diff --git a/9b/5b833472e1/0/content_hash.txt b/9b/5b833472e1/0/content_hash.txt new file mode 100644 index 00000000..c09a676c --- /dev/null +++ b/9b/5b833472e1/0/content_hash.txt @@ -0,0 +1 @@ +sha256:856f1d60310da96e311b6c81f99ad34c64a8d999468c5a1c286e3ba489663e2c \ No newline at end of file diff --git a/9b/5b833472e1/0/full.jsonl b/9b/5b833472e1/0/full.jsonl new file mode 100644 index 00000000..85fecff4 --- /dev/null +++ b/9b/5b833472e1/0/full.jsonl @@ -0,0 +1,145 @@ +{"type":"file-history-snapshot","messageId":"7c9c06ad-3241-4b89-b282-79d680032f38","snapshot":{"messageId":"7c9c06ad-3241-4b89-b282-79d680032f38","trackedFileBackups":{},"timestamp":"2026-03-19T09:59:12.088Z"},"isSnapshotUpdate":false} +{"parentUuid":null,"isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"73699580-a5a4-4a0e-b103-6528b1c72c5f","toolUseID":"73699580-a5a4-4a0e-b103-6528b1c72c5f","timestamp":"2026-03-19T09:59:12.037Z","uuid":"57929479-b46e-40e7-b5f5-1818d675ae32","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"57929479-b46e-40e7-b5f5-1818d675ae32","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Plan: Fix Slow Project Stats Query\n\n## Context\n\nThe `/monitoring/projects/` page is significantly slower than `/monitoring/users/` despite using the same code path (`List.root.svelte`, same GraphQL query, same SQL structure). Both call `JobsStatsGrouped` via the `jobsStatistics` resolver.\n\n## Root Cause\n\n`WithStatsGroupCache` is injected into **every** GraphQL request context via `AroundOperations` in `cmd/cc-backend/server.go:96`. This means the cache path in the resolver is **always** taken for grouped stats queries.\n\nThe cache path calls:\n```go\nreturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n```\nwith `nil` for `reqFields`, which forces **all** SQL columns to be computed — including:\n```sql\nCOUNT(DISTINCT job.hpc_user) AS totalUsers\n```\n\nThis is the performance bottleneck:\n\n- **User grouping** (`GROUP BY hpc_user`): Each group has exactly 1 distinct `hpc_user` value → `COUNT(DISTINCT)` = trivially 1 per group → fast\n- **Project grouping** (`GROUP BY project`): Each project can have 10s–100s of distinct users across thousands of jobs → SQLite must maintain a hash set per group → expensive\n\nThe `List.root.svelte` frontend query does **not** request `totalUsers` for either page. It only requests: `id, name, totalJobs, shortJobs, totalWalltime, totalCoreHours, totalAccHours`. So `COUNT(DISTINCT hpc_user)` is computed for no reason, but is only costly for project grouping.\n\n**Why user page is fast**: `COUNT(DISTINCT hpc_user)` when grouping by `hpc_user` is trivially 1 per group — effectively O(1) per group.\n\n**Why project page is slow**: `COUNT(DISTINCT hpc_user)` when grouping by `project` requires deduplicating all users across potentially thousands of jobs per project.\n\n## What the Status Page Needs\n\n`StatusDash.svelte` requests `totalUsers` for `groupBy: SUBCLUSTER` — so `COUNT(DISTINCT hpc_user)` IS needed there. The fix must not break this.\n\n## Fix\n\nChange the cache path to pass the actual `reqFields` (derived from the GraphQL selection set) instead of `nil`, and include `reqFields` in the cache key so that identical requests still share cached results.\n\n### Files to Modify\n\n1. **`internal/graph/schema.resolvers.go`** (line ~678–688)\n - Pass `reqFields` instead of `nil` to `JobsStatsGrouped` in the cache path\n\n2. **`internal/graph/stats_cache.go`** (function `statsCacheKey`)\n - Include reqFields in the cache key so caching still deduplicates identical requests\n\n### Changes\n\n**`internal/graph/stats_cache.go`**:\n\nUpdate `statsCacheKey` to accept and include reqFields:\n```go\nfunc statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate, reqFields map[string]bool) string {\n return fmt.Sprintf(\"%v|%v|%v\", filter, *groupBy, reqFields)\n}\n```\n\n**`internal/graph/schema.resolvers.go`**:\n\nChange the cache call from:\n```go\nkey := statsCacheKey(filter, groupBy)\nallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n})\n```\nTo:\n```go\nkey := statsCacheKey(filter, groupBy, reqFields)\nallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n})\n```\n\n## Why This Works\n\n- The project list query never requests `totalUsers` → `COUNT(DISTINCT hpc_user)` is skipped → fast query\n- The user list query also never requests `totalUsers` → same benefit (marginal since the user `COUNT(DISTINCT)` is trivial)\n- The status page requests `totalUsers` → `COUNT(DISTINCT hpc_user)` is computed → no regression\n- Cache deduplication still works: if two aliases in the same request have the same filter+groupBy+reqFields, they share the cached result\n\n## Critical Files\n\n- `internal/graph/schema.resolvers.go` — cache invocation (lines ~678–688)\n- `internal/graph/stats_cache.go` — `statsCacheKey` function (line 57–59)\n- `internal/repository/stats.go` — `buildStatsQuery` (lines 136–229, `need()` helper)\n\n## Verification\n\n1. Build: `go build ./...`\n2. Test: `go test ./internal/repository/... ./internal/graph/...`\n3. Start server: `./cc-backend -server -dev -loglevel debug`\n4. Load `/monitoring/projects/?cluster=alex&startTime=last30d` — check that it loads at similar speed to `/monitoring/users/`\n5. Check backend logs for `Timer JobsStatsGrouped call:` — project query should now be much faster\n6. Verify `/monitoring/status/` still shows correct `Active Users` counts per subcluster\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/258fc5cb-f8b6-4d74-92a9-df4954615c17.jsonl"},"uuid":"7c9c06ad-3241-4b89-b282-79d680032f38","timestamp":"2026-03-19T09:59:11.864Z","planContent":"# Plan: Fix Slow Project Stats Query\n\n## Context\n\nThe `/monitoring/projects/` page is significantly slower than `/monitoring/users/` despite using the same code path (`List.root.svelte`, same GraphQL query, same SQL structure). Both call `JobsStatsGrouped` via the `jobsStatistics` resolver.\n\n## Root Cause\n\n`WithStatsGroupCache` is injected into **every** GraphQL request context via `AroundOperations` in `cmd/cc-backend/server.go:96`. This means the cache path in the resolver is **always** taken for grouped stats queries.\n\nThe cache path calls:\n```go\nreturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n```\nwith `nil` for `reqFields`, which forces **all** SQL columns to be computed — including:\n```sql\nCOUNT(DISTINCT job.hpc_user) AS totalUsers\n```\n\nThis is the performance bottleneck:\n\n- **User grouping** (`GROUP BY hpc_user`): Each group has exactly 1 distinct `hpc_user` value → `COUNT(DISTINCT)` = trivially 1 per group → fast\n- **Project grouping** (`GROUP BY project`): Each project can have 10s–100s of distinct users across thousands of jobs → SQLite must maintain a hash set per group → expensive\n\nThe `List.root.svelte` frontend query does **not** request `totalUsers` for either page. It only requests: `id, name, totalJobs, shortJobs, totalWalltime, totalCoreHours, totalAccHours`. So `COUNT(DISTINCT hpc_user)` is computed for no reason, but is only costly for project grouping.\n\n**Why user page is fast**: `COUNT(DISTINCT hpc_user)` when grouping by `hpc_user` is trivially 1 per group — effectively O(1) per group.\n\n**Why project page is slow**: `COUNT(DISTINCT hpc_user)` when grouping by `project` requires deduplicating all users across potentially thousands of jobs per project.\n\n## What the Status Page Needs\n\n`StatusDash.svelte` requests `totalUsers` for `groupBy: SUBCLUSTER` — so `COUNT(DISTINCT hpc_user)` IS needed there. The fix must not break this.\n\n## Fix\n\nChange the cache path to pass the actual `reqFields` (derived from the GraphQL selection set) instead of `nil`, and include `reqFields` in the cache key so that identical requests still share cached results.\n\n### Files to Modify\n\n1. **`internal/graph/schema.resolvers.go`** (line ~678–688)\n - Pass `reqFields` instead of `nil` to `JobsStatsGrouped` in the cache path\n\n2. **`internal/graph/stats_cache.go`** (function `statsCacheKey`)\n - Include reqFields in the cache key so caching still deduplicates identical requests\n\n### Changes\n\n**`internal/graph/stats_cache.go`**:\n\nUpdate `statsCacheKey` to accept and include reqFields:\n```go\nfunc statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate, reqFields map[string]bool) string {\n return fmt.Sprintf(\"%v|%v|%v\", filter, *groupBy, reqFields)\n}\n```\n\n**`internal/graph/schema.resolvers.go`**:\n\nChange the cache call from:\n```go\nkey := statsCacheKey(filter, groupBy)\nallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n})\n```\nTo:\n```go\nkey := statsCacheKey(filter, groupBy, reqFields)\nallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n})\n```\n\n## Why This Works\n\n- The project list query never requests `totalUsers` → `COUNT(DISTINCT hpc_user)` is skipped → fast query\n- The user list query also never requests `totalUsers` → same benefit (marginal since the user `COUNT(DISTINCT)` is trivial)\n- The status page requests `totalUsers` → `COUNT(DISTINCT hpc_user)` is computed → no regression\n- Cache deduplication still works: if two aliases in the same request have the same filter+groupBy+reqFields, they share the cached result\n\n## Critical Files\n\n- `internal/graph/schema.resolvers.go` — cache invocation (lines ~678–688)\n- `internal/graph/stats_cache.go` — `statsCacheKey` function (line 57–59)\n- `internal/repository/stats.go` — `buildStatsQuery` (lines 136–229, `need()` helper)\n\n## Verification\n\n1. Build: `go build ./...`\n2. Test: `go test ./internal/repository/... ./internal/graph/...`\n3. Start server: `./cc-backend -server -dev -loglevel debug`\n4. Load `/monitoring/projects/?cluster=alex&startTime=last30d` — check that it loads at similar speed to `/monitoring/users/`\n5. Check backend logs for `Timer JobsStatsGrouped call:` — project query should now be much faster\n6. Verify `/monitoring/status/` still shows correct `Active Users` counts per subcluster\n","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"type":"custom-title","customTitle":"fix-slow-project-stats-query","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe"} +{"type":"agent-name","agentName":"fix-slow-project-stats-query","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe"} +{"parentUuid":"7c9c06ad-3241-4b89-b282-79d680032f38","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_016DrDGb9M5uHLanccPZA3un","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"Ev0BCkYICxgCKkCvMDcUYzXh7HJOC76+xKPRVCxBJHlrUAPGBnCv6Dq4G6Nrs4imvYnaBAQYvWVSjH7O8aY+5skd53KDl7KTWCYBEgyB+GmcQnOWEKe/MRoaDAd+/inHP4xI4ivuNiIwAuTxHAgAOzGyPdshU8+lOBmxwFfceT2uzggy8a+09BBXm1DcDZFHThGzY5v0WdkmKmXD/6KVaUHqmA2QmzOw0c++p8YsDWCGNK6jEsTrgio/BRk7Xxh/AQBfZzA3uOPoVEAT2Se6gTQWDbgbJYtafRkWsT1VWi23bYi810XFT+cl3JM3Cg4SPHRiHvaQr6OygP6/ae+HmRgB"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":5687,"cache_read_input_tokens":14528,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5687},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF2rKPU74rm9zphDZW7","type":"assistant","uuid":"08458f91-b0e4-4e93-b495-058a580b58dc","timestamp":"2026-03-19T09:59:17.360Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"08458f91-b0e4-4e93-b495-058a580b58dc","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_016DrDGb9M5uHLanccPZA3un","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NiKPdBkFLhPa2j9wRLCewc","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":5687,"cache_read_input_tokens":14528,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5687},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF2rKPU74rm9zphDZW7","type":"assistant","uuid":"81616078-7330-4b2d-9627-fe2dcf64e012","timestamp":"2026-03-19T09:59:18.290Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"81616078-7330-4b2d-9627-fe2dcf64e012","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01NiKPdBkFLhPa2j9wRLCewc","toolUseID":"toolu_01NiKPdBkFLhPa2j9wRLCewc","timestamp":"2026-03-19T09:59:18.312Z","uuid":"7de09a93-7237-407c-a07b-31d9d50183ca","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"81616078-7330-4b2d-9627-fe2dcf64e012","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NiKPdBkFLhPa2j9wRLCewc","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→package graph\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"fmt\"\n 11→\t\"slices\"\n 12→\t\"sync\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 15→)\n 16→\n 17→// statsGroupCache is a per-request cache for grouped JobsStatistics results.\n 18→// It deduplicates identical (filter+groupBy) SQL queries that arise when the\n 19→// frontend requests multiple sort/page slices of the same underlying data\n 20→// (e.g. topUserJobs, topUserNodes, topUserAccs all group by USER).\n 21→type statsGroupCache struct {\n 22→\tmu sync.Mutex\n 23→\tentries map[string]*cacheEntry\n 24→}\n 25→\n 26→type cacheEntry struct {\n 27→\tonce sync.Once\n 28→\tresult []*model.JobsStatistics\n 29→\terr error\n 30→}\n 31→\n 32→type ctxKey int\n 33→\n 34→const statsGroupCacheKey ctxKey = iota\n 35→\n 36→// newStatsGroupCache creates a new empty cache.\n 37→func newStatsGroupCache() *statsGroupCache {\n 38→\treturn &statsGroupCache{\n 39→\t\tentries: make(map[string]*cacheEntry),\n 40→\t}\n 41→}\n 42→\n 43→// WithStatsGroupCache injects a new cache into the context.\n 44→func WithStatsGroupCache(ctx context.Context) context.Context {\n 45→\treturn context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())\n 46→}\n 47→\n 48→// getStatsGroupCache retrieves the cache from context, or nil if absent.\n 49→func getStatsGroupCache(ctx context.Context) *statsGroupCache {\n 50→\tif c, ok := ctx.Value(statsGroupCacheKey).(*statsGroupCache); ok {\n 51→\t\treturn c\n 52→\t}\n 53→\treturn nil\n 54→}\n 55→\n 56→// cacheKey builds a deterministic string key from filter + groupBy.\n 57→func statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate) string {\n 58→\treturn fmt.Sprintf(\"%v|%v\", filter, *groupBy)\n 59→}\n 60→\n 61→// getOrCompute returns cached results for the given key, computing them on\n 62→// first access via the provided function.\n 63→func (c *statsGroupCache) getOrCompute(\n 64→\tkey string,\n 65→\tcompute func() ([]*model.JobsStatistics, error),\n 66→) ([]*model.JobsStatistics, error) {\n 67→\tc.mu.Lock()\n 68→\tentry, ok := c.entries[key]\n 69→\tif !ok {\n 70→\t\tentry = &cacheEntry{}\n 71→\t\tc.entries[key] = entry\n 72→\t}\n 73→\tc.mu.Unlock()\n 74→\n 75→\tentry.once.Do(func() {\n 76→\t\tentry.result, entry.err = compute()\n 77→\t})\n 78→\treturn entry.result, entry.err\n 79→}\n 80→\n 81→// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)\n 82→// and returns the requested page slice.\n 83→func sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {\n 84→\t// Work on a shallow copy so the cached slice order is not mutated.\n 85→\tsorted := make([]*model.JobsStatistics, len(allStats))\n 86→\tcopy(sorted, allStats)\n 87→\n 88→\tif sortBy != nil {\n 89→\t\tgetter := statsFieldGetter(*sortBy)\n 90→\t\tslices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {\n 91→\t\t\treturn getter(b) - getter(a) // descending\n 92→\t\t})\n 93→\t}\n 94→\n 95→\tif page != nil && page.ItemsPerPage != -1 {\n 96→\t\tstart := (page.Page - 1) * page.ItemsPerPage\n 97→\t\tif start >= len(sorted) {\n 98→\t\t\treturn nil\n 99→\t\t}\n 100→\t\tend := start + page.ItemsPerPage\n 101→\t\tif end > len(sorted) {\n 102→\t\t\tend = len(sorted)\n 103→\t\t}\n 104→\t\tsorted = sorted[start:end]\n 105→\t}\n 106→\n 107→\treturn sorted\n 108→}\n 109→\n 110→// statsFieldGetter returns a function that extracts the sortable int field\n 111→// from a JobsStatistics struct for the given sort key.\n 112→func statsFieldGetter(sortBy model.SortByAggregate) func(*model.JobsStatistics) int {\n 113→\tswitch sortBy {\n 114→\tcase model.SortByAggregateTotaljobs:\n 115→\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n 116→\tcase model.SortByAggregateTotalusers:\n 117→\t\treturn func(s *model.JobsStatistics) int { return s.TotalUsers }\n 118→\tcase model.SortByAggregateTotalwalltime:\n 119→\t\treturn func(s *model.JobsStatistics) int { return s.TotalWalltime }\n 120→\tcase model.SortByAggregateTotalnodes:\n 121→\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodes }\n 122→\tcase model.SortByAggregateTotalnodehours:\n 123→\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodeHours }\n 124→\tcase model.SortByAggregateTotalcores:\n 125→\t\treturn func(s *model.JobsStatistics) int { return s.TotalCores }\n 126→\tcase model.SortByAggregateTotalcorehours:\n 127→\t\treturn func(s *model.JobsStatistics) int { return s.TotalCoreHours }\n 128→\tcase model.SortByAggregateTotalaccs:\n 129→\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccs }\n 130→\tcase model.SortByAggregateTotalacchours:\n 131→\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccHours }\n 132→\tdefault:\n 133→\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n 134→\t}\n 135→}\n 136→\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"uuid":"9475e67e-a98a-4423-af71-22ef9c81c75a","timestamp":"2026-03-19T09:59:18.312Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.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\npackage graph\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"slices\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n)\n\n// statsGroupCache is a per-request cache for grouped JobsStatistics results.\n// It deduplicates identical (filter+groupBy) SQL queries that arise when the\n// frontend requests multiple sort/page slices of the same underlying data\n// (e.g. topUserJobs, topUserNodes, topUserAccs all group by USER).\ntype statsGroupCache struct {\n\tmu sync.Mutex\n\tentries map[string]*cacheEntry\n}\n\ntype cacheEntry struct {\n\tonce sync.Once\n\tresult []*model.JobsStatistics\n\terr error\n}\n\ntype ctxKey int\n\nconst statsGroupCacheKey ctxKey = iota\n\n// newStatsGroupCache creates a new empty cache.\nfunc newStatsGroupCache() *statsGroupCache {\n\treturn &statsGroupCache{\n\t\tentries: make(map[string]*cacheEntry),\n\t}\n}\n\n// WithStatsGroupCache injects a new cache into the context.\nfunc WithStatsGroupCache(ctx context.Context) context.Context {\n\treturn context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())\n}\n\n// getStatsGroupCache retrieves the cache from context, or nil if absent.\nfunc getStatsGroupCache(ctx context.Context) *statsGroupCache {\n\tif c, ok := ctx.Value(statsGroupCacheKey).(*statsGroupCache); ok {\n\t\treturn c\n\t}\n\treturn nil\n}\n\n// cacheKey builds a deterministic string key from filter + groupBy.\nfunc statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate) string {\n\treturn fmt.Sprintf(\"%v|%v\", filter, *groupBy)\n}\n\n// getOrCompute returns cached results for the given key, computing them on\n// first access via the provided function.\nfunc (c *statsGroupCache) getOrCompute(\n\tkey string,\n\tcompute func() ([]*model.JobsStatistics, error),\n) ([]*model.JobsStatistics, error) {\n\tc.mu.Lock()\n\tentry, ok := c.entries[key]\n\tif !ok {\n\t\tentry = &cacheEntry{}\n\t\tc.entries[key] = entry\n\t}\n\tc.mu.Unlock()\n\n\tentry.once.Do(func() {\n\t\tentry.result, entry.err = compute()\n\t})\n\treturn entry.result, entry.err\n}\n\n// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)\n// and returns the requested page slice.\nfunc sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {\n\t// Work on a shallow copy so the cached slice order is not mutated.\n\tsorted := make([]*model.JobsStatistics, len(allStats))\n\tcopy(sorted, allStats)\n\n\tif sortBy != nil {\n\t\tgetter := statsFieldGetter(*sortBy)\n\t\tslices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {\n\t\t\treturn getter(b) - getter(a) // descending\n\t\t})\n\t}\n\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tstart := (page.Page - 1) * page.ItemsPerPage\n\t\tif start >= len(sorted) {\n\t\t\treturn nil\n\t\t}\n\t\tend := start + page.ItemsPerPage\n\t\tif end > len(sorted) {\n\t\t\tend = len(sorted)\n\t\t}\n\t\tsorted = sorted[start:end]\n\t}\n\n\treturn sorted\n}\n\n// statsFieldGetter returns a function that extracts the sortable int field\n// from a JobsStatistics struct for the given sort key.\nfunc statsFieldGetter(sortBy model.SortByAggregate) func(*model.JobsStatistics) int {\n\tswitch sortBy {\n\tcase model.SortByAggregateTotaljobs:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n\tcase model.SortByAggregateTotalusers:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalUsers }\n\tcase model.SortByAggregateTotalwalltime:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalWalltime }\n\tcase model.SortByAggregateTotalnodes:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodes }\n\tcase model.SortByAggregateTotalnodehours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodeHours }\n\tcase model.SortByAggregateTotalcores:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalCores }\n\tcase model.SortByAggregateTotalcorehours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalCoreHours }\n\tcase model.SortByAggregateTotalaccs:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccs }\n\tcase model.SortByAggregateTotalacchours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccHours }\n\tdefault:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n\t}\n}\n","numLines":136,"startLine":1,"totalLines":136}},"sourceToolAssistantUUID":"81616078-7330-4b2d-9627-fe2dcf64e012","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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else {\n 675→\t\t\tstartGrouped := time.Now()\n 676→\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n 677→\t\t\t// but different sortBy/page hit the DB only once.\n 678→\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n 679→\t\t\t\tkey := statsCacheKey(filter, groupBy)\n 680→\t\t\t\tvar allStats []*model.JobsStatistics\n 681→\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n 682→\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n 683→\t\t\t\t})\n 684→\t\t\t\tif err == nil {\n 685→\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n 686→\t\t\t\t}\n 687→\t\t\t} else {\n 688→\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n 689→\t\t\t}\n 690→\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n 691→\t\t}\n 692→\t} else {\n 693→\t\tstats = make([]*model.JobsStatistics, 0, 1)\n 694→\t\tstats = append(stats, &model.JobsStatistics{})\n 695→\t}\n 696→\n 697→\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n 698→\t// Only run separate count queries if main stats were not fetched.\n 699→\tif !fetchedMainStats {\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"uuid":"4aacd2cd-eb79-4def-aaf8-3015eea66a5b","timestamp":"2026-03-19T09:59:18.711Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","content":"\n\tif fetchedMainStats {\n\t\tif groupBy == nil {\n\t\t\tstats, err = r.Repo.JobsStats(ctx, filter, reqFields)\n\t\t} else {\n\t\t\tstartGrouped := time.Now()\n\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n\t\t\t// but different sortBy/page hit the DB only once.\n\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n\t\t\t\tkey := statsCacheKey(filter, groupBy)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n\t\t\t\t})\n\t\t\t\tif err == nil {\n\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n\t\t\t}\n\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n\t\t}\n\t} else {\n\t\tstats = make([]*model.JobsStatistics, 0, 1)\n\t\tstats = append(stats, &model.JobsStatistics{})\n\t}\n\n\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n\t// Only run separate count queries if main stats were not fetched.\n\tif !fetchedMainStats {","numLines":30,"startLine":670,"totalLines":1075}},"sourceToolAssistantUUID":"ba3c1e59-d9fc-4519-8619-0e8788e3e950","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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reqFields)\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3310,"cache_read_input_tokens":20215,"output_tokens":262,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3310,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCF3LCBh8kJGe2Zkh73f","type":"assistant","uuid":"be8ca8a3-73dc-4799-9a6b-6c0e6df79385","timestamp":"2026-03-19T09:59:26.959Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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fmt.Sprintf(\"%v|%v|%v\", filter, *groupBy, reqFields)\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\npackage graph\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"slices\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n)\n\n// statsGroupCache is a per-request cache for grouped JobsStatistics results.\n// It deduplicates identical (filter+groupBy) SQL queries that arise when the\n// frontend requests multiple sort/page slices of the same underlying data\n// (e.g. topUserJobs, topUserNodes, topUserAccs all group by USER).\ntype statsGroupCache struct {\n\tmu sync.Mutex\n\tentries map[string]*cacheEntry\n}\n\ntype cacheEntry struct {\n\tonce sync.Once\n\tresult []*model.JobsStatistics\n\terr error\n}\n\ntype ctxKey int\n\nconst statsGroupCacheKey ctxKey = iota\n\n// newStatsGroupCache creates a new empty cache.\nfunc newStatsGroupCache() *statsGroupCache {\n\treturn &statsGroupCache{\n\t\tentries: make(map[string]*cacheEntry),\n\t}\n}\n\n// WithStatsGroupCache injects a new cache into the context.\nfunc WithStatsGroupCache(ctx context.Context) context.Context {\n\treturn context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())\n}\n\n// getStatsGroupCache retrieves the cache from context, or nil if absent.\nfunc getStatsGroupCache(ctx context.Context) *statsGroupCache {\n\tif c, ok := ctx.Value(statsGroupCacheKey).(*statsGroupCache); ok {\n\t\treturn c\n\t}\n\treturn nil\n}\n\n// cacheKey builds a deterministic string key from filter + groupBy.\nfunc statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate) string {\n\treturn fmt.Sprintf(\"%v|%v\", filter, *groupBy)\n}\n\n// getOrCompute returns cached results for the given key, computing them on\n// first access via the provided function.\nfunc (c *statsGroupCache) getOrCompute(\n\tkey string,\n\tcompute func() ([]*model.JobsStatistics, error),\n) ([]*model.JobsStatistics, error) {\n\tc.mu.Lock()\n\tentry, ok := c.entries[key]\n\tif !ok {\n\t\tentry = &cacheEntry{}\n\t\tc.entries[key] = entry\n\t}\n\tc.mu.Unlock()\n\n\tentry.once.Do(func() {\n\t\tentry.result, entry.err = compute()\n\t})\n\treturn entry.result, entry.err\n}\n\n// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)\n// and returns the requested page slice.\nfunc sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {\n\t// Work on a shallow copy so the cached slice order is not mutated.\n\tsorted := make([]*model.JobsStatistics, len(allStats))\n\tcopy(sorted, allStats)\n\n\tif sortBy != nil {\n\t\tgetter := statsFieldGetter(*sortBy)\n\t\tslices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {\n\t\t\treturn getter(b) - getter(a) // descending\n\t\t})\n\t}\n\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tstart := (page.Page - 1) * page.ItemsPerPage\n\t\tif start >= len(sorted) {\n\t\t\treturn nil\n\t\t}\n\t\tend := start + page.ItemsPerPage\n\t\tif end > len(sorted) {\n\t\t\tend = len(sorted)\n\t\t}\n\t\tsorted = sorted[start:end]\n\t}\n\n\treturn sorted\n}\n\n// statsFieldGetter returns a function that extracts the sortable int field\n// from a JobsStatistics struct for the given sort key.\nfunc statsFieldGetter(sortBy model.SortByAggregate) func(*model.JobsStatistics) int {\n\tswitch sortBy {\n\tcase model.SortByAggregateTotaljobs:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n\tcase model.SortByAggregateTotalusers:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalUsers }\n\tcase model.SortByAggregateTotalwalltime:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalWalltime }\n\tcase model.SortByAggregateTotalnodes:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodes }\n\tcase model.SortByAggregateTotalnodehours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodeHours }\n\tcase model.SortByAggregateTotalcores:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalCores }\n\tcase model.SortByAggregateTotalcorehours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalCoreHours }\n\tcase model.SortByAggregateTotalaccs:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccs }\n\tcase model.SortByAggregateTotalacchours:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccHours }\n\tdefault:\n\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n\t}\n}\n","structuredPatch":[{"oldStart":53,"oldLines":9,"newStart":53,"newLines":9,"lines":[" return nil"," }"," ","-// cacheKey builds a deterministic string key from filter + groupBy.","-func statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate) string {","- return fmt.Sprintf(\"%v|%v\", filter, *groupBy)","+// cacheKey builds a deterministic string key from filter + groupBy + reqFields.","+func statsCacheKey(filter []*model.JobFilter, groupBy 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allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n\t\t\t\t})","new_string":"\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, 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successfully."}]},"uuid":"96c57c31-74df-4ab3-af2d-58847abf6e2f","timestamp":"2026-03-19T09:59:33.739Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","oldString":"\t\t\tkey := statsCacheKey(filter, groupBy)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n\t\t\t\t})","newString":"\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n\t\t\t\t})","originalFile":"package graph\n\n// This file will be automatically regenerated based on the schema, any resolver\n// implementations\n// will be copied through when generating and any unknown code will be moved to the end.\n// Code generated by github.com/99designs/gqlgen version v0.17.88\n\nimport (\n\t\"context\"\n\t\"errors\"\n\t\"fmt\"\n\t\"math\"\n\t\"regexp\"\n\t\"slices\"\n\t\"strconv\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/repository\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\tccunit \"github.com/ClusterCockpit/cc-lib/v2/ccUnits\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\n// Partitions is the resolver for the partitions field.\nfunc (r *clusterResolver) Partitions(ctx context.Context, obj *schema.Cluster) ([]string, error) {\n\treturn r.Repo.Partitions(obj.Name)\n}\n\n// StartTime is the resolver for the startTime field.\nfunc (r *jobResolver) StartTime(ctx context.Context, obj *schema.Job) (*time.Time, error) {\n\ttimestamp := time.Unix(obj.StartTime, 0)\n\treturn ×tamp, nil\n}\n\n// Tags is the resolver for the tags field.\nfunc (r *jobResolver) Tags(ctx context.Context, obj *schema.Job) ([]*schema.Tag, error) {\n\treturn r.Repo.GetTags(repository.GetUserFromContext(ctx), obj.ID)\n}\n\n// ConcurrentJobs is the resolver for the concurrentJobs field.\nfunc (r *jobResolver) ConcurrentJobs(ctx context.Context, obj *schema.Job) (*model.JobLinkResultList, error) {\n\t// FIXME: Make the hardcoded duration configurable\n\tif obj.Shared != \"none\" && obj.Duration > 600 {\n\t\treturn r.Repo.FindConcurrentJobs(ctx, obj)\n\t}\n\n\treturn nil, nil\n}\n\n// Footprint is the resolver for the footprint field.\nfunc (r *jobResolver) Footprint(ctx context.Context, obj *schema.Job) ([]*model.FootprintValue, error) {\n\trawFootprint, err := r.Repo.FetchFootprint(obj)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while fetching job footprint data\")\n\t\treturn nil, err\n\t}\n\n\tres := []*model.FootprintValue{}\n\tfor name, value := range rawFootprint {\n\n\t\tparts := strings.Split(name, \"_\")\n\t\tstatPart := parts[len(parts)-1]\n\t\tnameParts := parts[:len(parts)-1]\n\n\t\tres = append(res, &model.FootprintValue{\n\t\t\tName: strings.Join(nameParts, \"_\"),\n\t\t\tStat: statPart,\n\t\t\tValue: value,\n\t\t})\n\t}\n\n\treturn res, err\n}\n\n// EnergyFootprint is the resolver for the energyFootprint field.\nfunc (r *jobResolver) EnergyFootprint(ctx context.Context, obj *schema.Job) ([]*model.EnergyFootprintValue, error) {\n\trawEnergyFootprint, err := r.Repo.FetchEnergyFootprint(obj)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while fetching job energy footprint data\")\n\t\treturn nil, err\n\t}\n\n\tres := []*model.EnergyFootprintValue{}\n\tfor name, value := range rawEnergyFootprint {\n\t\t// Suboptimal: Nearly hardcoded metric name expectations\n\t\tmatchCPU := regexp.MustCompile(`cpu|Cpu|CPU`)\n\t\tmatchAcc := regexp.MustCompile(`acc|Acc|ACC`)\n\t\tmatchMem := regexp.MustCompile(`mem|Mem|MEM`)\n\t\tmatchCore := regexp.MustCompile(`core|Core|CORE`)\n\n\t\thwType := \"\"\n\t\tswitch test := name; { // NOtice ';' for var declaration\n\t\tcase matchCPU.MatchString(test):\n\t\t\thwType = \"CPU\"\n\t\tcase matchAcc.MatchString(test):\n\t\t\thwType = \"Accelerator\"\n\t\tcase matchMem.MatchString(test):\n\t\t\thwType = \"Memory\"\n\t\tcase matchCore.MatchString(test):\n\t\t\thwType = \"Core\"\n\t\tdefault:\n\t\t\thwType = \"Other\"\n\t\t}\n\n\t\tres = append(res, &model.EnergyFootprintValue{\n\t\t\tHardware: hwType,\n\t\t\tMetric: name,\n\t\t\tValue: value,\n\t\t})\n\t}\n\treturn res, err\n}\n\n// MetaData is the resolver for the metaData field.\nfunc (r *jobResolver) MetaData(ctx context.Context, obj *schema.Job) (any, error) {\n\treturn r.Repo.FetchMetadata(obj)\n}\n\n// UserData is the resolver for the userData field.\nfunc (r *jobResolver) UserData(ctx context.Context, obj *schema.Job) (*model.User, error) {\n\treturn repository.GetUserRepository().FetchUserInCtx(ctx, obj.User)\n}\n\n// Name is the resolver for the name field.\nfunc (r *metricValueResolver) Name(ctx context.Context, obj *schema.MetricValue) (*string, error) {\n\tpanic(fmt.Errorf(\"not implemented: Name - name\"))\n}\n\n// CreateTag is the resolver for the createTag field.\nfunc (r *mutationResolver) CreateTag(ctx context.Context, typeArg string, name string, scope string) (*schema.Tag, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"no user in context\")\n\t}\n\n\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n\tif user.HasRole(schema.RoleAdmin) && scope == \"admin\" ||\n\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && scope == \"global\" ||\n\t\tuser.Username == scope {\n\t\t// Create in DB\n\t\tid, err := r.Repo.CreateTag(typeArg, name, scope)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while creating tag\")\n\t\t\treturn nil, err\n\t\t}\n\t\treturn &schema.Tag{ID: id, Type: typeArg, Name: name, Scope: scope}, nil\n\t} else {\n\t\tcclog.Warnf(\"Not authorized to create tag with scope: %s\", scope)\n\t\treturn nil, fmt.Errorf(\"not authorized to create tag with scope: %s\", scope)\n\t}\n}\n\n// DeleteTag is the resolver for the deleteTag field.\nfunc (r *mutationResolver) DeleteTag(ctx context.Context, id string) (string, error) {\n\t// This Uses ID string <-> ID string, removeTagFromList uses []string <-> []int\n\tpanic(fmt.Errorf(\"not implemented: DeleteTag - deleteTag\"))\n}\n\n// AddTagsToJob is the resolver for the addTagsToJob field.\nfunc (r *mutationResolver) AddTagsToJob(ctx context.Context, job string, tagIds []string) ([]*schema.Tag, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"no user in context\")\n\t}\n\n\tjid, err := strconv.ParseInt(job, 10, 64)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while adding tag to job\")\n\t\treturn nil, err\n\t}\n\n\ttags := []*schema.Tag{}\n\tfor _, tagID := range tagIds {\n\t\t// Get ID\n\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while parsing tag id\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\t// Test Exists\n\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n\t\tif !exists {\n\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n\t\t}\n\n\t\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n\t\tif user.HasRole(schema.RoleAdmin) && tscope == \"admin\" ||\n\t\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && tscope == \"global\" ||\n\t\t\tuser.Username == tscope {\n\t\t\t// Add to Job\n\t\t\tif tags, err = r.Repo.AddTag(user, jid, tid); err != nil {\n\t\t\t\tcclog.Warn(\"Error while adding tag\")\n\t\t\t\treturn nil, err\n\t\t\t}\n\t\t} else {\n\t\t\tcclog.Warnf(\"Not authorized to add tag: %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"not authorized to add tag: %d\", tid)\n\t\t}\n\t}\n\n\treturn tags, nil\n}\n\n// RemoveTagsFromJob is the resolver for the removeTagsFromJob field.\nfunc (r *mutationResolver) RemoveTagsFromJob(ctx context.Context, job string, tagIds []string) ([]*schema.Tag, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"no user in context\")\n\t}\n\n\tjid, err := strconv.ParseInt(job, 10, 64)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while parsing job id\")\n\t\treturn nil, err\n\t}\n\n\ttags := []*schema.Tag{}\n\tfor _, tagID := range tagIds {\n\t\t// Get ID\n\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while parsing tag id\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\t// Test Exists\n\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n\t\tif !exists {\n\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n\t\t}\n\n\t\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n\t\tif user.HasRole(schema.RoleAdmin) && tscope == \"admin\" ||\n\t\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && tscope == \"global\" ||\n\t\t\tuser.Username == tscope {\n\t\t\t// Remove from Job\n\t\t\tif tags, err = r.Repo.RemoveTag(user, jid, tid); err != nil {\n\t\t\t\tcclog.Warn(\"Error while removing tag\")\n\t\t\t\treturn nil, err\n\t\t\t}\n\t\t} else {\n\t\t\tcclog.Warnf(\"Not authorized to remove tag: %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"not authorized to remove tag: %d\", tid)\n\t\t}\n\n\t}\n\n\treturn tags, nil\n}\n\n// RemoveTagFromList is the resolver for the removeTagFromList field.\nfunc (r *mutationResolver) RemoveTagFromList(ctx context.Context, tagIds []string) ([]int, error) {\n\t// Needs Contextuser\n\tuser := repository.GetUserFromContext(ctx)\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"no user in context\")\n\t}\n\n\ttags := []int{}\n\tfor _, tagID := range tagIds {\n\t\t// Get ID\n\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while parsing tag id for removal\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\t// Test Exists\n\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n\t\tif !exists {\n\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n\t\t}\n\n\t\t// Test Access: Admins && Admin Tag OR Everyone && Private Tag\n\t\tif user.HasRole(schema.RoleAdmin) && (tscope == \"global\" || tscope == \"admin\") || user.Username == tscope {\n\t\t\t// Remove from DB\n\t\t\tif err = r.Repo.RemoveTagByID(tid); err != nil {\n\t\t\t\tcclog.Warn(\"Error while removing tag\")\n\t\t\t\treturn nil, err\n\t\t\t} else {\n\t\t\t\ttags = append(tags, int(tid))\n\t\t\t}\n\t\t} else {\n\t\t\tcclog.Warnf(\"Not authorized to remove tag: %d\", tid)\n\t\t\treturn nil, fmt.Errorf(\"not authorized to remove tag: %d\", tid)\n\t\t}\n\t}\n\treturn tags, nil\n}\n\n// UpdateConfiguration is the resolver for the updateConfiguration field.\nfunc (r *mutationResolver) UpdateConfiguration(ctx context.Context, name string, value string) (*string, error) {\n\tif err := repository.GetUserCfgRepo().UpdateConfig(name, value, repository.GetUserFromContext(ctx)); err != nil {\n\t\tcclog.Warn(\"Error while updating user config\")\n\t\treturn nil, err\n\t}\n\n\treturn nil, nil\n}\n\n// ID is the resolver for the id field.\nfunc (r *nodeResolver) ID(ctx context.Context, obj *schema.Node) (string, error) {\n\tpanic(fmt.Errorf(\"not implemented: ID - id\"))\n}\n\n// SchedulerState is the resolver for the schedulerState field.\nfunc (r *nodeResolver) SchedulerState(ctx context.Context, obj *schema.Node) (schema.SchedulerState, error) {\n\tif obj.NodeState != \"\" {\n\t\treturn obj.NodeState, nil\n\t} else {\n\t\treturn \"\", fmt.Errorf(\"resolver: no SchedulerState (NodeState) on node object\")\n\t}\n}\n\n// HealthState is the resolver for the healthState field.\nfunc (r *nodeResolver) HealthState(ctx context.Context, obj *schema.Node) (string, error) {\n\tif obj.HealthState != \"\" {\n\t\treturn string(obj.HealthState), nil\n\t} else {\n\t\treturn \"\", fmt.Errorf(\"resolver: no HealthState (NodeState) on node object\")\n\t}\n}\n\n// MetaData is the resolver for the metaData field.\nfunc (r *nodeResolver) MetaData(ctx context.Context, obj *schema.Node) (any, error) {\n\tif obj.MetaData != nil {\n\t\treturn obj.MetaData, nil\n\t} else {\n\t\tcclog.Debug(\"resolver: no MetaData (NodeState) on node object\")\n\t\temptyMeta := make(map[string]string, 0)\n\t\treturn emptyMeta, nil\n\t}\n}\n\n// HealthData is the resolver for the healthData field.\nfunc (r *nodeResolver) HealthData(ctx context.Context, obj *schema.Node) (any, error) {\n\tif obj.HealthData != nil {\n\t\treturn obj.HealthData, nil\n\t} else {\n\t\tcclog.Debug(\"resolver: no HealthData (NodeState) on node object\")\n\t\temptyHealth := make(map[string][]string, 0)\n\t\treturn emptyHealth, nil\n\t}\n}\n\n// Clusters is the resolver for the clusters field.\nfunc (r *queryResolver) Clusters(ctx context.Context) ([]*schema.Cluster, error) {\n\treturn archive.Clusters, nil\n}\n\n// Tags is the resolver for the tags field.\nfunc (r *queryResolver) Tags(ctx context.Context) ([]*schema.Tag, error) {\n\treturn r.Repo.GetTags(repository.GetUserFromContext(ctx), nil)\n}\n\n// GlobalMetrics is the resolver for the globalMetrics field.\nfunc (r *queryResolver) GlobalMetrics(ctx context.Context) ([]*schema.GlobalMetricListItem, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\n\tif user != nil {\n\t\tif user.HasRole(schema.RoleUser) || user.HasRole(schema.RoleManager) {\n\t\t\treturn archive.GlobalUserMetricList, nil\n\t\t}\n\t}\n\n\treturn archive.GlobalMetricList, nil\n}\n\n// User is the resolver for the user field.\nfunc (r *queryResolver) User(ctx context.Context, username string) (*model.User, error) {\n\treturn repository.GetUserRepository().FetchUserInCtx(ctx, username)\n}\n\n// AllocatedNodes is the resolver for the allocatedNodes field.\nfunc (r *queryResolver) AllocatedNodes(ctx context.Context, cluster string) ([]*model.Count, error) {\n\tdata, err := r.Repo.AllocatedNodes(cluster)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while fetching allocated nodes\")\n\t\treturn nil, err\n\t}\n\n\tcounts := make([]*model.Count, 0, len(data))\n\tfor subcluster, hosts := range data {\n\t\tcounts = append(counts, &model.Count{\n\t\t\tName: subcluster,\n\t\t\tCount: len(hosts),\n\t\t})\n\t}\n\n\treturn counts, nil\n}\n\n// Node is the resolver for the node field.\nfunc (r *queryResolver) Node(ctx context.Context, id string) (*schema.Node, error) {\n\trepo := repository.GetNodeRepository()\n\tnumericID, err := strconv.ParseInt(id, 10, 64)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while parsing job id\")\n\t\treturn nil, err\n\t}\n\treturn repo.GetNodeByID(numericID, false)\n}\n\n// Nodes is the resolver for the nodes field.\nfunc (r *queryResolver) Nodes(ctx context.Context, filter []*model.NodeFilter, order *model.OrderByInput) (*model.NodeStateResultList, error) {\n\trepo := repository.GetNodeRepository()\n\tnodes, err := repo.QueryNodes(ctx, filter, nil, order) // Ignore Paging, Order Unused\n\tcount := len(nodes)\n\treturn &model.NodeStateResultList{Items: nodes, Count: &count}, err\n}\n\n// NodesWithMeta is the resolver for the nodesWithMeta field.\nfunc (r *queryResolver) NodesWithMeta(ctx context.Context, filter []*model.NodeFilter, order *model.OrderByInput) (*model.NodeStateResultList, error) {\n\t// Why Extra Handler? -> graphql.CollectAllFields(ctx) only returns toplevel fields (i.e.: items, count), and not subfields like item.metaData\n\trepo := repository.GetNodeRepository()\n\tnodes, err := repo.QueryNodesWithMeta(ctx, filter, nil, order) // Ignore Paging, Order Unused\n\tcount := len(nodes)\n\treturn &model.NodeStateResultList{Items: nodes, Count: &count}, err\n}\n\n// NodeStates is the resolver for the nodeStates field.\nfunc (r *queryResolver) NodeStates(ctx context.Context, filter []*model.NodeFilter) ([]*model.NodeStates, error) {\n\trepo := repository.GetNodeRepository()\n\n\tstateCounts, serr := repo.CountStates(ctx, filter, \"node_state\")\n\tif serr != nil {\n\t\tcclog.Warnf(\"Error while counting nodeStates: %s\", serr.Error())\n\t\treturn nil, serr\n\t}\n\n\thealthCounts, herr := repo.CountStates(ctx, filter, \"health_state\")\n\tif herr != nil {\n\t\tcclog.Warnf(\"Error while counting healthStates: %s\", herr.Error())\n\t\treturn nil, herr\n\t}\n\n\tallCounts := append(stateCounts, healthCounts...)\n\n\treturn allCounts, nil\n}\n\n// NodeStatesTimed is the resolver for the nodeStatesTimed field.\nfunc (r *queryResolver) NodeStatesTimed(ctx context.Context, filter []*model.NodeFilter, typeArg string) ([]*model.NodeStatesTimed, error) {\n\trepo := repository.GetNodeRepository()\n\n\tif typeArg == \"node\" {\n\t\tstateCounts, serr := repo.CountStatesTimed(ctx, filter, \"node_state\")\n\t\tif serr != nil {\n\t\t\tcclog.Warnf(\"Error while counting nodeStates in time: %s\", serr.Error())\n\t\t\treturn nil, serr\n\t\t}\n\t\treturn stateCounts, nil\n\t}\n\n\tif typeArg == \"health\" {\n\t\thealthCounts, herr := repo.CountStatesTimed(ctx, filter, \"health_state\")\n\t\tif herr != nil {\n\t\t\tcclog.Warnf(\"Error while counting healthStates in time: %s\", herr.Error())\n\t\t\treturn nil, herr\n\t\t}\n\t\treturn healthCounts, nil\n\t}\n\n\treturn nil, errors.New(\"unknown Node State Query Type\")\n}\n\n// Job is the resolver for the job field.\nfunc (r *queryResolver) Job(ctx context.Context, id string) (*schema.Job, error) {\n\tnumericID, err := strconv.ParseInt(id, 10, 64)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while parsing job id\")\n\t\treturn nil, err\n\t}\n\n\tjob, err := r.Repo.FindByID(ctx, numericID)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while finding job by id\")\n\t\treturn nil, err\n\t}\n\n\tif user := repository.GetUserFromContext(ctx); user != nil &&\n\t\tjob.User != user.Username &&\n\t\tuser.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\treturn nil, errors.New(\"you are not allowed to see this job\")\n\t}\n\n\treturn job, nil\n}\n\n// JobMetrics is the resolver for the jobMetrics field.\nfunc (r *queryResolver) JobMetrics(ctx context.Context, id string, metrics []string, scopes []schema.MetricScope, resolution *int) ([]*model.JobMetricWithName, error) {\n\tif resolution == nil { // Load from Config\n\t\tif config.Keys.EnableResampling != nil {\n\t\t\tdefaultRes := slices.Max(config.Keys.EnableResampling.Resolutions)\n\t\t\tresolution = &defaultRes\n\t\t} else { // Set 0 (Loads configured metric timestep)\n\t\t\tdefaultRes := 0\n\t\t\tresolution = &defaultRes\n\t\t}\n\t}\n\n\tjob, err := r.Query().Job(ctx, id)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying job for metrics\")\n\t\treturn nil, err\n\t}\n\n\tdata, err := metricdispatch.LoadData(job, metrics, scopes, ctx, *resolution)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job data\")\n\t\treturn nil, err\n\t}\n\n\tres := []*model.JobMetricWithName{}\n\tfor name, md := range data {\n\t\tfor scope, metric := range md {\n\t\t\tres = append(res, &model.JobMetricWithName{\n\t\t\t\tName: name,\n\t\t\t\tScope: scope,\n\t\t\t\tMetric: metric,\n\t\t\t})\n\t\t}\n\t}\n\n\treturn res, err\n}\n\n// JobStats is the resolver for the jobStats field.\nfunc (r *queryResolver) JobStats(ctx context.Context, id string, metrics []string) ([]*model.NamedStats, error) {\n\tjob, err := r.Query().Job(ctx, id)\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while querying job %s for metadata\", id)\n\t\treturn nil, err\n\t}\n\n\tdata, err := metricdispatch.LoadJobStats(job, metrics, ctx)\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while loading jobStats data for job id %s\", id)\n\t\treturn nil, err\n\t}\n\n\tres := []*model.NamedStats{}\n\tfor name, md := range data {\n\t\tres = append(res, &model.NamedStats{\n\t\t\tName: name,\n\t\t\tData: &md,\n\t\t})\n\t}\n\n\treturn res, err\n}\n\n// ScopedJobStats is the resolver for the scopedJobStats field.\nfunc (r *queryResolver) ScopedJobStats(ctx context.Context, id string, metrics []string, scopes []schema.MetricScope) ([]*model.NamedStatsWithScope, error) {\n\tjob, err := r.Query().Job(ctx, id)\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while querying job %s for metadata\", id)\n\t\treturn nil, err\n\t}\n\n\tdata, err := metricdispatch.LoadScopedJobStats(job, metrics, scopes, ctx)\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while loading scopedJobStats data for job id %s\", id)\n\t\treturn nil, err\n\t}\n\n\tres := make([]*model.NamedStatsWithScope, 0)\n\tfor name, scoped := range data {\n\t\tfor scope, stats := range scoped {\n\n\t\t\tmdlStats := make([]*model.ScopedStats, 0)\n\t\t\tfor _, stat := range stats {\n\t\t\t\tmdlStats = append(mdlStats, &model.ScopedStats{\n\t\t\t\t\tHostname: stat.Hostname,\n\t\t\t\t\tID: stat.ID,\n\t\t\t\t\tData: stat.Data,\n\t\t\t\t})\n\t\t\t}\n\n\t\t\tres = append(res, &model.NamedStatsWithScope{\n\t\t\t\tName: name,\n\t\t\t\tScope: scope,\n\t\t\t\tStats: mdlStats,\n\t\t\t})\n\t\t}\n\t}\n\n\treturn res, nil\n}\n\n// Jobs is the resolver for the jobs field.\nfunc (r *queryResolver) Jobs(ctx context.Context, filter []*model.JobFilter, page *model.PageRequest, order *model.OrderByInput) (*model.JobResultList, error) {\n\tif page == nil {\n\t\tpage = &model.PageRequest{\n\t\t\tItemsPerPage: 50,\n\t\t\tPage: 1,\n\t\t}\n\t}\n\n\tjobs, err := r.Repo.QueryJobs(ctx, filter, page, order)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying jobs\")\n\t\treturn nil, err\n\t}\n\n\tcount, err := r.Repo.CountJobs(ctx, filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while counting jobs\")\n\t\treturn nil, err\n\t}\n\n\t// Note: Even if App-Default 'config.Keys.UiDefaults[\"job_list_usePaging\"]' is set, always return hasNextPage boolean.\n\t// Users can decide in frontend to use continuous scroll, even if app-default is paging!\n\t// Skip if page.ItemsPerPage == -1 (\"Load All\" -> No Next Page required, Status Dashboards)\n\t/*\n\t Example Page 4 @ 10 IpP : Does item 41 exist?\n\t Minimal Page 41 @ 1 IpP : If len(result) is 1, Page 5 @ 10 IpP exists.\n\t*/\n\thasNextPage := false\n\tif page.ItemsPerPage != -1 {\n\t\tnextPage := &model.PageRequest{\n\t\t\tItemsPerPage: 1,\n\t\t\tPage: ((page.Page * page.ItemsPerPage) + 1),\n\t\t}\n\t\tnextJobs, err := r.Repo.QueryJobs(ctx, filter, nextPage, order)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while querying next jobs\")\n\t\t\treturn nil, err\n\t\t}\n\t\thasNextPage = len(nextJobs) == 1\n\t}\n\n\treturn &model.JobResultList{Items: jobs, Count: &count, HasNextPage: &hasNextPage}, nil\n}\n\n// JobsStatistics is the resolver for the jobsStatistics field.\nfunc (r *queryResolver) JobsStatistics(ctx context.Context, filter []*model.JobFilter, metrics []string, page *model.PageRequest, sortBy *model.SortByAggregate, groupBy *model.Aggregate, numDurationBins *string, numMetricBins *int) ([]*model.JobsStatistics, error) {\n\tvar err error\n\tvar stats []*model.JobsStatistics\n\n\t// Top Level Defaults\n\tdefaultDurationBins := \"1h\"\n\tdefaultMetricBins := 10\n\n\t// Build requested fields map for selective column computation\n\tstatsFields := []string{\n\t\t\"totalJobs\", \"totalUsers\", \"totalWalltime\", \"totalNodes\", \"totalCores\",\n\t\t\"totalAccs\", \"totalNodeHours\", \"totalCoreHours\", \"totalAccHours\", \"runningJobs\", \"shortJobs\",\n\t}\n\treqFields := make(map[string]bool, len(statsFields))\n\tfetchedMainStats := false\n\tfor _, f := range statsFields {\n\t\tif requireField(ctx, f) {\n\t\t\treqFields[f] = true\n\t\t\tif f != \"runningJobs\" && f != \"shortJobs\" {\n\t\t\t\tfetchedMainStats = true\n\t\t\t}\n\t\t}\n\t}\n\n\tif fetchedMainStats {\n\t\tif groupBy == nil {\n\t\t\tstats, err = r.Repo.JobsStats(ctx, filter, reqFields)\n\t\t} else {\n\t\t\tstartGrouped := time.Now()\n\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n\t\t\t// but different sortBy/page hit the DB only once.\n\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n\t\t\t\tkey := statsCacheKey(filter, groupBy)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)\n\t\t\t\t})\n\t\t\t\tif err == nil {\n\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n\t\t\t}\n\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n\t\t}\n\t} else {\n\t\tstats = make([]*model.JobsStatistics, 0, 1)\n\t\tstats = append(stats, &model.JobsStatistics{})\n\t}\n\n\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n\t// Only run separate count queries if main stats were not fetched.\n\tif !fetchedMainStats {\n\t\tif groupBy != nil {\n\t\t\tif requireField(ctx, \"shortJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n\t\t\t}\n\t\t\tif requireField(ctx, \"runningJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n\t\t\t}\n\t\t} else {\n\t\t\tif requireField(ctx, \"shortJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n\t\t\t}\n\t\t\tif requireField(ctx, \"runningJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n\t\t\t}\n\t\t}\n\t}\n\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif requireField(ctx, \"histDuration\") || requireField(ctx, \"histNumNodes\") || requireField(ctx, \"histNumCores\") || requireField(ctx, \"histNumAccs\") {\n\n\t\tif numDurationBins == nil {\n\t\t\tnumDurationBins = &defaultDurationBins\n\t\t}\n\n\t\tif groupBy == nil {\n\t\t\tstats[0], err = r.Repo.AddHistograms(ctx, filter, stats[0], numDurationBins)\n\t\t\tif err != nil {\n\t\t\t\treturn nil, err\n\t\t\t}\n\t\t} else {\n\t\t\treturn nil, errors.New(\"histograms only implemented without groupBy argument\")\n\t\t}\n\t}\n\n\tif requireField(ctx, \"histMetrics\") {\n\n\t\tif numMetricBins == nil {\n\t\t\tnumMetricBins = &defaultMetricBins\n\t\t}\n\n\t\tif groupBy == nil {\n\t\t\tstats[0], err = r.Repo.AddMetricHistograms(ctx, filter, metrics, stats[0], numMetricBins)\n\t\t\tif err != nil {\n\t\t\t\treturn nil, err\n\t\t\t}\n\t\t} else {\n\t\t\treturn nil, errors.New(\"metric histograms only implemented without groupBy argument\")\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// JobsMetricStats is the resolver for the jobsMetricStats field.\nfunc (r *queryResolver) JobsMetricStats(ctx context.Context, filter []*model.JobFilter, metrics []string) ([]*model.JobStats, error) {\n\t// No Paging, Fixed Order by StartTime ASC\n\torder := &model.OrderByInput{\n\t\tField: \"startTime\",\n\t\tType: \"col\",\n\t\tOrder: \"ASC\",\n\t}\n\n\tjobs, err := r.Repo.QueryJobs(ctx, filter, nil, order)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying jobs for comparison\")\n\t\treturn nil, err\n\t}\n\n\tres := []*model.JobStats{}\n\tfor _, job := range jobs {\n\t\tdata, err := metricdispatch.LoadJobStats(job, metrics, ctx)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while loading comparison jobStats data for job id %d\", job.JobID)\n\t\t\tcontinue\n\t\t\t// return nil, err\n\t\t}\n\n\t\tsres := []*model.NamedStats{}\n\t\tfor name, md := range data {\n\t\t\tsres = append(sres, &model.NamedStats{\n\t\t\t\tName: name,\n\t\t\t\tData: &md,\n\t\t\t})\n\t\t}\n\n\t\tnumThreadsInt := int(job.NumHWThreads)\n\t\tnumAccsInt := int(job.NumAcc)\n\t\tres = append(res, &model.JobStats{\n\t\t\tID: int(*job.ID),\n\t\t\tJobID: strconv.Itoa(int(job.JobID)),\n\t\t\tStartTime: int(job.StartTime),\n\t\t\tDuration: int(job.Duration),\n\t\t\tCluster: job.Cluster,\n\t\t\tSubCluster: job.SubCluster,\n\t\t\tNumNodes: int(job.NumNodes),\n\t\t\tNumHWThreads: &numThreadsInt,\n\t\t\tNumAccelerators: &numAccsInt,\n\t\t\tStats: sres,\n\t\t})\n\t}\n\treturn res, err\n}\n\n// JobsFootprints is the resolver for the jobsFootprints field.\nfunc (r *queryResolver) JobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n\t// NOTE: Legacy Naming! This resolver is for normalized histograms in analysis view only - *Not* related to DB \"footprint\" column!\n\treturn r.jobsFootprints(ctx, filter, metrics)\n}\n\n// RooflineHeatmap is the resolver for the rooflineHeatmap field.\nfunc (r *queryResolver) RooflineHeatmap(ctx context.Context, filter []*model.JobFilter, rows int, cols int, minX float64, minY float64, maxX float64, maxY float64) ([][]float64, error) {\n\treturn r.rooflineHeatmap(ctx, filter, rows, cols, minX, minY, maxX, maxY)\n}\n\n// NodeMetrics is the resolver for the nodeMetrics field.\nfunc (r *queryResolver) NodeMetrics(ctx context.Context, cluster string, nodes []string, scopes []schema.MetricScope, metrics []string, from time.Time, to time.Time) ([]*model.NodeMetrics, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n\t}\n\n\tdefaultMetrics := make([]string, 0)\n\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n\t\tdefaultMetrics = append(defaultMetrics, mc.Name)\n\t}\n\tif metrics == nil {\n\t\tmetrics = defaultMetrics\n\t} else {\n\t\tmetrics = slices.DeleteFunc(metrics, func(metric string) bool {\n\t\t\treturn !slices.Contains(defaultMetrics, metric) // Remove undefined metrics.\n\t\t})\n\t}\n\n\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nodes, scopes, from, to, ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"error while loading node data\")\n\t\treturn nil, err\n\t}\n\n\tnodeRepo := repository.GetNodeRepository()\n\tstateMap, _ := nodeRepo.MapNodes(cluster)\n\n\tnodeMetrics := make([]*model.NodeMetrics, 0, len(data))\n\tfor hostname, metrics := range data {\n\t\thost := &model.NodeMetrics{\n\t\t\tHost: hostname,\n\t\t\tState: stateMap[hostname],\n\t\t\tMetrics: make([]*model.JobMetricWithName, 0, len(metrics)*len(scopes)),\n\t\t}\n\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n\t\t}\n\n\t\tfor metric, scopedMetrics := range metrics {\n\t\t\tfor _, scopedMetric := range scopedMetrics {\n\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n\t\t\t\t\tName: metric,\n\t\t\t\t\tScope: schema.MetricScopeNode,\n\t\t\t\t\tMetric: scopedMetric,\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\n\t\tnodeMetrics = append(nodeMetrics, host)\n\t}\n\n\treturn nodeMetrics, nil\n}\n\n// NodeMetricsList is the resolver for the nodeMetricsList field.\nfunc (r *queryResolver) NodeMetricsList(ctx context.Context, cluster string, subCluster string, stateFilter string, nodeFilter string, scopes []schema.MetricScope, metrics []string, from time.Time, to time.Time, page *model.PageRequest, resolution *int) (*model.NodesResultList, error) {\n\tif resolution == nil { // Load from Config\n\t\tif config.Keys.EnableResampling != nil {\n\t\t\tdefaultRes := slices.Max(config.Keys.EnableResampling.Resolutions)\n\t\t\tresolution = &defaultRes\n\t\t} else { // Set 0 (Loads configured metric timestep)\n\t\t\tdefaultRes := 0\n\t\t\tresolution = &defaultRes\n\t\t}\n\t}\n\n\tuser := repository.GetUserFromContext(ctx)\n\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n\t}\n\n\tnodeRepo := repository.GetNodeRepository()\n\t// nodes -> array hostname\n\tnodes, stateMap, countNodes, hasNextPage, nerr := nodeRepo.GetNodesForList(ctx, cluster, subCluster, stateFilter, nodeFilter, page)\n\tif nerr != nil {\n\t\treturn nil, errors.New(\"could not retrieve node list required for resolving NodeMetricsList\")\n\t}\n\n\tif metrics == nil {\n\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n\t\t\tmetrics = append(metrics, mc.Name)\n\t\t}\n\t}\n\n\t// data -> map hostname:jobdata\n\tdata, err := metricdispatch.LoadNodeListData(cluster, subCluster, nodes, metrics, scopes, *resolution, from, to, ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"error while loading node data (Resolver.NodeMetricsList\")\n\t\treturn nil, err\n\t}\n\n\tnodeMetricsList := make([]*model.NodeMetrics, 0, len(data))\n\tfor _, hostname := range nodes {\n\t\thost := &model.NodeMetrics{\n\t\t\tHost: hostname,\n\t\t\tState: stateMap[hostname],\n\t\t\tMetrics: make([]*model.JobMetricWithName, 0),\n\t\t}\n\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n\t\t}\n\n\t\tfor metric, scopedMetrics := range data[hostname] {\n\t\t\tfor scope, scopedMetric := range scopedMetrics {\n\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n\t\t\t\t\tName: metric,\n\t\t\t\t\tScope: scope,\n\t\t\t\t\tMetric: scopedMetric,\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\n\t\tnodeMetricsList = append(nodeMetricsList, host)\n\t}\n\n\tnodeMetricsListResult := &model.NodesResultList{\n\t\tItems: nodeMetricsList,\n\t\t// TotalNodes depends on sum of nodes grouped on latest timestamp, see repo/node.go:357\n\t\tTotalNodes: &countNodes,\n\t\tHasNextPage: &hasNextPage,\n\t}\n\n\treturn nodeMetricsListResult, nil\n}\n\n// ClusterMetrics is the resolver for the clusterMetrics field.\nfunc (r *queryResolver) ClusterMetrics(ctx context.Context, cluster string, metrics []string, from time.Time, to time.Time) (*model.ClusterMetrics, error) {\n\tuser := repository.GetUserFromContext(ctx)\n\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n\t}\n\n\tif metrics == nil {\n\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n\t\t\tmetrics = append(metrics, mc.Name)\n\t\t}\n\t}\n\n\t// 'nodes' == nil -> Defaults to all nodes of cluster for existing query workflow\n\tscopes := []schema.MetricScope{\"node\"}\n\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nil, scopes, from, to, ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"error while loading node data\")\n\t\treturn nil, err\n\t}\n\n\tclusterMetricData := make([]*model.ClusterMetricWithName, 0)\n\tclusterMetrics := model.ClusterMetrics{NodeCount: 0, Metrics: clusterMetricData}\n\n\tcollectorTimestep := make(map[string]int)\n\tcollectorUnit := make(map[string]schema.Unit)\n\tcollectorData := make(map[string][]schema.Float)\n\n\tfor _, metrics := range data {\n\t\tclusterMetrics.NodeCount += 1\n\t\tfor metric, scopedMetrics := range metrics {\n\t\t\tfor _, scopedMetric := range scopedMetrics {\n\t\t\t\t// Collect Info Once\n\t\t\t\t_, okTimestep := collectorTimestep[metric]\n\t\t\t\tif !okTimestep {\n\t\t\t\t\tcollectorTimestep[metric] = scopedMetric.Timestep\n\t\t\t\t}\n\t\t\t\t_, okUnit := collectorUnit[metric]\n\t\t\t\tif !okUnit {\n\t\t\t\t\tcollectorUnit[metric] = scopedMetric.Unit\n\t\t\t\t}\n\t\t\t\t// Collect Data\n\t\t\t\tfor _, ser := range scopedMetric.Series {\n\t\t\t\t\t_, okData := collectorData[metric]\n\t\t\t\t\t// Init With Datasize > 0\n\t\t\t\t\tif !okData && len(ser.Data) != 0 {\n\t\t\t\t\t\tcollectorData[metric] = make([]schema.Float, len(ser.Data))\n\t\t\t\t\t} else if !okData {\n\t\t\t\t\t\tcclog.Debugf(\"[SCHEMARESOLVER] clusterMetrics skip init: no data -> %s at %s; size %d\", metric, ser.Hostname, len(ser.Data))\n\t\t\t\t\t}\n\t\t\t\t\t// Sum if init'd and matching size\n\t\t\t\t\tif okData && len(ser.Data) == len(collectorData[metric]) {\n\t\t\t\t\t\tfor i, val := range ser.Data {\n\t\t\t\t\t\t\tif val.IsNaN() {\n\t\t\t\t\t\t\t\tcontinue\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\tcollectorData[metric][i] += val\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t} else if okData {\n\t\t\t\t\t\tcclog.Debugf(\"[SCHEMARESOLVER] clusterMetrics skip sum: data diff -> %s at %s; want size %d, have size %d\", metric, ser.Hostname, len(collectorData[metric]), len(ser.Data))\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\tfor metricName, data := range collectorData {\n\t\t// use ccUnits for backend normalization to \"Tera\"\n\t\tp_old := ccunit.NewPrefix(collectorUnit[metricName].Prefix)\n\t\tp_new := ccunit.NewPrefix(\"T\")\n\t\tconvFunc := ccunit.GetPrefixPrefixFactor(p_old, p_new)\n\t\tu_new := schema.Unit{Prefix: p_new.Prefix(), Base: collectorUnit[metricName].Base}\n\n\t\troundedData := make([]schema.Float, 0)\n\t\tfor _, v_old := range data {\n\t\t\tv_new := math.Round(convFunc(float64(v_old)).(float64)*100.0) / 100.0\n\t\t\troundedData = append(roundedData, schema.Float(v_new))\n\t\t}\n\n\t\tcm := model.ClusterMetricWithName{\n\t\t\tName: metricName,\n\t\t\tUnit: &u_new,\n\t\t\tTimestep: collectorTimestep[metricName],\n\t\t\tData: roundedData,\n\t\t}\n\n\t\tclusterMetrics.Metrics = append(clusterMetrics.Metrics, &cm)\n\t}\n\n\treturn &clusterMetrics, nil\n}\n\n// NumberOfNodes is the resolver for the numberOfNodes field.\nfunc (r *subClusterResolver) NumberOfNodes(ctx context.Context, obj *schema.SubCluster) (int, error) {\n\tnodeList, err := archive.ParseNodeList(obj.Nodes)\n\tif err != nil {\n\t\treturn 0, err\n\t}\n\treturn nodeList.NodeCount(), nil\n}\n\n// Cluster returns generated.ClusterResolver implementation.\nfunc (r *Resolver) Cluster() generated.ClusterResolver { return &clusterResolver{r} }\n\n// Job returns generated.JobResolver implementation.\nfunc (r *Resolver) Job() generated.JobResolver { return &jobResolver{r} }\n\n// MetricValue returns generated.MetricValueResolver implementation.\nfunc (r *Resolver) MetricValue() generated.MetricValueResolver { return &metricValueResolver{r} }\n\n// Mutation returns generated.MutationResolver implementation.\nfunc (r *Resolver) Mutation() generated.MutationResolver { return &mutationResolver{r} }\n\n// Node returns generated.NodeResolver implementation.\nfunc (r *Resolver) Node() generated.NodeResolver { return &nodeResolver{r} }\n\n// Query returns generated.QueryResolver implementation.\nfunc (r *Resolver) Query() generated.QueryResolver { return &queryResolver{r} }\n\n// SubCluster returns generated.SubClusterResolver implementation.\nfunc (r *Resolver) SubCluster() generated.SubClusterResolver { return &subClusterResolver{r} }\n\ntype clusterResolver struct{ *Resolver }\ntype jobResolver struct{ *Resolver }\ntype metricValueResolver struct{ *Resolver }\ntype mutationResolver struct{ *Resolver }\ntype nodeResolver struct{ *Resolver }\ntype queryResolver struct{ *Resolver }\ntype subClusterResolver struct{ *Resolver }\n","structuredPatch":[{"oldStart":676,"oldLines":10,"newStart":676,"newLines":10,"lines":[" // Use request-scoped cache: multiple aliases with same (filter, groupBy)"," // but different sortBy/page hit the DB only once."," if cache := getStatsGroupCache(ctx); cache != nil {","- key := statsCacheKey(filter, groupBy)","+ key := statsCacheKey(filter, groupBy, reqFields)"," var allStats []*model.JobsStatistics"," allStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {","- return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)","+ return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)"," })"," if err == nil {"," stats = sortAndPageStats(allStats, sortBy, page)"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"34428c1b-a455-45e5-b389-32f4e44de37d","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"96c57c31-74df-4ab3-af2d-58847abf6e2f","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01NUxnZFZEWH5gAbgnpuTXLj","type":"message","role":"assistant","content":[{"type":"text","text":"There's another call site. Let me find it:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":469,"cache_read_input_tokens":23851,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":469},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF4SXxgHSxmnWmySkFY","type":"assistant","uuid":"de9576cc-676d-4225-af66-cd3c24111cb3","timestamp":"2026-03-19T09:59:38.922Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"de9576cc-676d-4225-af66-cd3c24111cb3","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01NUxnZFZEWH5gAbgnpuTXLj","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Ug4TTHQ63o1BjuuM1yt6ss","name":"Grep","input":{"pattern":"statsCacheKey","path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","output_mode":"content"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":469,"cache_read_input_tokens":23851,"output_tokens":130,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":469,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCF4SXxgHSxmnWmySkFY","type":"assistant","uuid":"cb322ae0-9cc7-415f-9bc0-619f951a7216","timestamp":"2026-03-19T09:59:39.455Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"cb322ae0-9cc7-415f-9bc0-619f951a7216","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Grep","command":"callback"},"parentToolUseID":"toolu_01Ug4TTHQ63o1BjuuM1yt6ss","toolUseID":"toolu_01Ug4TTHQ63o1BjuuM1yt6ss","timestamp":"2026-03-19T09:59:39.504Z","uuid":"ecc46803-a84f-4703-be8e-a719e86c9d74","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"cb322ae0-9cc7-415f-9bc0-619f951a7216","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Ug4TTHQ63o1BjuuM1yt6ss","type":"tool_result","content":"679:\t\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)"}]},"uuid":"bd09ceda-835e-4269-9496-6d68e368e695","timestamp":"2026-03-19T09:59:39.504Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"679:\t\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)","numLines":1},"sourceToolAssistantUUID":"cb322ae0-9cc7-415f-9bc0-619f951a7216","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"bd09ceda-835e-4269-9496-6d68e368e695","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Q6SqFa2j9b5Ci1z2Rs9Lm","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"EuMCCkYICxgCKkCUy23qXUI8uZuo0jLD6Fj5mRgM12V54cm3hwRvQ3HwTKy0xEWFMqbDmFZjhsAmR9s/pnKYIdh6CTGo4vohl/vvEgxg2a7YiG4U3zsU5ckaDCb4BDRyhJWYRuEgTyIwudOVY1snvJUWKRnxRYaU29we53ZdoBXV6g1nx1jazTqiVbm6Ljta7ke8yDzYf+pXKsoBiPf1Adgr7toNhuXU5v2GY2V2x7ne3ShvHPCfra4dBRRLsvhgmFh/9DH+zLHZxqoYM223H/6vuThlm9VgiVJxkXrYuGT4QZ7voklZiyvz025zgad/TOakndK5qEM4eWUL7VFq1N6pV9OKO3P2B3BjVRilp+KzlPD5LJMpb3GkBJEKiYKVEXZ7/u0QQ5Sp6V1fl1dRcFmTSKvRDq9lcct83WpPmwxOD1eVK0LS5rAMt9HSYx1KZpaasvrCYiBBQ3cFpuNXOES70/gygRgB"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":225,"cache_read_input_tokens":24320,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":225},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF4s2cQbpaXCnWYUhMc","type":"assistant","uuid":"0f5141f3-cda3-4a45-b0b6-5ab78208ced7","timestamp":"2026-03-19T09:59:44.837Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"0f5141f3-cda3-4a45-b0b6-5ab78208ced7","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Q6SqFa2j9b5Ci1z2Rs9Lm","type":"message","role":"assistant","content":[{"type":"text","text":"The diagnostic seems stale — there's only one call site and it already has the new signature. Let me verify the build:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":225,"cache_read_input_tokens":24320,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":225},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF4s2cQbpaXCnWYUhMc","type":"assistant","uuid":"edccfd90-b4f2-4ad8-bdc8-b965ea69afc6","timestamp":"2026-03-19T09:59:45.751Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"edccfd90-b4f2-4ad8-bdc8-b965ea69afc6","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Q6SqFa2j9b5Ci1z2Rs9Lm","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_019uqsDjxmzoBnCiDFDpxXct","name":"Bash","input":{"command":"go build ./... 2>&1","description":"Build to verify changes compile"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":225,"cache_read_input_tokens":24320,"output_tokens":184,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":225,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCF4s2cQbpaXCnWYUhMc","type":"assistant","uuid":"e9cfdf56-3494-4621-8220-2d91e1b2b0bc","timestamp":"2026-03-19T09:59:46.244Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"e9cfdf56-3494-4621-8220-2d91e1b2b0bc","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019uqsDjxmzoBnCiDFDpxXct","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"uuid":"73072921-6881-48c7-a444-70a3dd84d712","timestamp":"2026-03-19T09:59:52.813Z","toolUseResult":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"e9cfdf56-3494-4621-8220-2d91e1b2b0bc","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"73072921-6881-48c7-a444-70a3dd84d712","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01JB5TCLbRk8UMbE9MeZjeoq","type":"message","role":"assistant","content":[{"type":"text","text":"Clean build. Let me run the relevant tests:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":183,"cache_read_input_tokens":24545,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":183},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCF5qvuW5RUbh8YzmEDM","type":"assistant","uuid":"be1afdfb-1862-40a1-b06d-11af72e8065d","timestamp":"2026-03-19T09:59:57.144Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"be1afdfb-1862-40a1-b06d-11af72e8065d","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01JB5TCLbRk8UMbE9MeZjeoq","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01TqzJumCwUNtLyKRS1EiRCx","name":"Bash","input":{"command":"go test ./internal/repository/... ./internal/graph/... 2>&1","description":"Run repository and graph tests"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":183,"cache_read_input_tokens":24545,"output_tokens":101,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":183,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCF5qvuW5RUbh8YzmEDM","type":"assistant","uuid":"ebe8900a-adb1-460a-a92c-78b75095b28e","timestamp":"2026-03-19T09:59:57.842Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"ebe8900a-adb1-460a-a92c-78b75095b28e","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TqzJumCwUNtLyKRS1EiRCx","type":"tool_result","content":"ok \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.956s\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph\t[no test files]\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph/generated\t[no test files]\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph/model\t[no test files]","is_error":false}]},"uuid":"eeeadc7b-2959-4cb0-a162-077f45d00523","timestamp":"2026-03-19T10:00:00.124Z","toolUseResult":{"stdout":"ok \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.956s\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph\t[no test files]\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph/generated\t[no test files]\n? \tgithub.com/ClusterCockpit/cc-backend/internal/graph/model\t[no test files]","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"ebe8900a-adb1-460a-a92c-78b75095b28e","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"eeeadc7b-2959-4cb0-a162-077f45d00523","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01CxDhFv5eFy3G1EYufM4fas","type":"message","role":"assistant","content":[{"type":"text","text":"All tests pass. The two changes made:\n\n1. **`stats_cache.go`**: `statsCacheKey` now accepts `reqFields map[string]bool` and includes it in the cache key, so requests with different field sets are cached separately.\n\n2. **`schema.resolvers.go`**: The cache path now passes `reqFields` (instead of `nil`) to `JobsStatsGrouped`, so `COUNT(DISTINCT hpc_user)` is only computed when the frontend actually requests `totalUsers`.\n\n**Effect**: The `/monitoring/projects/` page (which doesn't request `totalUsers`) will no longer trigger the expensive `COUNT(DISTINCT hpc_user)` per-project query. The `/monitoring/status/` page that does request `totalUsers` for subcluster grouping is unaffected."}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":333,"cache_read_input_tokens":24728,"output_tokens":189,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":333,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCF6PBbvZUKwApp7NqHu","type":"assistant","uuid":"0f403fed-554b-44c8-b344-c8fbd1f27717","timestamp":"2026-03-19T10:00:09.372Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"0f403fed-554b-44c8-b344-c8fbd1f27717","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"Stop","hookName":"Stop","command":"entire hooks claude-code stop"},"parentToolUseID":"8f1ebbcb-fd26-496c-a551-45ed5a7e7554","toolUseID":"8f1ebbcb-fd26-496c-a551-45ed5a7e7554","timestamp":"2026-03-19T10:00:09.416Z","uuid":"b2648cbc-d3a7-4505-be0e-ae611f961131","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"b2648cbc-d3a7-4505-be0e-ae611f961131","isSidechain":false,"type":"system","subtype":"stop_hook_summary","hookCount":1,"hookInfos":[{"command":"entire hooks claude-code stop","durationMs":501}],"hookErrors":[],"preventedContinuation":false,"stopReason":"","hasOutput":false,"level":"suggestion","timestamp":"2026-03-19T10:00:09.918Z","uuid":"cb96f557-7805-432f-9cf6-7881bd11dfff","toolUseID":"8f1ebbcb-fd26-496c-a551-45ed5a7e7554","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"cb96f557-7805-432f-9cf6-7881bd11dfff","isSidechain":false,"type":"system","subtype":"turn_duration","durationMs":57823,"timestamp":"2026-03-19T10:00:09.919Z","uuid":"dbe03f79-66db-4eaa-9294-1e5462238d70","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"type":"file-history-snapshot","messageId":"b9574428-39fc-475b-8e4c-9423f2e02bbb","snapshot":{"messageId":"b9574428-39fc-475b-8e4c-9423f2e02bbb","trackedFileBackups":{"internal/graph/stats_cache.go":{"backupFileName":"192476250d06317a@v2","version":2,"backupTime":"2026-03-19T10:05:43.697Z"},"internal/graph/schema.resolvers.go":{"backupFileName":"117e2419c7a90363@v2","version":2,"backupTime":"2026-03-19T10:05:43.697Z"}},"timestamp":"2026-03-19T10:05:43.696Z"},"isSnapshotUpdate":false} +{"parentUuid":"dbe03f79-66db-4eaa-9294-1e5462238d70","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":"Caveat: The messages below were generated by the user while running local commands. DO NOT respond to these messages or otherwise consider them in your response unless the user explicitly asks you to."},"isMeta":true,"uuid":"0f3b450b-2c0a-42c7-b6ad-7e7c5dfeb5e6","timestamp":"2026-03-19T10:05:43.696Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"0f3b450b-2c0a-42c7-b6ad-7e7c5dfeb5e6","isSidechain":false,"promptId":"4fcd0306-e2ee-4526-a0bf-c87699d19405","type":"user","message":{"role":"user","content":"/model\n model\n "},"uuid":"b9574428-39fc-475b-8e4c-9423f2e02bbb","timestamp":"2026-03-19T10:05:43.695Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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623→\t// Users can decide in frontend to use continuous scroll, even if app-default is paging!\n 624→\t// Skip if page.ItemsPerPage == -1 (\"Load All\" -> No Next Page required, Status Dashboards)\n 625→\t/*\n 626→\t Example Page 4 @ 10 IpP : Does item 41 exist?\n 627→\t Minimal Page 41 @ 1 IpP : If len(result) is 1, Page 5 @ 10 IpP exists.\n 628→\t*/\n 629→\thasNextPage := false\n 630→\tif page.ItemsPerPage != -1 {\n 631→\t\tnextPage := &model.PageRequest{\n 632→\t\t\tItemsPerPage: 1,\n 633→\t\t\tPage: ((page.Page * page.ItemsPerPage) + 1),\n 634→\t\t}\n 635→\t\tnextJobs, err := r.Repo.QueryJobs(ctx, filter, nextPage, order)\n 636→\t\tif err != nil {\n 637→\t\t\tcclog.Warn(\"Error while querying next jobs\")\n 638→\t\t\treturn nil, err\n 639→\t\t}\n 640→\t\thasNextPage = len(nextJobs) == 1\n 641→\t}\n 642→\n 643→\treturn &model.JobResultList{Items: jobs, Count: &count, HasNextPage: &hasNextPage}, nil\n 644→}\n 645→\n 646→// JobsStatistics is the resolver for the jobsStatistics field.\n 647→func (r *queryResolver) JobsStatistics(ctx context.Context, filter []*model.JobFilter, metrics []string, page *model.PageRequest, sortBy *model.SortByAggregate, groupBy *model.Aggregate, numDurationBins *string, numMetricBins *int) ([]*model.JobsStatistics, error) {\n 648→\tvar err error\n 649→\tvar stats []*model.JobsStatistics\n 650→\n 651→\t// Top Level Defaults\n 652→\tdefaultDurationBins := \"1h\"\n 653→\tdefaultMetricBins := 10\n 654→\n 655→\t// Build requested fields map for selective column computation\n 656→\tstatsFields := []string{\n 657→\t\t\"totalJobs\", \"totalUsers\", \"totalWalltime\", \"totalNodes\", \"totalCores\",\n 658→\t\t\"totalAccs\", \"totalNodeHours\", \"totalCoreHours\", \"totalAccHours\", \"runningJobs\", \"shortJobs\",\n 659→\t}\n 660→\treqFields := make(map[string]bool, len(statsFields))\n 661→\tfetchedMainStats := false\n 662→\tfor _, f := range statsFields {\n 663→\t\tif requireField(ctx, f) {\n 664→\t\t\treqFields[f] = true\n 665→\t\t\tif f != \"runningJobs\" && f != \"shortJobs\" {\n 666→\t\t\t\tfetchedMainStats = true\n 667→\t\t\t}\n 668→\t\t}\n 669→\t}\n 670→\n 671→\tif fetchedMainStats {\n 672→\t\tif groupBy == nil {\n 673→\t\t\tstats, err = r.Repo.JobsStats(ctx, filter, reqFields)\n 674→\t\t} else {\n 675→\t\t\tstartGrouped := time.Now()\n 676→\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n 677→\t\t\t// but different sortBy/page hit the DB only once.\n 678→\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n 679→\t\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)\n 680→\t\t\t\tvar allStats []*model.JobsStatistics\n 681→\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n 682→\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n 683→\t\t\t\t})\n 684→\t\t\t\tif err == nil {\n 685→\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n 686→\t\t\t\t}\n 687→\t\t\t} else {\n 688→\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n 689→\t\t\t}\n 690→\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n 691→\t\t}\n 692→\t} else {\n 693→\t\tstats = make([]*model.JobsStatistics, 0, 1)\n 694→\t\tstats = append(stats, &model.JobsStatistics{})\n 695→\t}\n 696→\n 697→\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n 698→\t// Only run separate count queries if main stats were not fetched.\n 699→\tif !fetchedMainStats {\n 700→\t\tif groupBy != nil {\n 701→\t\t\tif requireField(ctx, \"shortJobs\") {\n 702→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n 703→\t\t\t}\n 704→\t\t\tif requireField(ctx, \"runningJobs\") {\n 705→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n 706→\t\t\t}\n 707→\t\t} else {\n 708→\t\t\tif requireField(ctx, \"shortJobs\") {\n 709→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n 710→\t\t\t}\n 711→\t\t\tif requireField(ctx, \"runningJobs\") {\n 712→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n 713→\t\t\t}\n 714→\t\t}\n 715→\t}\n 716→\n 717→\tif err != nil {\n 718→\t\treturn nil, err\n 719→\t}\n 720→\n 721→\tif requireField(ctx, \"histDuration\") || requireField(ctx, \"histNumNodes\") || requireField(ctx, \"histNumCores\") || requireField(ctx, \"histNumAccs\") {\n 722→\n 723→\t\tif numDurationBins == nil {\n 724→\t\t\tnumDurationBins = &defaultDurationBins\n 725→\t\t}\n 726→\n 727→\t\tif groupBy == nil {\n 728→\t\t\tstats[0], err = r.Repo.AddHistograms(ctx, filter, stats[0], numDurationBins)\n 729→\t\t\tif err != nil {\n 730→\t\t\t\treturn nil, err\n 731→\t\t\t}\n 732→\t\t} else {\n 733→\t\t\treturn nil, errors.New(\"histograms only implemented without groupBy argument\")\n 734→\t\t}\n 735→\t}\n 736→\n 737→\tif requireField(ctx, \"histMetrics\") {\n 738→\n 739→\t\tif numMetricBins == nil {"}]},"uuid":"1a045482-3cd5-41ef-90b6-2979faff1572","timestamp":"2026-03-19T10:06:21.766Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","content":"\t}\n\n\t// Note: Even if App-Default 'config.Keys.UiDefaults[\"job_list_usePaging\"]' is set, always return hasNextPage boolean.\n\t// Users can decide in frontend to use continuous scroll, even if app-default is paging!\n\t// Skip if page.ItemsPerPage == -1 (\"Load All\" -> No Next Page required, Status Dashboards)\n\t/*\n\t Example Page 4 @ 10 IpP : Does item 41 exist?\n\t Minimal Page 41 @ 1 IpP : If len(result) is 1, Page 5 @ 10 IpP exists.\n\t*/\n\thasNextPage := false\n\tif page.ItemsPerPage != -1 {\n\t\tnextPage := &model.PageRequest{\n\t\t\tItemsPerPage: 1,\n\t\t\tPage: ((page.Page * page.ItemsPerPage) + 1),\n\t\t}\n\t\tnextJobs, err := r.Repo.QueryJobs(ctx, filter, nextPage, order)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while querying next jobs\")\n\t\t\treturn nil, err\n\t\t}\n\t\thasNextPage = len(nextJobs) == 1\n\t}\n\n\treturn &model.JobResultList{Items: jobs, Count: &count, HasNextPage: &hasNextPage}, nil\n}\n\n// JobsStatistics is the resolver for the jobsStatistics field.\nfunc (r *queryResolver) JobsStatistics(ctx context.Context, filter []*model.JobFilter, metrics []string, page *model.PageRequest, sortBy *model.SortByAggregate, groupBy *model.Aggregate, numDurationBins *string, numMetricBins *int) ([]*model.JobsStatistics, error) {\n\tvar err error\n\tvar stats []*model.JobsStatistics\n\n\t// Top Level Defaults\n\tdefaultDurationBins := \"1h\"\n\tdefaultMetricBins := 10\n\n\t// Build requested fields map for selective column computation\n\tstatsFields := []string{\n\t\t\"totalJobs\", \"totalUsers\", \"totalWalltime\", \"totalNodes\", \"totalCores\",\n\t\t\"totalAccs\", \"totalNodeHours\", \"totalCoreHours\", \"totalAccHours\", \"runningJobs\", \"shortJobs\",\n\t}\n\treqFields := make(map[string]bool, len(statsFields))\n\tfetchedMainStats := false\n\tfor _, f := range statsFields {\n\t\tif requireField(ctx, f) {\n\t\t\treqFields[f] = true\n\t\t\tif f != \"runningJobs\" && f != \"shortJobs\" {\n\t\t\t\tfetchedMainStats = true\n\t\t\t}\n\t\t}\n\t}\n\n\tif fetchedMainStats {\n\t\tif groupBy == nil {\n\t\t\tstats, err = r.Repo.JobsStats(ctx, filter, reqFields)\n\t\t} else {\n\t\t\tstartGrouped := time.Now()\n\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n\t\t\t// but different sortBy/page hit the DB only once.\n\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n\t\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)\n\t\t\t\tvar allStats []*model.JobsStatistics\n\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n\t\t\t\t})\n\t\t\t\tif err == nil {\n\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n\t\t\t}\n\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n\t\t}\n\t} else {\n\t\tstats = make([]*model.JobsStatistics, 0, 1)\n\t\tstats = append(stats, &model.JobsStatistics{})\n\t}\n\n\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n\t// Only run separate count queries if main stats were not fetched.\n\tif !fetchedMainStats {\n\t\tif groupBy != nil {\n\t\t\tif requireField(ctx, \"shortJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n\t\t\t}\n\t\t\tif requireField(ctx, \"runningJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n\t\t\t}\n\t\t} else {\n\t\t\tif requireField(ctx, \"shortJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n\t\t\t}\n\t\t\tif requireField(ctx, \"runningJobs\") {\n\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n\t\t\t}\n\t\t}\n\t}\n\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif requireField(ctx, \"histDuration\") || requireField(ctx, \"histNumNodes\") || requireField(ctx, \"histNumCores\") || requireField(ctx, \"histNumAccs\") {\n\n\t\tif numDurationBins == nil {\n\t\t\tnumDurationBins = &defaultDurationBins\n\t\t}\n\n\t\tif groupBy == nil {\n\t\t\tstats[0], err = r.Repo.AddHistograms(ctx, filter, stats[0], numDurationBins)\n\t\t\tif err != nil {\n\t\t\t\treturn nil, err\n\t\t\t}\n\t\t} else {\n\t\t\treturn nil, errors.New(\"histograms only implemented without groupBy argument\")\n\t\t}\n\t}\n\n\tif requireField(ctx, \"histMetrics\") {\n\n\t\tif numMetricBins == nil 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empty string for overall statistics without grouping\n 134→// - shortThreshold: Duration threshold in seconds for counting short-running jobs\n 135→// - reqFields: Set of requested field names; nil means compute all fields\n 136→func (r *JobRepository) buildStatsQuery(\n 137→\tfilter []*model.JobFilter,\n 138→\tcol string,\n 139→\tshortThreshold int,\n 140→\treqFields map[string]bool,\n 141→) sq.SelectBuilder {\n 142→\tnow := time.Now().Unix()\n 143→\n 144→\t// Helper: return real expression if field is requested (or reqFields is nil), else \"0 as alias\"\n 145→\tneed := func(field string) bool {\n 146→\t\treturn reqFields == nil || reqFields[field]\n 147→\t}\n 148→\tdurationExpr := fmt.Sprintf(`(CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END)`, now)\n 149→\n 150→\t// Build column list\n 151→\tcolumns := make([]string, 0, 14)\n 152→\n 153→\tif col != \"\" {\n 154→\t\tcolumns = append(columns, col)\n 155→\t}\n 156→\n 157→\tcolumns = append(columns, \"COUNT(*) as totalJobs\")\n 158→\n 159→\tif need(\"totalUsers\") {\n 160→\t\tcolumns = append(columns, \"COUNT(DISTINCT job.hpc_user) AS totalUsers\")\n 161→\t} else {\n 162→\t\tcolumns = append(columns, \"0 AS totalUsers\")\n 163→\t}\n 164→\n 165→\tif need(\"totalWalltime\") {\n 166→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s) / 3600) as int) as totalWalltime`, durationExpr))\n 167→\t} else {\n 168→\t\tcolumns = append(columns, \"0 as totalWalltime\")\n 169→\t}\n 170→\n 171→\tif need(\"totalNodes\") {\n 172→\t\tcolumns = append(columns, `CAST(SUM(job.num_nodes) as int) as totalNodes`)\n 173→\t} else {\n 174→\t\tcolumns = append(columns, \"0 as totalNodes\")\n 175→\t}\n 176→\n 177→\tif need(\"totalNodeHours\") {\n 178→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_nodes) / 3600) as int) as totalNodeHours`, durationExpr))\n 179→\t} else {\n 180→\t\tcolumns = append(columns, \"0 as totalNodeHours\")\n 181→\t}\n 182→\n 183→\tif need(\"totalCores\") {\n 184→\t\tcolumns = append(columns, `CAST(SUM(job.num_hwthreads) as int) as totalCores`)\n 185→\t} else {\n 186→\t\tcolumns = append(columns, \"0 as totalCores\")\n 187→\t}\n 188→\n 189→\tif need(\"totalCoreHours\") {\n 190→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_hwthreads) / 3600) as int) as totalCoreHours`, durationExpr))\n 191→\t} else {\n 192→\t\tcolumns = append(columns, \"0 as totalCoreHours\")\n 193→\t}\n 194→\n 195→\tif need(\"totalAccs\") {\n 196→\t\tcolumns = append(columns, `CAST(SUM(job.num_acc) as int) as totalAccs`)\n 197→\t} else {\n 198→\t\tcolumns = append(columns, \"0 as totalAccs\")\n 199→\t}\n 200→\n 201→\tif need(\"totalAccHours\") {\n 202→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_acc) / 3600) as int) as totalAccHours`, durationExpr))\n 203→\t} else {\n 204→\t\tcolumns = append(columns, \"0 as totalAccHours\")\n 205→\t}\n 206→\n 207→\tif need(\"runningJobs\") {\n 208→\t\tcolumns = append(columns, `COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs`)\n 209→\t} else {\n 210→\t\tcolumns = append(columns, \"0 as runningJobs\")\n 211→\t}\n 212→\n 213→\tif need(\"shortJobs\") {\n 214→\t\tcolumns = append(columns, fmt.Sprintf(`COUNT(CASE WHEN job.duration < %d THEN 1 END) as shortJobs`, shortThreshold))\n 215→\t} else {\n 216→\t\tcolumns = append(columns, \"0 as shortJobs\")\n 217→\t}\n 218→\n 219→\tquery := sq.Select(columns...).From(\"job\")\n 220→\tif col != \"\" {\n 221→\t\tquery = query.GroupBy(col)\n 222→\t}\n 223→\n 224→\tfor _, f := range filter {\n 225→\t\tquery = BuildWhereClause(f, query)\n 226→\t}\n 227→\n 228→\treturn query\n 229→}"}]},"uuid":"63ced036-dea3-48c8-9c52-54a5e3c8f175","timestamp":"2026-03-19T10:06:22.670Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go","content":"//\n// Parameters:\n// - filter: Job filters to apply (cluster, user, time range, etc.)\n// - col: Column name to GROUP BY; empty string for overall statistics without grouping\n// - shortThreshold: Duration threshold in seconds for counting short-running jobs\n// - reqFields: Set of requested field names; nil means compute all fields\nfunc (r *JobRepository) buildStatsQuery(\n\tfilter []*model.JobFilter,\n\tcol string,\n\tshortThreshold int,\n\treqFields map[string]bool,\n) sq.SelectBuilder {\n\tnow := time.Now().Unix()\n\n\t// Helper: return real expression if field is requested (or reqFields is nil), else \"0 as alias\"\n\tneed := func(field string) bool {\n\t\treturn reqFields == nil || reqFields[field]\n\t}\n\tdurationExpr := fmt.Sprintf(`(CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END)`, now)\n\n\t// Build column list\n\tcolumns := make([]string, 0, 14)\n\n\tif col != \"\" {\n\t\tcolumns = append(columns, col)\n\t}\n\n\tcolumns = append(columns, \"COUNT(*) as totalJobs\")\n\n\tif need(\"totalUsers\") {\n\t\tcolumns = append(columns, \"COUNT(DISTINCT job.hpc_user) AS totalUsers\")\n\t} else {\n\t\tcolumns = append(columns, \"0 AS totalUsers\")\n\t}\n\n\tif need(\"totalWalltime\") {\n\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s) / 3600) as int) as totalWalltime`, durationExpr))\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalWalltime\")\n\t}\n\n\tif need(\"totalNodes\") {\n\t\tcolumns = append(columns, `CAST(SUM(job.num_nodes) as int) as totalNodes`)\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalNodes\")\n\t}\n\n\tif need(\"totalNodeHours\") {\n\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_nodes) / 3600) as int) as totalNodeHours`, durationExpr))\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalNodeHours\")\n\t}\n\n\tif need(\"totalCores\") {\n\t\tcolumns = append(columns, `CAST(SUM(job.num_hwthreads) as int) as totalCores`)\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalCores\")\n\t}\n\n\tif need(\"totalCoreHours\") {\n\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_hwthreads) / 3600) as int) as totalCoreHours`, durationExpr))\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalCoreHours\")\n\t}\n\n\tif need(\"totalAccs\") {\n\t\tcolumns = append(columns, `CAST(SUM(job.num_acc) as int) as totalAccs`)\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalAccs\")\n\t}\n\n\tif need(\"totalAccHours\") {\n\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_acc) / 3600) as int) as totalAccHours`, durationExpr))\n\t} else {\n\t\tcolumns = append(columns, \"0 as totalAccHours\")\n\t}\n\n\tif need(\"runningJobs\") {\n\t\tcolumns = append(columns, `COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs`)\n\t} else {\n\t\tcolumns = append(columns, \"0 as runningJobs\")\n\t}\n\n\tif need(\"shortJobs\") {\n\t\tcolumns = append(columns, fmt.Sprintf(`COUNT(CASE WHEN job.duration < %d THEN 1 END) as shortJobs`, shortThreshold))\n\t} else {\n\t\tcolumns = append(columns, \"0 as shortJobs\")\n\t}\n\n\tquery := sq.Select(columns...).From(\"job\")\n\tif col != \"\" {\n\t\tquery = query.GroupBy(col)\n\t}\n\n\tfor _, f := range filter {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\treturn query\n}","numLines":100,"startLine":130,"totalLines":1150}},"sourceToolAssistantUUID":"ac055d21-8588-4032-aa52-44f241c41cca","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"63ced036-dea3-48c8-9c52-54a5e3c8f175","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NT7Y6xRphTYtrGUnJvRP2E","type":"message","role":"assistant","content":[{"type":"text","text":"Good. Now let me check a critical edge case: what happens when `sortBy` references a field not in `reqFields`?"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4042,"cache_read_input_tokens":25461,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4042},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZCFaayoLdVEzNFFJwwYn","type":"assistant","uuid":"641d5263-d625-43d7-84fe-6d0c9d9d78f2","timestamp":"2026-03-19T10:06:28.046Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"641d5263-d625-43d7-84fe-6d0c9d9d78f2","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NT7Y6xRphTYtrGUnJvRP2E","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","name":"Agent","input":{"subagent_type":"Explore","description":"Find sortBy+reqFields interactions","prompt":"In the cc-backend codebase, I need to understand if there's a potential bug where `sortAndPageStats` might sort by a field that was zeroed out because it wasn't in `reqFields`.\n\nSpecifically:\n1. Find all GraphQL queries/frontend code that call `jobsStatistics` with both a `groupBy` and `sortBy` argument. Check if any of them sort by a field (e.g. `TOTALUSERS`) without also selecting that field in the response.\n2. Look in `web/frontend/src/` for how `jobsStatistics` is called — what fields are requested and what `sortBy` values are used.\n3. Check `internal/graph/schema.resolvers.go` around the `requireField` function — how does it determine which fields are requested from the GraphQL selection set?\n\nBe thorough — check all .svelte, .js, .ts, and .graphql files in the frontend, plus the GraphQL schema."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4042,"cache_read_input_tokens":25461,"output_tokens":343,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":4042,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZCFaayoLdVEzNFFJwwYn","type":"assistant","uuid":"6abc7913-0cc4-4eeb-9ae0-3179de20cd34","timestamp":"2026-03-19T10:06:34.912Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"6abc7913-0cc4-4eeb-9ae0-3179de20cd34","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PreToolUse","hookName":"PreToolUse:Agent","command":"entire hooks claude-code pre-task"},"toolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"e0851a26-d5ab-48e0-b79e-68807107ec4f","timestamp":"2026-03-19T10:06:34.915Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"e0851a26-d5ab-48e0-b79e-68807107ec4f","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"In the cc-backend codebase, I need to understand if there's a potential bug where `sortAndPageStats` might sort by a field that was zeroed out because it wasn't in `reqFields`.\n\nSpecifically:\n1. Find all GraphQL queries/frontend code that call `jobsStatistics` with both a `groupBy` and `sortBy` argument. Check if any of them sort by a field (e.g. `TOTALUSERS`) without also selecting that field in the response.\n2. Look in `web/frontend/src/` for how `jobsStatistics` is called — what fields are requested and what `sortBy` values are used.\n3. Check `internal/graph/schema.resolvers.go` around the `requireField` function — how does it determine which fields are requested from the GraphQL selection set?\n\nBe thorough — check all .svelte, .js, .ts, and .graphql files in the frontend, plus the GraphQL schema."}]},"uuid":"5fc22ac0-2c70-40c1-8f6f-c8282e801a07","timestamp":"2026-03-19T10:06:35.213Z"},"type":"agent_progress","prompt":"In the cc-backend codebase, I need to understand if there's a potential bug where `sortAndPageStats` might sort by a field that was zeroed out because it wasn't in `reqFields`.\n\nSpecifically:\n1. Find all GraphQL queries/frontend code that call `jobsStatistics` with both a `groupBy` and `sortBy` argument. Check if any of them sort by a field (e.g. `TOTALUSERS`) without also selecting that field in the response.\n2. Look in `web/frontend/src/` for how `jobsStatistics` is called — what fields are requested and what `sortBy` values are used.\n3. Check `internal/graph/schema.resolvers.go` around the `requireField` function — how does it determine which fields are requested from the GraphQL selection set?\n\nBe thorough — check all .svelte, .js, .ts, and .graphql files in the frontend, plus the GraphQL schema.","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"b5a027ae-06aa-4644-a48c-76ebdf4e1909","timestamp":"2026-03-19T10:06:35.214Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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+{"parentUuid":"80bd67c3-2c46-40f3-99a5-3fc3aef3a236","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GihZwpAmU8yaBmHuJamCyB","type":"tool_result","content":" 1→package graph\n 2→\n 3→// This file will be automatically regenerated based on the schema, any resolver\n 4→// implementations\n 5→// will be copied through when generating and any unknown code will be moved to the end.\n 6→// Code generated by github.com/99designs/gqlgen version v0.17.88\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"errors\"\n 11→\t\"fmt\"\n 12→\t\"math\"\n 13→\t\"regexp\"\n 14→\t\"slices\"\n 15→\t\"strconv\"\n 16→\t\"strings\"\n 17→\t\"time\"\n 18→\n 19→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n 20→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n 21→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 22→\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n 23→\t\"github.com/ClusterCockpit/cc-backend/internal/repository\"\n 24→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 25→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 26→\tccunit \"github.com/ClusterCockpit/cc-lib/v2/ccUnits\"\n 27→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 28→)\n 29→\n 30→// Partitions is the resolver for the partitions field.\n 31→func (r *clusterResolver) Partitions(ctx context.Context, obj *schema.Cluster) ([]string, error) {\n 32→\treturn r.Repo.Partitions(obj.Name)\n 33→}\n 34→\n 35→// StartTime is the resolver for the startTime field.\n 36→func (r *jobResolver) StartTime(ctx context.Context, obj *schema.Job) (*time.Time, error) {\n 37→\ttimestamp := time.Unix(obj.StartTime, 0)\n 38→\treturn ×tamp, nil\n 39→}\n 40→\n 41→// Tags is the resolver for the tags field.\n 42→func (r *jobResolver) Tags(ctx context.Context, obj *schema.Job) ([]*schema.Tag, error) {\n 43→\treturn r.Repo.GetTags(repository.GetUserFromContext(ctx), obj.ID)\n 44→}\n 45→\n 46→// ConcurrentJobs is the resolver for the concurrentJobs field.\n 47→func (r *jobResolver) ConcurrentJobs(ctx context.Context, obj *schema.Job) (*model.JobLinkResultList, error) {\n 48→\t// FIXME: Make the hardcoded duration configurable\n 49→\tif obj.Shared != \"none\" && obj.Duration > 600 {\n 50→\t\treturn r.Repo.FindConcurrentJobs(ctx, obj)\n 51→\t}\n 52→\n 53→\treturn nil, nil\n 54→}\n 55→\n 56→// Footprint is the resolver for the footprint field.\n 57→func (r *jobResolver) Footprint(ctx context.Context, obj *schema.Job) ([]*model.FootprintValue, error) {\n 58→\trawFootprint, err := r.Repo.FetchFootprint(obj)\n 59→\tif err != nil {\n 60→\t\tcclog.Warn(\"Error while fetching job footprint data\")\n 61→\t\treturn nil, err\n 62→\t}\n 63→\n 64→\tres := []*model.FootprintValue{}\n 65→\tfor name, value := range rawFootprint {\n 66→\n 67→\t\tparts := strings.Split(name, \"_\")\n 68→\t\tstatPart := parts[len(parts)-1]\n 69→\t\tnameParts := parts[:len(parts)-1]\n 70→\n 71→\t\tres = append(res, &model.FootprintValue{\n 72→\t\t\tName: strings.Join(nameParts, \"_\"),\n 73→\t\t\tStat: statPart,\n 74→\t\t\tValue: value,\n 75→\t\t})\n 76→\t}\n 77→\n 78→\treturn res, err\n 79→}\n 80→\n 81→// EnergyFootprint is the resolver for the energyFootprint field.\n 82→func (r *jobResolver) EnergyFootprint(ctx context.Context, obj *schema.Job) ([]*model.EnergyFootprintValue, error) {\n 83→\trawEnergyFootprint, err := r.Repo.FetchEnergyFootprint(obj)\n 84→\tif err != nil {\n 85→\t\tcclog.Warn(\"Error while fetching job energy footprint data\")\n 86→\t\treturn nil, err\n 87→\t}\n 88→\n 89→\tres := []*model.EnergyFootprintValue{}\n 90→\tfor name, value := range rawEnergyFootprint {\n 91→\t\t// Suboptimal: Nearly hardcoded metric name expectations\n 92→\t\tmatchCPU := regexp.MustCompile(`cpu|Cpu|CPU`)\n 93→\t\tmatchAcc := regexp.MustCompile(`acc|Acc|ACC`)\n 94→\t\tmatchMem := regexp.MustCompile(`mem|Mem|MEM`)\n 95→\t\tmatchCore := regexp.MustCompile(`core|Core|CORE`)\n 96→\n 97→\t\thwType := \"\"\n 98→\t\tswitch test := name; { // NOtice ';' for var declaration\n 99→\t\tcase matchCPU.MatchString(test):\n 100→\t\t\thwType = \"CPU\"\n 101→\t\tcase matchAcc.MatchString(test):\n 102→\t\t\thwType = \"Accelerator\"\n 103→\t\tcase matchMem.MatchString(test):\n 104→\t\t\thwType = \"Memory\"\n 105→\t\tcase matchCore.MatchString(test):\n 106→\t\t\thwType = \"Core\"\n 107→\t\tdefault:\n 108→\t\t\thwType = \"Other\"\n 109→\t\t}\n 110→\n 111→\t\tres = append(res, &model.EnergyFootprintValue{\n 112→\t\t\tHardware: hwType,\n 113→\t\t\tMetric: name,\n 114→\t\t\tValue: value,\n 115→\t\t})\n 116→\t}\n 117→\treturn res, err\n 118→}\n 119→\n 120→// MetaData is the resolver for the metaData field.\n 121→func (r *jobResolver) MetaData(ctx context.Context, obj *schema.Job) (any, error) {\n 122→\treturn r.Repo.FetchMetadata(obj)\n 123→}\n 124→\n 125→// UserData is the resolver for the userData field.\n 126→func (r *jobResolver) UserData(ctx context.Context, obj *schema.Job) (*model.User, error) {\n 127→\treturn repository.GetUserRepository().FetchUserInCtx(ctx, obj.User)\n 128→}\n 129→\n 130→// Name is the resolver for the name field.\n 131→func (r *metricValueResolver) Name(ctx context.Context, obj *schema.MetricValue) (*string, error) {\n 132→\tpanic(fmt.Errorf(\"not implemented: Name - name\"))\n 133→}\n 134→\n 135→// CreateTag is the resolver for the createTag field.\n 136→func (r *mutationResolver) CreateTag(ctx context.Context, typeArg string, name string, scope string) (*schema.Tag, error) {\n 137→\tuser := repository.GetUserFromContext(ctx)\n 138→\tif user == nil {\n 139→\t\treturn nil, fmt.Errorf(\"no user in context\")\n 140→\t}\n 141→\n 142→\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n 143→\tif user.HasRole(schema.RoleAdmin) && scope == \"admin\" ||\n 144→\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && scope == \"global\" ||\n 145→\t\tuser.Username == scope {\n 146→\t\t// Create in DB\n 147→\t\tid, err := r.Repo.CreateTag(typeArg, name, scope)\n 148→\t\tif err != nil {\n 149→\t\t\tcclog.Warn(\"Error while creating tag\")\n 150→\t\t\treturn nil, err\n 151→\t\t}\n 152→\t\treturn &schema.Tag{ID: id, Type: typeArg, Name: name, Scope: scope}, nil\n 153→\t} else {\n 154→\t\tcclog.Warnf(\"Not authorized to create tag with scope: %s\", scope)\n 155→\t\treturn nil, fmt.Errorf(\"not authorized to create tag with scope: %s\", scope)\n 156→\t}\n 157→}\n 158→\n 159→// DeleteTag is the resolver for the deleteTag field.\n 160→func (r *mutationResolver) DeleteTag(ctx context.Context, id string) (string, error) {\n 161→\t// This Uses ID string <-> ID string, removeTagFromList uses []string <-> []int\n 162→\tpanic(fmt.Errorf(\"not implemented: DeleteTag - deleteTag\"))\n 163→}\n 164→\n 165→// AddTagsToJob is the resolver for the addTagsToJob field.\n 166→func (r *mutationResolver) AddTagsToJob(ctx context.Context, job string, tagIds []string) ([]*schema.Tag, error) {\n 167→\tuser := repository.GetUserFromContext(ctx)\n 168→\tif user == nil {\n 169→\t\treturn nil, fmt.Errorf(\"no user in context\")\n 170→\t}\n 171→\n 172→\tjid, err := strconv.ParseInt(job, 10, 64)\n 173→\tif err != nil {\n 174→\t\tcclog.Warn(\"Error while adding tag to job\")\n 175→\t\treturn nil, err\n 176→\t}\n 177→\n 178→\ttags := []*schema.Tag{}\n 179→\tfor _, tagID := range tagIds {\n 180→\t\t// Get ID\n 181→\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n 182→\t\tif err != nil {\n 183→\t\t\tcclog.Warn(\"Error while parsing tag id\")\n 184→\t\t\treturn nil, err\n 185→\t\t}\n 186→\n 187→\t\t// Test Exists\n 188→\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n 189→\t\tif !exists {\n 190→\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n 191→\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n 192→\t\t}\n 193→\n 194→\t\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n 195→\t\tif user.HasRole(schema.RoleAdmin) && tscope == \"admin\" ||\n 196→\t\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && tscope == \"global\" ||\n 197→\t\t\tuser.Username == tscope {\n 198→\t\t\t// Add to Job\n 199→\t\t\tif tags, err = r.Repo.AddTag(user, jid, tid); err != nil {\n 200→\t\t\t\tcclog.Warn(\"Error while adding tag\")\n 201→\t\t\t\treturn nil, err\n 202→\t\t\t}\n 203→\t\t} else {\n 204→\t\t\tcclog.Warnf(\"Not authorized to add tag: %d\", tid)\n 205→\t\t\treturn nil, fmt.Errorf(\"not authorized to add tag: %d\", tid)\n 206→\t\t}\n 207→\t}\n 208→\n 209→\treturn tags, nil\n 210→}\n 211→\n 212→// RemoveTagsFromJob is the resolver for the removeTagsFromJob field.\n 213→func (r *mutationResolver) RemoveTagsFromJob(ctx context.Context, job string, tagIds []string) ([]*schema.Tag, error) {\n 214→\tuser := repository.GetUserFromContext(ctx)\n 215→\tif user == nil {\n 216→\t\treturn nil, fmt.Errorf(\"no user in context\")\n 217→\t}\n 218→\n 219→\tjid, err := strconv.ParseInt(job, 10, 64)\n 220→\tif err != nil {\n 221→\t\tcclog.Warn(\"Error while parsing job id\")\n 222→\t\treturn nil, err\n 223→\t}\n 224→\n 225→\ttags := []*schema.Tag{}\n 226→\tfor _, tagID := range tagIds {\n 227→\t\t// Get ID\n 228→\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n 229→\t\tif err != nil {\n 230→\t\t\tcclog.Warn(\"Error while parsing tag id\")\n 231→\t\t\treturn nil, err\n 232→\t\t}\n 233→\n 234→\t\t// Test Exists\n 235→\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n 236→\t\tif !exists {\n 237→\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n 238→\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n 239→\t\t}\n 240→\n 241→\t\t// Test Access: Admins && Admin Tag OR Support/Admin and Global Tag OR Everyone && Private Tag\n 242→\t\tif user.HasRole(schema.RoleAdmin) && tscope == \"admin\" ||\n 243→\t\t\tuser.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) && tscope == \"global\" ||\n 244→\t\t\tuser.Username == tscope {\n 245→\t\t\t// Remove from Job\n 246→\t\t\tif tags, err = r.Repo.RemoveTag(user, jid, tid); err != nil {\n 247→\t\t\t\tcclog.Warn(\"Error while removing tag\")\n 248→\t\t\t\treturn nil, err\n 249→\t\t\t}\n 250→\t\t} else {\n 251→\t\t\tcclog.Warnf(\"Not authorized to remove tag: %d\", tid)\n 252→\t\t\treturn nil, fmt.Errorf(\"not authorized to remove tag: %d\", tid)\n 253→\t\t}\n 254→\n 255→\t}\n 256→\n 257→\treturn tags, nil\n 258→}\n 259→\n 260→// RemoveTagFromList is the resolver for the removeTagFromList field.\n 261→func (r *mutationResolver) RemoveTagFromList(ctx context.Context, tagIds []string) ([]int, error) {\n 262→\t// Needs Contextuser\n 263→\tuser := repository.GetUserFromContext(ctx)\n 264→\tif user == nil {\n 265→\t\treturn nil, fmt.Errorf(\"no user in context\")\n 266→\t}\n 267→\n 268→\ttags := []int{}\n 269→\tfor _, tagID := range tagIds {\n 270→\t\t// Get ID\n 271→\t\ttid, err := strconv.ParseInt(tagID, 10, 64)\n 272→\t\tif err != nil {\n 273→\t\t\tcclog.Warn(\"Error while parsing tag id for removal\")\n 274→\t\t\treturn nil, err\n 275→\t\t}\n 276→\n 277→\t\t// Test Exists\n 278→\t\t_, _, tscope, exists := r.Repo.TagInfo(tid)\n 279→\t\tif !exists {\n 280→\t\t\tcclog.Warnf(\"Tag does not exist (ID): %d\", tid)\n 281→\t\t\treturn nil, fmt.Errorf(\"tag does not exist (ID): %d\", tid)\n 282→\t\t}\n 283→\n 284→\t\t// Test Access: Admins && Admin Tag OR Everyone && Private Tag\n 285→\t\tif user.HasRole(schema.RoleAdmin) && (tscope == \"global\" || tscope == \"admin\") || user.Username == tscope {\n 286→\t\t\t// Remove from DB\n 287→\t\t\tif err = r.Repo.RemoveTagByID(tid); err != nil {\n 288→\t\t\t\tcclog.Warn(\"Error while removing tag\")\n 289→\t\t\t\treturn nil, err\n 290→\t\t\t} else {\n 291→\t\t\t\ttags = append(tags, int(tid))\n 292→\t\t\t}\n 293→\t\t} else {\n 294→\t\t\tcclog.Warnf(\"Not authorized to remove tag: %d\", tid)\n 295→\t\t\treturn nil, fmt.Errorf(\"not authorized to remove tag: %d\", tid)\n 296→\t\t}\n 297→\t}\n 298→\treturn tags, nil\n 299→}\n 300→\n 301→// UpdateConfiguration is the resolver for the updateConfiguration field.\n 302→func (r *mutationResolver) UpdateConfiguration(ctx context.Context, name string, value string) (*string, error) {\n 303→\tif err := repository.GetUserCfgRepo().UpdateConfig(name, value, repository.GetUserFromContext(ctx)); err != nil {\n 304→\t\tcclog.Warn(\"Error while updating user config\")\n 305→\t\treturn nil, err\n 306→\t}\n 307→\n 308→\treturn nil, nil\n 309→}\n 310→\n 311→// ID is the resolver for the id field.\n 312→func (r *nodeResolver) ID(ctx context.Context, obj *schema.Node) (string, error) {\n 313→\tpanic(fmt.Errorf(\"not implemented: ID - id\"))\n 314→}\n 315→\n 316→// SchedulerState is the resolver for the schedulerState field.\n 317→func (r *nodeResolver) SchedulerState(ctx context.Context, obj *schema.Node) (schema.SchedulerState, error) {\n 318→\tif obj.NodeState != \"\" {\n 319→\t\treturn obj.NodeState, nil\n 320→\t} else {\n 321→\t\treturn \"\", fmt.Errorf(\"resolver: no SchedulerState (NodeState) on node object\")\n 322→\t}\n 323→}\n 324→\n 325→// HealthState is the resolver for the healthState field.\n 326→func (r *nodeResolver) HealthState(ctx context.Context, obj *schema.Node) (string, error) {\n 327→\tif obj.HealthState != \"\" {\n 328→\t\treturn string(obj.HealthState), nil\n 329→\t} else {\n 330→\t\treturn \"\", fmt.Errorf(\"resolver: no HealthState (NodeState) on node object\")\n 331→\t}\n 332→}\n 333→\n 334→// MetaData is the resolver for the metaData field.\n 335→func (r *nodeResolver) MetaData(ctx context.Context, obj *schema.Node) (any, error) {\n 336→\tif obj.MetaData != nil {\n 337→\t\treturn obj.MetaData, nil\n 338→\t} else {\n 339→\t\tcclog.Debug(\"resolver: no MetaData (NodeState) on node object\")\n 340→\t\temptyMeta := make(map[string]string, 0)\n 341→\t\treturn emptyMeta, nil\n 342→\t}\n 343→}\n 344→\n 345→// HealthData is the resolver for the healthData field.\n 346→func (r *nodeResolver) HealthData(ctx context.Context, obj *schema.Node) (any, error) {\n 347→\tif obj.HealthData != nil {\n 348→\t\treturn obj.HealthData, nil\n 349→\t} else {\n 350→\t\tcclog.Debug(\"resolver: no HealthData (NodeState) on node object\")\n 351→\t\temptyHealth := make(map[string][]string, 0)\n 352→\t\treturn emptyHealth, nil\n 353→\t}\n 354→}\n 355→\n 356→// Clusters is the resolver for the clusters field.\n 357→func (r *queryResolver) Clusters(ctx context.Context) ([]*schema.Cluster, error) {\n 358→\treturn archive.Clusters, nil\n 359→}\n 360→\n 361→// Tags is the resolver for the tags field.\n 362→func (r *queryResolver) Tags(ctx context.Context) ([]*schema.Tag, error) {\n 363→\treturn r.Repo.GetTags(repository.GetUserFromContext(ctx), nil)\n 364→}\n 365→\n 366→// GlobalMetrics is the resolver for the globalMetrics field.\n 367→func (r *queryResolver) GlobalMetrics(ctx context.Context) ([]*schema.GlobalMetricListItem, error) {\n 368→\tuser := repository.GetUserFromContext(ctx)\n 369→\n 370→\tif user != nil {\n 371→\t\tif user.HasRole(schema.RoleUser) || user.HasRole(schema.RoleManager) {\n 372→\t\t\treturn archive.GlobalUserMetricList, nil\n 373→\t\t}\n 374→\t}\n 375→\n 376→\treturn archive.GlobalMetricList, nil\n 377→}\n 378→\n 379→// User is the resolver for the user field.\n 380→func (r *queryResolver) User(ctx context.Context, username string) (*model.User, error) {\n 381→\treturn repository.GetUserRepository().FetchUserInCtx(ctx, username)\n 382→}\n 383→\n 384→// AllocatedNodes is the resolver for the allocatedNodes field.\n 385→func (r *queryResolver) AllocatedNodes(ctx context.Context, cluster string) ([]*model.Count, error) {\n 386→\tdata, err := r.Repo.AllocatedNodes(cluster)\n 387→\tif err != nil {\n 388→\t\tcclog.Warn(\"Error while fetching allocated nodes\")\n 389→\t\treturn nil, err\n 390→\t}\n 391→\n 392→\tcounts := make([]*model.Count, 0, len(data))\n 393→\tfor subcluster, hosts := range data {\n 394→\t\tcounts = append(counts, &model.Count{\n 395→\t\t\tName: subcluster,\n 396→\t\t\tCount: len(hosts),\n 397→\t\t})\n 398→\t}\n 399→\n 400→\treturn counts, nil\n 401→}\n 402→\n 403→// Node is the resolver for the node field.\n 404→func (r *queryResolver) Node(ctx context.Context, id string) (*schema.Node, error) {\n 405→\trepo := repository.GetNodeRepository()\n 406→\tnumericID, err := strconv.ParseInt(id, 10, 64)\n 407→\tif err != nil {\n 408→\t\tcclog.Warn(\"Error while parsing job id\")\n 409→\t\treturn nil, err\n 410→\t}\n 411→\treturn repo.GetNodeByID(numericID, false)\n 412→}\n 413→\n 414→// Nodes is the resolver for the nodes field.\n 415→func (r *queryResolver) Nodes(ctx context.Context, filter []*model.NodeFilter, order *model.OrderByInput) (*model.NodeStateResultList, error) {\n 416→\trepo := repository.GetNodeRepository()\n 417→\tnodes, err := repo.QueryNodes(ctx, filter, nil, order) // Ignore Paging, Order Unused\n 418→\tcount := len(nodes)\n 419→\treturn &model.NodeStateResultList{Items: nodes, Count: &count}, err\n 420→}\n 421→\n 422→// NodesWithMeta is the resolver for the nodesWithMeta field.\n 423→func (r *queryResolver) NodesWithMeta(ctx context.Context, filter []*model.NodeFilter, order *model.OrderByInput) (*model.NodeStateResultList, error) {\n 424→\t// Why Extra Handler? -> graphql.CollectAllFields(ctx) only returns toplevel fields (i.e.: items, count), and not subfields like item.metaData\n 425→\trepo := repository.GetNodeRepository()\n 426→\tnodes, err := repo.QueryNodesWithMeta(ctx, filter, nil, order) // Ignore Paging, Order Unused\n 427→\tcount := len(nodes)\n 428→\treturn &model.NodeStateResultList{Items: nodes, Count: &count}, err\n 429→}\n 430→\n 431→// NodeStates is the resolver for the nodeStates field.\n 432→func (r *queryResolver) NodeStates(ctx context.Context, filter []*model.NodeFilter) ([]*model.NodeStates, error) {\n 433→\trepo := repository.GetNodeRepository()\n 434→\n 435→\tstateCounts, serr := repo.CountStates(ctx, filter, \"node_state\")\n 436→\tif serr != nil {\n 437→\t\tcclog.Warnf(\"Error while counting nodeStates: %s\", serr.Error())\n 438→\t\treturn nil, serr\n 439→\t}\n 440→\n 441→\thealthCounts, herr := repo.CountStates(ctx, filter, \"health_state\")\n 442→\tif herr != nil {\n 443→\t\tcclog.Warnf(\"Error while counting healthStates: %s\", herr.Error())\n 444→\t\treturn nil, herr\n 445→\t}\n 446→\n 447→\tallCounts := append(stateCounts, healthCounts...)\n 448→\n 449→\treturn allCounts, nil\n 450→}\n 451→\n 452→// NodeStatesTimed is the resolver for the nodeStatesTimed field.\n 453→func (r *queryResolver) NodeStatesTimed(ctx context.Context, filter []*model.NodeFilter, typeArg string) ([]*model.NodeStatesTimed, error) {\n 454→\trepo := repository.GetNodeRepository()\n 455→\n 456→\tif typeArg == \"node\" {\n 457→\t\tstateCounts, serr := repo.CountStatesTimed(ctx, filter, \"node_state\")\n 458→\t\tif serr != nil {\n 459→\t\t\tcclog.Warnf(\"Error while counting nodeStates in time: %s\", serr.Error())\n 460→\t\t\treturn nil, serr\n 461→\t\t}\n 462→\t\treturn stateCounts, nil\n 463→\t}\n 464→\n 465→\tif typeArg == \"health\" {\n 466→\t\thealthCounts, herr := repo.CountStatesTimed(ctx, filter, \"health_state\")\n 467→\t\tif herr != nil {\n 468→\t\t\tcclog.Warnf(\"Error while counting healthStates in time: %s\", herr.Error())\n 469→\t\t\treturn nil, herr\n 470→\t\t}\n 471→\t\treturn healthCounts, nil\n 472→\t}\n 473→\n 474→\treturn nil, errors.New(\"unknown Node State Query Type\")\n 475→}\n 476→\n 477→// Job is the resolver for the job field.\n 478→func (r *queryResolver) Job(ctx context.Context, id string) (*schema.Job, error) {\n 479→\tnumericID, err := strconv.ParseInt(id, 10, 64)\n 480→\tif err != nil {\n 481→\t\tcclog.Warn(\"Error while parsing job id\")\n 482→\t\treturn nil, err\n 483→\t}\n 484→\n 485→\tjob, err := r.Repo.FindByID(ctx, numericID)\n 486→\tif err != nil {\n 487→\t\tcclog.Warn(\"Error while finding job by id\")\n 488→\t\treturn nil, err\n 489→\t}\n 490→\n 491→\tif user := repository.GetUserFromContext(ctx); user != nil &&\n 492→\t\tjob.User != user.Username &&\n 493→\t\tuser.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n 494→\t\treturn nil, errors.New(\"you are not allowed to see this job\")\n 495→\t}\n 496→\n 497→\treturn job, nil\n 498→}\n 499→\n 500→// JobMetrics is the resolver for the jobMetrics field.\n 501→func (r *queryResolver) JobMetrics(ctx context.Context, id string, metrics []string, scopes []schema.MetricScope, resolution *int) ([]*model.JobMetricWithName, error) {\n 502→\tif resolution == nil { // Load from Config\n 503→\t\tif config.Keys.EnableResampling != nil {\n 504→\t\t\tdefaultRes := slices.Max(config.Keys.EnableResampling.Resolutions)\n 505→\t\t\tresolution = &defaultRes\n 506→\t\t} else { // Set 0 (Loads configured metric timestep)\n 507→\t\t\tdefaultRes := 0\n 508→\t\t\tresolution = &defaultRes\n 509→\t\t}\n 510→\t}\n 511→\n 512→\tjob, err := r.Query().Job(ctx, id)\n 513→\tif err != nil {\n 514→\t\tcclog.Warn(\"Error while querying job for metrics\")\n 515→\t\treturn nil, err\n 516→\t}\n 517→\n 518→\tdata, err := metricdispatch.LoadData(job, metrics, scopes, ctx, *resolution)\n 519→\tif err != nil {\n 520→\t\tcclog.Warn(\"Error while loading job data\")\n 521→\t\treturn nil, err\n 522→\t}\n 523→\n 524→\tres := []*model.JobMetricWithName{}\n 525→\tfor name, md := range data {\n 526→\t\tfor scope, metric := range md {\n 527→\t\t\tres = append(res, &model.JobMetricWithName{\n 528→\t\t\t\tName: name,\n 529→\t\t\t\tScope: scope,\n 530→\t\t\t\tMetric: metric,\n 531→\t\t\t})\n 532→\t\t}\n 533→\t}\n 534→\n 535→\treturn res, err\n 536→}\n 537→\n 538→// JobStats is the resolver for the jobStats field.\n 539→func (r *queryResolver) JobStats(ctx context.Context, id string, metrics []string) ([]*model.NamedStats, error) {\n 540→\tjob, err := r.Query().Job(ctx, id)\n 541→\tif err != nil {\n 542→\t\tcclog.Warnf(\"Error while querying job %s for metadata\", id)\n 543→\t\treturn nil, err\n 544→\t}\n 545→\n 546→\tdata, err := metricdispatch.LoadJobStats(job, metrics, ctx)\n 547→\tif err != nil {\n 548→\t\tcclog.Warnf(\"Error while loading jobStats data for job id %s\", id)\n 549→\t\treturn nil, err\n 550→\t}\n 551→\n 552→\tres := []*model.NamedStats{}\n 553→\tfor name, md := range data {\n 554→\t\tres = append(res, &model.NamedStats{\n 555→\t\t\tName: name,\n 556→\t\t\tData: &md,\n 557→\t\t})\n 558→\t}\n 559→\n 560→\treturn res, err\n 561→}\n 562→\n 563→// ScopedJobStats is the resolver for the scopedJobStats field.\n 564→func (r *queryResolver) ScopedJobStats(ctx context.Context, id string, metrics []string, scopes []schema.MetricScope) ([]*model.NamedStatsWithScope, error) {\n 565→\tjob, err := r.Query().Job(ctx, id)\n 566→\tif err != nil {\n 567→\t\tcclog.Warnf(\"Error while querying job %s for metadata\", id)\n 568→\t\treturn nil, err\n 569→\t}\n 570→\n 571→\tdata, err := metricdispatch.LoadScopedJobStats(job, metrics, scopes, ctx)\n 572→\tif err != nil {\n 573→\t\tcclog.Warnf(\"Error while loading scopedJobStats data for job id %s\", id)\n 574→\t\treturn nil, err\n 575→\t}\n 576→\n 577→\tres := make([]*model.NamedStatsWithScope, 0)\n 578→\tfor name, scoped := range data {\n 579→\t\tfor scope, stats := range scoped {\n 580→\n 581→\t\t\tmdlStats := make([]*model.ScopedStats, 0)\n 582→\t\t\tfor _, stat := range stats {\n 583→\t\t\t\tmdlStats = append(mdlStats, &model.ScopedStats{\n 584→\t\t\t\t\tHostname: stat.Hostname,\n 585→\t\t\t\t\tID: stat.ID,\n 586→\t\t\t\t\tData: stat.Data,\n 587→\t\t\t\t})\n 588→\t\t\t}\n 589→\n 590→\t\t\tres = append(res, &model.NamedStatsWithScope{\n 591→\t\t\t\tName: name,\n 592→\t\t\t\tScope: scope,\n 593→\t\t\t\tStats: mdlStats,\n 594→\t\t\t})\n 595→\t\t}\n 596→\t}\n 597→\n 598→\treturn res, nil\n 599→}\n 600→\n 601→// Jobs is the resolver for the jobs field.\n 602→func (r *queryResolver) Jobs(ctx context.Context, filter []*model.JobFilter, page *model.PageRequest, order *model.OrderByInput) (*model.JobResultList, error) {\n 603→\tif page == nil {\n 604→\t\tpage = &model.PageRequest{\n 605→\t\t\tItemsPerPage: 50,\n 606→\t\t\tPage: 1,\n 607→\t\t}\n 608→\t}\n 609→\n 610→\tjobs, err := r.Repo.QueryJobs(ctx, filter, page, order)\n 611→\tif err != nil {\n 612→\t\tcclog.Warn(\"Error while querying jobs\")\n 613→\t\treturn nil, err\n 614→\t}\n 615→\n 616→\tcount, err := r.Repo.CountJobs(ctx, filter)\n 617→\tif err != nil {\n 618→\t\tcclog.Warn(\"Error while counting jobs\")\n 619→\t\treturn nil, err\n 620→\t}\n 621→\n 622→\t// Note: Even if App-Default 'config.Keys.UiDefaults[\"job_list_usePaging\"]' is set, always return hasNextPage boolean.\n 623→\t// Users can decide in frontend to use continuous scroll, even if app-default is paging!\n 624→\t// Skip if page.ItemsPerPage == -1 (\"Load All\" -> No Next Page required, Status Dashboards)\n 625→\t/*\n 626→\t Example Page 4 @ 10 IpP : Does item 41 exist?\n 627→\t Minimal Page 41 @ 1 IpP : If len(result) is 1, Page 5 @ 10 IpP exists.\n 628→\t*/\n 629→\thasNextPage := false\n 630→\tif page.ItemsPerPage != -1 {\n 631→\t\tnextPage := &model.PageRequest{\n 632→\t\t\tItemsPerPage: 1,\n 633→\t\t\tPage: ((page.Page * page.ItemsPerPage) + 1),\n 634→\t\t}\n 635→\t\tnextJobs, err := r.Repo.QueryJobs(ctx, filter, nextPage, order)\n 636→\t\tif err != nil {\n 637→\t\t\tcclog.Warn(\"Error while querying next jobs\")\n 638→\t\t\treturn nil, err\n 639→\t\t}\n 640→\t\thasNextPage = len(nextJobs) == 1\n 641→\t}\n 642→\n 643→\treturn &model.JobResultList{Items: jobs, Count: &count, HasNextPage: &hasNextPage}, nil\n 644→}\n 645→\n 646→// JobsStatistics is the resolver for the jobsStatistics field.\n 647→func (r *queryResolver) JobsStatistics(ctx context.Context, filter []*model.JobFilter, metrics []string, page *model.PageRequest, sortBy *model.SortByAggregate, groupBy *model.Aggregate, numDurationBins *string, numMetricBins *int) ([]*model.JobsStatistics, error) {\n 648→\tvar err error\n 649→\tvar stats []*model.JobsStatistics\n 650→\n 651→\t// Top Level Defaults\n 652→\tdefaultDurationBins := \"1h\"\n 653→\tdefaultMetricBins := 10\n 654→\n 655→\t// Build requested fields map for selective column computation\n 656→\tstatsFields := []string{\n 657→\t\t\"totalJobs\", \"totalUsers\", \"totalWalltime\", \"totalNodes\", \"totalCores\",\n 658→\t\t\"totalAccs\", \"totalNodeHours\", \"totalCoreHours\", \"totalAccHours\", \"runningJobs\", \"shortJobs\",\n 659→\t}\n 660→\treqFields := make(map[string]bool, len(statsFields))\n 661→\tfetchedMainStats := false\n 662→\tfor _, f := range statsFields {\n 663→\t\tif requireField(ctx, f) {\n 664→\t\t\treqFields[f] = true\n 665→\t\t\tif f != \"runningJobs\" && f != \"shortJobs\" {\n 666→\t\t\t\tfetchedMainStats = true\n 667→\t\t\t}\n 668→\t\t}\n 669→\t}\n 670→\n 671→\tif fetchedMainStats {\n 672→\t\tif groupBy == nil {\n 673→\t\t\tstats, err = r.Repo.JobsStats(ctx, filter, reqFields)\n 674→\t\t} else {\n 675→\t\t\tstartGrouped := time.Now()\n 676→\t\t\t// Use request-scoped cache: multiple aliases with same (filter, groupBy)\n 677→\t\t\t// but different sortBy/page hit the DB only once.\n 678→\t\t\tif cache := getStatsGroupCache(ctx); cache != nil {\n 679→\t\t\t\tkey := statsCacheKey(filter, groupBy, reqFields)\n 680→\t\t\t\tvar allStats []*model.JobsStatistics\n 681→\t\t\t\tallStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {\n 682→\t\t\t\t\treturn r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, reqFields)\n 683→\t\t\t\t})\n 684→\t\t\t\tif err == nil {\n 685→\t\t\t\t\tstats = sortAndPageStats(allStats, sortBy, page)\n 686→\t\t\t\t}\n 687→\t\t\t} else {\n 688→\t\t\t\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n 689→\t\t\t}\n 690→\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n 691→\t\t}\n 692→\t} else {\n 693→\t\tstats = make([]*model.JobsStatistics, 0, 1)\n 694→\t\tstats = append(stats, &model.JobsStatistics{})\n 695→\t}\n 696→\n 697→\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n 698→\t// Only run separate count queries if main stats were not fetched.\n 699→\tif !fetchedMainStats {\n 700→\t\tif groupBy != nil {\n 701→\t\t\tif requireField(ctx, \"shortJobs\") {\n 702→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n 703→\t\t\t}\n 704→\t\t\tif requireField(ctx, \"runningJobs\") {\n 705→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n 706→\t\t\t}\n 707→\t\t} else {\n 708→\t\t\tif requireField(ctx, \"shortJobs\") {\n 709→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n 710→\t\t\t}\n 711→\t\t\tif requireField(ctx, \"runningJobs\") {\n 712→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n 713→\t\t\t}\n 714→\t\t}\n 715→\t}\n 716→\n 717→\tif err != nil {\n 718→\t\treturn nil, err\n 719→\t}\n 720→\n 721→\tif requireField(ctx, \"histDuration\") || requireField(ctx, \"histNumNodes\") || requireField(ctx, \"histNumCores\") || requireField(ctx, \"histNumAccs\") {\n 722→\n 723→\t\tif numDurationBins == nil {\n 724→\t\t\tnumDurationBins = &defaultDurationBins\n 725→\t\t}\n 726→\n 727→\t\tif groupBy == nil {\n 728→\t\t\tstats[0], err = r.Repo.AddHistograms(ctx, filter, stats[0], numDurationBins)\n 729→\t\t\tif err != nil {\n 730→\t\t\t\treturn nil, err\n 731→\t\t\t}\n 732→\t\t} else {\n 733→\t\t\treturn nil, errors.New(\"histograms only implemented without groupBy argument\")\n 734→\t\t}\n 735→\t}\n 736→\n 737→\tif requireField(ctx, \"histMetrics\") {\n 738→\n 739→\t\tif numMetricBins == nil {\n 740→\t\t\tnumMetricBins = &defaultMetricBins\n 741→\t\t}\n 742→\n 743→\t\tif groupBy == nil {\n 744→\t\t\tstats[0], err = r.Repo.AddMetricHistograms(ctx, filter, metrics, stats[0], numMetricBins)\n 745→\t\t\tif err != nil {\n 746→\t\t\t\treturn nil, err\n 747→\t\t\t}\n 748→\t\t} else {\n 749→\t\t\treturn nil, errors.New(\"metric histograms only implemented without groupBy argument\")\n 750→\t\t}\n 751→\t}\n 752→\n 753→\treturn stats, nil\n 754→}\n 755→\n 756→// JobsMetricStats is the resolver for the jobsMetricStats field.\n 757→func (r *queryResolver) JobsMetricStats(ctx context.Context, filter []*model.JobFilter, metrics []string) ([]*model.JobStats, error) {\n 758→\t// No Paging, Fixed Order by StartTime ASC\n 759→\torder := &model.OrderByInput{\n 760→\t\tField: \"startTime\",\n 761→\t\tType: \"col\",\n 762→\t\tOrder: \"ASC\",\n 763→\t}\n 764→\n 765→\tjobs, err := r.Repo.QueryJobs(ctx, filter, nil, order)\n 766→\tif err != nil {\n 767→\t\tcclog.Warn(\"Error while querying jobs for comparison\")\n 768→\t\treturn nil, err\n 769→\t}\n 770→\n 771→\tres := []*model.JobStats{}\n 772→\tfor _, job := range jobs {\n 773→\t\tdata, err := metricdispatch.LoadJobStats(job, metrics, ctx)\n 774→\t\tif err != nil {\n 775→\t\t\tcclog.Warnf(\"Error while loading comparison jobStats data for job id %d\", job.JobID)\n 776→\t\t\tcontinue\n 777→\t\t\t// return nil, err\n 778→\t\t}\n 779→\n 780→\t\tsres := []*model.NamedStats{}\n 781→\t\tfor name, md := range data {\n 782→\t\t\tsres = append(sres, &model.NamedStats{\n 783→\t\t\t\tName: name,\n 784→\t\t\t\tData: &md,\n 785→\t\t\t})\n 786→\t\t}\n 787→\n 788→\t\tnumThreadsInt := int(job.NumHWThreads)\n 789→\t\tnumAccsInt := int(job.NumAcc)\n 790→\t\tres = append(res, &model.JobStats{\n 791→\t\t\tID: int(*job.ID),\n 792→\t\t\tJobID: strconv.Itoa(int(job.JobID)),\n 793→\t\t\tStartTime: int(job.StartTime),\n 794→\t\t\tDuration: int(job.Duration),\n 795→\t\t\tCluster: job.Cluster,\n 796→\t\t\tSubCluster: job.SubCluster,\n 797→\t\t\tNumNodes: int(job.NumNodes),\n 798→\t\t\tNumHWThreads: &numThreadsInt,\n 799→\t\t\tNumAccelerators: &numAccsInt,\n 800→\t\t\tStats: sres,\n 801→\t\t})\n 802→\t}\n 803→\treturn res, err\n 804→}\n 805→\n 806→// JobsFootprints is the resolver for the jobsFootprints field.\n 807→func (r *queryResolver) JobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n 808→\t// NOTE: Legacy Naming! This resolver is for normalized histograms in analysis view only - *Not* related to DB \"footprint\" column!\n 809→\treturn r.jobsFootprints(ctx, filter, metrics)\n 810→}\n 811→\n 812→// RooflineHeatmap is the resolver for the rooflineHeatmap field.\n 813→func (r *queryResolver) RooflineHeatmap(ctx context.Context, filter []*model.JobFilter, rows int, cols int, minX float64, minY float64, maxX float64, maxY float64) ([][]float64, error) {\n 814→\treturn r.rooflineHeatmap(ctx, filter, rows, cols, minX, minY, maxX, maxY)\n 815→}\n 816→\n 817→// NodeMetrics is the resolver for the nodeMetrics field.\n 818→func (r *queryResolver) NodeMetrics(ctx context.Context, cluster string, nodes []string, scopes []schema.MetricScope, metrics []string, from time.Time, to time.Time) ([]*model.NodeMetrics, error) {\n 819→\tuser := repository.GetUserFromContext(ctx)\n 820→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 821→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 822→\t}\n 823→\n 824→\tdefaultMetrics := make([]string, 0)\n 825→\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 826→\t\tdefaultMetrics = append(defaultMetrics, mc.Name)\n 827→\t}\n 828→\tif metrics == nil {\n 829→\t\tmetrics = defaultMetrics\n 830→\t} else {\n 831→\t\tmetrics = slices.DeleteFunc(metrics, func(metric string) bool {\n 832→\t\t\treturn !slices.Contains(defaultMetrics, metric) // Remove undefined metrics.\n 833→\t\t})\n 834→\t}\n 835→\n 836→\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nodes, scopes, from, to, ctx)\n 837→\tif err != nil {\n 838→\t\tcclog.Warn(\"error while loading node data\")\n 839→\t\treturn nil, err\n 840→\t}\n 841→\n 842→\tnodeRepo := repository.GetNodeRepository()\n 843→\tstateMap, _ := nodeRepo.MapNodes(cluster)\n 844→\n 845→\tnodeMetrics := make([]*model.NodeMetrics, 0, len(data))\n 846→\tfor hostname, metrics := range data {\n 847→\t\thost := &model.NodeMetrics{\n 848→\t\t\tHost: hostname,\n 849→\t\t\tState: stateMap[hostname],\n 850→\t\t\tMetrics: make([]*model.JobMetricWithName, 0, len(metrics)*len(scopes)),\n 851→\t\t}\n 852→\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n 853→\t\tif err != nil {\n 854→\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n 855→\t\t}\n 856→\n 857→\t\tfor metric, scopedMetrics := range metrics {\n 858→\t\t\tfor _, scopedMetric := range scopedMetrics {\n 859→\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n 860→\t\t\t\t\tName: metric,\n 861→\t\t\t\t\tScope: schema.MetricScopeNode,\n 862→\t\t\t\t\tMetric: scopedMetric,\n 863→\t\t\t\t})\n 864→\t\t\t}\n 865→\t\t}\n 866→\n 867→\t\tnodeMetrics = append(nodeMetrics, host)\n 868→\t}\n 869→\n 870→\treturn nodeMetrics, nil\n 871→}\n 872→\n 873→// NodeMetricsList is the resolver for the nodeMetricsList field.\n 874→func (r *queryResolver) NodeMetricsList(ctx context.Context, cluster string, subCluster string, stateFilter string, nodeFilter string, scopes []schema.MetricScope, metrics []string, from time.Time, to time.Time, page *model.PageRequest, resolution *int) (*model.NodesResultList, error) {\n 875→\tif resolution == nil { // Load from Config\n 876→\t\tif config.Keys.EnableResampling != nil {\n 877→\t\t\tdefaultRes := slices.Max(config.Keys.EnableResampling.Resolutions)\n 878→\t\t\tresolution = &defaultRes\n 879→\t\t} else { // Set 0 (Loads configured metric timestep)\n 880→\t\t\tdefaultRes := 0\n 881→\t\t\tresolution = &defaultRes\n 882→\t\t}\n 883→\t}\n 884→\n 885→\tuser := repository.GetUserFromContext(ctx)\n 886→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 887→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 888→\t}\n 889→\n 890→\tnodeRepo := repository.GetNodeRepository()\n 891→\t// nodes -> array hostname\n 892→\tnodes, stateMap, countNodes, hasNextPage, nerr := nodeRepo.GetNodesForList(ctx, cluster, subCluster, stateFilter, nodeFilter, page)\n 893→\tif nerr != nil {\n 894→\t\treturn nil, errors.New(\"could not retrieve node list required for resolving NodeMetricsList\")\n 895→\t}\n 896→\n 897→\tif metrics == nil {\n 898→\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 899→\t\t\tmetrics = append(metrics, mc.Name)\n 900→\t\t}\n 901→\t}\n 902→\n 903→\t// data -> map hostname:jobdata\n 904→\tdata, err := metricdispatch.LoadNodeListData(cluster, subCluster, nodes, metrics, scopes, *resolution, from, to, ctx)\n 905→\tif err != nil {\n 906→\t\tcclog.Warn(\"error while loading node data (Resolver.NodeMetricsList\")\n 907→\t\treturn nil, err\n 908→\t}\n 909→\n 910→\tnodeMetricsList := make([]*model.NodeMetrics, 0, len(data))\n 911→\tfor _, hostname := range nodes {\n 912→\t\thost := &model.NodeMetrics{\n 913→\t\t\tHost: hostname,\n 914→\t\t\tState: stateMap[hostname],\n 915→\t\t\tMetrics: make([]*model.JobMetricWithName, 0),\n 916→\t\t}\n 917→\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n 918→\t\tif err != nil {\n 919→\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n 920→\t\t}\n 921→\n 922→\t\tfor metric, scopedMetrics := range data[hostname] {\n 923→\t\t\tfor scope, scopedMetric := range scopedMetrics {\n 924→\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n 925→\t\t\t\t\tName: metric,\n 926→\t\t\t\t\tScope: scope,\n 927→\t\t\t\t\tMetric: scopedMetric,\n 928→\t\t\t\t})\n 929→\t\t\t}\n 930→\t\t}\n 931→\n 932→\t\tnodeMetricsList = append(nodeMetricsList, host)\n 933→\t}\n 934→\n 935→\tnodeMetricsListResult := &model.NodesResultList{\n 936→\t\tItems: nodeMetricsList,\n 937→\t\t// TotalNodes depends on sum of nodes grouped on latest timestamp, see repo/node.go:357\n 938→\t\tTotalNodes: &countNodes,\n 939→\t\tHasNextPage: &hasNextPage,\n 940→\t}\n 941→\n 942→\treturn nodeMetricsListResult, nil\n 943→}\n 944→\n 945→// ClusterMetrics is the resolver for the clusterMetrics field.\n 946→func (r *queryResolver) ClusterMetrics(ctx context.Context, cluster string, metrics []string, from time.Time, to time.Time) (*model.ClusterMetrics, error) {\n 947→\tuser := repository.GetUserFromContext(ctx)\n 948→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 949→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 950→\t}\n 951→\n 952→\tif metrics == nil {\n 953→\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 954→\t\t\tmetrics = append(metrics, mc.Name)\n 955→\t\t}\n 956→\t}\n 957→\n 958→\t// 'nodes' == nil -> Defaults to all nodes of cluster for existing query workflow\n 959→\tscopes := []schema.MetricScope{\"node\"}\n 960→\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nil, scopes, from, to, ctx)\n 961→\tif err != nil {\n 962→\t\tcclog.Warn(\"error while loading node data\")\n 963→\t\treturn nil, err\n 964→\t}\n 965→\n 966→\tclusterMetricData := make([]*model.ClusterMetricWithName, 0)\n 967→\tclusterMetrics := model.ClusterMetrics{NodeCount: 0, Metrics: clusterMetricData}\n 968→\n 969→\tcollectorTimestep := make(map[string]int)\n 970→\tcollectorUnit := make(map[string]schema.Unit)\n 971→\tcollectorData := make(map[string][]schema.Float)\n 972→\n 973→\tfor _, metrics := range data {\n 974→\t\tclusterMetrics.NodeCount += 1\n 975→\t\tfor metric, scopedMetrics := range metrics {\n 976→\t\t\tfor _, scopedMetric := range scopedMetrics {\n 977→\t\t\t\t// Collect Info Once\n 978→\t\t\t\t_, okTimestep := collectorTimestep[metric]\n 979→\t\t\t\tif !okTimestep {\n 980→\t\t\t\t\tcollectorTimestep[metric] = scopedMetric.Timestep\n 981→\t\t\t\t}\n 982→\t\t\t\t_, okUnit := collectorUnit[metric]\n 983→\t\t\t\tif !okUnit {\n 984→\t\t\t\t\tcollectorUnit[metric] = scopedMetric.Unit\n 985→\t\t\t\t}\n 986→\t\t\t\t// Collect Data\n 987→\t\t\t\tfor _, ser := range scopedMetric.Series {\n 988→\t\t\t\t\t_, okData := collectorData[metric]\n 989→\t\t\t\t\t// Init With Datasize > 0\n 990→\t\t\t\t\tif !okData && len(ser.Data) != 0 {\n 991→\t\t\t\t\t\tcollectorData[metric] = make([]schema.Float, len(ser.Data))\n 992→\t\t\t\t\t} else if !okData {\n 993→\t\t\t\t\t\tcclog.Debugf(\"[SCHEMARESOLVER] clusterMetrics skip init: no data -> %s at %s; size %d\", metric, ser.Hostname, len(ser.Data))\n 994→\t\t\t\t\t}\n 995→\t\t\t\t\t// Sum if init'd and matching size\n 996→\t\t\t\t\tif okData && len(ser.Data) == len(collectorData[metric]) {\n 997→\t\t\t\t\t\tfor i, val := range ser.Data {\n 998→\t\t\t\t\t\t\tif val.IsNaN() {\n 999→\t\t\t\t\t\t\t\tcontinue\n 1000→\t\t\t\t\t\t\t} else {\n 1001→\t\t\t\t\t\t\t\tcollectorData[metric][i] += val\n 1002→\t\t\t\t\t\t\t}\n 1003→\t\t\t\t\t\t}\n 1004→\t\t\t\t\t} else if okData {\n 1005→\t\t\t\t\t\tcclog.Debugf(\"[SCHEMARESOLVER] clusterMetrics skip sum: data diff -> %s at %s; want size %d, have size %d\", metric, ser.Hostname, len(collectorData[metric]), len(ser.Data))\n 1006→\t\t\t\t\t}\n 1007→\t\t\t\t}\n 1008→\t\t\t}\n 1009→\t\t}\n 1010→\t}\n 1011→\n 1012→\tfor metricName, data := range collectorData {\n 1013→\t\t// use ccUnits for backend normalization to \"Tera\"\n 1014→\t\tp_old := ccunit.NewPrefix(collectorUnit[metricName].Prefix)\n 1015→\t\tp_new := ccunit.NewPrefix(\"T\")\n 1016→\t\tconvFunc := ccunit.GetPrefixPrefixFactor(p_old, p_new)\n 1017→\t\tu_new := schema.Unit{Prefix: p_new.Prefix(), Base: collectorUnit[metricName].Base}\n 1018→\n 1019→\t\troundedData := make([]schema.Float, 0)\n 1020→\t\tfor _, v_old := range data {\n 1021→\t\t\tv_new := math.Round(convFunc(float64(v_old)).(float64)*100.0) / 100.0\n 1022→\t\t\troundedData = append(roundedData, schema.Float(v_new))\n 1023→\t\t}\n 1024→\n 1025→\t\tcm := model.ClusterMetricWithName{\n 1026→\t\t\tName: metricName,\n 1027→\t\t\tUnit: &u_new,\n 1028→\t\t\tTimestep: collectorTimestep[metricName],\n 1029→\t\t\tData: roundedData,\n 1030→\t\t}\n 1031→\n 1032→\t\tclusterMetrics.Metrics = append(clusterMetrics.Metrics, &cm)\n 1033→\t}\n 1034→\n 1035→\treturn &clusterMetrics, nil\n 1036→}\n 1037→\n 1038→// NumberOfNodes is the resolver for the numberOfNodes field.\n 1039→func (r *subClusterResolver) NumberOfNodes(ctx context.Context, obj *schema.SubCluster) (int, error) {\n 1040→\tnodeList, err := archive.ParseNodeList(obj.Nodes)\n 1041→\tif err != nil {\n 1042→\t\treturn 0, err\n 1043→\t}\n 1044→\treturn nodeList.NodeCount(), nil\n 1045→}\n 1046→\n 1047→// Cluster returns generated.ClusterResolver implementation.\n 1048→func (r *Resolver) Cluster() generated.ClusterResolver { return &clusterResolver{r} }\n 1049→\n 1050→// Job returns generated.JobResolver implementation.\n 1051→func (r *Resolver) Job() generated.JobResolver { return &jobResolver{r} }\n 1052→\n 1053→// MetricValue returns generated.MetricValueResolver implementation.\n 1054→func (r *Resolver) MetricValue() generated.MetricValueResolver { return &metricValueResolver{r} }\n 1055→\n 1056→// Mutation returns generated.MutationResolver implementation.\n 1057→func (r *Resolver) Mutation() generated.MutationResolver { return &mutationResolver{r} }\n 1058→\n 1059→// Node returns generated.NodeResolver implementation.\n 1060→func (r *Resolver) Node() generated.NodeResolver { return &nodeResolver{r} }\n 1061→\n 1062→// Query returns generated.QueryResolver implementation.\n 1063→func (r *Resolver) Query() generated.QueryResolver { return &queryResolver{r} }\n 1064→\n 1065→// SubCluster returns generated.SubClusterResolver implementation.\n 1066→func (r *Resolver) SubCluster() generated.SubClusterResolver { return &subClusterResolver{r} }\n 1067→\n 1068→type clusterResolver struct{ *Resolver }\n 1069→type jobResolver struct{ *Resolver }\n 1070→type metricValueResolver struct{ *Resolver }\n 1071→type mutationResolver struct{ *Resolver }\n 1072→type nodeResolver struct{ *Resolver }\n 1073→type queryResolver struct{ *Resolver }\n 1074→type subClusterResolver struct{ *Resolver }\n 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+{"parentUuid":"68e38cea-a2ad-4248-94ed-ef9e407e3d3c","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NN7LzBDBBbMx4KFhLqiXxQ","type":"tool_result","content":" 1→scalar Time\n 2→scalar Any\n 3→\n 4→scalar NullableFloat\n 5→scalar MetricScope\n 6→scalar JobState\n 7→scalar SchedulerState\n 8→scalar MonitoringState\n 9→\n 10→type Node {\n 11→ id: ID!\n 12→ hostname: String!\n 13→ cluster: String!\n 14→ subCluster: String!\n 15→ jobsRunning: Int!\n 16→ cpusAllocated: Int\n 17→ memoryAllocated: Int\n 18→ gpusAllocated: Int\n 19→ schedulerState: SchedulerState!\n 20→ healthState: MonitoringState!\n 21→ metaData: Any\n 22→ healthData: Any\n 23→}\n 24→\n 25→type NodeStates {\n 26→ state: String!\n 27→ count: Int!\n 28→}\n 29→\n 30→type NodeStatesTimed {\n 31→ state: String!\n 32→ counts: [Int!]!\n 33→ times: [Int!]!\n 34→}\n 35→\n 36→type Job {\n 37→ id: ID!\n 38→ jobId: Int!\n 39→ user: String!\n 40→ project: String!\n 41→ cluster: String!\n 42→ subCluster: String!\n 43→ startTime: Time!\n 44→ duration: Int!\n 45→ walltime: Int!\n 46→ numNodes: Int!\n 47→ numHWThreads: Int!\n 48→ numAcc: Int!\n 49→ energy: Float!\n 50→ SMT: Int!\n 51→ shared: String!\n 52→ partition: String!\n 53→ arrayJobId: Int!\n 54→ monitoringStatus: Int!\n 55→ state: JobState!\n 56→ tags: [Tag!]!\n 57→ resources: [Resource!]!\n 58→ concurrentJobs: JobLinkResultList\n 59→ footprint: [FootprintValue]\n 60→ energyFootprint: [EnergyFootprintValue]\n 61→ metaData: Any\n 62→ userData: User\n 63→}\n 64→\n 65→type JobLink {\n 66→ id: ID!\n 67→ jobId: Int!\n 68→}\n 69→\n 70→type Cluster {\n 71→ name: String!\n 72→ partitions: [String!]! # Slurm partitions\n 73→ subClusters: [SubCluster!]! # Hardware partitions/subclusters\n 74→}\n 75→\n 76→type SubCluster {\n 77→ name: String!\n 78→ nodes: String!\n 79→ numberOfNodes: Int!\n 80→ processorType: String!\n 81→ socketsPerNode: Int!\n 82→ coresPerSocket: Int!\n 83→ threadsPerCore: Int!\n 84→ flopRateScalar: MetricValue!\n 85→ flopRateSimd: MetricValue!\n 86→ memoryBandwidth: MetricValue!\n 87→ topology: Topology!\n 88→ metricConfig: [MetricConfig!]!\n 89→ footprint: [String!]!\n 90→}\n 91→\n 92→type FootprintValue {\n 93→ name: String!\n 94→ stat: String!\n 95→ value: Float!\n 96→}\n 97→\n 98→type EnergyFootprintValue {\n 99→ hardware: String!\n 100→ metric: String!\n 101→ value: Float!\n 102→}\n 103→\n 104→type MetricValue {\n 105→ name: String\n 106→ unit: Unit!\n 107→ value: Float!\n 108→}\n 109→\n 110→type Topology {\n 111→ node: [Int!]\n 112→ socket: [[Int!]!]\n 113→ memoryDomain: [[Int!]!]\n 114→ die: [[Int!]!]\n 115→ core: [[Int!]!]\n 116→ accelerators: [Accelerator!]\n 117→}\n 118→\n 119→type Accelerator {\n 120→ id: String!\n 121→ type: String!\n 122→ model: String!\n 123→}\n 124→\n 125→type SubClusterConfig {\n 126→ name: String!\n 127→ peak: Float\n 128→ normal: Float\n 129→ caution: Float\n 130→ alert: Float\n 131→ remove: Boolean\n 132→}\n 133→\n 134→type MetricConfig {\n 135→ name: String!\n 136→ unit: Unit!\n 137→ scope: MetricScope!\n 138→ aggregation: String!\n 139→ timestep: Int!\n 140→ peak: Float!\n 141→ normal: Float\n 142→ caution: Float!\n 143→ alert: Float!\n 144→ lowerIsBetter: Boolean\n 145→ subClusters: [SubClusterConfig!]!\n 146→}\n 147→\n 148→type Tag {\n 149→ id: ID!\n 150→ type: String!\n 151→ name: String!\n 152→ scope: String!\n 153→}\n 154→\n 155→type Resource {\n 156→ hostname: String!\n 157→ hwthreads: [Int!]\n 158→ accelerators: [String!]\n 159→ configuration: String\n 160→}\n 161→\n 162→type JobMetricWithName {\n 163→ name: String!\n 164→ scope: MetricScope!\n 165→ metric: JobMetric!\n 166→}\n 167→\n 168→type ClusterMetricWithName {\n 169→ name: String!\n 170→ unit: Unit\n 171→ timestep: Int!\n 172→ data: [NullableFloat!]!\n 173→}\n 174→\n 175→type JobMetric {\n 176→ unit: Unit\n 177→ timestep: Int!\n 178→ series: [Series!]\n 179→ statisticsSeries: StatsSeries\n 180→}\n 181→\n 182→type Series {\n 183→ hostname: String!\n 184→ id: String\n 185→ statistics: MetricStatistics\n 186→ data: [NullableFloat!]!\n 187→}\n 188→\n 189→type StatsSeries {\n 190→ mean: [NullableFloat!]!\n 191→ median: [NullableFloat!]!\n 192→ min: [NullableFloat!]!\n 193→ max: [NullableFloat!]!\n 194→}\n 195→\n 196→type NamedStatsWithScope {\n 197→ name: String!\n 198→ scope: MetricScope!\n 199→ stats: [ScopedStats!]!\n 200→}\n 201→\n 202→type ScopedStats {\n 203→ hostname: String!\n 204→ id: String\n 205→ data: MetricStatistics!\n 206→}\n 207→\n 208→type JobStats {\n 209→ id: Int!\n 210→ jobId: String!\n 211→ startTime: Int!\n 212→ duration: Int!\n 213→ cluster: String!\n 214→ subCluster: String!\n 215→ numNodes: Int!\n 216→ numHWThreads: Int\n 217→ numAccelerators: Int\n 218→ stats: [NamedStats!]!\n 219→}\n 220→\n 221→type NamedStats {\n 222→ name: String!\n 223→ data: MetricStatistics!\n 224→}\n 225→\n 226→type Unit {\n 227→ base: String!\n 228→ prefix: String\n 229→}\n 230→\n 231→type MetricStatistics {\n 232→ avg: Float!\n 233→ min: Float!\n 234→ max: Float!\n 235→}\n 236→\n 237→type MetricFootprints {\n 238→ metric: String!\n 239→ data: [NullableFloat!]!\n 240→}\n 241→\n 242→type Footprints {\n 243→ timeWeights: TimeWeights!\n 244→ metrics: [MetricFootprints!]!\n 245→}\n 246→\n 247→type TimeWeights {\n 248→ nodeHours: [NullableFloat!]!\n 249→ accHours: [NullableFloat!]!\n 250→ coreHours: [NullableFloat!]!\n 251→}\n 252→\n 253→enum Aggregate {\n 254→ USER\n 255→ PROJECT\n 256→ CLUSTER\n 257→ SUBCLUSTER\n 258→}\n 259→enum SortByAggregate {\n 260→ TOTALWALLTIME\n 261→ TOTALJOBS\n 262→ TOTALUSERS\n 263→ TOTALNODES\n 264→ TOTALNODEHOURS\n 265→ TOTALCORES\n 266→ TOTALCOREHOURS\n 267→ TOTALACCS\n 268→ TOTALACCHOURS\n 269→}\n 270→\n 271→type NodeMetrics {\n 272→ host: String!\n 273→ state: String!\n 274→ subCluster: String!\n 275→ metrics: [JobMetricWithName!]!\n 276→}\n 277→\n 278→type ClusterMetrics {\n 279→ nodeCount: Int!\n 280→ metrics: [ClusterMetricWithName!]!\n 281→}\n 282→\n 283→type NodesResultList {\n 284→ items: [NodeMetrics!]!\n 285→ offset: Int\n 286→ limit: Int\n 287→ count: Int\n 288→ totalNodes: Int\n 289→ hasNextPage: Boolean\n 290→}\n 291→\n 292→type ClusterSupport {\n 293→ cluster: String!\n 294→ subClusters: [String!]!\n 295→}\n 296→\n 297→type GlobalMetricListItem {\n 298→ name: String!\n 299→ unit: Unit!\n 300→ scope: MetricScope!\n 301→ footprint: String\n 302→ availability: [ClusterSupport!]!\n 303→}\n 304→\n 305→type Count {\n 306→ name: String!\n 307→ count: Int!\n 308→}\n 309→\n 310→type User {\n 311→ username: String!\n 312→ name: String!\n 313→ email: String!\n 314→}\n 315→\n 316→input MetricStatItem {\n 317→ metricName: String!\n 318→ range: FloatRange!\n 319→}\n 320→\n 321→type Query {\n 322→ clusters: [Cluster!]! # List of all clusters\n 323→ tags: [Tag!]! # List of all tags\n 324→ globalMetrics: [GlobalMetricListItem!]!\n 325→\n 326→ user(username: String!): User\n 327→ allocatedNodes(cluster: String!): [Count!]!\n 328→\n 329→ ## Node Queries New\n 330→ node(id: ID!): Node\n 331→ nodes(filter: [NodeFilter!], order: OrderByInput): NodeStateResultList!\n 332→ nodesWithMeta(filter: [NodeFilter!], order: OrderByInput): NodeStateResultList!\n 333→ nodeStates(filter: [NodeFilter!]): [NodeStates!]!\n 334→ nodeStatesTimed(filter: [NodeFilter!], type: String!): [NodeStatesTimed!]!\n 335→\n 336→ job(id: ID!): Job\n 337→ jobMetrics(\n 338→ id: ID!\n 339→ metrics: [String!]\n 340→ scopes: [MetricScope!]\n 341→ resolution: Int\n 342→ ): [JobMetricWithName!]!\n 343→\n 344→ jobStats(id: ID!, metrics: [String!]): [NamedStats!]!\n 345→\n 346→ scopedJobStats(\n 347→ id: ID!\n 348→ metrics: [String!]\n 349→ scopes: [MetricScope!]\n 350→ ): [NamedStatsWithScope!]!\n 351→\n 352→ jobs(\n 353→ filter: [JobFilter!]\n 354→ page: PageRequest\n 355→ order: OrderByInput\n 356→ ): JobResultList!\n 357→\n 358→ jobsStatistics(\n 359→ filter: [JobFilter!]\n 360→ metrics: [String!]\n 361→ page: PageRequest\n 362→ sortBy: SortByAggregate\n 363→ groupBy: Aggregate\n 364→ numDurationBins: String\n 365→ numMetricBins: Int\n 366→ ): [JobsStatistics!]!\n 367→\n 368→ jobsMetricStats(filter: [JobFilter!], metrics: [String!]): [JobStats!]!\n 369→ jobsFootprints(filter: [JobFilter!], metrics: [String!]!): Footprints\n 370→\n 371→ rooflineHeatmap(\n 372→ filter: [JobFilter!]!\n 373→ rows: Int!\n 374→ cols: Int!\n 375→ minX: Float!\n 376→ minY: Float!\n 377→ maxX: Float!\n 378→ maxY: Float!\n 379→ ): [[Float!]!]!\n 380→\n 381→ nodeMetrics(\n 382→ cluster: String!\n 383→ nodes: [String!]\n 384→ scopes: [MetricScope!]\n 385→ metrics: [String!]\n 386→ from: Time!\n 387→ to: Time!\n 388→ ): [NodeMetrics!]!\n 389→\n 390→ nodeMetricsList(\n 391→ cluster: String!\n 392→ subCluster: String!\n 393→ stateFilter: String!\n 394→ nodeFilter: String!\n 395→ scopes: [MetricScope!]\n 396→ metrics: [String!]\n 397→ from: Time!\n 398→ to: Time!\n 399→ page: PageRequest\n 400→ resolution: Int\n 401→ ): NodesResultList!\n 402→\n 403→ clusterMetrics(\n 404→ cluster: String!\n 405→ metrics: [String!]\n 406→ from: Time!\n 407→ to: Time!\n 408→ ): ClusterMetrics!\n 409→}\n 410→\n 411→type Mutation {\n 412→ createTag(type: String!, name: String!, scope: String!): Tag!\n 413→ deleteTag(id: ID!): ID!\n 414→ addTagsToJob(job: ID!, tagIds: [ID!]!): [Tag!]!\n 415→ removeTagsFromJob(job: ID!, tagIds: [ID!]!): [Tag!]!\n 416→ removeTagFromList(tagIds: [ID!]!): [Int!]!\n 417→\n 418→ updateConfiguration(name: String!, value: String!): String\n 419→}\n 420→\n 421→type IntRangeOutput {\n 422→ from: Int!\n 423→ to: Int!\n 424→}\n 425→type TimeRangeOutput {\n 426→ range: String\n 427→ from: Time!\n 428→ to: Time!\n 429→}\n 430→\n 431→input NodeFilter {\n 432→ hostname: StringInput\n 433→ cluster: StringInput\n 434→ subCluster: StringInput\n 435→ schedulerState: SchedulerState\n 436→ healthState: MonitoringState\n 437→ timeStart: Int\n 438→}\n 439→\n 440→input JobFilter {\n 441→ tags: [ID!]\n 442→ dbId: [ID!]\n 443→ jobId: StringInput\n 444→ arrayJobId: Int\n 445→ user: StringInput\n 446→ project: StringInput\n 447→ jobName: StringInput\n 448→ cluster: StringInput\n 449→ subCluster: StringInput\n 450→ partition: StringInput\n 451→ duration: IntRange\n 452→ energy: FloatRange\n 453→\n 454→ minRunningFor: Int\n 455→\n 456→ numNodes: IntRange\n 457→ numAccelerators: IntRange\n 458→ numHWThreads: IntRange\n 459→\n 460→ startTime: TimeRange\n 461→ state: [JobState!]\n 462→ metricStats: [MetricStatItem!]\n 463→ shared: String\n 464→ schedule: String\n 465→ node: StringInput\n 466→}\n 467→\n 468→input OrderByInput {\n 469→ field: String!\n 470→ type: String!\n 471→ order: SortDirectionEnum! = ASC\n 472→}\n 473→\n 474→enum SortDirectionEnum {\n 475→ DESC\n 476→ ASC\n 477→}\n 478→\n 479→input StringInput {\n 480→ eq: String\n 481→ neq: String\n 482→ contains: String\n 483→ startsWith: String\n 484→ endsWith: String\n 485→ in: [String!]\n 486→}\n 487→\n 488→input IntRange {\n 489→ from: Int!\n 490→ to: Int!\n 491→}\n 492→input TimeRange {\n 493→ range: String\n 494→ from: Time\n 495→ to: Time\n 496→}\n 497→\n 498→input FloatRange {\n 499→ from: Float!\n 500→ to: Float!\n 501→}\n 502→\n 503→type NodeStateResultList {\n 504→ items: [Node!]!\n 505→ count: Int\n 506→}\n 507→\n 508→type JobResultList {\n 509→ items: [Job!]!\n 510→ offset: Int\n 511→ limit: Int\n 512→ count: Int\n 513→ hasNextPage: Boolean\n 514→}\n 515→\n 516→type JobLinkResultList {\n 517→ listQuery: String\n 518→ items: [JobLink!]!\n 519→ count: Int\n 520→}\n 521→\n 522→type HistoPoint {\n 523→ count: Int!\n 524→ value: Int!\n 525→}\n 526→\n 527→type MetricHistoPoints {\n 528→ metric: String!\n 529→ unit: String!\n 530→ stat: String\n 531→ data: [MetricHistoPoint!]\n 532→}\n 533→\n 534→type MetricHistoPoint {\n 535→ bin: Int\n 536→ count: Int!\n 537→ min: Int\n 538→ max: Int\n 539→}\n 540→\n 541→type JobsStatistics {\n 542→ id: ID! # If `groupBy` was used, ID of the user/project/cluster/subcluster\n 543→ name: String! # if User-Statistics: Given Name of Account (ID) Owner\n 544→ totalUsers: Int! # if *not* User-Statistics: Number of active users (based on running jobs)\n 545→ totalJobs: Int! # Number of jobs\n 546→ runningJobs: Int! # Number of running jobs\n 547→ shortJobs: Int! # Number of jobs with a duration of less than config'd ShortRunningJobsDuration\n 548→ totalWalltime: Int! # Sum of the duration of all matched jobs in hours\n 549→ totalNodes: Int! # Sum of the nodes of all matched jobs\n 550→ totalNodeHours: Int! # Sum of the node hours of all matched jobs\n 551→ totalCores: Int! # Sum of the cores of all matched jobs\n 552→ totalCoreHours: Int! # Sum of the core hours of all matched jobs\n 553→ totalAccs: Int! # Sum of the accs of all matched jobs\n 554→ totalAccHours: Int! # Sum of the gpu hours of all matched jobs\n 555→ histDuration: [HistoPoint!]! # value: hour, count: number of jobs with a rounded duration of value\n 556→ histNumNodes: [HistoPoint!]! # value: number of nodes, count: number of jobs with that number of nodes\n 557→ histNumCores: [HistoPoint!]! # value: number of cores, count: number of jobs with that number of cores\n 558→ histNumAccs: [HistoPoint!]! # value: number of accs, count: number of jobs with that number of accs\n 559→ histMetrics: [MetricHistoPoints!]! # metric: metricname, data array of histopoints: value: metric average bin, count: number of jobs with that metric average\n 560→}\n 561→\n 562→input PageRequest {\n 563→ itemsPerPage: Int!\n 564→ page: Int!\n 565→}\n 566→"}]},"uuid":"5c533d41-7ad1-49cf-9bda-99472c341b48","timestamp":"2026-03-19T10:06:41.731Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"063c4f18-2a54-4497-b891-5586057e6f8f","timestamp":"2026-03-19T10:06:41.737Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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+{"parentUuid":"8b728f80-0a7a-432b-ad8e-6d6daecf974f","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HArcyCtk6TsDAkocxBq6Ay","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→package graph\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"fmt\"\n 11→\t\"math\"\n 12→\t\"slices\"\n 13→\n 14→\t\"github.com/99designs/gqlgen/graphql\"\n 15→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 16→\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n 17→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 18→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 19→)\n 20→\n 21→const MAX_JOBS_FOR_ANALYSIS = 500\n 22→\n 23→// Helper function for the rooflineHeatmap GraphQL query placed here so that schema.resolvers.go is not too full.\n 24→func (r *queryResolver) rooflineHeatmap(\n 25→\tctx context.Context,\n 26→\tfilter []*model.JobFilter,\n 27→\trows int, cols int,\n 28→\tminX float64, minY float64, maxX float64, maxY float64,\n 29→) ([][]float64, error) {\n 30→\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n 31→\tif err != nil {\n 32→\t\tcclog.Error(\"Error while querying jobs for roofline\")\n 33→\t\treturn nil, err\n 34→\t}\n 35→\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n 36→\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n 37→\t}\n 38→\n 39→\tfcols, frows := float64(cols), float64(rows)\n 40→\tminX, minY, maxX, maxY = math.Log10(minX), math.Log10(minY), math.Log10(maxX), math.Log10(maxY)\n 41→\ttiles := make([][]float64, rows)\n 42→\tfor i := range tiles {\n 43→\t\ttiles[i] = make([]float64, cols)\n 44→\t}\n 45→\n 46→\tfor _, job := range jobs {\n 47→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 48→\t\t\tcontinue\n 49→\t\t}\n 50→\n 51→\t\t// metricConfigs := archive.GetCluster(job.Cluster).MetricConfig\n 52→\t\t// resolution := 0\n 53→\n 54→\t\t// for _, mc := range metricConfigs {\n 55→\t\t// \tresolution = max(resolution, mc.Timestep)\n 56→\t\t// }\n 57→\n 58→\t\tjobdata, err := metricdispatch.LoadData(job, []string{\"flops_any\", \"mem_bw\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 0)\n 59→\t\tif err != nil {\n 60→\t\t\tcclog.Warnf(\"Error while loading roofline metrics for job %d\", *job.ID)\n 61→\t\t\treturn nil, err\n 62→\t\t}\n 63→\n 64→\t\tflops_, membw_ := jobdata[\"flops_any\"], jobdata[\"mem_bw\"]\n 65→\t\tif flops_ == nil && membw_ == nil {\n 66→\t\t\tcclog.Warnf(\"rooflineHeatmap(): 'flops_any' or 'mem_bw' missing for job %d\", *job.ID)\n 67→\t\t\tcontinue\n 68→\t\t\t// return nil, fmt.Errorf(\"GRAPH/UTIL > 'flops_any' or 'mem_bw' missing for job %d\", job.ID)\n 69→\t\t}\n 70→\n 71→\t\tflops, ok1 := flops_[\"node\"]\n 72→\t\tmembw, ok2 := membw_[\"node\"]\n 73→\t\tif !ok1 || !ok2 {\n 74→\t\t\tcclog.Info(\"rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level\")\n 75→\t\t\tcontinue\n 76→\t\t\t// TODO/FIXME:\n 77→\t\t\t// return nil, errors.New(\"GRAPH/UTIL > todo: rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level\")\n 78→\t\t}\n 79→\n 80→\t\tfor n := 0; n < len(flops.Series); n++ {\n 81→\t\t\tflopsSeries, membwSeries := flops.Series[n], membw.Series[n]\n 82→\t\t\tfor i := 0; i < len(flopsSeries.Data); i++ {\n 83→\t\t\t\tif i >= len(membwSeries.Data) {\n 84→\t\t\t\t\tbreak\n 85→\t\t\t\t}\n 86→\n 87→\t\t\t\tx, y := math.Log10(float64(flopsSeries.Data[i]/membwSeries.Data[i])), math.Log10(float64(flopsSeries.Data[i]))\n 88→\t\t\t\tif math.IsNaN(x) || math.IsNaN(y) || x < minX || x >= maxX || y < minY || y > maxY {\n 89→\t\t\t\t\tcontinue\n 90→\t\t\t\t}\n 91→\n 92→\t\t\t\tx, y = math.Floor(((x-minX)/(maxX-minX))*fcols), math.Floor(((y-minY)/(maxY-minY))*frows)\n 93→\t\t\t\tif x < 0 || x >= fcols || y < 0 || y >= frows {\n 94→\t\t\t\t\tcontinue\n 95→\t\t\t\t}\n 96→\n 97→\t\t\t\ttiles[int(y)][int(x)] += 1\n 98→\t\t\t}\n 99→\t\t}\n 100→\t}\n 101→\n 102→\treturn tiles, nil\n 103→}\n 104→\n 105→// Helper function for the jobsFootprints GraphQL query placed here so that schema.resolvers.go is not too full.\n 106→func (r *queryResolver) jobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n 107→\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n 108→\tif err != nil {\n 109→\t\tcclog.Error(\"Error while querying jobs for footprint\")\n 110→\t\treturn nil, err\n 111→\t}\n 112→\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n 113→\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n 114→\t}\n 115→\n 116→\tavgs := make([][]schema.Float, len(metrics))\n 117→\tfor i := range avgs {\n 118→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n 119→\t}\n 120→\n 121→\ttimeweights := new(model.TimeWeights)\n 122→\ttimeweights.NodeHours = make([]schema.Float, 0, len(jobs))\n 123→\ttimeweights.AccHours = make([]schema.Float, 0, len(jobs))\n 124→\ttimeweights.CoreHours = make([]schema.Float, 0, len(jobs))\n 125→\n 126→\tfor _, job := range jobs {\n 127→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 128→\t\t\tcontinue\n 129→\t\t}\n 130→\n 131→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n 132→\t\t\tcclog.Error(\"Error while loading averages for footprint\")\n 133→\t\t\treturn nil, err\n 134→\t\t}\n 135→\n 136→\t\t// #166 collect arrays: Null values or no null values?\n 137→\t\ttimeweights.NodeHours = append(timeweights.NodeHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumNodes)))\n 138→\t\tif job.NumAcc > 0 {\n 139→\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumAcc)))\n 140→\t\t} else {\n 141→\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(1.0))\n 142→\t\t}\n 143→\t\tif job.NumHWThreads > 0 {\n 144→\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumHWThreads))) // SQLite HWThreads == Cores; numCoresForJob(job)\n 145→\t\t} else {\n 146→\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(1.0))\n 147→\t\t}\n 148→\t}\n 149→\n 150→\tres := make([]*model.MetricFootprints, len(avgs))\n 151→\tfor i, arr := range avgs {\n 152→\t\tres[i] = &model.MetricFootprints{\n 153→\t\t\tMetric: metrics[i],\n 154→\t\t\tData: arr,\n 155→\t\t}\n 156→\t}\n 157→\n 158→\treturn &model.Footprints{\n 159→\t\tTimeWeights: timeweights,\n 160→\t\tMetrics: res,\n 161→\t}, nil\n 162→}\n 163→\n 164→// func numCoresForJob(job *schema.Job) (numCores int) {\n 165→\n 166→// \tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n 167→// \tif scerr != nil {\n 168→// \t\treturn 1\n 169→// \t}\n 170→\n 171→// \ttotalJobCores := 0\n 172→// \ttopology := subcluster.Topology\n 173→\n 174→// \tfor _, host := range job.Resources {\n 175→// \t\thwthreads := host.HWThreads\n 176→// \t\tif hwthreads == nil {\n 177→// \t\t\thwthreads = topology.Node\n 178→// \t\t}\n 179→\n 180→// \t\thostCores, _ := topology.GetCoresFromHWThreads(hwthreads)\n 181→// \t\ttotalJobCores += len(hostCores)\n 182→// \t}\n 183→\n 184→// \treturn totalJobCores\n 185→// }\n 186→\n 187→func requireField(ctx context.Context, name string) bool {\n 188→\tfields := graphql.CollectAllFields(ctx)\n 189→\n 190→\treturn slices.Contains(fields, name)\n 191→}\n 192→"}]},"uuid":"37372227-95f1-4017-baf0-bb81965fa84e","timestamp":"2026-03-19T10:06:41.756Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"b7ae670d-286d-4999-95aa-6c58ad8a0bc0","timestamp":"2026-03-19T10:06:41.764Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"b7ae670d-286d-4999-95aa-6c58ad8a0bc0","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-19T10:06:44.313Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01UmtVK2tkhRqLSHvcKp8cNk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015V1vPWxVsHdxJsEujXEDq7","name":"Grep","input":{"pattern":"func sortAndPageStats","path":"/Users/jan/prg/ClusterCockpit/cc-backend","output_mode":"content","context":10},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":24542,"cache_read_input_tokens":19242,"cache_creation":{"ephemeral_5m_input_tokens":24542,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZCFbzSxPj9cYwXGHjnzJ","uuid":"e880934b-2662-4e41-b71b-ca1fc3ef159f"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"01f21cf5-3ac3-4e3d-88cb-3d91812cb411","timestamp":"2026-03-19T10:06:44.314Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"01f21cf5-3ac3-4e3d-88cb-3d91812cb411","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015V1vPWxVsHdxJsEujXEDq7","type":"tool_result","content":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-73-\tc.mu.Unlock()\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-74-\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-75-\tentry.once.Do(func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-76-\t\tentry.result, entry.err = compute()\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-77-\t})\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-78-\treturn entry.result, entry.err\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-79-}\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-80-\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-81-// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-82-// and returns the requested page slice.\ninternal/graph/stats_cache.go:83:func sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-84-\t// Work on a shallow copy so the cached slice order is not mutated.\ninternal/graph/stats_cache.go-85-\tsorted := make([]*model.JobsStatistics, len(allStats))\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-86-\tcopy(sorted, allStats)\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-87-\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-88-\tif sortBy != nil {\ninternal/graph/stats_cache.go-89-\t\tgetter := statsFieldGetter(*sortBy)\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-90-\t\tslices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-91-\t\t\treturn getter(b) - getter(a) // descending\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-92-\t\t})\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go-93-\t}"}]},"uuid":"7e7c17ab-d143-4304-9508-23702df4ce23","timestamp":"2026-03-19T10:06:44.357Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"9693a055-f35a-4998-a145-0df3a92abd06","timestamp":"2026-03-19T10:06:44.865Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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+{"parentUuid":"a16aa741-f236-4253-be4d-1b74192e7d04","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HDrPoABijhodB4upcpsGUN","type":"tool_result","content":" 1→\n 7→\n 8→ \n 81→\n 82→\n 83→\n 84→ \n 85→ (isHistogramSelectionOpen = true)}\n 89→ >\n 90→ Select Histograms\n 91→ \n 92→ \n 93→ \n 94→ {\n 97→ selectedHistograms = [...$state.snapshot(selectedHistograms)]\n 98→ }}\n 99→ />\n 100→ \n 101→\n 102→\n 103→\n 104→ {#if $metricStatusQuery?.fetching}\n 105→ \n 106→ \n 107→ \n 108→ {:else if $metricStatusQuery?.error}\n 109→ \n 110→ {$metricStatusQuery.error.message}\n 111→ \n 112→ {/if}\n 113→\n 114→\n 115→{#if $metricStatusQuery?.data}\n 116→ \n 117→ {#if selectedHistograms}\n 118→ \n 119→ {#snippet gridContent(item)}\n 120→ \n 130→ {/snippet}\n 131→ \n 132→ {#key $metricStatusQuery?.data?.jobsStatistics[0]?.histMetrics}\n 133→ \n 138→ {/key}\n 139→ {/if}\n 140→{/if}\n 141→\n 142→ {\n 149→ selectedHistograms = [...newSelection];\n 150→ }}\n 151→/>\n 152→"}]},"uuid":"dd9cbf0f-4a48-416c-ab59-12a323090437","timestamp":"2026-03-19T10:06:45.003Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"913a21c9-cfb2-48b9-b20d-09df9c1ce6dd","timestamp":"2026-03-19T10:06:45.007Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"913a21c9-cfb2-48b9-b20d-09df9c1ce6dd","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-19T10:06:45.048Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01UmtVK2tkhRqLSHvcKp8cNk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017NHbvPExj3VmLuMRhji5AH","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/Analysis.root.svelte"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":24542,"cache_read_input_tokens":19242,"cache_creation":{"ephemeral_5m_input_tokens":24542,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZCFbzSxPj9cYwXGHjnzJ","uuid":"6ad0f0d1-9e06-49e0-88d2-4111dc020660"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"9145c1fa-b8b9-408d-911c-a34a73c47ad7","timestamp":"2026-03-19T10:06:45.049Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"9145c1fa-b8b9-408d-911c-a34a73c47ad7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017NHbvPExj3VmLuMRhji5AH","type":"tool_result","content":" 1→\n 7→\n 8→\n 335→\n 336→\n 337→ {#if $initq.fetching || $statsQuery.fetching || $footprintsQuery.fetching}\n 338→ \n 339→ \n 340→ \n 341→ {/if}\n 342→ \n 343→ {#if $initq.error}\n 344→ {$initq.error.message}\n 345→ {:else if cluster}\n 346→ av.name)}\n 348→ presetMetricsInHistograms={metricsInHistograms}\n 349→ presetMetricsInScatterplots={metricsInScatterplots}\n 350→ applyHistograms={(metrics) => metricsInHistograms = [...metrics]}\n 351→ applyScatter={(metrics) => metricsInScatterplots = [...metrics]}\n 352→ />\n 353→ {/if}\n 354→ \n 355→ \n 356→ {\n 362→ jobFilters = detail.filters;\n 363→ }}\n 364→ />\n 365→ \n 366→\n 367→\n 368→
\n 369→{#if $statsQuery.error}\n 370→ \n 371→ \n 372→ {$statsQuery.error.message}\n 373→ \n 374→ \n 375→{:else if $statsQuery.data}\n 376→ \n 377→ \n 378→ \n 379→ \n 380→ \n 381→ \n 382→ \n 383→ \n 384→ \n 385→ \n 386→ \n 387→ \n 388→ \n 389→ \n 390→ \n 391→ \n 392→ \n 393→ \n 394→ \n 395→ \n 396→ \n 397→ \n 398→ \n 399→ \n 400→ \n 401→ \n 402→ \n 403→
Total Jobs{$statsQuery.data.stats[0].totalJobs}
Short Jobs{$statsQuery.data.stats[0].shortJobs}
Total Walltime{$statsQuery.data.stats[0].totalWalltime}
Total Node Hours{$statsQuery.data.stats[0].totalNodeHours}
Total Core Hours{$statsQuery.data.stats[0].totalCoreHours}
Total Accelerator Hours{$statsQuery.data.stats[0].totalAccHours}
\n 404→ \n 405→ \n 406→
\n 407→
\n 408→ Top\n 409→ \n 416→
\n 417→ {#key $topQuery.data}\n 418→ {#if $topQuery.fetching}\n 419→ \n 420→ {:else if $topQuery.error}\n 421→ {$topQuery.error.message}\n 422→ {:else}\n 423→ t[sortSelection.key],\n 429→ )}\n 430→ entities={$topQuery.data.topList.map((t) => scrambleNames ? scramble(t.id) : t.id)}\n 431→ />\n 432→ {/if}\n 433→ {/key}\n 434→
\n 435→ \n 436→ \n 437→ {#key $topQuery.data}\n 438→ {#if $topQuery.fetching}\n 439→ \n 440→ {:else if $topQuery.error}\n 441→ {$topQuery.error.message}\n 442→ {:else}\n 443→ \n 444→ \n 445→ \n 446→ \n 447→ \n 456→ \n 457→ {#each $topQuery.data.topList as te, i}\n 458→ \n 459→ \n 460→ {#if groupSelection.key == \"user\"}\n 461→ \n 482→ \n 483→ {/each}\n 484→
Legend{groupSelection.label}\n 448→ \n 455→
{scrambleNames ? scramble(te.id) : te.id}\n 466→ {#if te?.name}\n 467→ {scrambleNames ? scramble(te.name) : te.name}\n 472→ {/if}\n 473→ {:else}\n 474→ {scrambleNames ? scramble(te.id) : te.id}\n 480→ {/if}\n 481→ {te[sortSelection.key]}
\n 485→ {/if}\n 486→ {/key}\n 487→ \n 488→ \n 489→ \n 490→ \n 491→ {#if $rooflineQuery.fetching}\n 492→ \n 493→ {:else if $rooflineQuery.error}\n 494→ {$rooflineQuery.error.message}\n 495→ {:else if $rooflineQuery.data && cluster}\n 496→
\n 497→
Job Roofline Heatmap
\n 498→ \n 503→
\n 504→
\n 505→ {#key $rooflineQuery.data}\n 506→ = 1\n 511→ ? cluster.subClusters[0]\n 512→ : null}\n 513→ maxY={rooflineMaxY}\n 514→ />\n 515→ {/key}\n 516→
\n 517→ {/if}\n 518→ \n 519→ \n 520→ {#key $statsQuery.data.stats[0].histDuration}\n 521→ \n 532→ {/key}\n 533→ \n 534→ \n 535→ {#key $statsQuery.data.stats[0].histNumCores}\n 536→ \n 545→ {/key}\n 546→ \n 547→ \n 548→{/if}\n 549→\n 550→
\n 551→\n 552→{#if $footprintsQuery.error}\n 553→ \n 554→ \n 555→ {$footprintsQuery.error.message}\n 556→ \n 557→ \n 558→{:else if $footprintsQuery.data && $initq.data}\n 559→ \n 560→ \n 561→ \n 562→ These histograms show the distribution of the averages of all jobs\n 563→ matching the filters. Each job/average is weighted by its node hours by\n 564→ default (Accelerator hours for native accelerator scope metrics,\n 565→ coreHours for native core scope metrics). Note that some metrics could\n 566→ be disabled for specific subclusters as per metricConfig and thus could\n 567→ affect shown average values.\n 568→ \n 569→
\n 570→ \n 571→ \n 572→ \n 573→ \n 574→ \n 575→ {#snippet histoGridContent(item)}\n 576→ \n 585→ {/snippet}\n 586→\n 587→ ({\n 589→ metric,\n 590→ ...binsFromFootprint(\n 591→ $footprintsQuery.data.footprints.timeWeights,\n 592→ metricScopes[metric],\n 593→ $footprintsQuery.data.footprints.metrics.find(\n 594→ (f) => f.metric == metric,\n 595→ ).data,\n 596→ numBins,\n 597→ ),\n 598→ }))}\n 599→ itemsPerRow={ccconfig.plotConfiguration_plotsPerRow}\n 600→ gridContent={histoGridContent}\n 601→ />\n 602→ \n 603→ \n 604→
\n 605→ \n 606→ \n 607→ \n 608→ Each circle represents one job. The size of a circle is proportional to\n 609→ its node hours. Darker circles mean multiple jobs have the same averages\n 610→ for the respective metrics. Note that some metrics could be disabled for\n 611→ specific subclusters as per metricConfig and thus could affect shown\n 612→ average values.\n 613→ \n 614→
\n 615→ \n 616→ \n 617→ \n 618→ \n 619→ {#snippet metricsGridContent(item)}\n 620→ \n 629→ {/snippet}\n 630→\n 631→ ({\n 633→ m1,\n 634→ f1: $footprintsQuery.data.footprints.metrics.find(\n 635→ (f) => f.metric == m1,\n 636→ ).data,\n 637→ m2,\n 638→ f2: $footprintsQuery.data.footprints.metrics.find(\n 639→ (f) => f.metric == m2,\n 640→ ).data,\n 641→ }))}\n 642→ itemsPerRow={ccconfig.plotConfiguration_plotsPerRow}\n 643→ gridContent={metricsGridContent}\n 644→ />\n 645→ \n 646→ \n 647→{/if}\n 648→\n 649→\n 654→"}]},"uuid":"c2d836fd-5427-4bda-af46-6536174673e3","timestamp":"2026-03-19T10:06:45.059Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"56c15e07-9f97-4e5c-bfd4-26fe8fc41d83","timestamp":"2026-03-19T10:06:45.060Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"56c15e07-9f97-4e5c-bfd4-26fe8fc41d83","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-19T10:06:47.306Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01LvmLKSZXwa8MizVUJWBt4D","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018smE7UmaqQCPLqfgiWYAhD","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":10869,"cache_read_input_tokens":43784,"cache_creation":{"ephemeral_5m_input_tokens":10869,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZCFcEUozvDC5sjtHW9pK","uuid":"9ebd50b5-9f4b-4a84-801d-07c871be6311"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"f79010bb-fbbc-4e84-8de6-4d90774df605","timestamp":"2026-03-19T10:06:47.307Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} +{"parentUuid":"f79010bb-fbbc-4e84-8de6-4d90774df605","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018smE7UmaqQCPLqfgiWYAhD","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→package graph\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"fmt\"\n 11→\t\"slices\"\n 12→\t\"sync\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 15→)\n 16→\n 17→// statsGroupCache is a per-request cache for grouped JobsStatistics results.\n 18→// It deduplicates identical (filter+groupBy) SQL queries that arise when the\n 19→// frontend requests multiple sort/page slices of the same underlying data\n 20→// (e.g. topUserJobs, topUserNodes, topUserAccs all group by USER).\n 21→type statsGroupCache struct {\n 22→\tmu sync.Mutex\n 23→\tentries map[string]*cacheEntry\n 24→}\n 25→\n 26→type cacheEntry struct {\n 27→\tonce sync.Once\n 28→\tresult []*model.JobsStatistics\n 29→\terr error\n 30→}\n 31→\n 32→type ctxKey int\n 33→\n 34→const statsGroupCacheKey ctxKey = iota\n 35→\n 36→// newStatsGroupCache creates a new empty cache.\n 37→func newStatsGroupCache() *statsGroupCache {\n 38→\treturn &statsGroupCache{\n 39→\t\tentries: make(map[string]*cacheEntry),\n 40→\t}\n 41→}\n 42→\n 43→// WithStatsGroupCache injects a new cache into the context.\n 44→func WithStatsGroupCache(ctx context.Context) context.Context {\n 45→\treturn context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())\n 46→}\n 47→\n 48→// getStatsGroupCache retrieves the cache from context, or nil if absent.\n 49→func getStatsGroupCache(ctx context.Context) *statsGroupCache {\n 50→\tif c, ok := ctx.Value(statsGroupCacheKey).(*statsGroupCache); ok {\n 51→\t\treturn c\n 52→\t}\n 53→\treturn nil\n 54→}\n 55→\n 56→// cacheKey builds a deterministic string key from filter + groupBy + reqFields.\n 57→func statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate, reqFields map[string]bool) string {\n 58→\treturn fmt.Sprintf(\"%v|%v|%v\", filter, *groupBy, reqFields)\n 59→}\n 60→\n 61→// getOrCompute returns cached results for the given key, computing them on\n 62→// first access via the provided function.\n 63→func (c *statsGroupCache) getOrCompute(\n 64→\tkey string,\n 65→\tcompute func() ([]*model.JobsStatistics, error),\n 66→) ([]*model.JobsStatistics, error) {\n 67→\tc.mu.Lock()\n 68→\tentry, ok := c.entries[key]\n 69→\tif !ok {\n 70→\t\tentry = &cacheEntry{}\n 71→\t\tc.entries[key] = entry\n 72→\t}\n 73→\tc.mu.Unlock()\n 74→\n 75→\tentry.once.Do(func() {\n 76→\t\tentry.result, entry.err = compute()\n 77→\t})\n 78→\treturn entry.result, entry.err\n 79→}\n 80→\n 81→// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)\n 82→// and returns the requested page slice.\n 83→func sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {\n 84→\t// Work on a shallow copy so the cached slice order is not mutated.\n 85→\tsorted := make([]*model.JobsStatistics, len(allStats))\n 86→\tcopy(sorted, allStats)\n 87→\n 88→\tif sortBy != nil {\n 89→\t\tgetter := statsFieldGetter(*sortBy)\n 90→\t\tslices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {\n 91→\t\t\treturn getter(b) - getter(a) // descending\n 92→\t\t})\n 93→\t}\n 94→\n 95→\tif page != nil && page.ItemsPerPage != -1 {\n 96→\t\tstart := (page.Page - 1) * page.ItemsPerPage\n 97→\t\tif start >= len(sorted) {\n 98→\t\t\treturn nil\n 99→\t\t}\n 100→\t\tend := start + page.ItemsPerPage\n 101→\t\tif end > len(sorted) {\n 102→\t\t\tend = len(sorted)\n 103→\t\t}\n 104→\t\tsorted = sorted[start:end]\n 105→\t}\n 106→\n 107→\treturn sorted\n 108→}\n 109→\n 110→// statsFieldGetter returns a function that extracts the sortable int field\n 111→// from a JobsStatistics struct for the given sort key.\n 112→func statsFieldGetter(sortBy model.SortByAggregate) func(*model.JobsStatistics) int {\n 113→\tswitch sortBy {\n 114→\tcase model.SortByAggregateTotaljobs:\n 115→\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n 116→\tcase model.SortByAggregateTotalusers:\n 117→\t\treturn func(s *model.JobsStatistics) int { return s.TotalUsers }\n 118→\tcase model.SortByAggregateTotalwalltime:\n 119→\t\treturn func(s *model.JobsStatistics) int { return s.TotalWalltime }\n 120→\tcase model.SortByAggregateTotalnodes:\n 121→\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodes }\n 122→\tcase model.SortByAggregateTotalnodehours:\n 123→\t\treturn func(s *model.JobsStatistics) int { return s.TotalNodeHours }\n 124→\tcase model.SortByAggregateTotalcores:\n 125→\t\treturn func(s *model.JobsStatistics) int { return s.TotalCores }\n 126→\tcase model.SortByAggregateTotalcorehours:\n 127→\t\treturn func(s *model.JobsStatistics) int { return s.TotalCoreHours }\n 128→\tcase model.SortByAggregateTotalaccs:\n 129→\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccs }\n 130→\tcase model.SortByAggregateTotalacchours:\n 131→\t\treturn func(s *model.JobsStatistics) int { return s.TotalAccHours }\n 132→\tdefault:\n 133→\t\treturn func(s *model.JobsStatistics) int { return s.TotalJobs }\n 134→\t}\n 135→}\n 136→"}]},"uuid":"e61389e0-edee-43d4-b0b7-ed1933eb0979","timestamp":"2026-03-19T10:06:47.342Z"},"type":"agent_progress","prompt":"","agentId":"a2a88d9a86878e95a"},"toolUseID":"agent_msg_01NT7Y6xRphTYtrGUnJvRP2E","parentToolUseID":"toolu_01KyvAFfwW2mG4XmwNcuYhKu","uuid":"23480e5b-728a-43f6-9305-0642159e23d0","timestamp":"2026-03-19T10:06:47.344Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"c8010cd5-db40-4104-813d-673a42ac9dbe","version":"2.1.79","gitBranch":"hotfix","slug":"reactive-frolicking-kitten"} 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matchedJobs={showCompare? matchedCompareJobs: matchedListJobs}\n 227→ applyFilters={(detail) => {\n 228→ jobFilters = [...detail.filters, { user: { eq: user.username } }];\n 229→ selectedCluster = jobFilters[0]?.cluster\n 230→ ? jobFilters[0].cluster.eq\n 231→ : null;\n 232→ selectedSubCluster = jobFilters[1]?.partition\n 233→ ? jobFilters[1].partition.eq\n 234→ : null;\n 235→ filterBuffer = [...jobFilters]\n 236→ if (showCompare) {\n 237→ jobCompare.queryJobs(jobFilters);\n 238→ } else {\n 239→ jobList.queryJobs(jobFilters);\n 240→ }\n 241→ }}\n 242→ />\n 243→ \n 244→ \n 245→ {#if !showCompare}\n 246→ \n 247→ \n 248→ \n 249→ \n 250→ \n 251→ Duration Bin Size\n 252→ \n 253→ \n 254→ {#each durationBinOptions as dbin}\n 255→ \n 256→ {/each}\n 257→ \n 258→ \n 259→ {/if}\n 260→ \n 261→ \n 262→ {#if !showCompare}\n 263→ filterComponent.updateFilters(filter)}\n 266→ />\n 267→ {/if}\n 268→ \n 269→ \n 270→ {#if !showCompare}\n 271→ {\n 272→ jobList.refreshJobs()\n 273→ jobList.refreshAllMetrics()\n 274→ }} />\n 275→ {/if}\n 276→ \n 277→\n 278→\n 279→\n 280→{#if !showCompare}\n 281→ \n 282→ {#if $stats.error}\n 283→ \n 284→ {$stats.error.message}\n 285→ \n 286→ {:else if !$stats.data}\n 287→ \n 288→ \n 289→ \n 290→ {:else}\n 291→ \n 292→
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Username{scrambleNames ? scramble(user.username) : user.username}
Name