal/metricstoreclient/cc-metric-store.go:595` — add nil check + `continue` + +### 2. Bug fix: `LoadNodeData` missing `continue` after error (both packages) + +When `qdata.Error != nil`, the error is appended but execution falls through to append invalid data. Should `continue`. + +**Files:** +- `pkg/metricstore/query.go:589-590` +- `internal/metricstoreclient/cc-metric-store.go:583-585` + +### 3. Extract `ExtractTypeID` helper to `scopequery.go` + +The ID-extraction block is copy-pasted 6 times (3x in each package). Extract to shared helper in `pkg/metricstore/scopequery.go`. + +```go +func ExtractTypeID(queryType *string, typeIds []string, ndx int, metric, hostname string) *string { + if queryType == nil { + return nil + } + if ndx < len(typeIds) { + id := typeIds[ndx] + return &id + } + cclog.Warnf("TypeIds index out of range: %d with length %d for metric %s on host %s", + ndx, len(typeIds), metric, hostname) + return nil +} +``` + +**Files to update:** +- `pkg/metricstore/scopequery.go` — add function +- `pkg/metricstore/query.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData` +- `internal/metricstoreclient/cc-metric-store.go` — replace 3 occurrences in `LoadData`, `LoadScopedStats`, `LoadNodeListData` + +### 4. Extract `IsMetricRemovedForSubCluster` helper to `scopequery.go` + +The subcluster-removal check is duplicated 4 times (2x in each package). Extract to shared helper. + +```go +func IsMetricRemovedForSubCluster(mc *schema.MetricConfig, subCluster string) bool { + for _, scConfig := range mc.SubClusters { + if scConfig.Name == subCluster && scConfig.Remove { + return true + } + } + return false +} +``` + +**Files to update:** +- `pkg/metricstore/scopequery.go` — add function +- `pkg/metricstore/query.go` — replace in `buildQueries` and `buildNodeQueries` +- `internal/metricstoreclient/cc-metric-store-queries.go` — replace in `buildQueries` and `buildNodeQueries` + +### 5. Fix TODO in production error messages + +Replace `"TODO: unhandled case"` with proper error text in all 4 occurrences. + +**Files:** +- `pkg/metricstore/query.go:314,901` +- `internal/metricstoreclient/cc-metric-store-queries.go:126,237` + +### 6. Remove redundant inner bounds checks in `LoadData` and `LoadNodeListData` + +The outer truncation (e.g., lines 120-129 in internal `LoadData`) already ensures bounds safety, making the inner `if i >= len(...)` check dead code. Remove the inner checks. + +**Files (4 occurrences — 2 in each package):** +- `pkg/metricstore/query.go` — `LoadData` (lines 131-137), `LoadNodeListData` (lines 696-702) +- `internal/metricstoreclient/cc-metric-store.go` — `LoadData` (lines 278-283), `LoadNodeListData` (lines 682-688) + +### 7. Add capacity hint for `assignedScope` in internal `buildQueries`/`buildNodeQueries` + +**File:** `pkg/metricstore/query.go:254,822` + +Change `assignedScope := []schema.MetricScope{}` to use `make()` with matching capacity. + +### 8. Add bounds check to `LoadStats` for consistency (both packages) + +`LoadStats` indexes `req.Queries[i]` without checking bounds, unlike all other Load functions. Add a check. + +**Files:** +- `pkg/metricstore/query.go:376` +- `internal/metricstoreclient/cc-metric-store.go:395` + +## Verification + +1. `go build ./...` — ensure compilation succeeds +2. `go test ./pkg/metricstore/...` — run metricstore tests +3. `go test ./internal/metricstoreclient/...` — run client tests +4. `go vet ./pkg/metricstore/... ./internal/metricstoreclient/...` — check for issues + + +If 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/f0763fe7-f9bf-47b1-85f7-b16c2b9bffe1.jsonl \ No newline at end of file diff --git a/d1/0e6221ee4f/metadata.json b/d1/0e6221ee4f/metadata.json new file mode 100644 index 00000000..bbf396d1 --- /dev/null +++ b/d1/0e6221ee4f/metadata.json @@ -0,0 +1,29 @@ +{ + "cli_version": "0.4.9", + "checkpoint_id": "d10e6221ee4f", + "strategy": "manual-commit", + "branch": "dev", + "checkpoints_count": 1, + "files_touched": [ + "internal/metricstoreclient/cc-metric-store-queries.go", + "internal/metricstoreclient/cc-metric-store.go", + "pkg/metricstore/query.go", + "pkg/metricstore/scopequery.go" + ], + "sessions": [ + { + "metadata": "/d1/0e6221ee4f/0/metadata.json", + "transcript": "/d1/0e6221ee4f/0/full.jsonl", + "context": "/d1/0e6221ee4f/0/context.md", + "content_hash": "/d1/0e6221ee4f/0/content_hash.txt", + "prompt": "/d1/0e6221ee4f/0/prompt.txt" + } + ], + "token_usage": { + "input_tokens": 39, + "cache_creation_tokens": 53370, + "cache_read_tokens": 2335326, + "output_tokens": 14970, + "api_call_count": 37 + } +}