From d3dbbd48065973d69b46660ed09af0cf38754da6 Mon Sep 17 00:00:00 2001 From: Jan Eitzinger Date: Fri, 13 Mar 2026 17:22:34 +0100 Subject: [PATCH] Checkpoint: f770853c9fa0 Entire-Session: 889ef150-c6ca-4f35-81e5-c19dc95fe399 Entire-Strategy: manual-commit Entire-Agent: Claude Code Ephemeral-branch: entire/e83bd2b-e3b0c4 --- f7/70853c9fa0/0/content_hash.txt | 1 + f7/70853c9fa0/0/full.jsonl | 232 +++++++++++++++++++++++++++++++ f7/70853c9fa0/0/metadata.json | 33 +++++ f7/70853c9fa0/0/prompt.txt | 1 + f7/70853c9fa0/metadata.json | 25 ++++ 5 files changed, 292 insertions(+) create mode 100644 f7/70853c9fa0/0/content_hash.txt create mode 100644 f7/70853c9fa0/0/full.jsonl create mode 100644 f7/70853c9fa0/0/metadata.json create mode 100644 f7/70853c9fa0/0/prompt.txt create mode 100644 f7/70853c9fa0/metadata.json diff --git a/f7/70853c9fa0/0/content_hash.txt b/f7/70853c9fa0/0/content_hash.txt new file mode 100644 index 00000000..e4230c7b --- /dev/null +++ b/f7/70853c9fa0/0/content_hash.txt @@ -0,0 +1 @@ +sha256:b99c9b469fa38a87819748fa634a401dfd0c2b14393b77824abc59c9e0f5dcec \ No newline at end of file diff --git a/f7/70853c9fa0/0/full.jsonl b/f7/70853c9fa0/0/full.jsonl new file mode 100644 index 00000000..9bccd505 --- /dev/null +++ b/f7/70853c9fa0/0/full.jsonl @@ -0,0 +1,232 @@ +{"type":"file-history-snapshot","messageId":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","snapshot":{"messageId":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","trackedFileBackups":{},"timestamp":"2026-03-13T13:23:59.403Z"},"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":"70a112de-87e3-427c-a118-14893d28b404","toolUseID":"70a112de-87e3-427c-a118-14893d28b404","timestamp":"2026-03-13T13:23:59.350Z","uuid":"df60955c-f9ff-4dab-a61c-5f1dfbe81b17","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"df60955c-f9ff-4dab-a61c-5f1dfbe81b17","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Usage Dashboard Query Optimization\n\n## Change 1: Partial indexes for running jobs\n\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.\n- **`internal/repository/migration.go:30`** — `Version` 13 → 14.\n- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.\n\n## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)\n\n- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.\n- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.\n- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.\n\n## Change 3: Parallelize histogram queries\n\n- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.\n\n## Change 4: Frontend uses consolidated results\n\n- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. Update template refs.\n\n## Verification\n```bash\ncd web/frontend && npm run build && cd ../.. && go build ./... && go test ./internal/repository/...\n```\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/3643a384-f90b-4f89-9ba0-2e5861a4674c.jsonl"},"uuid":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","timestamp":"2026-03-13T13:23:56.397Z","planContent":"# Usage Dashboard Query Optimization\n\n## Change 1: Partial indexes for running jobs\n\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.\n- **`internal/repository/migration.go:30`** — `Version` 13 → 14.\n- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.\n\n## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)\n\n- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.\n- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.\n- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.\n\n## Change 3: Parallelize histogram queries\n\n- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.\n\n## Change 4: Frontend uses consolidated results\n\n- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. Update template refs.\n\n## Verification\n```bash\ncd web/frontend && npm run build && cd ../.. && go build ./... && go test ./internal/repository/...\n```\n","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVaeQyVwQga8xvbXHS7Y9H","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"EokCCkYICxgCKkCdG8qTncIMduu4zwRjj7Z6HD4E3ibSocGCEFy+okymW5hfegj+cwP+HURWuVT4O1mWtXVgfpBHoKX+2oLylj9sEgwzPGsPnXjYFcxrKFMaDAev4ooJ446eDxy1ByIw8Y/W4j3SnXno88TnaXfVze4x2NJ/fsEAd4xKVdz7anms4SsFMwuqBGzhkkNcE6cIKnFjrmygWDzz8SeuNa+3x/VHQgewNhEDgadxFWXFeP12LS0UWwVyFceHfznPgkQfzLjsXeu8yquLwdiYpbc7X4K47PYdHYV90GCwv/a1IwOBq1n9oZLjbgVCMGXto3AuEFw9aE+wxdxG40sfQfQOqepm1hgB"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4503,"cache_read_input_tokens":14321,"cache_creation":{"ephemeral_5m_input_tokens":4503,"ephemeral_1h_input_tokens":0},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19o6pkh8ABRUcYePjQF","type":"assistant","uuid":"d570cc63-fff0-4997-aee5-0171d2050e1c","timestamp":"2026-03-13T13:24:02.290Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"d570cc63-fff0-4997-aee5-0171d2050e1c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVaeQyVwQga8xvbXHS7Y9H","type":"message","role":"assistant","content":[{"type":"text","text":"Let me read the key files first."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4503,"cache_read_input_tokens":14321,"cache_creation":{"ephemeral_5m_input_tokens":4503,"ephemeral_1h_input_tokens":0},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19o6pkh8ABRUcYePjQF","type":"assistant","uuid":"d16731dc-9a95-47b3-bcee-11eed8eac424","timestamp":"2026-03-13T13:24:02.838Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"d16731dc-9a95-47b3-bcee-11eed8eac424","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVaeQyVwQga8xvbXHS7Y9H","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01C8kNf5XS2XsTbdPcUxHsuu","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migration.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4503,"cache_read_input_tokens":14321,"cache_creation":{"ephemeral_5m_input_tokens":4503,"ephemeral_1h_input_tokens":0},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19o6pkh8ABRUcYePjQF","type":"assistant","uuid":"a388e692-b0d1-481f-9f32-c6a06ebc2c25","timestamp":"2026-03-13T13:24:03.594Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a388e692-b0d1-481f-9f32-c6a06ebc2c25","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01C8kNf5XS2XsTbdPcUxHsuu","toolUseID":"toolu_01C8kNf5XS2XsTbdPcUxHsuu","timestamp":"2026-03-13T13:24:03.607Z","uuid":"4362feed-5761-4afe-9d12-74e8a7e8bb6b","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a388e692-b0d1-481f-9f32-c6a06ebc2c25","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01C8kNf5XS2XsTbdPcUxHsuu","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 repository\n 7→\n 8→import (\n 9→\t\"database/sql\"\n 10→\t\"embed\"\n 11→\t\"fmt\"\n 12→\n 13→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 14→\t\"github.com/golang-migrate/migrate/v4\"\n 15→\t\"github.com/golang-migrate/migrate/v4/database/sqlite3\"\n 16→\t\"github.com/golang-migrate/migrate/v4/source/iofs\"\n 17→)\n 18→\n 19→// Version is the current database schema version required by this version of cc-backend.\n 20→// When the database schema changes, this version is incremented and a new migration file\n 21→// is added to internal/repository/migrations/sqlite3/.\n 22→//\n 23→// Version history:\n 24→// - Version 13: Add covering indexes for status/dashboard queries (cluster, job_state, ...)\n 25→// - Version 12: Add covering index for stats queries (cluster, start_time, hpc_user, ...)\n 26→// - Version 11: Optimize job table indexes (reduce from ~78 to 48)\n 27→// - Version 10: Node table\n 28→//\n 29→// Migration files are embedded at build time from the migrations directory.\n 30→const Version uint = 13\n 31→\n 32→//go:embed migrations/*\n 33→var migrationFiles embed.FS\n 34→\n 35→// checkDBVersion verifies that the database schema version matches the expected version.\n 36→// This is called automatically during Connect() to ensure schema compatibility.\n 37→//\n 38→// Returns an error if:\n 39→// - Database version is older than expected (needs migration)\n 40→// - Database version is newer than expected (needs app upgrade)\n 41→// - Database is in a dirty state (failed migration)\n 42→//\n 43→// A \"dirty\" database indicates a migration was started but not completed successfully.\n 44→// This requires manual intervention to fix the database and force the version.\n 45→func checkDBVersion(db *sql.DB) error {\n 46→\tdriver, err := sqlite3.WithInstance(db, &sqlite3.Config{})\n 47→\tif err != nil {\n 48→\t\treturn err\n 49→\t}\n 50→\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n 51→\tif err != nil {\n 52→\t\treturn err\n 53→\t}\n 54→\n 55→\tm, err := migrate.NewWithInstance(\"iofs\", d, \"sqlite3\", driver)\n 56→\tif err != nil {\n 57→\t\treturn err\n 58→\t}\n 59→\n 60→\tv, dirty, err := m.Version()\n 61→\tif err != nil {\n 62→\t\tif err == migrate.ErrNilVersion {\n 63→\t\t\tcclog.Warn(\"Legacy database without version or missing database file!\")\n 64→\t\t} else {\n 65→\t\t\treturn err\n 66→\t\t}\n 67→\t}\n 68→\n 69→\tif v < Version {\n 70→\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n 71→\t} else if v > Version {\n 72→\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease refer to documentation how to downgrade db with external migrate tool\", v, Version)\n 73→\t}\n 74→\n 75→\tif dirty {\n 76→\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n 77→\t}\n 78→\n 79→\treturn nil\n 80→}\n 81→\n 82→// getMigrateInstance creates a new migration instance for the given database file.\n 83→// This is used internally by MigrateDB, RevertDB, and ForceDB.\n 84→func getMigrateInstance(db string) (m *migrate.Migrate, err error) {\n 85→\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n 86→\tif err != nil {\n 87→\t\treturn nil, err\n 88→\t}\n 89→\n 90→\tm, err = migrate.NewWithSourceInstance(\"iofs\", d, fmt.Sprintf(\"sqlite3://%s?_foreign_keys=on\", db))\n 91→\tif err != nil {\n 92→\t\treturn nil, err\n 93→\t}\n 94→\n 95→\treturn m, nil\n 96→}\n 97→\n 98→// MigrateDB applies all pending database migrations to bring the schema up to date.\n 99→// This should be run with the -migrate-db flag before starting the application\n 100→// after upgrading to a new version that requires schema changes.\n 101→//\n 102→// Process:\n 103→// 1. Checks current database version\n 104→// 2. Applies all migrations from current version to target Version\n 105→// 3. Updates schema_migrations table to track applied migrations\n 106→//\n 107→// Important:\n 108→// - Always backup your database before running migrations\n 109→// - Migrations are irreversible without manual intervention\n 110→// - If a migration fails, the database is marked \"dirty\" and requires manual fix\n 111→//\n 112→// Usage:\n 113→//\n 114→//\tcc-backend -migrate-db\n 115→func MigrateDB(db string) error {\n 116→\tm, err := getMigrateInstance(db)\n 117→\tif err != nil {\n 118→\t\treturn err\n 119→\t}\n 120→\n 121→\tv, dirty, err := m.Version()\n 122→\tif err != nil {\n 123→\t\tif err == migrate.ErrNilVersion {\n 124→\t\t\tcclog.Info(\"Legacy database without version or missing database file!\")\n 125→\t\t} else {\n 126→\t\t\treturn err\n 127→\t\t}\n 128→\t}\n 129→\n 130→\tif v < Version {\n 131→\t\tcclog.Infof(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n 132→\t}\n 133→\n 134→\tif dirty {\n 135→\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n 136→\t}\n 137→\n 138→\tif err := m.Up(); err != nil {\n 139→\t\tif err == migrate.ErrNoChange {\n 140→\t\t\tcclog.Info(\"DB already up to date!\")\n 141→\t\t} else {\n 142→\t\t\treturn err\n 143→\t\t}\n 144→\t}\n 145→\n 146→\tm.Close()\n 147→\treturn nil\n 148→}\n 149→\n 150→// RevertDB rolls back the database schema to the previous version (Version - 1).\n 151→// This is primarily used for testing or emergency rollback scenarios.\n 152→//\n 153→// Warning:\n 154→// - This may cause data loss if newer schema added columns/tables\n 155→// - Always backup before reverting\n 156→// - Not all migrations are safely reversible\n 157→//\n 158→// Usage:\n 159→//\n 160→//\tcc-backend -revert-db\n 161→func RevertDB(db string) error {\n 162→\tm, err := getMigrateInstance(db)\n 163→\tif err != nil {\n 164→\t\treturn err\n 165→\t}\n 166→\n 167→\tif err := m.Migrate(Version - 1); err != nil {\n 168→\t\tif err == migrate.ErrNoChange {\n 169→\t\t\tcclog.Info(\"DB already up to date!\")\n 170→\t\t} else {\n 171→\t\t\treturn err\n 172→\t\t}\n 173→\t}\n 174→\n 175→\tm.Close()\n 176→\treturn nil\n 177→}\n 178→\n 179→// ForceDB forces the database schema version to the current Version without running migrations.\n 180→// This is only used to recover from failed migrations that left the database in a \"dirty\" state.\n 181→//\n 182→// When to use:\n 183→// - After manually fixing a failed migration\n 184→// - When you've manually applied schema changes and need to update the version marker\n 185→//\n 186→// Warning:\n 187→// - This does NOT apply any schema changes\n 188→// - Only use after manually verifying the schema is correct\n 189→// - Improper use can cause schema/version mismatch\n 190→//\n 191→// Usage:\n 192→//\n 193→//\tcc-backend -force-db\n 194→func ForceDB(db string) error {\n 195→\tm, err := getMigrateInstance(db)\n 196→\tif err != nil {\n 197→\t\treturn err\n 198→\t}\n 199→\n 200→\tif err := m.Force(int(Version)); err != nil {\n 201→\t\treturn err\n 202→\t}\n 203→\n 204→\tm.Close()\n 205→\treturn nil\n 206→}\n 207→"}]},"uuid":"5b8ee254-de84-46c5-8a9d-26b77f4443ad","timestamp":"2026-03-13T13:24:03.607Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migration.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 repository\n\nimport (\n\t\"database/sql\"\n\t\"embed\"\n\t\"fmt\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/golang-migrate/migrate/v4\"\n\t\"github.com/golang-migrate/migrate/v4/database/sqlite3\"\n\t\"github.com/golang-migrate/migrate/v4/source/iofs\"\n)\n\n// Version is the current database schema version required by this version of cc-backend.\n// When the database schema changes, this version is incremented and a new migration file\n// is added to internal/repository/migrations/sqlite3/.\n//\n// Version history:\n// - Version 13: Add covering indexes for status/dashboard queries (cluster, job_state, ...)\n// - Version 12: Add covering index for stats queries (cluster, start_time, hpc_user, ...)\n// - Version 11: Optimize job table indexes (reduce from ~78 to 48)\n// - Version 10: Node table\n//\n// Migration files are embedded at build time from the migrations directory.\nconst Version uint = 13\n\n//go:embed migrations/*\nvar migrationFiles embed.FS\n\n// checkDBVersion verifies that the database schema version matches the expected version.\n// This is called automatically during Connect() to ensure schema compatibility.\n//\n// Returns an error if:\n// - Database version is older than expected (needs migration)\n// - Database version is newer than expected (needs app upgrade)\n// - Database is in a dirty state (failed migration)\n//\n// A \"dirty\" database indicates a migration was started but not completed successfully.\n// This requires manual intervention to fix the database and force the version.\nfunc checkDBVersion(db *sql.DB) error {\n\tdriver, err := sqlite3.WithInstance(db, &sqlite3.Config{})\n\tif err != nil {\n\t\treturn err\n\t}\n\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tm, err := migrate.NewWithInstance(\"iofs\", d, \"sqlite3\", driver)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tv, dirty, err := m.Version()\n\tif err != nil {\n\t\tif err == migrate.ErrNilVersion {\n\t\t\tcclog.Warn(\"Legacy database without version or missing database file!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tif v < Version {\n\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n\t} else if v > Version {\n\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease refer to documentation how to downgrade db with external migrate tool\", v, Version)\n\t}\n\n\tif dirty {\n\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n\t}\n\n\treturn nil\n}\n\n// getMigrateInstance creates a new migration instance for the given database file.\n// This is used internally by MigrateDB, RevertDB, and ForceDB.\nfunc getMigrateInstance(db string) (m *migrate.Migrate, err error) {\n\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tm, err = migrate.NewWithSourceInstance(\"iofs\", d, fmt.Sprintf(\"sqlite3://%s?_foreign_keys=on\", db))\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn m, nil\n}\n\n// MigrateDB applies all pending database migrations to bring the schema up to date.\n// This should be run with the -migrate-db flag before starting the application\n// after upgrading to a new version that requires schema changes.\n//\n// Process:\n// 1. Checks current database version\n// 2. Applies all migrations from current version to target Version\n// 3. Updates schema_migrations table to track applied migrations\n//\n// Important:\n// - Always backup your database before running migrations\n// - Migrations are irreversible without manual intervention\n// - If a migration fails, the database is marked \"dirty\" and requires manual fix\n//\n// Usage:\n//\n//\tcc-backend -migrate-db\nfunc MigrateDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tv, dirty, err := m.Version()\n\tif err != nil {\n\t\tif err == migrate.ErrNilVersion {\n\t\t\tcclog.Info(\"Legacy database without version or missing database file!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tif v < Version {\n\t\tcclog.Infof(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n\t}\n\n\tif dirty {\n\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n\t}\n\n\tif err := m.Up(); err != nil {\n\t\tif err == migrate.ErrNoChange {\n\t\t\tcclog.Info(\"DB already up to date!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tm.Close()\n\treturn nil\n}\n\n// RevertDB rolls back the database schema to the previous version (Version - 1).\n// This is primarily used for testing or emergency rollback scenarios.\n//\n// Warning:\n// - This may cause data loss if newer schema added columns/tables\n// - Always backup before reverting\n// - Not all migrations are safely reversible\n//\n// Usage:\n//\n//\tcc-backend -revert-db\nfunc RevertDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif err := m.Migrate(Version - 1); err != nil {\n\t\tif err == migrate.ErrNoChange {\n\t\t\tcclog.Info(\"DB already up to date!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tm.Close()\n\treturn nil\n}\n\n// ForceDB forces the database schema version to the current Version without running migrations.\n// This is only used to recover from failed migrations that left the database in a \"dirty\" state.\n//\n// When to use:\n// - After manually fixing a failed migration\n// - When you've manually applied schema changes and need to update the version marker\n//\n// Warning:\n// - This does NOT apply any schema changes\n// - Only use after manually verifying the schema is correct\n// - Improper use can cause schema/version mismatch\n//\n// Usage:\n//\n//\tcc-backend -force-db\nfunc ForceDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif err := m.Force(int(Version)); err != nil {\n\t\treturn err\n\t}\n\n\tm.Close()\n\treturn nil\n}\n","numLines":207,"startLine":1,"totalLines":207}},"sourceToolAssistantUUID":"a388e692-b0d1-481f-9f32-c6a06ebc2c25","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5b8ee254-de84-46c5-8a9d-26b77f4443ad","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVaeQyVwQga8xvbXHS7Y9H","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PfiZCsHyYcQR4fTz7f2rTQ","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4503,"cache_read_input_tokens":14321,"cache_creation":{"ephemeral_5m_input_tokens":4503,"ephemeral_1h_input_tokens":0},"output_tokens":9,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19o6pkh8ABRUcYePjQF","type":"assistant","uuid":"5810ecbf-ac9a-44ac-86a2-74647d424b28","timestamp":"2026-03-13T13:24:04.177Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5810ecbf-ac9a-44ac-86a2-74647d424b28","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01PfiZCsHyYcQR4fTz7f2rTQ","toolUseID":"toolu_01PfiZCsHyYcQR4fTz7f2rTQ","timestamp":"2026-03-13T13:24:04.186Z","uuid":"26758fad-e9a2-40f3-bf96-47654bd998e9","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5810ecbf-ac9a-44ac-86a2-74647d424b28","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PfiZCsHyYcQR4fTz7f2rTQ","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 repository provides job query functionality with filtering, pagination,\n 7→// and security controls. This file contains the main query builders and security\n 8→// checks for job retrieval operations.\n 9→package repository\n 10→\n 11→import (\n 12→\t\"context\"\n 13→\t\"errors\"\n 14→\t\"fmt\"\n 15→\t\"regexp\"\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/model\"\n 21→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 22→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 23→\tsq \"github.com/Masterminds/squirrel\"\n 24→)\n 25→\n 26→const (\n 27→\t// Default initial capacity for job result slices\n 28→\tdefaultJobsCapacity = 50\n 29→)\n 30→\n 31→// QueryJobs retrieves jobs from the database with optional filtering, pagination,\n 32→// and sorting. Security controls are automatically applied based on the user context.\n 33→//\n 34→// Parameters:\n 35→// - ctx: Context containing user authentication information\n 36→// - filters: Optional job filters (cluster, state, user, time ranges, etc.)\n 37→// - page: Optional pagination parameters (page number and items per page)\n 38→// - order: Optional sorting specification (column or footprint field)\n 39→//\n 40→// Returns a slice of jobs matching the criteria, or an error if the query fails.\n 41→// The function enforces role-based access control through SecurityCheck.\n 42→func (r *JobRepository) QueryJobs(\n 43→\tctx context.Context,\n 44→\tfilters []*model.JobFilter,\n 45→\tpage *model.PageRequest,\n 46→\torder *model.OrderByInput,\n 47→) ([]*schema.Job, error) {\n 48→\tquery, qerr := SecurityCheck(ctx, sq.Select(jobColumns...).From(\"job\"))\n 49→\tif qerr != nil {\n 50→\t\treturn nil, qerr\n 51→\t}\n 52→\n 53→\tif order != nil {\n 54→\t\tfield := toSnakeCase(order.Field)\n 55→\t\tif order.Type == \"col\" {\n 56→\t\t\tswitch order.Order {\n 57→\t\t\tcase model.SortDirectionEnumAsc:\n 58→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s ASC\", field))\n 59→\t\t\tcase model.SortDirectionEnumDesc:\n 60→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s DESC\", field))\n 61→\t\t\tdefault:\n 62→\t\t\t\treturn nil, errors.New(\"invalid sorting order for column\")\n 63→\t\t\t}\n 64→\t\t} else {\n 65→\t\t\t// Order by footprint JSON field values\n 66→\t\t\tquery = query.Where(\"JSON_VALID(footprint)\")\n 67→\t\t\tswitch order.Order {\n 68→\t\t\tcase model.SortDirectionEnumAsc:\n 69→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") ASC\", field))\n 70→\t\t\tcase model.SortDirectionEnumDesc:\n 71→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") DESC\", field))\n 72→\t\t\tdefault:\n 73→\t\t\t\treturn nil, errors.New(\"invalid sorting order for footprint\")\n 74→\t\t\t}\n 75→\t\t}\n 76→\t}\n 77→\n 78→\tif page != nil && page.ItemsPerPage != -1 {\n 79→\t\tlimit := uint64(page.ItemsPerPage)\n 80→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 81→\t}\n 82→\n 83→\tfor _, f := range filters {\n 84→\t\tquery = BuildWhereClause(f, query)\n 85→\t}\n 86→\n 87→\trows, err := query.RunWith(r.stmtCache).QueryContext(ctx)\n 88→\tif err != nil {\n 89→\t\tqueryString, queryVars, _ := query.ToSql()\n 90→\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n 91→\t}\n 92→\tdefer rows.Close()\n 93→\n 94→\tjobs := make([]*schema.Job, 0, defaultJobsCapacity)\n 95→\tfor rows.Next() {\n 96→\t\tjob, err := scanJob(rows)\n 97→\t\tif err != nil {\n 98→\t\t\tcclog.Warnf(\"Error scanning job row: %v\", err)\n 99→\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n 100→\t\t}\n 101→\t\tjobs = append(jobs, job)\n 102→\t}\n 103→\n 104→\tif err := rows.Err(); err != nil {\n 105→\t\treturn nil, fmt.Errorf(\"error iterating job rows: %w\", err)\n 106→\t}\n 107→\n 108→\treturn jobs, nil\n 109→}\n 110→\n 111→// CountJobs returns the total number of jobs matching the given filters.\n 112→// Security controls are automatically applied based on the user context.\n 113→// Uses DISTINCT count to handle tag filters correctly (jobs may appear multiple\n 114→// times when joined with the tag table).\n 115→func (r *JobRepository) CountJobs(\n 116→\tctx context.Context,\n 117→\tfilters []*model.JobFilter,\n 118→) (int, error) {\n 119→\tquery, qerr := SecurityCheck(ctx, sq.Select(\"count(DISTINCT job.id)\").From(\"job\"))\n 120→\tif qerr != nil {\n 121→\t\treturn 0, qerr\n 122→\t}\n 123→\n 124→\tfor _, f := range filters {\n 125→\t\tquery = BuildWhereClause(f, query)\n 126→\t}\n 127→\n 128→\tvar count int\n 129→\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&count); err != nil {\n 130→\t\treturn 0, fmt.Errorf(\"failed to count jobs: %w\", err)\n 131→\t}\n 132→\n 133→\treturn count, nil\n 134→}\n 135→\n 136→// SecurityCheckWithUser applies role-based access control filters to a job query\n 137→// based on the provided user's roles and permissions.\n 138→//\n 139→// Access rules by role:\n 140→// - API role (exclusive): Full access to all jobs\n 141→// - Admin/Support roles: Full access to all jobs\n 142→// - Manager role: Access to jobs in managed projects plus own jobs\n 143→// - User role: Access only to own jobs\n 144→//\n 145→// Returns an error if the user is nil or has no recognized roles.\n 146→func SecurityCheckWithUser(user *schema.User, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n 147→\tif user == nil {\n 148→\t\tvar qnil sq.SelectBuilder\n 149→\t\treturn qnil, fmt.Errorf(\"user context is nil\")\n 150→\t}\n 151→\n 152→\tswitch {\n 153→\tcase len(user.Roles) == 1 && user.HasRole(schema.RoleAPI):\n 154→\t\treturn query, nil\n 155→\tcase user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}):\n 156→\t\treturn query, nil\n 157→\tcase user.HasRole(schema.RoleManager):\n 158→\t\tif len(user.Projects) != 0 {\n 159→\t\t\treturn query.Where(sq.Or{sq.Eq{\"job.project\": user.Projects}, sq.Eq{\"job.hpc_user\": user.Username}}), nil\n 160→\t\t}\n 161→\t\tcclog.Debugf(\"Manager '%s' has no assigned projects, restricting to personal jobs\", user.Username)\n 162→\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n 163→\tcase user.HasRole(schema.RoleUser):\n 164→\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n 165→\tdefault:\n 166→\t\tvar qnil sq.SelectBuilder\n 167→\t\treturn qnil, fmt.Errorf(\"user has no or unknown roles\")\n 168→\t}\n 169→}\n 170→\n 171→// SecurityCheck extracts the user from the context and applies role-based access\n 172→// control filters to the query. This is a convenience wrapper around SecurityCheckWithUser.\n 173→func SecurityCheck(ctx context.Context, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n 174→\tuser := GetUserFromContext(ctx)\n 175→\treturn SecurityCheckWithUser(user, query)\n 176→}\n 177→\n 178→// BuildWhereClause constructs SQL WHERE conditions from a JobFilter and applies\n 179→// them to the query. Supports filtering by job properties (cluster, state, user),\n 180→// time ranges, resource usage, tags, and JSON field searches in meta_data,\n 181→// footprint, and resources columns.\n 182→func BuildWhereClause(filter *model.JobFilter, query sq.SelectBuilder) sq.SelectBuilder {\n 183→\t// Primary Key\n 184→\tif filter.DbID != nil {\n 185→\t\tdbIDs := make([]string, len(filter.DbID))\n 186→\t\tcopy(dbIDs, filter.DbID)\n 187→\t\tquery = query.Where(sq.Eq{\"job.id\": dbIDs})\n 188→\t}\n 189→\t// Explicit indices\n 190→\tif filter.Cluster != nil {\n 191→\t\tquery = buildStringCondition(\"job.cluster\", filter.Cluster, query)\n 192→\t}\n 193→\tif filter.SubCluster != nil {\n 194→\t\tquery = buildStringCondition(\"job.subcluster\", filter.SubCluster, query)\n 195→\t}\n 196→\tif filter.Partition != nil {\n 197→\t\tquery = buildStringCondition(\"job.cluster_partition\", filter.Partition, query)\n 198→\t}\n 199→\tif filter.State != nil {\n 200→\t\tif len(filter.State) == 1 {\n 201→\t\t\tsingleStat := string(filter.State[0])\n 202→\t\t\tquery = query.Where(\"job.job_state = ?\", singleStat)\n 203→\t\t} else {\n 204→\t\t\tstates := make([]string, len(filter.State))\n 205→\t\t\tfor i, val := range filter.State {\n 206→\t\t\t\tstates[i] = string(val)\n 207→\t\t\t}\n 208→\t\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n 209→\t\t}\n 210→\t}\n 211→\tif filter.Shared != nil {\n 212→\t\tquery = query.Where(\"job.shared = ?\", *filter.Shared)\n 213→\t}\n 214→\tif filter.Project != nil {\n 215→\t\tquery = buildStringCondition(\"job.project\", filter.Project, query)\n 216→\t}\n 217→\tif filter.User != nil {\n 218→\t\tquery = buildStringCondition(\"job.hpc_user\", filter.User, query)\n 219→\t}\n 220→\tif filter.NumNodes != nil {\n 221→\t\tquery = buildIntCondition(\"job.num_nodes\", filter.NumNodes, query)\n 222→\t}\n 223→\tif filter.NumAccelerators != nil {\n 224→\t\tquery = buildIntCondition(\"job.num_acc\", filter.NumAccelerators, query)\n 225→\t}\n 226→\tif filter.NumHWThreads != nil {\n 227→\t\tquery = buildIntCondition(\"job.num_hwthreads\", filter.NumHWThreads, query)\n 228→\t}\n 229→\tif filter.ArrayJobID != nil {\n 230→\t\tquery = query.Where(\"job.array_job_id = ?\", *filter.ArrayJobID)\n 231→\t}\n 232→\tif filter.StartTime != nil {\n 233→\t\tquery = buildTimeCondition(\"job.start_time\", filter.StartTime, query)\n 234→\t}\n 235→\tif filter.Duration != nil {\n 236→\t\tquery = buildIntCondition(\"job.duration\", filter.Duration, query)\n 237→\t}\n 238→\tif filter.Energy != nil {\n 239→\t\tquery = buildFloatCondition(\"job.energy\", filter.Energy, query)\n 240→\t}\n 241→\t// Indices on Tag Table\n 242→\tif filter.Tags != nil {\n 243→\t\t// This is an OR-Logic query: Returns all distinct jobs with at least one of the requested tags; TODO: AND-Logic query?\n 244→\t\tquery = query.Join(\"jobtag ON jobtag.job_id = job.id\").Where(sq.Eq{\"jobtag.tag_id\": filter.Tags}).Distinct()\n 245→\t}\n 246→\t// No explicit Indices\n 247→\tif filter.JobID != nil {\n 248→\t\tquery = buildStringCondition(\"job.job_id\", filter.JobID, query)\n 249→\t}\n 250→\t// Queries Within JSONs\n 251→\tif filter.MetricStats != nil {\n 252→\t\tfor _, ms := range filter.MetricStats {\n 253→\t\t\tquery = buildFloatJSONCondition(ms.MetricName, ms.Range, query)\n 254→\t\t}\n 255→\t}\n 256→\tif filter.Node != nil {\n 257→\t\tquery = buildResourceJSONCondition(\"hostname\", filter.Node, query)\n 258→\t}\n 259→\tif filter.JobName != nil {\n 260→\t\tquery = buildMetaJSONCondition(\"jobName\", filter.JobName, query)\n 261→\t}\n 262→\tif filter.Schedule != nil {\n 263→\t\tinteractiveJobname := \"interactive\"\n 264→\t\tswitch *filter.Schedule {\n 265→\t\tcase \"interactive\":\n 266→\t\t\tiFilter := model.StringInput{Eq: &interactiveJobname}\n 267→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &iFilter, query)\n 268→\t\tcase \"batch\":\n 269→\t\t\tsFilter := model.StringInput{Neq: &interactiveJobname}\n 270→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &sFilter, query)\n 271→\t\t}\n 272→\t}\n 273→\n 274→\t// Configurable Filter to exclude recently started jobs, see config.go: ShortRunningJobsDuration\n 275→\tif filter.MinRunningFor != nil {\n 276→\t\tnow := time.Now().Unix()\n 277→\t\t// Only jobs whose start timestamp is more than MinRunningFor seconds in the past\n 278→\t\t// If a job completed within the configured timeframe, it will still show up after the start_time matches the condition!\n 279→\t\tquery = query.Where(sq.Lt{\"job.start_time\": (now - int64(*filter.MinRunningFor))})\n 280→\t}\n 281→\treturn query\n 282→}\n 283→\n 284→// buildIntCondition creates clauses for integer range filters, using BETWEEN only if required.\n 285→func buildIntCondition(field string, cond *config.IntRange, query sq.SelectBuilder) sq.SelectBuilder {\n 286→\tif cond.From != 1 && cond.To != 0 {\n 287→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 288→\t} else if cond.From != 1 && cond.To == 0 {\n 289→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 290→\t} else if cond.From == 1 && cond.To != 0 {\n 291→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 292→\t} else {\n 293→\t\treturn query\n 294→\t}\n 295→}\n 296→\n 297→// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\n 298→func buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 299→\tif cond.From != 1.0 && cond.To != 0.0 {\n 300→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 301→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 302→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 303→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 304→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 305→\t} else {\n 306→\t\treturn query\n 307→\t}\n 308→}\n 309→\n 310→// buildTimeCondition creates time range filters supporting absolute timestamps,\n 311→// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n 312→// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\n 313→func buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n 314→\tif cond.From != nil && cond.To != nil {\n 315→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n 316→\t} else if cond.From != nil {\n 317→\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n 318→\t} else if cond.To != nil {\n 319→\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n 320→\t} else if cond.Range != \"\" {\n 321→\t\tnow := time.Now().Unix()\n 322→\t\tvar then int64\n 323→\t\tswitch cond.Range {\n 324→\t\tcase \"last6h\":\n 325→\t\t\tthen = now - (60 * 60 * 6)\n 326→\t\tcase \"last24h\":\n 327→\t\t\tthen = now - (60 * 60 * 24)\n 328→\t\tcase \"last7d\":\n 329→\t\t\tthen = now - (60 * 60 * 24 * 7)\n 330→\t\tcase \"last30d\":\n 331→\t\t\tthen = now - (60 * 60 * 24 * 30)\n 332→\t\tdefault:\n 333→\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n 334→\t\t\treturn query\n 335→\t\t}\n 336→\t\treturn query.Where(field+\" >= ?\", then)\n 337→\t} else {\n 338→\t\treturn query\n 339→\t}\n 340→}\n 341→\n 342→// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\n 343→func buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 344→\tquery = query.Where(\"JSON_VALID(footprint)\")\n 345→\tif cond.From != 1.0 && cond.To != 0.0 {\n 346→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n 347→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 348→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n 349→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 350→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n 351→\t} else {\n 352→\t\treturn query\n 353→\t}\n 354→}\n 355→\n 356→// buildStringCondition creates filters for string fields supporting equality,\n 357→// inequality, prefix, suffix, substring, and IN list matching.\n 358→func buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 359→\tif cond.Eq != nil {\n 360→\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n 361→\t}\n 362→\tif cond.Neq != nil {\n 363→\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n 364→\t}\n 365→\tif cond.StartsWith != nil {\n 366→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 367→\t}\n 368→\tif cond.EndsWith != nil {\n 369→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 370→\t}\n 371→\tif cond.Contains != nil {\n 372→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 373→\t}\n 374→\tif cond.In != nil {\n 375→\t\tqueryElements := make([]string, len(cond.In))\n 376→\t\tcopy(queryElements, cond.In)\n 377→\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n 378→\t}\n 379→\treturn query\n 380→}\n 381→\n 382→// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\n 383→func buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 384→\tquery = query.Where(\"JSON_VALID(meta_data)\")\n 385→\tif cond.Eq != nil {\n 386→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n 387→\t}\n 388→\tif cond.Neq != nil {\n 389→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n 390→\t}\n 391→\tif cond.StartsWith != nil {\n 392→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 393→\t}\n 394→\tif cond.EndsWith != nil {\n 395→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 396→\t}\n 397→\tif cond.Contains != nil {\n 398→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 399→\t}\n 400→\treturn query\n 401→}\n 402→\n 403→// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n 404→// Uses json_each to search within array elements.\n 405→func buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 406→\tquery = query.Where(\"JSON_VALID(resources)\")\n 407→\tif cond.Eq != nil {\n 408→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n 409→\t}\n 410→\tif cond.Neq != nil { // Currently Unused\n 411→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n 412→\t}\n 413→\tif cond.StartsWith != nil { // Currently Unused\n 414→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 415→\t}\n 416→\tif cond.EndsWith != nil { // Currently Unused\n 417→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n 418→\t}\n 419→\tif cond.Contains != nil {\n 420→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 421→\t}\n 422→\treturn query\n 423→}\n 424→\n 425→var (\n 426→\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n 427→\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n 428→)\n 429→\n 430→// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n 431→// Includes security checks to prevent SQL injection attempts.\n 432→// Panics if potentially dangerous characters are detected.\n 433→func toSnakeCase(str string) string {\n 434→\tfor _, c := range str {\n 435→\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n 436→\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n 437→\t\t}\n 438→\t}\n 439→\n 440→\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n 441→\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n 442→\treturn strings.ToLower(snake)\n 443→}\n 444→"}]},"uuid":"05d5a5ee-cecf-4697-839a-b3bf8970dacf","timestamp":"2026-03-13T13:24:04.185Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package repository provides job query functionality with filtering, pagination,\n// and security controls. This file contains the main query builders and security\n// checks for job retrieval operations.\npackage repository\n\nimport (\n\t\"context\"\n\t\"errors\"\n\t\"fmt\"\n\t\"regexp\"\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/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n)\n\nconst (\n\t// Default initial capacity for job result slices\n\tdefaultJobsCapacity = 50\n)\n\n// QueryJobs retrieves jobs from the database with optional filtering, pagination,\n// and sorting. Security controls are automatically applied based on the user context.\n//\n// Parameters:\n// - ctx: Context containing user authentication information\n// - filters: Optional job filters (cluster, state, user, time ranges, etc.)\n// - page: Optional pagination parameters (page number and items per page)\n// - order: Optional sorting specification (column or footprint field)\n//\n// Returns a slice of jobs matching the criteria, or an error if the query fails.\n// The function enforces role-based access control through SecurityCheck.\nfunc (r *JobRepository) QueryJobs(\n\tctx context.Context,\n\tfilters []*model.JobFilter,\n\tpage *model.PageRequest,\n\torder *model.OrderByInput,\n) ([]*schema.Job, error) {\n\tquery, qerr := SecurityCheck(ctx, sq.Select(jobColumns...).From(\"job\"))\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tif order != nil {\n\t\tfield := toSnakeCase(order.Field)\n\t\tif order.Type == \"col\" {\n\t\t\tswitch order.Order {\n\t\t\tcase model.SortDirectionEnumAsc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s ASC\", field))\n\t\t\tcase model.SortDirectionEnumDesc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s DESC\", field))\n\t\t\tdefault:\n\t\t\t\treturn nil, errors.New(\"invalid sorting order for column\")\n\t\t\t}\n\t\t} else {\n\t\t\t// Order by footprint JSON field values\n\t\t\tquery = query.Where(\"JSON_VALID(footprint)\")\n\t\t\tswitch order.Order {\n\t\t\tcase model.SortDirectionEnumAsc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") ASC\", field))\n\t\t\tcase model.SortDirectionEnumDesc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") DESC\", field))\n\t\t\tdefault:\n\t\t\t\treturn nil, errors.New(\"invalid sorting order for footprint\")\n\t\t\t}\n\t\t}\n\t}\n\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tlimit := uint64(page.ItemsPerPage)\n\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.RunWith(r.stmtCache).QueryContext(ctx)\n\tif err != nil {\n\t\tqueryString, queryVars, _ := query.ToSql()\n\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, defaultJobsCapacity)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error scanning job row: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, fmt.Errorf(\"error iterating job rows: %w\", err)\n\t}\n\n\treturn jobs, nil\n}\n\n// CountJobs returns the total number of jobs matching the given filters.\n// Security controls are automatically applied based on the user context.\n// Uses DISTINCT count to handle tag filters correctly (jobs may appear multiple\n// times when joined with the tag table).\nfunc (r *JobRepository) CountJobs(\n\tctx context.Context,\n\tfilters []*model.JobFilter,\n) (int, error) {\n\tquery, qerr := SecurityCheck(ctx, sq.Select(\"count(DISTINCT job.id)\").From(\"job\"))\n\tif qerr != nil {\n\t\treturn 0, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\tvar count int\n\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&count); err != nil {\n\t\treturn 0, fmt.Errorf(\"failed to count jobs: %w\", err)\n\t}\n\n\treturn count, nil\n}\n\n// SecurityCheckWithUser applies role-based access control filters to a job query\n// based on the provided user's roles and permissions.\n//\n// Access rules by role:\n// - API role (exclusive): Full access to all jobs\n// - Admin/Support roles: Full access to all jobs\n// - Manager role: Access to jobs in managed projects plus own jobs\n// - User role: Access only to own jobs\n//\n// Returns an error if the user is nil or has no recognized roles.\nfunc SecurityCheckWithUser(user *schema.User, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n\tif user == nil {\n\t\tvar qnil sq.SelectBuilder\n\t\treturn qnil, fmt.Errorf(\"user context is nil\")\n\t}\n\n\tswitch {\n\tcase len(user.Roles) == 1 && user.HasRole(schema.RoleAPI):\n\t\treturn query, nil\n\tcase user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}):\n\t\treturn query, nil\n\tcase user.HasRole(schema.RoleManager):\n\t\tif len(user.Projects) != 0 {\n\t\t\treturn query.Where(sq.Or{sq.Eq{\"job.project\": user.Projects}, sq.Eq{\"job.hpc_user\": user.Username}}), nil\n\t\t}\n\t\tcclog.Debugf(\"Manager '%s' has no assigned projects, restricting to personal jobs\", user.Username)\n\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n\tcase user.HasRole(schema.RoleUser):\n\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n\tdefault:\n\t\tvar qnil sq.SelectBuilder\n\t\treturn qnil, fmt.Errorf(\"user has no or unknown roles\")\n\t}\n}\n\n// SecurityCheck extracts the user from the context and applies role-based access\n// control filters to the query. This is a convenience wrapper around SecurityCheckWithUser.\nfunc SecurityCheck(ctx context.Context, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n\tuser := GetUserFromContext(ctx)\n\treturn SecurityCheckWithUser(user, query)\n}\n\n// BuildWhereClause constructs SQL WHERE conditions from a JobFilter and applies\n// them to the query. Supports filtering by job properties (cluster, state, user),\n// time ranges, resource usage, tags, and JSON field searches in meta_data,\n// footprint, and resources columns.\nfunc BuildWhereClause(filter *model.JobFilter, query sq.SelectBuilder) sq.SelectBuilder {\n\t// Primary Key\n\tif filter.DbID != nil {\n\t\tdbIDs := make([]string, len(filter.DbID))\n\t\tcopy(dbIDs, filter.DbID)\n\t\tquery = query.Where(sq.Eq{\"job.id\": dbIDs})\n\t}\n\t// Explicit indices\n\tif filter.Cluster != nil {\n\t\tquery = buildStringCondition(\"job.cluster\", filter.Cluster, query)\n\t}\n\tif filter.SubCluster != nil {\n\t\tquery = buildStringCondition(\"job.subcluster\", filter.SubCluster, query)\n\t}\n\tif filter.Partition != nil {\n\t\tquery = buildStringCondition(\"job.cluster_partition\", filter.Partition, query)\n\t}\n\tif filter.State != nil {\n\t\tif len(filter.State) == 1 {\n\t\t\tsingleStat := string(filter.State[0])\n\t\t\tquery = query.Where(\"job.job_state = ?\", singleStat)\n\t\t} else {\n\t\t\tstates := make([]string, len(filter.State))\n\t\t\tfor i, val := range filter.State {\n\t\t\t\tstates[i] = string(val)\n\t\t\t}\n\t\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n\t\t}\n\t}\n\tif filter.Shared != nil {\n\t\tquery = query.Where(\"job.shared = ?\", *filter.Shared)\n\t}\n\tif filter.Project != nil {\n\t\tquery = buildStringCondition(\"job.project\", filter.Project, query)\n\t}\n\tif filter.User != nil {\n\t\tquery = buildStringCondition(\"job.hpc_user\", filter.User, query)\n\t}\n\tif filter.NumNodes != nil {\n\t\tquery = buildIntCondition(\"job.num_nodes\", filter.NumNodes, query)\n\t}\n\tif filter.NumAccelerators != nil {\n\t\tquery = buildIntCondition(\"job.num_acc\", filter.NumAccelerators, query)\n\t}\n\tif filter.NumHWThreads != nil {\n\t\tquery = buildIntCondition(\"job.num_hwthreads\", filter.NumHWThreads, query)\n\t}\n\tif filter.ArrayJobID != nil {\n\t\tquery = query.Where(\"job.array_job_id = ?\", *filter.ArrayJobID)\n\t}\n\tif filter.StartTime != nil {\n\t\tquery = buildTimeCondition(\"job.start_time\", filter.StartTime, query)\n\t}\n\tif filter.Duration != nil {\n\t\tquery = buildIntCondition(\"job.duration\", filter.Duration, query)\n\t}\n\tif filter.Energy != nil {\n\t\tquery = buildFloatCondition(\"job.energy\", filter.Energy, query)\n\t}\n\t// Indices on Tag Table\n\tif filter.Tags != nil {\n\t\t// This is an OR-Logic query: Returns all distinct jobs with at least one of the requested tags; TODO: AND-Logic query?\n\t\tquery = query.Join(\"jobtag ON jobtag.job_id = job.id\").Where(sq.Eq{\"jobtag.tag_id\": filter.Tags}).Distinct()\n\t}\n\t// No explicit Indices\n\tif filter.JobID != nil {\n\t\tquery = buildStringCondition(\"job.job_id\", filter.JobID, query)\n\t}\n\t// Queries Within JSONs\n\tif filter.MetricStats != nil {\n\t\tfor _, ms := range filter.MetricStats {\n\t\t\tquery = buildFloatJSONCondition(ms.MetricName, ms.Range, query)\n\t\t}\n\t}\n\tif filter.Node != nil {\n\t\tquery = buildResourceJSONCondition(\"hostname\", filter.Node, query)\n\t}\n\tif filter.JobName != nil {\n\t\tquery = buildMetaJSONCondition(\"jobName\", filter.JobName, query)\n\t}\n\tif filter.Schedule != nil {\n\t\tinteractiveJobname := \"interactive\"\n\t\tswitch *filter.Schedule {\n\t\tcase \"interactive\":\n\t\t\tiFilter := model.StringInput{Eq: &interactiveJobname}\n\t\t\tquery = buildMetaJSONCondition(\"jobName\", &iFilter, query)\n\t\tcase \"batch\":\n\t\t\tsFilter := model.StringInput{Neq: &interactiveJobname}\n\t\t\tquery = buildMetaJSONCondition(\"jobName\", &sFilter, query)\n\t\t}\n\t}\n\n\t// Configurable Filter to exclude recently started jobs, see config.go: ShortRunningJobsDuration\n\tif filter.MinRunningFor != nil {\n\t\tnow := time.Now().Unix()\n\t\t// Only jobs whose start timestamp is more than MinRunningFor seconds in the past\n\t\t// If a job completed within the configured timeframe, it will still show up after the start_time matches the condition!\n\t\tquery = query.Where(sq.Lt{\"job.start_time\": (now - int64(*filter.MinRunningFor))})\n\t}\n\treturn query\n}\n\n// buildIntCondition creates clauses for integer range filters, using BETWEEN only if required.\nfunc buildIntCondition(field string, cond *config.IntRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != 1 && cond.To != 0 {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1 && cond.To == 0 {\n\t\treturn query.Where(field+\" >= ?\", cond.From)\n\t} else if cond.From == 1 && cond.To != 0 {\n\t\treturn query.Where(field+\" <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\nfunc buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1.0 && cond.To == 0.0 {\n\t\treturn query.Where(field+\" >= ?\", cond.From)\n\t} else if cond.From == 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(field+\" <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildTimeCondition creates time range filters supporting absolute timestamps,\n// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\nfunc buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != nil && cond.To != nil {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n\t} else if cond.From != nil {\n\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n\t} else if cond.To != nil {\n\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n\t} else if cond.Range != \"\" {\n\t\tnow := time.Now().Unix()\n\t\tvar then int64\n\t\tswitch cond.Range {\n\t\tcase \"last6h\":\n\t\t\tthen = now - (60 * 60 * 6)\n\t\tcase \"last24h\":\n\t\t\tthen = now - (60 * 60 * 24)\n\t\tcase \"last7d\":\n\t\t\tthen = now - (60 * 60 * 24 * 7)\n\t\tcase \"last30d\":\n\t\t\tthen = now - (60 * 60 * 24 * 30)\n\t\tdefault:\n\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n\t\t\treturn query\n\t\t}\n\t\treturn query.Where(field+\" >= ?\", then)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\nfunc buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(footprint)\")\n\tif cond.From != 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1.0 && cond.To == 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n\t} else if cond.From == 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildStringCondition creates filters for string fields supporting equality,\n// inequality, prefix, suffix, substring, and IN list matching.\nfunc buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.Eq != nil {\n\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n\t}\n\tif cond.Neq != nil {\n\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\tif cond.In != nil {\n\t\tqueryElements := make([]string, len(cond.In))\n\t\tcopy(queryElements, cond.In)\n\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n\t}\n\treturn query\n}\n\n// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\nfunc buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(meta_data)\")\n\tif cond.Eq != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n\t}\n\tif cond.Neq != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\treturn query\n}\n\n// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n// Uses json_each to search within array elements.\nfunc buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(resources)\")\n\tif cond.Eq != nil {\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n\t}\n\tif cond.Neq != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\treturn query\n}\n\nvar (\n\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n)\n\n// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n// Includes security checks to prevent SQL injection attempts.\n// Panics if potentially dangerous characters are detected.\nfunc toSnakeCase(str string) string {\n\tfor _, c := range str {\n\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n\t\t}\n\t}\n\n\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n\treturn strings.ToLower(snake)\n}\n","numLines":444,"startLine":1,"totalLines":444}},"sourceToolAssistantUUID":"5810ecbf-ac9a-44ac-86a2-74647d424b28","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"5d2038c7-8918-48d3-ad30-8bb309e197ed","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_015rgbQvnn2SaNjtrqjbgg9E","toolUseID":"toolu_015rgbQvnn2SaNjtrqjbgg9E","timestamp":"2026-03-13T13:24:04.577Z","uuid":"c1f3007a-e867-46c6-aab9-71b10e97b17d","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5d2038c7-8918-48d3-ad30-8bb309e197ed","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015rgbQvnn2SaNjtrqjbgg9E","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// This file contains job statistics and histogram generation functionality for the JobRepository.\n 7→//\n 8→// # Job Statistics\n 9→//\n 10→// The statistics methods provide aggregated metrics about jobs including total jobs, users,\n 11→// walltime, and resource usage (nodes, cores, accelerators). Statistics can be computed:\n 12→// - Overall (JobsStats): Single aggregate across all matching jobs\n 13→// - Grouped (JobsStatsGrouped): Aggregated by user, project, cluster, or subcluster\n 14→// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n 15→//\n 16→// All statistics methods support filtering via JobFilter and respect security contexts.\n 17→//\n 18→// # Histograms\n 19→//\n 20→// Histogram methods generate distribution data for visualization:\n 21→// - Duration, nodes, cores, accelerators (AddHistograms)\n 22→// - Job metrics like CPU load, memory usage (AddMetricHistograms)\n 23→//\n 24→// Histograms use intelligent binning:\n 25→// - Duration: Variable bin sizes (1m, 10m, 1h, 6h, 12h, 24h) with zero-padding\n 26→// - Resources: Natural value-based bins\n 27→// - Metrics: Normalized to peak values with configurable bin counts\n 28→//\n 29→// # Running vs. Completed Jobs\n 30→//\n 31→// Statistics handle running jobs specially:\n 32→// - Duration calculated as (now - start_time) for running jobs\n 33→// - Metric histograms for running jobs load data from metric backend instead of footprint\n 34→// - Job state filtering distinguishes running/completed jobs\n 35→//\n 36→// # Performance Considerations\n 37→//\n 38→// - All queries use prepared statements via stmtCache\n 39→// - Complex aggregations use SQL for efficiency\n 40→// - Histogram pre-initialization ensures consistent bin ranges\n 41→// - Metric histogram queries limited to 5000 jobs for running job analysis\n 42→\n 43→package repository\n 44→\n 45→import (\n 46→\t\"context\"\n 47→\t\"database/sql\"\n 48→\t\"fmt\"\n 49→\t\"time\"\n 50→\n 51→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n 52→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 53→\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n 54→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 55→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 56→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 57→\tsq \"github.com/Masterminds/squirrel\"\n 58→)\n 59→\n 60→// groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names.\n 61→// Used by JobsStatsGrouped and JobCountGrouped to translate user-facing grouping dimensions\n 62→// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\n 63→var groupBy2column = map[model.Aggregate]string{\n 64→\tmodel.AggregateUser: \"job.hpc_user\",\n 65→\tmodel.AggregateProject: \"job.project\",\n 66→\tmodel.AggregateCluster: \"job.cluster\",\n 67→\tmodel.AggregateSubcluster: \"job.subcluster\",\n 68→}\n 69→\n 70→// sortBy2column maps GraphQL SortByAggregate enum values to their corresponding computed column names.\n 71→// Used by JobsStatsGrouped to translate sort preferences into SQL ORDER BY clauses.\n 72→// Column names match the AS aliases used in buildStatsQuery.\n 73→var sortBy2column = map[model.SortByAggregate]string{\n 74→\tmodel.SortByAggregateTotaljobs: \"totalJobs\",\n 75→\tmodel.SortByAggregateTotalusers: \"totalUsers\",\n 76→\tmodel.SortByAggregateTotalwalltime: \"totalWalltime\",\n 77→\tmodel.SortByAggregateTotalnodes: \"totalNodes\",\n 78→\tmodel.SortByAggregateTotalnodehours: \"totalNodeHours\",\n 79→\tmodel.SortByAggregateTotalcores: \"totalCores\",\n 80→\tmodel.SortByAggregateTotalcorehours: \"totalCoreHours\",\n 81→\tmodel.SortByAggregateTotalaccs: \"totalAccs\",\n 82→\tmodel.SortByAggregateTotalacchours: \"totalAccHours\",\n 83→}\n 84→\n 85→// buildCountQuery constructs a SQL query to count jobs with optional grouping and filtering.\n 86→//\n 87→// Parameters:\n 88→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 89→// - kind: Special filter - \"running\" for running jobs only, \"short\" for jobs under threshold\n 90→// - col: Column name to GROUP BY; empty string for total count without grouping\n 91→//\n 92→// Returns a SelectBuilder that produces either:\n 93→// - Single count: COUNT(job.id) when col is empty\n 94→// - Grouped counts: col, COUNT(job.id) when col is specified\n 95→//\n 96→// The kind parameter enables counting specific job categories:\n 97→// - \"running\": Only jobs with job_state = 'running'\n 98→// - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n 99→// - empty: All jobs matching filters\n 100→func (r *JobRepository) buildCountQuery(\n 101→\tfilter []*model.JobFilter,\n 102→\tkind string,\n 103→\tcol string,\n 104→) sq.SelectBuilder {\n 105→\tvar query sq.SelectBuilder\n 106→\n 107→\tif col != \"\" {\n 108→\t\tquery = sq.Select(col, \"COUNT(*)\").From(\"job\").GroupBy(col)\n 109→\t} else {\n 110→\t\tquery = sq.Select(\"COUNT(*)\").From(\"job\")\n 111→\t}\n 112→\n 113→\tswitch kind {\n 114→\tcase \"running\":\n 115→\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n 116→\tcase \"short\":\n 117→\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n 118→\t}\n 119→\n 120→\tfor _, f := range filter {\n 121→\t\tquery = BuildWhereClause(f, query)\n 122→\t}\n 123→\n 124→\treturn query\n 125→}\n 126→\n 127→// buildStatsQuery constructs a SQL query to compute job statistics with optional grouping.\n 128→// Only requested columns are computed; unrequested columns select 0 as placeholder.\n 129→//\n 130→// Parameters:\n 131→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 132→// - col: Column name to GROUP BY; empty string for overall statistics without grouping\n 133→// - shortThreshold: Duration threshold in seconds for counting short-running jobs\n 134→// - reqFields: Set of requested field names; nil means compute all fields\n 135→func (r *JobRepository) buildStatsQuery(\n 136→\tfilter []*model.JobFilter,\n 137→\tcol string,\n 138→\tshortThreshold int,\n 139→\treqFields map[string]bool,\n 140→) sq.SelectBuilder {\n 141→\tnow := time.Now().Unix()\n 142→\n 143→\t// Helper: return real expression if field is requested (or reqFields is nil), else \"0 as alias\"\n 144→\tneed := func(field string) bool {\n 145→\t\treturn reqFields == nil || reqFields[field]\n 146→\t}\n 147→\tdurationExpr := fmt.Sprintf(`(CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END)`, now)\n 148→\n 149→\t// Build column list\n 150→\tcolumns := make([]string, 0, 14)\n 151→\n 152→\tif col != \"\" {\n 153→\t\tcolumns = append(columns, col)\n 154→\t}\n 155→\n 156→\tcolumns = append(columns, \"COUNT(*) as totalJobs\")\n 157→\n 158→\tif need(\"totalUsers\") && col != \"job.hpc_user\" {\n 159→\t\tcolumns = append(columns, \"COUNT(DISTINCT job.hpc_user) AS totalUsers\")\n 160→\t} else {\n 161→\t\tcolumns = append(columns, \"0 AS totalUsers\")\n 162→\t}\n 163→\n 164→\tif need(\"totalWalltime\") {\n 165→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s) / 3600) as int) as totalWalltime`, durationExpr))\n 166→\t} else {\n 167→\t\tcolumns = append(columns, \"0 as totalWalltime\")\n 168→\t}\n 169→\n 170→\tif need(\"totalNodes\") {\n 171→\t\tcolumns = append(columns, `CAST(SUM(job.num_nodes) as int) as totalNodes`)\n 172→\t} else {\n 173→\t\tcolumns = append(columns, \"0 as totalNodes\")\n 174→\t}\n 175→\n 176→\tif need(\"totalNodeHours\") {\n 177→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_nodes) / 3600) as int) as totalNodeHours`, durationExpr))\n 178→\t} else {\n 179→\t\tcolumns = append(columns, \"0 as totalNodeHours\")\n 180→\t}\n 181→\n 182→\tif need(\"totalCores\") {\n 183→\t\tcolumns = append(columns, `CAST(SUM(job.num_hwthreads) as int) as totalCores`)\n 184→\t} else {\n 185→\t\tcolumns = append(columns, \"0 as totalCores\")\n 186→\t}\n 187→\n 188→\tif need(\"totalCoreHours\") {\n 189→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_hwthreads) / 3600) as int) as totalCoreHours`, durationExpr))\n 190→\t} else {\n 191→\t\tcolumns = append(columns, \"0 as totalCoreHours\")\n 192→\t}\n 193→\n 194→\tif need(\"totalAccs\") {\n 195→\t\tcolumns = append(columns, `CAST(SUM(job.num_acc) as int) as totalAccs`)\n 196→\t} else {\n 197→\t\tcolumns = append(columns, \"0 as totalAccs\")\n 198→\t}\n 199→\n 200→\tif need(\"totalAccHours\") {\n 201→\t\tcolumns = append(columns, fmt.Sprintf(`CAST(ROUND(SUM(%s * job.num_acc) / 3600) as int) as totalAccHours`, durationExpr))\n 202→\t} else {\n 203→\t\tcolumns = append(columns, \"0 as totalAccHours\")\n 204→\t}\n 205→\n 206→\tif need(\"runningJobs\") {\n 207→\t\tcolumns = append(columns, `COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs`)\n 208→\t} else {\n 209→\t\tcolumns = append(columns, \"0 as runningJobs\")\n 210→\t}\n 211→\n 212→\tif need(\"shortJobs\") {\n 213→\t\tcolumns = append(columns, fmt.Sprintf(`COUNT(CASE WHEN job.duration < %d THEN 1 END) as shortJobs`, shortThreshold))\n 214→\t} else {\n 215→\t\tcolumns = append(columns, \"0 as shortJobs\")\n 216→\t}\n 217→\n 218→\tquery := sq.Select(columns...).From(\"job\")\n 219→\tif col != \"\" {\n 220→\t\tquery = query.GroupBy(col)\n 221→\t}\n 222→\n 223→\tfor _, f := range filter {\n 224→\t\tquery = BuildWhereClause(f, query)\n 225→\t}\n 226→\n 227→\treturn query\n 228→}\n 229→\n 230→// JobsStatsGrouped computes job statistics grouped by a dimension (user, project, cluster, or subcluster).\n 231→// Only columns listed in reqFields are computed; others return 0. User display names are looked up\n 232→// in a separate lightweight query to avoid JOIN overhead on the main aggregation.\n 233→func (r *JobRepository) JobsStatsGrouped(\n 234→\tctx context.Context,\n 235→\tfilter []*model.JobFilter,\n 236→\tpage *model.PageRequest,\n 237→\tsortBy *model.SortByAggregate,\n 238→\tgroupBy *model.Aggregate,\n 239→\treqFields map[string]bool,\n 240→) ([]*model.JobsStatistics, error) {\n 241→\tcol := groupBy2column[*groupBy]\n 242→\tquery := r.buildStatsQuery(filter, col, config.Keys.ShortRunningJobsDuration, reqFields)\n 243→\n 244→\tquery, err := SecurityCheck(ctx, query)\n 245→\tif err != nil {\n 246→\t\treturn nil, err\n 247→\t}\n 248→\n 249→\tif sortBy != nil {\n 250→\t\tsortBy := sortBy2column[*sortBy]\n 251→\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n 252→\t}\n 253→\tif page != nil && page.ItemsPerPage != -1 {\n 254→\t\tlimit := uint64(page.ItemsPerPage)\n 255→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 256→\t}\n 257→\n 258→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 259→\tif err != nil {\n 260→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 261→\t\treturn nil, err\n 262→\t}\n 263→\tdefer rows.Close()\n 264→\n 265→\tstats := make([]*model.JobsStatistics, 0, 100)\n 266→\n 267→\tfor rows.Next() {\n 268→\t\tvar id sql.NullString\n 269→\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n 270→\t\tif err := rows.Scan(&id, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n 271→\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n 272→\t\t\treturn nil, err\n 273→\t\t}\n 274→\n 275→\t\tif id.Valid {\n 276→\t\t\tstats = append(stats,\n 277→\t\t\t\t&model.JobsStatistics{\n 278→\t\t\t\t\tID: id.String,\n 279→\t\t\t\t\tTotalJobs: int(jobs.Int64),\n 280→\t\t\t\t\tTotalUsers: int(users.Int64),\n 281→\t\t\t\t\tTotalWalltime: int(walltime.Int64),\n 282→\t\t\t\t\tTotalNodes: int(nodes.Int64),\n 283→\t\t\t\t\tTotalNodeHours: int(nodeHours.Int64),\n 284→\t\t\t\t\tTotalCores: int(cores.Int64),\n 285→\t\t\t\t\tTotalCoreHours: int(coreHours.Int64),\n 286→\t\t\t\t\tTotalAccs: int(accs.Int64),\n 287→\t\t\t\t\tTotalAccHours: int(accHours.Int64),\n 288→\t\t\t\t\tRunningJobs: int(runningJobs.Int64),\n 289→\t\t\t\t\tShortJobs: int(shortJobs.Int64),\n 290→\t\t\t\t})\n 291→\t\t}\n 292→\t}\n 293→\n 294→\tif err := rows.Err(); err != nil {\n 295→\t\treturn nil, err\n 296→\t}\n 297→\n 298→\t// Post-query name lookup for user grouping (avoids LEFT JOIN on aggregation query)\n 299→\tif col == \"job.hpc_user\" && len(stats) > 0 {\n 300→\t\tusernames := make([]any, len(stats))\n 301→\t\tfor i, s := range stats {\n 302→\t\t\tusernames[i] = s.ID\n 303→\t\t}\n 304→\n 305→\t\tnameQuery := sq.Select(\"username\", \"name\").From(\"hpc_user\").Where(sq.Eq{\"username\": usernames})\n 306→\t\tnameRows, err := nameQuery.RunWith(r.DB).QueryContext(ctx)\n 307→\t\tif err != nil {\n 308→\t\t\tcclog.Warnf(\"Error looking up user names: %s\", err.Error())\n 309→\t\t\t// Non-fatal: stats are still valid without display names\n 310→\t\t} else {\n 311→\t\t\tdefer nameRows.Close()\n 312→\t\t\tnameMap := make(map[string]string, len(stats))\n 313→\t\t\tfor nameRows.Next() {\n 314→\t\t\t\tvar username, name string\n 315→\t\t\t\tif err := nameRows.Scan(&username, &name); err == nil {\n 316→\t\t\t\t\tnameMap[username] = name\n 317→\t\t\t\t}\n 318→\t\t\t}\n 319→\t\t\tfor _, s := range stats {\n 320→\t\t\t\tif name, ok := nameMap[s.ID]; ok {\n 321→\t\t\t\t\ts.Name = name\n 322→\t\t\t\t}\n 323→\t\t\t}\n 324→\t\t}\n 325→\t}\n 326→\n 327→\treturn stats, nil\n 328→}\n 329→\n 330→// JobsStats computes overall job statistics across all matching jobs without grouping.\n 331→//\n 332→// This method provides a single aggregate view of job metrics, useful for dashboard\n 333→// summaries and overall system utilization reports.\n 334→//\n 335→// Parameters:\n 336→// - ctx: Context for security checks and cancellation\n 337→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 338→//\n 339→// Returns a single-element slice containing aggregate statistics:\n 340→// - totalJobs, totalUsers, totalWalltime\n 341→// - totalNodeHours, totalCoreHours, totalAccHours\n 342→//\n 343→// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n 344→// Security checks are applied via SecurityCheck to respect user access levels.\n 345→func (r *JobRepository) JobsStats(\n 346→\tctx context.Context,\n 347→\tfilter []*model.JobFilter,\n 348→\treqFields map[string]bool,\n 349→) ([]*model.JobsStatistics, error) {\n 350→\tstart := time.Now()\n 351→\tquery := r.buildStatsQuery(filter, \"\", config.Keys.ShortRunningJobsDuration, reqFields)\n 352→\tquery, err := SecurityCheck(ctx, query)\n 353→\tif err != nil {\n 354→\t\treturn nil, err\n 355→\t}\n 356→\n 357→\trow := query.RunWith(r.DB).QueryRowContext(ctx)\n 358→\tstats := make([]*model.JobsStatistics, 0, 1)\n 359→\n 360→\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n 361→\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n 362→\t\tcclog.Warn(\"Error while scanning rows\")\n 363→\t\treturn nil, err\n 364→\t}\n 365→\n 366→\tif jobs.Valid {\n 367→\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n 368→\n 369→\t\tif nodeHours.Valid {\n 370→\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 371→\t\t}\n 372→\t\tif coreHours.Valid {\n 373→\t\t\ttotalCoreHours = int(coreHours.Int64)\n 374→\t\t}\n 375→\t\tif accHours.Valid {\n 376→\t\t\ttotalAccHours = int(accHours.Int64)\n 377→\t\t}\n 378→\t\tstats = append(stats,\n 379→\t\t\t&model.JobsStatistics{\n 380→\t\t\t\tTotalJobs: int(jobs.Int64),\n 381→\t\t\t\tTotalUsers: int(users.Int64),\n 382→\t\t\t\tTotalWalltime: int(walltime.Int64),\n 383→\t\t\t\tTotalNodeHours: totalNodeHours,\n 384→\t\t\t\tTotalCoreHours: totalCoreHours,\n 385→\t\t\t\tTotalAccHours: totalAccHours,\n 386→\t\t\t\tRunningJobs: int(runningJobs.Int64),\n 387→\t\t\t\tShortJobs: int(shortJobs.Int64),\n 388→\t\t\t})\n 389→\t}\n 390→\n 391→\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n 392→\treturn stats, nil\n 393→}\n 394→\n 395→// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n 396→// Returns 0.0 if the metric is not found or statType is invalid.\n 397→//\n 398→// Parameters:\n 399→// - job: Job struct with populated Statistics field\n 400→// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n 401→// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n 402→//\n 403→// Returns the requested statistic value or 0.0 if not found.\n 404→func LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n 405→\tif stats, ok := job.Statistics[metric]; ok {\n 406→\t\tswitch statType {\n 407→\t\tcase \"avg\":\n 408→\t\t\treturn stats.Avg\n 409→\t\tcase \"max\":\n 410→\t\t\treturn stats.Max\n 411→\t\tcase \"min\":\n 412→\t\t\treturn stats.Min\n 413→\t\tdefault:\n 414→\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n 415→\t\t}\n 416→\t}\n 417→\n 418→\treturn 0.0\n 419→}\n 420→\n 421→// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n 422→//\n 423→// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n 424→// avoiding the overhead of calculating walltime and resource usage metrics.\n 425→//\n 426→// Parameters:\n 427→// - ctx: Context for security checks\n 428→// - filter: Filters to apply\n 429→// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n 430→//\n 431→// Returns JobsStatistics with only ID and TotalJobs populated for each group.\n 432→func (r *JobRepository) JobCountGrouped(\n 433→\tctx context.Context,\n 434→\tfilter []*model.JobFilter,\n 435→\tgroupBy *model.Aggregate,\n 436→) ([]*model.JobsStatistics, error) {\n 437→\tstart := time.Now()\n 438→\tcol := groupBy2column[*groupBy]\n 439→\tquery := r.buildCountQuery(filter, \"\", col)\n 440→\tquery, err := SecurityCheck(ctx, query)\n 441→\tif err != nil {\n 442→\t\treturn nil, err\n 443→\t}\n 444→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 445→\tif err != nil {\n 446→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 447→\t\treturn nil, err\n 448→\t}\n 449→\tdefer rows.Close()\n 450→\n 451→\tstats := make([]*model.JobsStatistics, 0, 100)\n 452→\n 453→\tfor rows.Next() {\n 454→\t\tvar id sql.NullString\n 455→\t\tvar cnt sql.NullInt64\n 456→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 457→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 458→\t\t\treturn nil, err\n 459→\t\t}\n 460→\t\tif id.Valid {\n 461→\t\t\tstats = append(stats,\n 462→\t\t\t\t&model.JobsStatistics{\n 463→\t\t\t\t\tID: id.String,\n 464→\t\t\t\t\tTotalJobs: int(cnt.Int64),\n 465→\t\t\t\t})\n 466→\t\t}\n 467→\t}\n 468→\n 469→\tif err := rows.Err(); err != nil {\n 470→\t\treturn nil, err\n 471→\t}\n 472→\n 473→\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n 474→\treturn stats, nil\n 475→}\n 476→\n 477→// AddJobCountGrouped augments existing statistics with additional job counts by category.\n 478→//\n 479→// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n 480→// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n 481→//\n 482→// Parameters:\n 483→// - ctx: Context for security checks\n 484→// - filter: Filters to apply\n 485→// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n 486→// - stats: Existing statistics to augment (modified in-place by ID matching)\n 487→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 488→//\n 489→// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n 490→// Groups without matching jobs will have 0 for the added field.\n 491→func (r *JobRepository) AddJobCountGrouped(\n 492→\tctx context.Context,\n 493→\tfilter []*model.JobFilter,\n 494→\tgroupBy *model.Aggregate,\n 495→\tstats []*model.JobsStatistics,\n 496→\tkind string,\n 497→) ([]*model.JobsStatistics, error) {\n 498→\tstart := time.Now()\n 499→\tcol := groupBy2column[*groupBy]\n 500→\tquery := r.buildCountQuery(filter, kind, col)\n 501→\tquery, err := SecurityCheck(ctx, query)\n 502→\tif err != nil {\n 503→\t\treturn nil, err\n 504→\t}\n 505→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 506→\tif err != nil {\n 507→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 508→\t\treturn nil, err\n 509→\t}\n 510→\tdefer rows.Close()\n 511→\n 512→\tcounts := make(map[string]int)\n 513→\n 514→\tfor rows.Next() {\n 515→\t\tvar id sql.NullString\n 516→\t\tvar cnt sql.NullInt64\n 517→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 518→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 519→\t\t\treturn nil, err\n 520→\t\t}\n 521→\t\tif id.Valid {\n 522→\t\t\tcounts[id.String] = int(cnt.Int64)\n 523→\t\t}\n 524→\t}\n 525→\n 526→\tif err := rows.Err(); err != nil {\n 527→\t\treturn nil, err\n 528→\t}\n 529→\n 530→\tswitch kind {\n 531→\tcase \"running\":\n 532→\t\tfor _, s := range stats {\n 533→\t\t\ts.RunningJobs = counts[s.ID]\n 534→\t\t}\n 535→\tcase \"short\":\n 536→\t\tfor _, s := range stats {\n 537→\t\t\ts.ShortJobs = counts[s.ID]\n 538→\t\t}\n 539→\t}\n 540→\n 541→\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n 542→\treturn stats, nil\n 543→}\n 544→\n 545→// AddJobCount augments existing overall statistics with additional job counts by category.\n 546→//\n 547→// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n 548→// to all statistics entries (typically just one).\n 549→//\n 550→// Parameters:\n 551→// - ctx: Context for security checks\n 552→// - filter: Filters to apply\n 553→// - stats: Existing statistics to augment (modified in-place)\n 554→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 555→//\n 556→// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\n 557→func (r *JobRepository) AddJobCount(\n 558→\tctx context.Context,\n 559→\tfilter []*model.JobFilter,\n 560→\tstats []*model.JobsStatistics,\n 561→\tkind string,\n 562→) ([]*model.JobsStatistics, error) {\n 563→\tstart := time.Now()\n 564→\tquery := r.buildCountQuery(filter, kind, \"\")\n 565→\tquery, err := SecurityCheck(ctx, query)\n 566→\tif err != nil {\n 567→\t\treturn nil, err\n 568→\t}\n 569→\tvar cnt sql.NullInt64\n 570→\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&cnt); err != nil {\n 571→\t\tcclog.Warn(\"Error while querying DB for job count\")\n 572→\t\treturn nil, err\n 573→\t}\n 574→\n 575→\tcount := int(cnt.Int64)\n 576→\n 577→\tswitch kind {\n 578→\tcase \"running\":\n 579→\t\tfor _, s := range stats {\n 580→\t\t\ts.RunningJobs = count\n 581→\t\t}\n 582→\tcase \"short\":\n 583→\t\tfor _, s := range stats {\n 584→\t\t\ts.ShortJobs = count\n 585→\t\t}\n 586→\t}\n 587→\n 588→\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n 589→\treturn stats, nil\n 590→}\n 591→\n 592→// AddHistograms augments statistics with distribution histograms for job properties.\n 593→//\n 594→// Generates histogram data for visualization of job duration, node count, core count,\n 595→// and accelerator count distributions. Duration histogram uses intelligent binning based\n 596→// on the requested resolution.\n 597→//\n 598→// Parameters:\n 599→// - ctx: Context for security checks\n 600→// - filter: Filters to apply to jobs included in histograms\n 601→// - stat: Statistics struct to augment (modified in-place)\n 602→// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n 603→//\n 604→// Populates these fields in stat:\n 605→// - HistDuration: Job duration distribution (zero-padded bins)\n 606→// - HistNumNodes: Node count distribution\n 607→// - HistNumCores: Core (hwthread) count distribution\n 608→// - HistNumAccs: Accelerator count distribution\n 609→//\n 610→// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n 611→// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\n 612→func (r *JobRepository) AddHistograms(\n 613→\tctx context.Context,\n 614→\tfilter []*model.JobFilter,\n 615→\tstat *model.JobsStatistics,\n 616→\tdurationBins *string,\n 617→) (*model.JobsStatistics, error) {\n 618→\tstart := time.Now()\n 619→\n 620→\tvar targetBinCount int\n 621→\tvar targetBinSize int\n 622→\tswitch *durationBins {\n 623→\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n 624→\t\ttargetBinCount = 60\n 625→\t\ttargetBinSize = 60\n 626→\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n 627→\t\ttargetBinCount = 72\n 628→\t\ttargetBinSize = 600\n 629→\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n 630→\t\ttargetBinCount = 48\n 631→\t\ttargetBinSize = 3600\n 632→\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n 633→\t\ttargetBinCount = 12\n 634→\t\ttargetBinSize = 21600\n 635→\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n 636→\t\ttargetBinCount = 14\n 637→\t\ttargetBinSize = 43200\n 638→\tdefault: // 24h\n 639→\t\ttargetBinCount = 24\n 640→\t\ttargetBinSize = 3600\n 641→\t}\n 642→\n 643→\tvar err error\n 644→\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n 645→\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n 646→\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n 647→\tif err != nil {\n 648→\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n 649→\t\treturn nil, err\n 650→\t}\n 651→\n 652→\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n 653→\tif err != nil {\n 654→\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n 655→\t\treturn nil, err\n 656→\t}\n 657→\n 658→\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n 659→\tif err != nil {\n 660→\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n 661→\t\treturn nil, err\n 662→\t}\n 663→\n 664→\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n 665→\tif err != nil {\n 666→\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n 667→\t\treturn nil, err\n 668→\t}\n 669→\n 670→\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n 671→\treturn stat, nil\n 672→}\n 673→\n 674→// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n 675→//\n 676→// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n 677→// and completed jobs differently: running jobs load data from metric backend, completed jobs\n 678→// use footprint data from database.\n 679→//\n 680→// Parameters:\n 681→// - ctx: Context for security checks\n 682→// - filter: Filters to apply (MUST contain State filter for running jobs)\n 683→// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n 684→// - stat: Statistics struct to augment (modified in-place)\n 685→// - targetBinCount: Number of histogram bins (default: 10)\n 686→//\n 687→// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n 688→//\n 689→// Binning algorithm:\n 690→// - Values normalized to metric's peak value from cluster configuration\n 691→// - Bins evenly distributed from 0 to peak\n 692→// - Pre-initialized with zeros for consistent visualization\n 693→//\n 694→// Limitations:\n 695→// - Running jobs: Limited to 5000 jobs for performance\n 696→// - Requires valid cluster configuration with metric peak values\n 697→// - Uses footprint statistic (avg/max/min) configured per metric\n 698→func (r *JobRepository) AddMetricHistograms(\n 699→\tctx context.Context,\n 700→\tfilter []*model.JobFilter,\n 701→\tmetrics []string,\n 702→\tstat *model.JobsStatistics,\n 703→\ttargetBinCount *int,\n 704→) (*model.JobsStatistics, error) {\n 705→\tstart := time.Now()\n 706→\n 707→\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n 708→\tfor _, f := range filter {\n 709→\t\tif f.State != nil {\n 710→\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n 711→\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n 712→\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 713→\t\t\t\treturn stat, nil\n 714→\t\t\t}\n 715→\t\t}\n 716→\t}\n 717→\n 718→\t// All other cases: Query and make bins in sqlite directly\n 719→\tfor _, m := range metrics {\n 720→\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n 721→\t\tif err != nil {\n 722→\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n 723→\t\t\tcontinue\n 724→\t\t}\n 725→\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n 726→\t}\n 727→\n 728→\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 729→\treturn stat, nil\n 730→}\n 731→\n 732→// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n 733→//\n 734→// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n 735→// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n 736→//\n 737→// Parameters:\n 738→// - value: SQL expression that produces the histogram value, aliased as \"value\"\n 739→// - filters: Job filters to apply\n 740→//\n 741→// Returns histogram points with Value (from column) and Count (number of jobs).\n 742→func (r *JobRepository) jobsStatisticsHistogram(\n 743→\tctx context.Context,\n 744→\tvalue string,\n 745→\tfilters []*model.JobFilter,\n 746→) ([]*model.HistoPoint, error) {\n 747→\tstart := time.Now()\n 748→\tquery, qerr := SecurityCheck(ctx,\n 749→\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n 750→\n 751→\tif qerr != nil {\n 752→\t\treturn nil, qerr\n 753→\t}\n 754→\n 755→\tfor _, f := range filters {\n 756→\t\tquery = BuildWhereClause(f, query)\n 757→\t}\n 758→\n 759→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n 760→\tif err != nil {\n 761→\t\tcclog.Error(\"Error while running query\")\n 762→\t\treturn nil, err\n 763→\t}\n 764→\tdefer rows.Close()\n 765→\n 766→\tpoints := make([]*model.HistoPoint, 0)\n 767→\t// is it possible to introduce zero values here? requires info about bincount\n 768→\tfor rows.Next() {\n 769→\t\tpoint := model.HistoPoint{}\n 770→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 771→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 772→\t\t\treturn nil, err\n 773→\t\t}\n 774→\n 775→\t\tpoints = append(points, &point)\n 776→\t}\n 777→\n 778→\tif err := rows.Err(); err != nil {\n 779→\t\treturn nil, err\n 780→\t}\n 781→\n 782→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 783→\treturn points, nil\n 784→}\n 785→\n 786→// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n 787→//\n 788→// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n 789→// histograms which only return bins with data. The value parameter should compute\n 790→// the bin number from job duration.\n 791→//\n 792→// Parameters:\n 793→// - value: SQL expression computing bin number from duration, aliased as \"value\"\n 794→// - filters: Job filters to apply\n 795→// - binSizeSeconds: Width of each bin in seconds\n 796→// - targetBinCount: Number of bins to pre-initialize\n 797→//\n 798→// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n 799→// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n 800→//\n 801→// Algorithm:\n 802→// 1. Pre-initialize targetBinCount bins with zero counts\n 803→// 2. Query database for actual counts per bin\n 804→// 3. Match query results to pre-initialized bins by value\n 805→// 4. Bins without matches remain at zero\n 806→func (r *JobRepository) jobsDurationStatisticsHistogram(\n 807→\tctx context.Context,\n 808→\tvalue string,\n 809→\tfilters []*model.JobFilter,\n 810→\tbinSizeSeconds int,\n 811→\ttargetBinCount *int,\n 812→) ([]*model.HistoPoint, error) {\n 813→\tstart := time.Now()\n 814→\tquery, qerr := SecurityCheck(ctx,\n 815→\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n 816→\n 817→\tif qerr != nil {\n 818→\t\treturn nil, qerr\n 819→\t}\n 820→\n 821→\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n 822→\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n 823→\tpoints := make([]*model.HistoPoint, 0, *targetBinCount)\n 824→\tfor i := 1; i <= *targetBinCount; i++ {\n 825→\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n 826→\t\tpoints = append(points, &point)\n 827→\t}\n 828→\n 829→\t// Build a map from bin value (seconds) to slice index for O(1) lookup.\n 830→\tbinMap := make(map[int]int, len(points))\n 831→\tfor i, p := range points {\n 832→\t\tbinMap[p.Value] = i\n 833→\t}\n 834→\n 835→\tfor _, f := range filters {\n 836→\t\tquery = BuildWhereClause(f, query)\n 837→\t}\n 838→\n 839→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n 840→\tif err != nil {\n 841→\t\tcclog.Error(\"Error while running query\")\n 842→\t\treturn nil, err\n 843→\t}\n 844→\tdefer rows.Close()\n 845→\n 846→\t// Match query results to pre-initialized bins using map lookup.\n 847→\t// point.Value from query is the bin number; multiply by binSizeSeconds to get bin key.\n 848→\tfor rows.Next() {\n 849→\t\tpoint := model.HistoPoint{}\n 850→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 851→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 852→\t\t\treturn nil, err\n 853→\t\t}\n 854→\n 855→\t\tif idx, ok := binMap[point.Value*binSizeSeconds]; ok {\n 856→\t\t\tpoints[idx].Count = point.Count\n 857→\t\t}\n 858→\t}\n 859→\n 860→\tif err := rows.Err(); err != nil {\n 861→\t\treturn nil, err\n 862→\t}\n 863→\n 864→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 865→\treturn points, nil\n 866→}\n 867→\n 868→// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n 869→//\n 870→// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n 871→// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n 872→// and computing bin assignments in SQL.\n 873→//\n 874→// Parameters:\n 875→// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n 876→// - filters: Job filters to apply\n 877→// - bins: Number of bins to generate\n 878→//\n 879→// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n 880→//\n 881→// Algorithm:\n 882→// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n 883→// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n 884→// 3. Pre-initialize bins with min/max ranges based on peak value\n 885→// 4. Query database for counts per bin\n 886→// 5. Match results to pre-initialized bins\n 887→//\n 888→// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n 889→// peak by 0.999999999 to avoid creating an extra bin.\n 890→func (r *JobRepository) jobsMetricStatisticsHistogram(\n 891→\tctx context.Context,\n 892→\tmetric string,\n 893→\tfilters []*model.JobFilter,\n 894→\tbins *int,\n 895→) (*model.MetricHistoPoints, error) {\n 896→\t// Peak value defines the upper bound for binning: values are distributed across\n 897→\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n 898→\t// scan all clusters to find the maximum peak value.\n 899→\tvar metricConfig *schema.MetricConfig\n 900→\tvar peak float64\n 901→\tvar unit string\n 902→\tvar footprintStat string\n 903→\n 904→\t// Try to get metric config from filtered cluster\n 905→\tfor _, f := range filters {\n 906→\t\tif f.Cluster != nil {\n 907→\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 908→\t\t\tpeak = metricConfig.Peak\n 909→\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 910→\t\t\tfootprintStat = metricConfig.Footprint\n 911→\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n 912→\t\t}\n 913→\t}\n 914→\n 915→\t// If no cluster filter or peak not found, find largest peak across all clusters\n 916→\t// This ensures histogram can accommodate all possible values\n 917→\tif peak == 0.0 {\n 918→\t\tfor _, c := range archive.Clusters {\n 919→\t\t\tfor _, m := range c.MetricConfig {\n 920→\t\t\t\tif m.Name == metric {\n 921→\t\t\t\t\tif m.Peak > peak {\n 922→\t\t\t\t\t\tpeak = m.Peak\n 923→\t\t\t\t\t}\n 924→\t\t\t\t\tif unit == \"\" {\n 925→\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 926→\t\t\t\t\t}\n 927→\t\t\t\t\tif footprintStat == \"\" {\n 928→\t\t\t\t\t\tfootprintStat = m.Footprint\n 929→\t\t\t\t\t}\n 930→\t\t\t\t}\n 931→\t\t\t}\n 932→\t\t}\n 933→\t}\n 934→\n 935→\t// Construct SQL histogram bins using normalized values.\n 936→\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n 937→\tstart := time.Now()\n 938→\n 939→\t// Bin calculation formula:\n 940→\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n 941→\t// Special case: value == peak would create bin N+1, so we test for equality\n 942→\t// and multiply peak by 0.999999999 to force it into bin N.\n 943→\tbinQuery := fmt.Sprintf(`CAST(\n 944→\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n 945→\t\t* %v as INTEGER )`,\n 946→\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n 947→\n 948→\tmainQuery := sq.Select(\n 949→\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n 950→\t\t`count(*) as count`,\n 951→\t).From(\"job\").Where(\n 952→\t\t\"JSON_VALID(footprint)\",\n 953→\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n 954→\n 955→\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n 956→\tif qerr != nil {\n 957→\t\treturn nil, qerr\n 958→\t}\n 959→\n 960→\tfor _, f := range filters {\n 961→\t\tmainQuery = BuildWhereClause(f, mainQuery)\n 962→\t}\n 963→\n 964→\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n 965→\n 966→\trows, err := mainQuery.RunWith(r.DB).QueryContext(ctx)\n 967→\tif err != nil {\n 968→\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n 969→\t\treturn nil, err\n 970→\t}\n 971→\tdefer rows.Close()\n 972→\n 973→\t// Pre-initialize bins with calculated min/max ranges.\n 974→\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n 975→\tpoints := make([]*model.MetricHistoPoint, 0, *bins)\n 976→\tbinStep := int(peak) / *bins\n 977→\tfor i := 1; i <= *bins; i++ {\n 978→\t\tbinMin := (binStep * (i - 1))\n 979→\t\tbinMax := (binStep * i)\n 980→\t\tidx := i\n 981→\t\tepoint := model.MetricHistoPoint{Bin: &idx, Count: 0, Min: &binMin, Max: &binMax}\n 982→\t\tpoints = append(points, &epoint)\n 983→\t}\n 984→\n 985→\t// Build a map from bin number to slice index for O(1) lookup.\n 986→\tbinMap := make(map[int]int, len(points))\n 987→\tfor i, p := range points {\n 988→\t\tif p.Bin != nil {\n 989→\t\t\tbinMap[*p.Bin] = i\n 990→\t\t}\n 991→\t}\n 992→\n 993→\t// Match query results to pre-initialized bins using map lookup.\n 994→\tfor rows.Next() {\n 995→\t\trpoint := model.MetricHistoPoint{}\n 996→\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n 997→\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n 998→\t\t\treturn nil, err\n 999→\t\t}\n 1000→\n 1001→\t\tif rpoint.Bin != nil {\n 1002→\t\t\tif idx, ok := binMap[*rpoint.Bin]; ok {\n 1003→\t\t\t\tpoints[idx].Count = rpoint.Count\n 1004→\t\t\t}\n 1005→\t\t}\n 1006→\t}\n 1007→\n 1008→\tif err := rows.Err(); err != nil {\n 1009→\t\treturn nil, err\n 1010→\t}\n 1011→\n 1012→\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n 1013→\n 1014→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 1015→\treturn &result, nil\n 1016→}\n 1017→\n 1018→// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n 1019→//\n 1020→// Unlike completed jobs which use footprint data from the database, running jobs require\n 1021→// fetching current metric averages from the metric backend (via metricdispatch).\n 1022→//\n 1023→// Parameters:\n 1024→// - metrics: List of metric names\n 1025→// - filters: Job filters (should filter to running jobs only)\n 1026→// - bins: Number of histogram bins\n 1027→//\n 1028→// Returns slice of MetricHistoPoints, one per metric.\n 1029→//\n 1030→// Limitations:\n 1031→// - Maximum 5000 jobs (returns nil if more jobs match)\n 1032→// - Requires metric backend availability\n 1033→// - Bins based on metric peak values from cluster configuration\n 1034→//\n 1035→// Algorithm:\n 1036→// 1. Query first 5001 jobs to check count limit\n 1037→// 2. Load metric averages for all jobs via metricdispatch\n 1038→// 3. For each metric, create bins based on peak value\n 1039→// 4. Iterate averages and count jobs per bin\n 1040→func (r *JobRepository) runningJobsMetricStatisticsHistogram(\n 1041→\tctx context.Context,\n 1042→\tmetrics []string,\n 1043→\tfilters []*model.JobFilter,\n 1044→\tbins *int,\n 1045→) []*model.MetricHistoPoints {\n 1046→\t// Get Jobs\n 1047→\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n 1048→\tif err != nil {\n 1049→\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n 1050→\t\treturn nil\n 1051→\t}\n 1052→\tif len(jobs) > 5000 {\n 1053→\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n 1054→\t\treturn nil\n 1055→\t}\n 1056→\n 1057→\t// Get AVGs from metric repo\n 1058→\tavgs := make([][]schema.Float, len(metrics))\n 1059→\tfor i := range avgs {\n 1060→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n 1061→\t}\n 1062→\n 1063→\tfor _, job := range jobs {\n 1064→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 1065→\t\t\tcontinue\n 1066→\t\t}\n 1067→\n 1068→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n 1069→\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n 1070→\t\t\treturn nil\n 1071→\t\t}\n 1072→\t}\n 1073→\n 1074→\t// Iterate metrics to fill endresult\n 1075→\tdata := make([]*model.MetricHistoPoints, 0)\n 1076→\tfor idx, metric := range metrics {\n 1077→\t\t// Get specific Peak or largest Peak\n 1078→\t\tvar metricConfig *schema.MetricConfig\n 1079→\t\tvar peak float64\n 1080→\t\tvar unit string\n 1081→\n 1082→\t\tfor _, f := range filters {\n 1083→\t\t\tif f.Cluster != nil {\n 1084→\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 1085→\t\t\t\tpeak = metricConfig.Peak\n 1086→\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 1087→\t\t\t}\n 1088→\t\t}\n 1089→\n 1090→\t\tif peak == 0.0 {\n 1091→\t\t\tfor _, c := range archive.Clusters {\n 1092→\t\t\t\tfor _, m := range c.MetricConfig {\n 1093→\t\t\t\t\tif m.Name == metric {\n 1094→\t\t\t\t\t\tif m.Peak > peak {\n 1095→\t\t\t\t\t\t\tpeak = m.Peak\n 1096→\t\t\t\t\t\t}\n 1097→\t\t\t\t\t\tif unit == \"\" {\n 1098→\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 1099→\t\t\t\t\t\t}\n 1100→\t\t\t\t\t}\n 1101→\t\t\t\t}\n 1102→\t\t\t}\n 1103→\t\t}\n 1104→\n 1105→\t\t// Make and fill bins\n 1106→\t\tpeakBin := int(peak) / *bins\n 1107→\n 1108→\t\tpoints := make([]*model.MetricHistoPoint, 0)\n 1109→\t\tfor b := 0; b < *bins; b++ {\n 1110→\t\t\tcount := 0\n 1111→\t\t\tbindex := b + 1\n 1112→\t\t\tbmin := peakBin * b\n 1113→\t\t\tbmax := peakBin * (b + 1)\n 1114→\n 1115→\t\t\t// Iterate AVG values for indexed metric and count for bins\n 1116→\t\t\tfor _, val := range avgs[idx] {\n 1117→\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n 1118→\t\t\t\t\tcount += 1\n 1119→\t\t\t\t}\n 1120→\t\t\t}\n 1121→\n 1122→\t\t\t// Append Bin to Metric Result Array\n 1123→\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n 1124→\t\t\tpoints = append(points, &point)\n 1125→\t\t}\n 1126→\n 1127→\t\t// Append Metric Result Array to final results array\n 1128→\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n 1129→\t\tdata = append(data, &result)\n 1130→\t}\n 1131→\n 1132→\treturn data\n 1133→}\n 1134→"}]},"uuid":"8e648dca-247d-4294-b32e-57b625e2752a","timestamp":"2026-03-13T13:24:04.576Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file contains job statistics and histogram generation functionality for the JobRepository.\n//\n// # Job Statistics\n//\n// The statistics methods provide aggregated metrics about jobs including total jobs, users,\n// walltime, and resource usage (nodes, cores, accelerators). Statistics can be computed:\n// - Overall (JobsStats): Single aggregate across all matching jobs\n// - Grouped (JobsStatsGrouped): Aggregated by user, project, cluster, or subcluster\n// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n//\n// All statistics methods support filtering via JobFilter and respect security contexts.\n//\n// # Histograms\n//\n// Histogram methods generate distribution data for visualization:\n// - Duration, nodes, cores, accelerators (AddHistograms)\n// - Job metrics like CPU load, memory usage (AddMetricHistograms)\n//\n// Histograms use intelligent binning:\n// - Duration: Variable bin sizes (1m, 10m, 1h, 6h, 12h, 24h) with zero-padding\n// - Resources: Natural value-based bins\n// - Metrics: Normalized to peak values with configurable bin counts\n//\n// # Running vs. Completed Jobs\n//\n// Statistics handle running jobs specially:\n// - Duration calculated as (now - start_time) for running jobs\n// - Metric histograms for running jobs load data from metric backend instead of footprint\n// - Job state filtering distinguishes running/completed jobs\n//\n// # Performance Considerations\n//\n// - All queries use prepared statements via stmtCache\n// - Complex aggregations use SQL for efficiency\n// - Histogram pre-initialization ensures consistent bin ranges\n// - Metric histogram queries limited to 5000 jobs for running job analysis\n\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"fmt\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\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/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n)\n\n// groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names.\n// Used by JobsStatsGrouped and JobCountGrouped to translate user-facing grouping dimensions\n// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\nvar groupBy2column = map[model.Aggregate]string{\n\tmodel.AggregateUser: \"job.hpc_user\",\n\tmodel.AggregateProject: \"job.project\",\n\tmodel.AggregateCluster: \"job.cluster\",\n\tmodel.AggregateSubcluster: \"job.subcluster\",\n}\n\n// sortBy2column maps GraphQL SortByAggregate enum values to their corresponding computed column names.\n// Used by JobsStatsGrouped to translate sort preferences into SQL ORDER BY clauses.\n// Column names match the AS aliases used in buildStatsQuery.\nvar sortBy2column = map[model.SortByAggregate]string{\n\tmodel.SortByAggregateTotaljobs: \"totalJobs\",\n\tmodel.SortByAggregateTotalusers: \"totalUsers\",\n\tmodel.SortByAggregateTotalwalltime: \"totalWalltime\",\n\tmodel.SortByAggregateTotalnodes: \"totalNodes\",\n\tmodel.SortByAggregateTotalnodehours: \"totalNodeHours\",\n\tmodel.SortByAggregateTotalcores: \"totalCores\",\n\tmodel.SortByAggregateTotalcorehours: \"totalCoreHours\",\n\tmodel.SortByAggregateTotalaccs: \"totalAccs\",\n\tmodel.SortByAggregateTotalacchours: \"totalAccHours\",\n}\n\n// buildCountQuery constructs a SQL query to count jobs with optional grouping and filtering.\n//\n// Parameters:\n// - filter: Job filters to apply (cluster, user, time range, etc.)\n// - kind: Special filter - \"running\" for running jobs only, \"short\" for jobs under threshold\n// - col: Column name to GROUP BY; empty string for total count without grouping\n//\n// Returns a SelectBuilder that produces either:\n// - Single count: COUNT(job.id) when col is empty\n// - Grouped counts: col, COUNT(job.id) when col is specified\n//\n// The kind parameter enables counting specific job categories:\n// - \"running\": Only jobs with job_state = 'running'\n// - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n// - empty: All jobs matching filters\nfunc (r *JobRepository) buildCountQuery(\n\tfilter []*model.JobFilter,\n\tkind string,\n\tcol string,\n) sq.SelectBuilder {\n\tvar query sq.SelectBuilder\n\n\tif col != \"\" {\n\t\tquery = sq.Select(col, \"COUNT(*)\").From(\"job\").GroupBy(col)\n\t} else {\n\t\tquery = sq.Select(\"COUNT(*)\").From(\"job\")\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n\tcase \"short\":\n\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n\t}\n\n\tfor _, f := range filter {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\treturn query\n}\n\n// buildStatsQuery constructs a SQL query to compute job statistics with optional grouping.\n// Only requested columns are computed; unrequested columns select 0 as placeholder.\n//\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\") && col != \"job.hpc_user\" {\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}\n\n// JobsStatsGrouped computes job statistics grouped by a dimension (user, project, cluster, or subcluster).\n// Only columns listed in reqFields are computed; others return 0. User display names are looked up\n// in a separate lightweight query to avoid JOIN overhead on the main aggregation.\nfunc (r *JobRepository) JobsStatsGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tpage *model.PageRequest,\n\tsortBy *model.SortByAggregate,\n\tgroupBy *model.Aggregate,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildStatsQuery(filter, col, config.Keys.ShortRunningJobsDuration, reqFields)\n\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif sortBy != nil {\n\t\tsortBy := sortBy2column[*sortBy]\n\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n\t}\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tlimit := uint64(page.ItemsPerPage)\n\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n\t}\n\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\t\tif err := rows.Scan(&id, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\t\tTotalNodes: int(nodes.Int64),\n\t\t\t\t\tTotalNodeHours: int(nodeHours.Int64),\n\t\t\t\t\tTotalCores: int(cores.Int64),\n\t\t\t\t\tTotalCoreHours: int(coreHours.Int64),\n\t\t\t\t\tTotalAccs: int(accs.Int64),\n\t\t\t\t\tTotalAccHours: int(accHours.Int64),\n\t\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\t// Post-query name lookup for user grouping (avoids LEFT JOIN on aggregation query)\n\tif col == \"job.hpc_user\" && len(stats) > 0 {\n\t\tusernames := make([]any, len(stats))\n\t\tfor i, s := range stats {\n\t\t\tusernames[i] = s.ID\n\t\t}\n\n\t\tnameQuery := sq.Select(\"username\", \"name\").From(\"hpc_user\").Where(sq.Eq{\"username\": usernames})\n\t\tnameRows, err := nameQuery.RunWith(r.DB).QueryContext(ctx)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error looking up user names: %s\", err.Error())\n\t\t\t// Non-fatal: stats are still valid without display names\n\t\t} else {\n\t\t\tdefer nameRows.Close()\n\t\t\tnameMap := make(map[string]string, len(stats))\n\t\t\tfor nameRows.Next() {\n\t\t\t\tvar username, name string\n\t\t\t\tif err := nameRows.Scan(&username, &name); err == nil {\n\t\t\t\t\tnameMap[username] = name\n\t\t\t\t}\n\t\t\t}\n\t\t\tfor _, s := range stats {\n\t\t\t\tif name, ok := nameMap[s.ID]; ok {\n\t\t\t\t\ts.Name = name\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// JobsStats computes overall job statistics across all matching jobs without grouping.\n//\n// This method provides a single aggregate view of job metrics, useful for dashboard\n// summaries and overall system utilization reports.\n//\n// Parameters:\n// - ctx: Context for security checks and cancellation\n// - filter: Filters to apply (time range, cluster, job state, etc.)\n//\n// Returns a single-element slice containing aggregate statistics:\n// - totalJobs, totalUsers, totalWalltime\n// - totalNodeHours, totalCoreHours, totalAccHours\n//\n// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n// Security checks are applied via SecurityCheck to respect user access levels.\nfunc (r *JobRepository) JobsStats(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildStatsQuery(filter, \"\", config.Keys.ShortRunningJobsDuration, reqFields)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\trow := query.RunWith(r.DB).QueryRowContext(ctx)\n\tstats := make([]*model.JobsStatistics, 0, 1)\n\n\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\tcclog.Warn(\"Error while scanning rows\")\n\t\treturn nil, err\n\t}\n\n\tif jobs.Valid {\n\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n\n\t\tif nodeHours.Valid {\n\t\t\ttotalNodeHours = int(nodeHours.Int64)\n\t\t}\n\t\tif coreHours.Valid {\n\t\t\ttotalCoreHours = int(coreHours.Int64)\n\t\t}\n\t\tif accHours.Valid {\n\t\t\ttotalAccHours = int(accHours.Int64)\n\t\t}\n\t\tstats = append(stats,\n\t\t\t&model.JobsStatistics{\n\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\tTotalNodeHours: totalNodeHours,\n\t\t\t\tTotalCoreHours: totalCoreHours,\n\t\t\t\tTotalAccHours: totalAccHours,\n\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t})\n\t}\n\n\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n// Returns 0.0 if the metric is not found or statType is invalid.\n//\n// Parameters:\n// - job: Job struct with populated Statistics field\n// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n//\n// Returns the requested statistic value or 0.0 if not found.\nfunc LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n\tif stats, ok := job.Statistics[metric]; ok {\n\t\tswitch statType {\n\t\tcase \"avg\":\n\t\t\treturn stats.Avg\n\t\tcase \"max\":\n\t\t\treturn stats.Max\n\t\tcase \"min\":\n\t\t\treturn stats.Min\n\t\tdefault:\n\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n\t\t}\n\t}\n\n\treturn 0.0\n}\n\n// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n//\n// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n// avoiding the overhead of calculating walltime and resource usage metrics.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n//\n// Returns JobsStatistics with only ID and TotalJobs populated for each group.\nfunc (r *JobRepository) JobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, \"\", col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(cnt.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCountGrouped augments existing statistics with additional job counts by category.\n//\n// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n// - stats: Existing statistics to augment (modified in-place by ID matching)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n// Groups without matching jobs will have 0 for the added field.\nfunc (r *JobRepository) AddJobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, kind, col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tcounts := make(map[string]int)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tcounts[id.String] = int(cnt.Int64)\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = counts[s.ID]\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = counts[s.ID]\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCount augments existing overall statistics with additional job counts by category.\n//\n// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n// to all statistics entries (typically just one).\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - stats: Existing statistics to augment (modified in-place)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\nfunc (r *JobRepository) AddJobCount(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildCountQuery(filter, kind, \"\")\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tvar cnt sql.NullInt64\n\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&cnt); err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job count\")\n\t\treturn nil, err\n\t}\n\n\tcount := int(cnt.Int64)\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = count\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = count\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddHistograms augments statistics with distribution histograms for job properties.\n//\n// Generates histogram data for visualization of job duration, node count, core count,\n// and accelerator count distributions. Duration histogram uses intelligent binning based\n// on the requested resolution.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply to jobs included in histograms\n// - stat: Statistics struct to augment (modified in-place)\n// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n//\n// Populates these fields in stat:\n// - HistDuration: Job duration distribution (zero-padded bins)\n// - HistNumNodes: Node count distribution\n// - HistNumCores: Core (hwthread) count distribution\n// - HistNumAccs: Accelerator count distribution\n//\n// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\nfunc (r *JobRepository) AddHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstat *model.JobsStatistics,\n\tdurationBins *string,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\tvar targetBinCount int\n\tvar targetBinSize int\n\tswitch *durationBins {\n\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n\t\ttargetBinCount = 60\n\t\ttargetBinSize = 60\n\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n\t\ttargetBinCount = 72\n\t\ttargetBinSize = 600\n\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n\t\ttargetBinCount = 48\n\t\ttargetBinSize = 3600\n\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n\t\ttargetBinCount = 12\n\t\ttargetBinSize = 21600\n\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n\t\ttargetBinCount = 14\n\t\ttargetBinSize = 43200\n\tdefault: // 24h\n\t\ttargetBinCount = 24\n\t\ttargetBinSize = 3600\n\t}\n\n\tvar err error\n\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n//\n// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n// and completed jobs differently: running jobs load data from metric backend, completed jobs\n// use footprint data from database.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply (MUST contain State filter for running jobs)\n// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n// - stat: Statistics struct to augment (modified in-place)\n// - targetBinCount: Number of histogram bins (default: 10)\n//\n// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n//\n// Binning algorithm:\n// - Values normalized to metric's peak value from cluster configuration\n// - Bins evenly distributed from 0 to peak\n// - Pre-initialized with zeros for consistent visualization\n//\n// Limitations:\n// - Running jobs: Limited to 5000 jobs for performance\n// - Requires valid cluster configuration with metric peak values\n// - Uses footprint statistic (avg/max/min) configured per metric\nfunc (r *JobRepository) AddMetricHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tmetrics []string,\n\tstat *model.JobsStatistics,\n\ttargetBinCount *int,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n\tfor _, f := range filter {\n\t\tif f.State != nil {\n\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\t\t\t\treturn stat, nil\n\t\t\t}\n\t\t}\n\t}\n\n\t// All other cases: Query and make bins in sqlite directly\n\tfor _, m := range metrics {\n\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n\t\t\tcontinue\n\t\t}\n\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n\t}\n\n\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n//\n// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n//\n// Parameters:\n// - value: SQL expression that produces the histogram value, aliased as \"value\"\n// - filters: Job filters to apply\n//\n// Returns histogram points with Value (from column) and Count (number of jobs).\nfunc (r *JobRepository) jobsStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tpoints := make([]*model.HistoPoint, 0)\n\t// is it possible to introduce zero values here? requires info about bincount\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tpoints = append(points, &point)\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n//\n// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n// histograms which only return bins with data. The value parameter should compute\n// the bin number from job duration.\n//\n// Parameters:\n// - value: SQL expression computing bin number from duration, aliased as \"value\"\n// - filters: Job filters to apply\n// - binSizeSeconds: Width of each bin in seconds\n// - targetBinCount: Number of bins to pre-initialize\n//\n// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n//\n// Algorithm:\n// 1. Pre-initialize targetBinCount bins with zero counts\n// 2. Query database for actual counts per bin\n// 3. Match query results to pre-initialized bins by value\n// 4. Bins without matches remain at zero\nfunc (r *JobRepository) jobsDurationStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n\tbinSizeSeconds int,\n\ttargetBinCount *int,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n\tpoints := make([]*model.HistoPoint, 0, *targetBinCount)\n\tfor i := 1; i <= *targetBinCount; i++ {\n\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n\t\tpoints = append(points, &point)\n\t}\n\n\t// Build a map from bin value (seconds) to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tbinMap[p.Value] = i\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Match query results to pre-initialized bins using map lookup.\n\t// point.Value from query is the bin number; multiply by binSizeSeconds to get bin key.\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif idx, ok := binMap[point.Value*binSizeSeconds]; ok {\n\t\t\tpoints[idx].Count = point.Count\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n//\n// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n// and computing bin assignments in SQL.\n//\n// Parameters:\n// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n// - filters: Job filters to apply\n// - bins: Number of bins to generate\n//\n// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n//\n// Algorithm:\n// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n// 3. Pre-initialize bins with min/max ranges based on peak value\n// 4. Query database for counts per bin\n// 5. Match results to pre-initialized bins\n//\n// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n// peak by 0.999999999 to avoid creating an extra bin.\nfunc (r *JobRepository) jobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetric string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) (*model.MetricHistoPoints, error) {\n\t// Peak value defines the upper bound for binning: values are distributed across\n\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n\t// scan all clusters to find the maximum peak value.\n\tvar metricConfig *schema.MetricConfig\n\tvar peak float64\n\tvar unit string\n\tvar footprintStat string\n\n\t// Try to get metric config from filtered cluster\n\tfor _, f := range filters {\n\t\tif f.Cluster != nil {\n\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\tpeak = metricConfig.Peak\n\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\tfootprintStat = metricConfig.Footprint\n\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n\t\t}\n\t}\n\n\t// If no cluster filter or peak not found, find largest peak across all clusters\n\t// This ensures histogram can accommodate all possible values\n\tif peak == 0.0 {\n\t\tfor _, c := range archive.Clusters {\n\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\tif m.Name == metric {\n\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t}\n\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t}\n\t\t\t\t\tif footprintStat == \"\" {\n\t\t\t\t\t\tfootprintStat = m.Footprint\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\t// Construct SQL histogram bins using normalized values.\n\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n\tstart := time.Now()\n\n\t// Bin calculation formula:\n\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n\t// Special case: value == peak would create bin N+1, so we test for equality\n\t// and multiply peak by 0.999999999 to force it into bin N.\n\tbinQuery := fmt.Sprintf(`CAST(\n\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n\t\t* %v as INTEGER )`,\n\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n\n\tmainQuery := sq.Select(\n\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n\t\t`count(*) as count`,\n\t).From(\"job\").Where(\n\t\t\"JSON_VALID(footprint)\",\n\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n\n\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tmainQuery = BuildWhereClause(f, mainQuery)\n\t}\n\n\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n\n\trows, err := mainQuery.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Pre-initialize bins with calculated min/max ranges.\n\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n\tpoints := make([]*model.MetricHistoPoint, 0, *bins)\n\tbinStep := int(peak) / *bins\n\tfor i := 1; i <= *bins; i++ {\n\t\tbinMin := (binStep * (i - 1))\n\t\tbinMax := (binStep * i)\n\t\tidx := i\n\t\tepoint := model.MetricHistoPoint{Bin: &idx, Count: 0, Min: &binMin, Max: &binMax}\n\t\tpoints = append(points, &epoint)\n\t}\n\n\t// Build a map from bin number to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tif p.Bin != nil {\n\t\t\tbinMap[*p.Bin] = i\n\t\t}\n\t}\n\n\t// Match query results to pre-initialized bins using map lookup.\n\tfor rows.Next() {\n\t\trpoint := model.MetricHistoPoint{}\n\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif rpoint.Bin != nil {\n\t\t\tif idx, ok := binMap[*rpoint.Bin]; ok {\n\t\t\t\tpoints[idx].Count = rpoint.Count\n\t\t\t}\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn &result, nil\n}\n\n// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n//\n// Unlike completed jobs which use footprint data from the database, running jobs require\n// fetching current metric averages from the metric backend (via metricdispatch).\n//\n// Parameters:\n// - metrics: List of metric names\n// - filters: Job filters (should filter to running jobs only)\n// - bins: Number of histogram bins\n//\n// Returns slice of MetricHistoPoints, one per metric.\n//\n// Limitations:\n// - Maximum 5000 jobs (returns nil if more jobs match)\n// - Requires metric backend availability\n// - Bins based on metric peak values from cluster configuration\n//\n// Algorithm:\n// 1. Query first 5001 jobs to check count limit\n// 2. Load metric averages for all jobs via metricdispatch\n// 3. For each metric, create bins based on peak value\n// 4. Iterate averages and count jobs per bin\nfunc (r *JobRepository) runningJobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetrics []string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) []*model.MetricHistoPoints {\n\t// Get Jobs\n\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n\t\treturn nil\n\t}\n\tif len(jobs) > 5000 {\n\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n\t\treturn nil\n\t}\n\n\t// Get AVGs from metric repo\n\tavgs := make([][]schema.Float, len(metrics))\n\tfor i := range avgs {\n\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n\t}\n\n\tfor _, job := range jobs {\n\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n\t\t\tcontinue\n\t\t}\n\n\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n\t\t\treturn nil\n\t\t}\n\t}\n\n\t// Iterate metrics to fill endresult\n\tdata := make([]*model.MetricHistoPoints, 0)\n\tfor idx, metric := range metrics {\n\t\t// Get specific Peak or largest Peak\n\t\tvar metricConfig *schema.MetricConfig\n\t\tvar peak float64\n\t\tvar unit string\n\n\t\tfor _, f := range filters {\n\t\t\tif f.Cluster != nil {\n\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\t\tpeak = metricConfig.Peak\n\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\t}\n\t\t}\n\n\t\tif peak == 0.0 {\n\t\t\tfor _, c := range archive.Clusters {\n\t\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\t\tif m.Name == metric {\n\t\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// Make and fill bins\n\t\tpeakBin := int(peak) / *bins\n\n\t\tpoints := make([]*model.MetricHistoPoint, 0)\n\t\tfor b := 0; b < *bins; b++ {\n\t\t\tcount := 0\n\t\t\tbindex := b + 1\n\t\t\tbmin := peakBin * b\n\t\t\tbmax := peakBin * (b + 1)\n\n\t\t\t// Iterate AVG values for indexed metric and count for bins\n\t\t\tfor _, val := range avgs[idx] {\n\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n\t\t\t\t\tcount += 1\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// Append Bin to Metric Result Array\n\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n\t\t\tpoints = append(points, &point)\n\t\t}\n\n\t\t// Append Metric Result Array to final results array\n\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n\t\tdata = append(data, &result)\n\t}\n\n\treturn 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generating and any unknown code will be moved to the end.\n 6→// Code generated by github.com/99designs/gqlgen version v0.17.87\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\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n 677→\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n 678→\t\t}\n 679→\t} else {\n 680→\t\tstats = make([]*model.JobsStatistics, 0, 1)\n 681→\t\tstats = append(stats, &model.JobsStatistics{})\n 682→\t}\n 683→\n 684→\t// runningJobs and shortJobs are already inlined in JobsStats/JobsStatsGrouped.\n 685→\t// Only run separate count queries if main stats were not fetched.\n 686→\tif !fetchedMainStats {\n 687→\t\tif groupBy != nil {\n 688→\t\t\tif requireField(ctx, \"shortJobs\") {\n 689→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n 690→\t\t\t}\n 691→\t\t\tif requireField(ctx, \"runningJobs\") {\n 692→\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n 693→\t\t\t}\n 694→\t\t} else {\n 695→\t\t\tif requireField(ctx, \"shortJobs\") {\n 696→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n 697→\t\t\t}\n 698→\t\t\tif requireField(ctx, \"runningJobs\") {\n 699→\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n 700→\t\t\t}\n 701→\t\t}\n 702→\t}\n 703→\n 704→\tif err != nil {\n 705→\t\treturn nil, err\n 706→\t}\n 707→\n 708→\tif requireField(ctx, \"histDuration\") || requireField(ctx, \"histNumNodes\") || requireField(ctx, \"histNumCores\") || requireField(ctx, \"histNumAccs\") {\n 709→\n 710→\t\tif numDurationBins == nil {\n 711→\t\t\tnumDurationBins = &defaultDurationBins\n 712→\t\t}\n 713→\n 714→\t\tif groupBy == nil {\n 715→\t\t\tstats[0], err = r.Repo.AddHistograms(ctx, filter, stats[0], numDurationBins)\n 716→\t\t\tif err != nil {\n 717→\t\t\t\treturn nil, err\n 718→\t\t\t}\n 719→\t\t} else {\n 720→\t\t\treturn nil, errors.New(\"histograms only implemented without groupBy argument\")\n 721→\t\t}\n 722→\t}\n 723→\n 724→\tif requireField(ctx, \"histMetrics\") {\n 725→\n 726→\t\tif numMetricBins == nil {\n 727→\t\t\tnumMetricBins = &defaultMetricBins\n 728→\t\t}\n 729→\n 730→\t\tif groupBy == nil {\n 731→\t\t\tstats[0], err = r.Repo.AddMetricHistograms(ctx, filter, metrics, stats[0], numMetricBins)\n 732→\t\t\tif err != nil {\n 733→\t\t\t\treturn nil, err\n 734→\t\t\t}\n 735→\t\t} else {\n 736→\t\t\treturn nil, errors.New(\"metric histograms only implemented without groupBy argument\")\n 737→\t\t}\n 738→\t}\n 739→\n 740→\treturn stats, nil\n 741→}\n 742→\n 743→// JobsMetricStats is the resolver for the jobsMetricStats field.\n 744→func (r *queryResolver) JobsMetricStats(ctx context.Context, filter []*model.JobFilter, metrics []string) ([]*model.JobStats, error) {\n 745→\t// No Paging, Fixed Order by StartTime ASC\n 746→\torder := &model.OrderByInput{\n 747→\t\tField: \"startTime\",\n 748→\t\tType: \"col\",\n 749→\t\tOrder: \"ASC\",\n 750→\t}\n 751→\n 752→\tjobs, err := r.Repo.QueryJobs(ctx, filter, nil, order)\n 753→\tif err != nil {\n 754→\t\tcclog.Warn(\"Error while querying jobs for comparison\")\n 755→\t\treturn nil, err\n 756→\t}\n 757→\n 758→\tres := []*model.JobStats{}\n 759→\tfor _, job := range jobs {\n 760→\t\tdata, err := metricdispatch.LoadJobStats(job, metrics, ctx)\n 761→\t\tif err != nil {\n 762→\t\t\tcclog.Warnf(\"Error while loading comparison jobStats data for job id %d\", job.JobID)\n 763→\t\t\tcontinue\n 764→\t\t\t// return nil, err\n 765→\t\t}\n 766→\n 767→\t\tsres := []*model.NamedStats{}\n 768→\t\tfor name, md := range data {\n 769→\t\t\tsres = append(sres, &model.NamedStats{\n 770→\t\t\t\tName: name,\n 771→\t\t\t\tData: &md,\n 772→\t\t\t})\n 773→\t\t}\n 774→\n 775→\t\tnumThreadsInt := int(job.NumHWThreads)\n 776→\t\tnumAccsInt := int(job.NumAcc)\n 777→\t\tres = append(res, &model.JobStats{\n 778→\t\t\tID: int(*job.ID),\n 779→\t\t\tJobID: strconv.Itoa(int(job.JobID)),\n 780→\t\t\tStartTime: int(job.StartTime),\n 781→\t\t\tDuration: int(job.Duration),\n 782→\t\t\tCluster: job.Cluster,\n 783→\t\t\tSubCluster: job.SubCluster,\n 784→\t\t\tNumNodes: int(job.NumNodes),\n 785→\t\t\tNumHWThreads: &numThreadsInt,\n 786→\t\t\tNumAccelerators: &numAccsInt,\n 787→\t\t\tStats: sres,\n 788→\t\t})\n 789→\t}\n 790→\treturn res, err\n 791→}\n 792→\n 793→// JobsFootprints is the resolver for the jobsFootprints field.\n 794→func (r *queryResolver) JobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n 795→\t// NOTE: Legacy Naming! This resolver is for normalized histograms in analysis view only - *Not* related to DB \"footprint\" column!\n 796→\treturn r.jobsFootprints(ctx, filter, metrics)\n 797→}\n 798→\n 799→// RooflineHeatmap is the resolver for the rooflineHeatmap field.\n 800→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 801→\treturn r.rooflineHeatmap(ctx, filter, rows, cols, minX, minY, maxX, maxY)\n 802→}\n 803→\n 804→// NodeMetrics is the resolver for the nodeMetrics field.\n 805→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 806→\tuser := repository.GetUserFromContext(ctx)\n 807→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 808→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 809→\t}\n 810→\n 811→\tdefaultMetrics := make([]string, 0)\n 812→\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 813→\t\tdefaultMetrics = append(defaultMetrics, mc.Name)\n 814→\t}\n 815→\tif metrics == nil {\n 816→\t\tmetrics = defaultMetrics\n 817→\t} else {\n 818→\t\tmetrics = slices.DeleteFunc(metrics, func(metric string) bool {\n 819→\t\t\treturn !slices.Contains(defaultMetrics, metric) // Remove undefined metrics.\n 820→\t\t})\n 821→\t}\n 822→\n 823→\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nodes, scopes, from, to, ctx)\n 824→\tif err != nil {\n 825→\t\tcclog.Warn(\"error while loading node data\")\n 826→\t\treturn nil, err\n 827→\t}\n 828→\n 829→\tnodeRepo := repository.GetNodeRepository()\n 830→\tstateMap, _ := nodeRepo.MapNodes(cluster)\n 831→\n 832→\tnodeMetrics := make([]*model.NodeMetrics, 0, len(data))\n 833→\tfor hostname, metrics := range data {\n 834→\t\thost := &model.NodeMetrics{\n 835→\t\t\tHost: hostname,\n 836→\t\t\tState: stateMap[hostname],\n 837→\t\t\tMetrics: make([]*model.JobMetricWithName, 0, len(metrics)*len(scopes)),\n 838→\t\t}\n 839→\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n 840→\t\tif err != nil {\n 841→\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n 842→\t\t}\n 843→\n 844→\t\tfor metric, scopedMetrics := range metrics {\n 845→\t\t\tfor _, scopedMetric := range scopedMetrics {\n 846→\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n 847→\t\t\t\t\tName: metric,\n 848→\t\t\t\t\tScope: schema.MetricScopeNode,\n 849→\t\t\t\t\tMetric: scopedMetric,\n 850→\t\t\t\t})\n 851→\t\t\t}\n 852→\t\t}\n 853→\n 854→\t\tnodeMetrics = append(nodeMetrics, host)\n 855→\t}\n 856→\n 857→\treturn nodeMetrics, nil\n 858→}\n 859→\n 860→// NodeMetricsList is the resolver for the nodeMetricsList field.\n 861→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 862→\tif resolution == nil { // Load from Config\n 863→\t\tif config.Keys.EnableResampling != nil {\n 864→\t\t\tdefaultRes := slices.Max(config.Keys.EnableResampling.Resolutions)\n 865→\t\t\tresolution = &defaultRes\n 866→\t\t} else { // Set 0 (Loads configured metric timestep)\n 867→\t\t\tdefaultRes := 0\n 868→\t\t\tresolution = &defaultRes\n 869→\t\t}\n 870→\t}\n 871→\n 872→\tuser := repository.GetUserFromContext(ctx)\n 873→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 874→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 875→\t}\n 876→\n 877→\tnodeRepo := repository.GetNodeRepository()\n 878→\t// nodes -> array hostname\n 879→\tnodes, stateMap, countNodes, hasNextPage, nerr := nodeRepo.GetNodesForList(ctx, cluster, subCluster, stateFilter, nodeFilter, page)\n 880→\tif nerr != nil {\n 881→\t\treturn nil, errors.New(\"could not retrieve node list required for resolving NodeMetricsList\")\n 882→\t}\n 883→\n 884→\tif metrics == nil {\n 885→\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 886→\t\t\tmetrics = append(metrics, mc.Name)\n 887→\t\t}\n 888→\t}\n 889→\n 890→\t// data -> map hostname:jobdata\n 891→\tdata, err := metricdispatch.LoadNodeListData(cluster, subCluster, nodes, metrics, scopes, *resolution, from, to, ctx)\n 892→\tif err != nil {\n 893→\t\tcclog.Warn(\"error while loading node data (Resolver.NodeMetricsList\")\n 894→\t\treturn nil, err\n 895→\t}\n 896→\n 897→\tnodeMetricsList := make([]*model.NodeMetrics, 0, len(data))\n 898→\tfor _, hostname := range nodes {\n 899→\t\thost := &model.NodeMetrics{\n 900→\t\t\tHost: hostname,\n 901→\t\t\tState: stateMap[hostname],\n 902→\t\t\tMetrics: make([]*model.JobMetricWithName, 0),\n 903→\t\t}\n 904→\t\thost.SubCluster, err = archive.GetSubClusterByNode(cluster, hostname)\n 905→\t\tif err != nil {\n 906→\t\t\tcclog.Warnf(\"error in nodeMetrics resolver: %s\", err)\n 907→\t\t}\n 908→\n 909→\t\tfor metric, scopedMetrics := range data[hostname] {\n 910→\t\t\tfor scope, scopedMetric := range scopedMetrics {\n 911→\t\t\t\thost.Metrics = append(host.Metrics, &model.JobMetricWithName{\n 912→\t\t\t\t\tName: metric,\n 913→\t\t\t\t\tScope: scope,\n 914→\t\t\t\t\tMetric: scopedMetric,\n 915→\t\t\t\t})\n 916→\t\t\t}\n 917→\t\t}\n 918→\n 919→\t\tnodeMetricsList = append(nodeMetricsList, host)\n 920→\t}\n 921→\n 922→\tnodeMetricsListResult := &model.NodesResultList{\n 923→\t\tItems: nodeMetricsList,\n 924→\t\t// TotalNodes depends on sum of nodes grouped on latest timestamp, see repo/node.go:357\n 925→\t\tTotalNodes: &countNodes,\n 926→\t\tHasNextPage: &hasNextPage,\n 927→\t}\n 928→\n 929→\treturn nodeMetricsListResult, nil\n 930→}\n 931→\n 932→// ClusterMetrics is the resolver for the clusterMetrics field.\n 933→func (r *queryResolver) ClusterMetrics(ctx context.Context, cluster string, metrics []string, from time.Time, to time.Time) (*model.ClusterMetrics, error) {\n 934→\tuser := repository.GetUserFromContext(ctx)\n 935→\tif user != nil && !user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 936→\t\treturn nil, errors.New(\"you need to be administrator or support staff for this query\")\n 937→\t}\n 938→\n 939→\tif metrics == nil {\n 940→\t\tfor _, mc := range archive.GetCluster(cluster).MetricConfig {\n 941→\t\t\tmetrics = append(metrics, mc.Name)\n 942→\t\t}\n 943→\t}\n 944→\n 945→\t// 'nodes' == nil -> Defaults to all nodes of cluster for existing query workflow\n 946→\tscopes := []schema.MetricScope{\"node\"}\n 947→\tdata, err := metricdispatch.LoadNodeData(cluster, metrics, nil, scopes, from, to, ctx)\n 948→\tif err != nil {\n 949→\t\tcclog.Warn(\"error while loading node data\")\n 950→\t\treturn nil, err\n 951→\t}\n 952→\n 953→\tclusterMetricData := make([]*model.ClusterMetricWithName, 0)\n 954→\tclusterMetrics := model.ClusterMetrics{NodeCount: 0, Metrics: clusterMetricData}\n 955→\n 956→\tcollectorTimestep := make(map[string]int)\n 957→\tcollectorUnit := make(map[string]schema.Unit)\n 958→\tcollectorData := make(map[string][]schema.Float)\n 959→\n 960→\tfor _, metrics := range data {\n 961→\t\tclusterMetrics.NodeCount += 1\n 962→\t\tfor metric, scopedMetrics := range metrics {\n 963→\t\t\tfor _, scopedMetric := range scopedMetrics {\n 964→\t\t\t\t// Collect Info Once\n 965→\t\t\t\t_, okTimestep := collectorTimestep[metric]\n 966→\t\t\t\tif !okTimestep {\n 967→\t\t\t\t\tcollectorTimestep[metric] = scopedMetric.Timestep\n 968→\t\t\t\t}\n 969→\t\t\t\t_, okUnit := collectorUnit[metric]\n 970→\t\t\t\tif !okUnit {\n 971→\t\t\t\t\tcollectorUnit[metric] = scopedMetric.Unit\n 972→\t\t\t\t}\n 973→\t\t\t\t// Collect Data\n 974→\t\t\t\tfor _, ser := range scopedMetric.Series {\n 975→\t\t\t\t\t_, okData := collectorData[metric]\n 976→\t\t\t\t\t// Init With Datasize > 0\n 977→\t\t\t\t\tif !okData && len(ser.Data) != 0 {\n 978→\t\t\t\t\t\tcollectorData[metric] = make([]schema.Float, len(ser.Data))\n 979→\t\t\t\t\t} else if !okData {\n 980→\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 981→\t\t\t\t\t}\n 982→\t\t\t\t\t// Sum if init'd and matching size\n 983→\t\t\t\t\tif okData && len(ser.Data) == len(collectorData[metric]) {\n 984→\t\t\t\t\t\tfor i, val := range ser.Data {\n 985→\t\t\t\t\t\t\tif val.IsNaN() {\n 986→\t\t\t\t\t\t\t\tcontinue\n 987→\t\t\t\t\t\t\t} else {\n 988→\t\t\t\t\t\t\t\tcollectorData[metric][i] += val\n 989→\t\t\t\t\t\t\t}\n 990→\t\t\t\t\t\t}\n 991→\t\t\t\t\t} else if okData {\n 992→\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 993→\t\t\t\t\t}\n 994→\t\t\t\t}\n 995→\t\t\t}\n 996→\t\t}\n 997→\t}\n 998→\n 999→\tfor metricName, data := range collectorData {\n 1000→\t\t// use ccUnits for backend normalization to \"Tera\"\n 1001→\t\tp_old := ccunit.NewPrefix(collectorUnit[metricName].Prefix)\n 1002→\t\tp_new := ccunit.NewPrefix(\"T\")\n 1003→\t\tconvFunc := ccunit.GetPrefixPrefixFactor(p_old, p_new)\n 1004→\t\tu_new := schema.Unit{Prefix: p_new.Prefix(), Base: collectorUnit[metricName].Base}\n 1005→\n 1006→\t\troundedData := make([]schema.Float, 0)\n 1007→\t\tfor _, v_old := range data {\n 1008→\t\t\tv_new := math.Round(convFunc(float64(v_old)).(float64)*100.0) / 100.0\n 1009→\t\t\troundedData = append(roundedData, schema.Float(v_new))\n 1010→\t\t}\n 1011→\n 1012→\t\tcm := model.ClusterMetricWithName{\n 1013→\t\t\tName: metricName,\n 1014→\t\t\tUnit: &u_new,\n 1015→\t\t\tTimestep: collectorTimestep[metricName],\n 1016→\t\t\tData: roundedData,\n 1017→\t\t}\n 1018→\n 1019→\t\tclusterMetrics.Metrics = append(clusterMetrics.Metrics, &cm)\n 1020→\t}\n 1021→\n 1022→\treturn &clusterMetrics, nil\n 1023→}\n 1024→\n 1025→// NumberOfNodes is the resolver for the numberOfNodes field.\n 1026→func (r *subClusterResolver) NumberOfNodes(ctx context.Context, obj *schema.SubCluster) (int, error) {\n 1027→\tnodeList, err := archive.ParseNodeList(obj.Nodes)\n 1028→\tif err != nil {\n 1029→\t\treturn 0, err\n 1030→\t}\n 1031→\treturn nodeList.NodeCount(), nil\n 1032→}\n 1033→\n 1034→// Cluster returns generated.ClusterResolver implementation.\n 1035→func (r *Resolver) Cluster() generated.ClusterResolver { return &clusterResolver{r} }\n 1036→\n 1037→// Job returns generated.JobResolver implementation.\n 1038→func (r *Resolver) Job() generated.JobResolver { return &jobResolver{r} }\n 1039→\n 1040→// MetricValue returns generated.MetricValueResolver implementation.\n 1041→func (r *Resolver) MetricValue() generated.MetricValueResolver { return &metricValueResolver{r} }\n 1042→\n 1043→// Mutation returns generated.MutationResolver implementation.\n 1044→func (r *Resolver) Mutation() generated.MutationResolver { return &mutationResolver{r} }\n 1045→\n 1046→// Node returns generated.NodeResolver implementation.\n 1047→func (r *Resolver) Node() generated.NodeResolver { return &nodeResolver{r} }\n 1048→\n 1049→// Query returns generated.QueryResolver implementation.\n 1050→func (r *Resolver) Query() generated.QueryResolver { return &queryResolver{r} }\n 1051→\n 1052→// SubCluster returns generated.SubClusterResolver implementation.\n 1053→func (r *Resolver) SubCluster() generated.SubClusterResolver { return &subClusterResolver{r} }\n 1054→\n 1055→type (\n 1056→\tclusterResolver struct{ *Resolver }\n 1057→\tjobResolver struct{ *Resolver }\n 1058→\tmetricValueResolver struct{ *Resolver }\n 1059→\tmutationResolver struct{ *Resolver }\n 1060→\tnodeResolver struct{ *Resolver }\n 1061→\tqueryResolver struct{ *Resolver }\n 1062→\tsubClusterResolver struct{ *Resolver }\n 1063→)\n 1064→"}]},"uuid":"933214bf-62de-45d4-9b28-2162f768f0a7","timestamp":"2026-03-13T13:24:05.028Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","content":"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 v0.17.87\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\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\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 (\n\tclusterResolver struct{ *Resolver }\n\tjobResolver struct{ *Resolver }\n\tmetricValueResolver struct{ *Resolver }\n\tmutationResolver struct{ *Resolver }\n\tnodeResolver struct{ *Resolver }\n\tqueryResolver struct{ *Resolver }\n\tsubClusterResolver struct{ *Resolver }\n)\n","numLines":1064,"startLine":1,"totalLines":1064}},"sourceToolAssistantUUID":"d3e42f29-d9b9-4e5b-ab97-5f8241c416ec","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"66dad0f2-fc58-44e5-977a-5d74ad681ef4","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01VwHRQb2SDr4szLiNEVD4XN","toolUseID":"toolu_01VwHRQb2SDr4szLiNEVD4XN","timestamp":"2026-03-13T13:24:11.088Z","uuid":"64f87274-d25d-4e07-abf6-94604d4e2bab","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"66dad0f2-fc58-44e5-977a-5d74ad681ef4","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VwHRQb2SDr4szLiNEVD4XN","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 main provides the entry point for the ClusterCockpit backend server.\n 7→// This file contains HTTP server setup, routing configuration, and\n 8→// authentication middleware integration.\n 9→package main\n 10→\n 11→import (\n 12→\t\"context\"\n 13→\t\"crypto/tls\"\n 14→\t\"encoding/json\"\n 15→\t\"errors\"\n 16→\t\"fmt\"\n 17→\t\"net\"\n 18→\t\"net/http\"\n 19→\t\"os\"\n 20→\t\"strings\"\n 21→\t\"time\"\n 22→\n 23→\t\"github.com/99designs/gqlgen/graphql/handler\"\n 24→\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n 25→\t\"github.com/99designs/gqlgen/graphql/playground\"\n 26→\t\"github.com/ClusterCockpit/cc-backend/internal/api\"\n 27→\t\"github.com/ClusterCockpit/cc-backend/internal/archiver\"\n 28→\t\"github.com/ClusterCockpit/cc-backend/internal/auth\"\n 29→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n 30→\t\"github.com/ClusterCockpit/cc-backend/internal/graph\"\n 31→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n 32→\t\"github.com/ClusterCockpit/cc-backend/internal/routerConfig\"\n 33→\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n 34→\t\"github.com/ClusterCockpit/cc-backend/web\"\n 35→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 36→\t\"github.com/ClusterCockpit/cc-lib/v2/nats\"\n 37→\t\"github.com/ClusterCockpit/cc-lib/v2/runtime\"\n 38→\t\"github.com/go-chi/chi/v5\"\n 39→\t\"github.com/go-chi/chi/v5/middleware\"\n 40→\t\"github.com/go-chi/cors\"\n 41→\thttpSwagger \"github.com/swaggo/http-swagger\"\n 42→)\n 43→\n 44→var buildInfo web.Build\n 45→\n 46→// Environment variable names\n 47→const (\n 48→\tenvDebug = \"DEBUG\"\n 49→)\n 50→\n 51→// Server encapsulates the HTTP server state and dependencies\n 52→type Server struct {\n 53→\trouter chi.Router\n 54→\tserver *http.Server\n 55→\trestAPIHandle *api.RestAPI\n 56→\tnatsAPIHandle *api.NatsAPI\n 57→}\n 58→\n 59→func onFailureResponse(rw http.ResponseWriter, r *http.Request, err error) {\n 60→\trw.Header().Add(\"Content-Type\", \"application/json\")\n 61→\trw.WriteHeader(http.StatusUnauthorized)\n 62→\tjson.NewEncoder(rw).Encode(map[string]string{\n 63→\t\t\"status\": http.StatusText(http.StatusUnauthorized),\n 64→\t\t\"error\": err.Error(),\n 65→\t})\n 66→}\n 67→\n 68→// NewServer creates and initializes a new Server instance\n 69→func NewServer(version, commit, buildDate string) (*Server, error) {\n 70→\tbuildInfo = web.Build{Version: version, Hash: commit, Buildtime: buildDate}\n 71→\n 72→\ts := &Server{\n 73→\t\trouter: chi.NewRouter(),\n 74→\t}\n 75→\n 76→\tif err := s.init(); err != nil {\n 77→\t\treturn nil, err\n 78→\t}\n 79→\n 80→\treturn s, nil\n 81→}\n 82→\n 83→func (s *Server) init() error {\n 84→\t// Setup the http.Handler/Router used by the server\n 85→\tgraph.Init()\n 86→\tresolver := graph.GetResolverInstance()\n 87→\tgraphQLServer := handler.New(\n 88→\t\tgenerated.NewExecutableSchema(generated.Config{Resolvers: resolver}))\n 89→\n 90→\tgraphQLServer.AddTransport(transport.POST{})\n 91→\n 92→\tif os.Getenv(envDebug) != \"1\" {\n 93→\t\t// Having this handler means that a error message is returned via GraphQL instead of the connection simply beeing closed.\n 94→\t\t// The problem with this is that then, no more stacktrace is printed to stderr.\n 95→\t\tgraphQLServer.SetRecoverFunc(func(ctx context.Context, err any) error {\n 96→\t\t\tswitch e := err.(type) {\n 97→\t\t\tcase string:\n 98→\t\t\t\treturn fmt.Errorf(\"MAIN > Panic: %s\", e)\n 99→\t\t\tcase error:\n 100→\t\t\t\treturn fmt.Errorf(\"MAIN > Panic caused by: %s\", e.Error())\n 101→\t\t\t}\n 102→\n 103→\t\t\treturn errors.New(\"MAIN > Internal server error (panic)\")\n 104→\t\t})\n 105→\t}\n 106→\n 107→\tauthHandle := auth.GetAuthInstance()\n 108→\n 109→\t// Middleware must be defined before routes in chi\n 110→\ts.router.Use(func(next http.Handler) http.Handler {\n 111→\t\treturn http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n 112→\t\t\tstart := time.Now()\n 113→\t\t\tww := middleware.NewWrapResponseWriter(rw, r.ProtoMajor)\n 114→\t\t\tnext.ServeHTTP(ww, r)\n 115→\t\t\tcclog.Debugf(\"%s %s (%d, %.02fkb, %dms)\",\n 116→\t\t\t\tr.Method, r.URL.RequestURI(),\n 117→\t\t\t\tww.Status(), float32(ww.BytesWritten())/1024,\n 118→\t\t\t\ttime.Since(start).Milliseconds())\n 119→\t\t})\n 120→\t})\n 121→\ts.router.Use(middleware.Compress(5))\n 122→\ts.router.Use(middleware.Recoverer)\n 123→\ts.router.Use(cors.Handler(cors.Options{\n 124→\t\tAllowCredentials: true,\n 125→\t\tAllowedHeaders: []string{\"X-Requested-With\", \"Content-Type\", \"Authorization\", \"Origin\"},\n 126→\t\tAllowedMethods: []string{\"GET\", \"POST\", \"HEAD\", \"OPTIONS\"},\n 127→\t\tAllowedOrigins: []string{\"*\"},\n 128→\t}))\n 129→\n 130→\ts.restAPIHandle = api.New()\n 131→\n 132→\tinfo := map[string]any{}\n 133→\tinfo[\"hasOpenIDConnect\"] = false\n 134→\n 135→\tif auth.Keys.OpenIDConfig != nil {\n 136→\t\topenIDConnect := auth.NewOIDC(authHandle)\n 137→\t\topenIDConnect.RegisterEndpoints(s.router)\n 138→\t\tinfo[\"hasOpenIDConnect\"] = true\n 139→\t}\n 140→\n 141→\ts.router.Get(\"/login\", func(rw http.ResponseWriter, r *http.Request) {\n 142→\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n 143→\t\tcclog.Debugf(\"##%v##\", info)\n 144→\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{Title: \"Login\", Build: buildInfo, Infos: info})\n 145→\t})\n 146→\ts.router.HandleFunc(\"/imprint\", func(rw http.ResponseWriter, r *http.Request) {\n 147→\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n 148→\t\tweb.RenderTemplate(rw, \"imprint.tmpl\", &web.Page{Title: \"Imprint\", Build: buildInfo})\n 149→\t})\n 150→\ts.router.HandleFunc(\"/privacy\", func(rw http.ResponseWriter, r *http.Request) {\n 151→\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n 152→\t\tweb.RenderTemplate(rw, \"privacy.tmpl\", &web.Page{Title: \"Privacy\", Build: buildInfo})\n 153→\t})\n 154→\n 155→\tif !config.Keys.DisableAuthentication {\n 156→\t\t// Create login failure handler (used by both /login and /jwt-login)\n 157→\t\tloginFailureHandler := func(rw http.ResponseWriter, r *http.Request, err error) {\n 158→\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n 159→\t\t\trw.WriteHeader(http.StatusUnauthorized)\n 160→\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n 161→\t\t\t\tTitle: \"Login failed - ClusterCockpit\",\n 162→\t\t\t\tMsgType: \"alert-warning\",\n 163→\t\t\t\tMessage: err.Error(),\n 164→\t\t\t\tBuild: buildInfo,\n 165→\t\t\t\tInfos: info,\n 166→\t\t\t})\n 167→\t\t}\n 168→\n 169→\t\ts.router.Post(\"/login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n 170→\t\ts.router.HandleFunc(\"/jwt-login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n 171→\n 172→\t\ts.router.Post(\"/logout\", authHandle.Logout(\n 173→\t\t\thttp.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n 174→\t\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n 175→\t\t\t\trw.WriteHeader(http.StatusOK)\n 176→\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n 177→\t\t\t\t\tTitle: \"Bye - ClusterCockpit\",\n 178→\t\t\t\t\tMsgType: \"alert-info\",\n 179→\t\t\t\t\tMessage: \"Logout successful\",\n 180→\t\t\t\t\tBuild: buildInfo,\n 181→\t\t\t\t\tInfos: info,\n 182→\t\t\t\t})\n 183→\t\t\t})).ServeHTTP)\n 184→\t}\n 185→\n 186→\tif flagDev {\n 187→\t\ts.router.Handle(\"/playground\", playground.Handler(\"GraphQL playground\", \"/query\"))\n 188→\t\ts.router.Get(\"/swagger/*\", httpSwagger.Handler(\n 189→\t\t\thttpSwagger.URL(\"http://\"+config.Keys.Addr+\"/swagger/doc.json\")))\n 190→\t}\n 191→\n 192→\t// Secured routes (require authentication)\n 193→\ts.router.Group(func(secured chi.Router) {\n 194→\t\tif !config.Keys.DisableAuthentication {\n 195→\t\t\tsecured.Use(func(next http.Handler) http.Handler {\n 196→\t\t\t\treturn authHandle.Auth(\n 197→\t\t\t\t\tnext,\n 198→\t\t\t\t\tfunc(rw http.ResponseWriter, r *http.Request, err error) {\n 199→\t\t\t\t\t\trw.WriteHeader(http.StatusUnauthorized)\n 200→\t\t\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n 201→\t\t\t\t\t\t\tTitle: \"Authentication failed - ClusterCockpit\",\n 202→\t\t\t\t\t\t\tMsgType: \"alert-danger\",\n 203→\t\t\t\t\t\t\tMessage: err.Error(),\n 204→\t\t\t\t\t\t\tBuild: buildInfo,\n 205→\t\t\t\t\t\t\tInfos: info,\n 206→\t\t\t\t\t\t\tRedirect: r.RequestURI,\n 207→\t\t\t\t\t\t})\n 208→\t\t\t\t\t})\n 209→\t\t\t})\n 210→\t\t}\n 211→\n 212→\t\tsecured.Handle(\"/query\", graphQLServer)\n 213→\n 214→\t\tsecured.HandleFunc(\"/search\", func(rw http.ResponseWriter, r *http.Request) {\n 215→\t\t\trouterConfig.HandleSearchBar(rw, r, buildInfo)\n 216→\t\t})\n 217→\n 218→\t\trouterConfig.SetupRoutes(secured, buildInfo)\n 219→\t})\n 220→\n 221→\t// API routes (JWT token auth)\n 222→\ts.router.Route(\"/api\", func(apiRouter chi.Router) {\n 223→\t\t// Main API routes with API auth\n 224→\t\tapiRouter.Group(func(securedapi chi.Router) {\n 225→\t\t\tif !config.Keys.DisableAuthentication {\n 226→\t\t\t\tsecuredapi.Use(func(next http.Handler) http.Handler {\n 227→\t\t\t\t\treturn authHandle.AuthAPI(next, onFailureResponse)\n 228→\t\t\t\t})\n 229→\t\t\t}\n 230→\t\t\ts.restAPIHandle.MountAPIRoutes(securedapi)\n 231→\t\t})\n 232→\n 233→\t\t// Metric store API routes with separate auth\n 234→\t\tapiRouter.Group(func(metricstoreapi chi.Router) {\n 235→\t\t\tif !config.Keys.DisableAuthentication {\n 236→\t\t\t\tmetricstoreapi.Use(func(next http.Handler) http.Handler {\n 237→\t\t\t\t\treturn authHandle.AuthMetricStoreAPI(next, onFailureResponse)\n 238→\t\t\t\t})\n 239→\t\t\t}\n 240→\t\t\ts.restAPIHandle.MountMetricStoreAPIRoutes(metricstoreapi)\n 241→\t\t})\n 242→\t})\n 243→\n 244→\t// User API routes\n 245→\ts.router.Route(\"/userapi\", func(userapi chi.Router) {\n 246→\t\tif !config.Keys.DisableAuthentication {\n 247→\t\t\tuserapi.Use(func(next http.Handler) http.Handler {\n 248→\t\t\t\treturn authHandle.AuthUserAPI(next, onFailureResponse)\n 249→\t\t\t})\n 250→\t\t}\n 251→\t\ts.restAPIHandle.MountUserAPIRoutes(userapi)\n 252→\t})\n 253→\n 254→\t// Config API routes (uses Group with full paths to avoid shadowing\n 255→\t// the /config page route that is registered in the secured group)\n 256→\ts.router.Group(func(configapi chi.Router) {\n 257→\t\tif !config.Keys.DisableAuthentication {\n 258→\t\t\tconfigapi.Use(func(next http.Handler) http.Handler {\n 259→\t\t\t\treturn authHandle.AuthConfigAPI(next, onFailureResponse)\n 260→\t\t\t})\n 261→\t\t}\n 262→\t\ts.restAPIHandle.MountConfigAPIRoutes(configapi)\n 263→\t})\n 264→\n 265→\t// Frontend API routes\n 266→\ts.router.Route(\"/frontend\", func(frontendapi chi.Router) {\n 267→\t\tif !config.Keys.DisableAuthentication {\n 268→\t\t\tfrontendapi.Use(func(next http.Handler) http.Handler {\n 269→\t\t\t\treturn authHandle.AuthFrontendAPI(next, onFailureResponse)\n 270→\t\t\t})\n 271→\t\t}\n 272→\t\ts.restAPIHandle.MountFrontendAPIRoutes(frontendapi)\n 273→\t})\n 274→\n 275→\tif config.Keys.APISubjects != nil {\n 276→\t\ts.natsAPIHandle = api.NewNatsAPI()\n 277→\t\tif err := s.natsAPIHandle.StartSubscriptions(); err != nil {\n 278→\t\t\treturn fmt.Errorf(\"starting NATS subscriptions: %w\", err)\n 279→\t\t}\n 280→\t}\n 281→\n 282→\t// 404 handler for pages and API routes\n 283→\tnotFoundHandler := func(rw http.ResponseWriter, r *http.Request) {\n 284→\t\tif strings.HasPrefix(r.URL.Path, \"/api/\") || strings.HasPrefix(r.URL.Path, \"/userapi/\") ||\n 285→\t\t\tstrings.HasPrefix(r.URL.Path, \"/frontend/\") || strings.HasPrefix(r.URL.Path, \"/config/\") {\n 286→\t\t\trw.Header().Set(\"Content-Type\", \"application/json\")\n 287→\t\t\trw.WriteHeader(http.StatusNotFound)\n 288→\t\t\tjson.NewEncoder(rw).Encode(map[string]string{\n 289→\t\t\t\t\"status\": \"Resource not found\",\n 290→\t\t\t\t\"error\": \"the requested endpoint does not exist\",\n 291→\t\t\t})\n 292→\t\t\treturn\n 293→\t\t}\n 294→\t\trw.Header().Set(\"Content-Type\", \"text/html; charset=utf-8\")\n 295→\t\trw.WriteHeader(http.StatusNotFound)\n 296→\t\tweb.RenderTemplate(rw, \"404.tmpl\", &web.Page{\n 297→\t\t\tTitle: \"Page Not Found\",\n 298→\t\t\tBuild: buildInfo,\n 299→\t\t})\n 300→\t}\n 301→\n 302→\t// Set NotFound on the router so chi uses it for all unmatched routes,\n 303→\t// including those under subrouters like /api, /userapi, /frontend, etc.\n 304→\ts.router.NotFound(notFoundHandler)\n 305→\n 306→\tif config.Keys.EmbedStaticFiles {\n 307→\t\tif i, err := os.Stat(\"./var/img\"); err == nil {\n 308→\t\t\tif i.IsDir() {\n 309→\t\t\t\tcclog.Info(\"Use local directory for static images\")\n 310→\t\t\t\ts.router.Handle(\"/img/*\", http.StripPrefix(\"/img/\", http.FileServer(http.Dir(\"./var/img\"))))\n 311→\t\t\t}\n 312→\t\t}\n 313→\t\tfileServer := http.StripPrefix(\"/\", web.ServeFiles())\n 314→\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n 315→\t\t\tif web.StaticFileExists(r.URL.Path) {\n 316→\t\t\t\tfileServer.ServeHTTP(rw, r)\n 317→\t\t\t\treturn\n 318→\t\t\t}\n 319→\t\t\tnotFoundHandler(rw, r)\n 320→\t\t}))\n 321→\t} else {\n 322→\t\tstaticDir := http.Dir(config.Keys.StaticFiles)\n 323→\t\tfileServer := http.FileServer(staticDir)\n 324→\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n 325→\t\t\tf, err := staticDir.Open(r.URL.Path)\n 326→\t\t\tif err == nil {\n 327→\t\t\t\tf.Close()\n 328→\t\t\t\tfileServer.ServeHTTP(rw, r)\n 329→\t\t\t\treturn\n 330→\t\t\t}\n 331→\t\t\tnotFoundHandler(rw, r)\n 332→\t\t}))\n 333→\t}\n 334→\n 335→\treturn nil\n 336→}\n 337→\n 338→// Server timeout defaults (in seconds)\n 339→const (\n 340→\tdefaultReadTimeout = 20\n 341→\tdefaultWriteTimeout = 20\n 342→)\n 343→\n 344→func (s *Server) Start(ctx context.Context) error {\n 345→\t// Use configurable timeouts with defaults\n 346→\treadTimeout := time.Duration(defaultReadTimeout) * time.Second\n 347→\twriteTimeout := time.Duration(defaultWriteTimeout) * time.Second\n 348→\n 349→\ts.server = &http.Server{\n 350→\t\tReadTimeout: readTimeout,\n 351→\t\tWriteTimeout: writeTimeout,\n 352→\t\tHandler: s.router,\n 353→\t\tAddr: config.Keys.Addr,\n 354→\t}\n 355→\n 356→\t// Start http or https server\n 357→\tlistener, err := net.Listen(\"tcp\", config.Keys.Addr)\n 358→\tif err != nil {\n 359→\t\treturn fmt.Errorf(\"starting listener on '%s': %w\", config.Keys.Addr, err)\n 360→\t}\n 361→\n 362→\tif !strings.HasSuffix(config.Keys.Addr, \":80\") && config.Keys.RedirectHTTPTo != \"\" {\n 363→\t\tgo func() {\n 364→\t\t\thttp.ListenAndServe(\":80\", http.RedirectHandler(config.Keys.RedirectHTTPTo, http.StatusMovedPermanently))\n 365→\t\t}()\n 366→\t}\n 367→\n 368→\tif config.Keys.HTTPSCertFile != \"\" && config.Keys.HTTPSKeyFile != \"\" {\n 369→\t\tcert, err := tls.LoadX509KeyPair(\n 370→\t\t\tconfig.Keys.HTTPSCertFile, config.Keys.HTTPSKeyFile)\n 371→\t\tif err != nil {\n 372→\t\t\treturn fmt.Errorf(\"loading X509 keypair (check 'https-cert-file' and 'https-key-file' in config.json): %w\", err)\n 373→\t\t}\n 374→\t\tlistener = tls.NewListener(listener, &tls.Config{\n 375→\t\t\tCertificates: []tls.Certificate{cert},\n 376→\t\t\tCipherSuites: []uint16{\n 377→\t\t\t\ttls.TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256,\n 378→\t\t\t\ttls.TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256,\n 379→\t\t\t},\n 380→\t\t\tMinVersion: tls.VersionTLS12,\n 381→\t\t\tPreferServerCipherSuites: true,\n 382→\t\t})\n 383→\t\tcclog.Infof(\"HTTPS server listening at %s...\", config.Keys.Addr)\n 384→\t} else {\n 385→\t\tcclog.Infof(\"HTTP server listening at %s...\", config.Keys.Addr)\n 386→\t}\n 387→\t//\n 388→\t// Because this program will want to bind to a privileged port (like 80), the listener must\n 389→\t// be established first, then the user can be changed, and after that,\n 390→\t// the actual http server can be started.\n 391→\tif err := runtime.DropPrivileges(config.Keys.Group, config.Keys.User); err != nil {\n 392→\t\treturn fmt.Errorf(\"dropping privileges: %w\", err)\n 393→\t}\n 394→\n 395→\t// Handle context cancellation for graceful shutdown\n 396→\tgo func() {\n 397→\t\t<-ctx.Done()\n 398→\t\tshutdownCtx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n 399→\t\tdefer cancel()\n 400→\t\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n 401→\t\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n 402→\t\t}\n 403→\t}()\n 404→\n 405→\tif err = s.server.Serve(listener); err != nil && err != http.ErrServerClosed {\n 406→\t\treturn fmt.Errorf(\"server failed: %w\", err)\n 407→\t}\n 408→\treturn nil\n 409→}\n 410→\n 411→func (s *Server) Shutdown(ctx context.Context) {\n 412→\t// Create a shutdown context with timeout\n 413→\tshutdownCtx, cancel := context.WithTimeout(ctx, 30*time.Second)\n 414→\tdefer cancel()\n 415→\n 416→\tnc := nats.GetClient()\n 417→\tif nc != nil {\n 418→\t\tnc.Close()\n 419→\t}\n 420→\n 421→\t// First shut down the server gracefully (waiting for all ongoing requests)\n 422→\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n 423→\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n 424→\t}\n 425→\n 426→\t// Archive all the metric store data\n 427→\tms := metricstore.GetMemoryStore()\n 428→\n 429→\tif ms != nil {\n 430→\t\tmetricstore.Shutdown()\n 431→\t}\n 432→\n 433→\t// Shutdown archiver with 10 second timeout for fast shutdown\n 434→\tif err := archiver.Shutdown(10 * time.Second); err != nil {\n 435→\t\tcclog.Warnf(\"Archiver shutdown: %v\", err)\n 436→\t}\n 437→}\n 438→"}]},"uuid":"00363808-b3e5-478d-91c4-0f1a2749621e","timestamp":"2026-03-13T13:24:11.088Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/cmd/cc-backend/server.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package main provides the entry point for the ClusterCockpit backend server.\n// This file contains HTTP server setup, routing configuration, and\n// authentication middleware integration.\npackage main\n\nimport (\n\t\"context\"\n\t\"crypto/tls\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"net\"\n\t\"net/http\"\n\t\"os\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/99designs/gqlgen/graphql/handler\"\n\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n\t\"github.com/99designs/gqlgen/graphql/playground\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/api\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/archiver\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/auth\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/routerConfig\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\t\"github.com/ClusterCockpit/cc-backend/web\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/nats\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/runtime\"\n\t\"github.com/go-chi/chi/v5\"\n\t\"github.com/go-chi/chi/v5/middleware\"\n\t\"github.com/go-chi/cors\"\n\thttpSwagger \"github.com/swaggo/http-swagger\"\n)\n\nvar buildInfo web.Build\n\n// Environment variable names\nconst (\n\tenvDebug = \"DEBUG\"\n)\n\n// Server encapsulates the HTTP server state and dependencies\ntype Server struct {\n\trouter chi.Router\n\tserver *http.Server\n\trestAPIHandle *api.RestAPI\n\tnatsAPIHandle *api.NatsAPI\n}\n\nfunc onFailureResponse(rw http.ResponseWriter, r *http.Request, err error) {\n\trw.Header().Add(\"Content-Type\", \"application/json\")\n\trw.WriteHeader(http.StatusUnauthorized)\n\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\"status\": http.StatusText(http.StatusUnauthorized),\n\t\t\"error\": err.Error(),\n\t})\n}\n\n// NewServer creates and initializes a new Server instance\nfunc NewServer(version, commit, buildDate string) (*Server, error) {\n\tbuildInfo = web.Build{Version: version, Hash: commit, Buildtime: buildDate}\n\n\ts := &Server{\n\t\trouter: chi.NewRouter(),\n\t}\n\n\tif err := s.init(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn s, nil\n}\n\nfunc (s *Server) init() error {\n\t// Setup the http.Handler/Router used by the server\n\tgraph.Init()\n\tresolver := graph.GetResolverInstance()\n\tgraphQLServer := handler.New(\n\t\tgenerated.NewExecutableSchema(generated.Config{Resolvers: resolver}))\n\n\tgraphQLServer.AddTransport(transport.POST{})\n\n\tif os.Getenv(envDebug) != \"1\" {\n\t\t// Having this handler means that a error message is returned via GraphQL instead of the connection simply beeing closed.\n\t\t// The problem with this is that then, no more stacktrace is printed to stderr.\n\t\tgraphQLServer.SetRecoverFunc(func(ctx context.Context, err any) error {\n\t\t\tswitch e := err.(type) {\n\t\t\tcase string:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic: %s\", e)\n\t\t\tcase error:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic caused by: %s\", e.Error())\n\t\t\t}\n\n\t\t\treturn errors.New(\"MAIN > Internal server error (panic)\")\n\t\t})\n\t}\n\n\tauthHandle := auth.GetAuthInstance()\n\n\t// Middleware must be defined before routes in chi\n\ts.router.Use(func(next http.Handler) http.Handler {\n\t\treturn http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tstart := time.Now()\n\t\t\tww := middleware.NewWrapResponseWriter(rw, r.ProtoMajor)\n\t\t\tnext.ServeHTTP(ww, r)\n\t\t\tcclog.Debugf(\"%s %s (%d, %.02fkb, %dms)\",\n\t\t\t\tr.Method, r.URL.RequestURI(),\n\t\t\t\tww.Status(), float32(ww.BytesWritten())/1024,\n\t\t\t\ttime.Since(start).Milliseconds())\n\t\t})\n\t})\n\ts.router.Use(middleware.Compress(5))\n\ts.router.Use(middleware.Recoverer)\n\ts.router.Use(cors.Handler(cors.Options{\n\t\tAllowCredentials: true,\n\t\tAllowedHeaders: []string{\"X-Requested-With\", \"Content-Type\", \"Authorization\", \"Origin\"},\n\t\tAllowedMethods: []string{\"GET\", \"POST\", \"HEAD\", \"OPTIONS\"},\n\t\tAllowedOrigins: []string{\"*\"},\n\t}))\n\n\ts.restAPIHandle = api.New()\n\n\tinfo := map[string]any{}\n\tinfo[\"hasOpenIDConnect\"] = false\n\n\tif auth.Keys.OpenIDConfig != nil {\n\t\topenIDConnect := auth.NewOIDC(authHandle)\n\t\topenIDConnect.RegisterEndpoints(s.router)\n\t\tinfo[\"hasOpenIDConnect\"] = true\n\t}\n\n\ts.router.Get(\"/login\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tcclog.Debugf(\"##%v##\", info)\n\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{Title: \"Login\", Build: buildInfo, Infos: info})\n\t})\n\ts.router.HandleFunc(\"/imprint\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"imprint.tmpl\", &web.Page{Title: \"Imprint\", Build: buildInfo})\n\t})\n\ts.router.HandleFunc(\"/privacy\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"privacy.tmpl\", &web.Page{Title: \"Privacy\", Build: buildInfo})\n\t})\n\n\tif !config.Keys.DisableAuthentication {\n\t\t// Create login failure handler (used by both /login and /jwt-login)\n\t\tloginFailureHandler := func(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\tTitle: \"Login failed - ClusterCockpit\",\n\t\t\t\tMsgType: \"alert-warning\",\n\t\t\t\tMessage: err.Error(),\n\t\t\t\tBuild: buildInfo,\n\t\t\t\tInfos: info,\n\t\t\t})\n\t\t}\n\n\t\ts.router.Post(\"/login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\t\ts.router.HandleFunc(\"/jwt-login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\n\t\ts.router.Post(\"/logout\", authHandle.Logout(\n\t\t\thttp.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\t\trw.WriteHeader(http.StatusOK)\n\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\tTitle: \"Bye - ClusterCockpit\",\n\t\t\t\t\tMsgType: \"alert-info\",\n\t\t\t\t\tMessage: \"Logout successful\",\n\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\tInfos: info,\n\t\t\t\t})\n\t\t\t})).ServeHTTP)\n\t}\n\n\tif flagDev {\n\t\ts.router.Handle(\"/playground\", playground.Handler(\"GraphQL playground\", \"/query\"))\n\t\ts.router.Get(\"/swagger/*\", httpSwagger.Handler(\n\t\t\thttpSwagger.URL(\"http://\"+config.Keys.Addr+\"/swagger/doc.json\")))\n\t}\n\n\t// Secured routes (require authentication)\n\ts.router.Group(func(secured chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tsecured.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.Auth(\n\t\t\t\t\tnext,\n\t\t\t\t\tfunc(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\t\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\t\t\tTitle: \"Authentication failed - ClusterCockpit\",\n\t\t\t\t\t\t\tMsgType: \"alert-danger\",\n\t\t\t\t\t\t\tMessage: err.Error(),\n\t\t\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\t\t\tInfos: info,\n\t\t\t\t\t\t\tRedirect: r.RequestURI,\n\t\t\t\t\t\t})\n\t\t\t\t\t})\n\t\t\t})\n\t\t}\n\n\t\tsecured.Handle(\"/query\", graphQLServer)\n\n\t\tsecured.HandleFunc(\"/search\", func(rw http.ResponseWriter, r *http.Request) {\n\t\t\trouterConfig.HandleSearchBar(rw, r, buildInfo)\n\t\t})\n\n\t\trouterConfig.SetupRoutes(secured, buildInfo)\n\t})\n\n\t// API routes (JWT token auth)\n\ts.router.Route(\"/api\", func(apiRouter chi.Router) {\n\t\t// Main API routes with API auth\n\t\tapiRouter.Group(func(securedapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tsecuredapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountAPIRoutes(securedapi)\n\t\t})\n\n\t\t// Metric store API routes with separate auth\n\t\tapiRouter.Group(func(metricstoreapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tmetricstoreapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthMetricStoreAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountMetricStoreAPIRoutes(metricstoreapi)\n\t\t})\n\t})\n\n\t// User API routes\n\ts.router.Route(\"/userapi\", func(userapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tuserapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthUserAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountUserAPIRoutes(userapi)\n\t})\n\n\t// Config API routes (uses Group with full paths to avoid shadowing\n\t// the /config page route that is registered in the secured group)\n\ts.router.Group(func(configapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tconfigapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthConfigAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountConfigAPIRoutes(configapi)\n\t})\n\n\t// Frontend API routes\n\ts.router.Route(\"/frontend\", func(frontendapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tfrontendapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthFrontendAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountFrontendAPIRoutes(frontendapi)\n\t})\n\n\tif config.Keys.APISubjects != nil {\n\t\ts.natsAPIHandle = api.NewNatsAPI()\n\t\tif err := s.natsAPIHandle.StartSubscriptions(); err != nil {\n\t\t\treturn fmt.Errorf(\"starting NATS subscriptions: %w\", err)\n\t\t}\n\t}\n\n\t// 404 handler for pages and API routes\n\tnotFoundHandler := func(rw http.ResponseWriter, r *http.Request) {\n\t\tif strings.HasPrefix(r.URL.Path, \"/api/\") || strings.HasPrefix(r.URL.Path, \"/userapi/\") ||\n\t\t\tstrings.HasPrefix(r.URL.Path, \"/frontend/\") || strings.HasPrefix(r.URL.Path, \"/config/\") {\n\t\t\trw.Header().Set(\"Content-Type\", \"application/json\")\n\t\t\trw.WriteHeader(http.StatusNotFound)\n\t\t\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\t\t\"status\": \"Resource not found\",\n\t\t\t\t\"error\": \"the requested endpoint does not exist\",\n\t\t\t})\n\t\t\treturn\n\t\t}\n\t\trw.Header().Set(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\trw.WriteHeader(http.StatusNotFound)\n\t\tweb.RenderTemplate(rw, \"404.tmpl\", &web.Page{\n\t\t\tTitle: \"Page Not Found\",\n\t\t\tBuild: buildInfo,\n\t\t})\n\t}\n\n\t// Set NotFound on the router so chi uses it for all unmatched routes,\n\t// including those under subrouters like /api, /userapi, /frontend, etc.\n\ts.router.NotFound(notFoundHandler)\n\n\tif config.Keys.EmbedStaticFiles {\n\t\tif i, err := os.Stat(\"./var/img\"); err == nil {\n\t\t\tif i.IsDir() {\n\t\t\t\tcclog.Info(\"Use local directory for static images\")\n\t\t\t\ts.router.Handle(\"/img/*\", http.StripPrefix(\"/img/\", http.FileServer(http.Dir(\"./var/img\"))))\n\t\t\t}\n\t\t}\n\t\tfileServer := http.StripPrefix(\"/\", web.ServeFiles())\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tif web.StaticFileExists(r.URL.Path) {\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t} else {\n\t\tstaticDir := http.Dir(config.Keys.StaticFiles)\n\t\tfileServer := http.FileServer(staticDir)\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tf, err := staticDir.Open(r.URL.Path)\n\t\t\tif err == nil {\n\t\t\t\tf.Close()\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t}\n\n\treturn nil\n}\n\n// Server timeout defaults (in seconds)\nconst (\n\tdefaultReadTimeout = 20\n\tdefaultWriteTimeout = 20\n)\n\nfunc (s *Server) Start(ctx context.Context) error {\n\t// Use configurable timeouts with defaults\n\treadTimeout := time.Duration(defaultReadTimeout) * time.Second\n\twriteTimeout := time.Duration(defaultWriteTimeout) * time.Second\n\n\ts.server = &http.Server{\n\t\tReadTimeout: readTimeout,\n\t\tWriteTimeout: writeTimeout,\n\t\tHandler: s.router,\n\t\tAddr: config.Keys.Addr,\n\t}\n\n\t// Start http or https server\n\tlistener, err := net.Listen(\"tcp\", config.Keys.Addr)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"starting listener on '%s': %w\", config.Keys.Addr, err)\n\t}\n\n\tif !strings.HasSuffix(config.Keys.Addr, \":80\") && config.Keys.RedirectHTTPTo != \"\" {\n\t\tgo func() {\n\t\t\thttp.ListenAndServe(\":80\", http.RedirectHandler(config.Keys.RedirectHTTPTo, http.StatusMovedPermanently))\n\t\t}()\n\t}\n\n\tif config.Keys.HTTPSCertFile != \"\" && config.Keys.HTTPSKeyFile != \"\" {\n\t\tcert, err := tls.LoadX509KeyPair(\n\t\t\tconfig.Keys.HTTPSCertFile, config.Keys.HTTPSKeyFile)\n\t\tif err != nil {\n\t\t\treturn fmt.Errorf(\"loading X509 keypair (check 'https-cert-file' and 'https-key-file' in config.json): %w\", err)\n\t\t}\n\t\tlistener = tls.NewListener(listener, &tls.Config{\n\t\t\tCertificates: []tls.Certificate{cert},\n\t\t\tCipherSuites: []uint16{\n\t\t\t\ttls.TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256,\n\t\t\t\ttls.TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256,\n\t\t\t},\n\t\t\tMinVersion: tls.VersionTLS12,\n\t\t\tPreferServerCipherSuites: true,\n\t\t})\n\t\tcclog.Infof(\"HTTPS server listening at %s...\", config.Keys.Addr)\n\t} else {\n\t\tcclog.Infof(\"HTTP server listening at %s...\", config.Keys.Addr)\n\t}\n\t//\n\t// Because this program will want to bind to a privileged port (like 80), the listener must\n\t// be established first, then the user can be changed, and after that,\n\t// the actual http server can be started.\n\tif err := runtime.DropPrivileges(config.Keys.Group, config.Keys.User); err != nil {\n\t\treturn fmt.Errorf(\"dropping privileges: %w\", err)\n\t}\n\n\t// Handle context cancellation for graceful shutdown\n\tgo func() {\n\t\t<-ctx.Done()\n\t\tshutdownCtx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n\t\tdefer cancel()\n\t\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n\t\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n\t\t}\n\t}()\n\n\tif err = s.server.Serve(listener); err != nil && err != http.ErrServerClosed {\n\t\treturn fmt.Errorf(\"server failed: %w\", err)\n\t}\n\treturn nil\n}\n\nfunc (s *Server) Shutdown(ctx context.Context) {\n\t// Create a shutdown context with timeout\n\tshutdownCtx, cancel := context.WithTimeout(ctx, 30*time.Second)\n\tdefer cancel()\n\n\tnc := nats.GetClient()\n\tif nc != nil {\n\t\tnc.Close()\n\t}\n\n\t// First shut down the 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210→ {/each}\n 211→ \n 212→ \n 213→ \n 214→ \n 215→ {\n 218→ pagingState = { page: 1, itemsPerPage: 10 };\n 219→ selectedHistograms = [...$state.snapshot(selectedHistograms)];\n 220→ }}\n 221→ />\n 222→ \n 223→\n 224→\n 225→
\n 226→\n 227→\n 228→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n 229→ \n 230→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n 231→ \n 232→ \n 233→ {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n 234→ \n 248→ {/key}\n 249→ \n 250→ \n 251→
\n 252→

Top Users: Jobs

\n 253→ tu[\"totalJobs\"],\n 260→ )}\n 261→ entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n 262→ scrambleNames ? scramble(tu.id) : tu.id,\n 263→ )}\n 264→ />\n 265→
\n 266→ \n 267→ \n 268→ \n 269→ \n 270→ \n 271→ \n 272→ \n 273→ \n 274→ {#each $topStatsQuery.data.topUserJobs as tu, i}\n 275→ \n 276→ \n 279→ \n 288→ {#if tu?.name}\n 289→ {scrambleNames ? scramble(tu.name) : tu.name}\n 294→ {/if}\n 295→ \n 296→ \n 297→ {/each}\n 298→
UserJobs
\n 280→ {scrambleNames ? scramble(tu.id) : tu.id}\n 286→ \n 287→ {tu[\"totalJobs\"]}
\n 299→ \n 300→\n 301→ \n 302→

Top Projects: Jobs

\n 303→ tp[\"totalJobs\"],\n 310→ )}\n 311→ entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n 312→ scrambleNames ? scramble(tp.id) : tp.id,\n 313→ )}\n 314→ />\n 315→ \n 316→ \n 317→ \n 318→ \n 319→ \n 320→ \n 321→ \n 322→ \n 323→ {#each $topStatsQuery.data.topProjectJobs as tp, i}\n 324→ \n 325→ \n 328→ \n 337→ \n 338→ \n 339→ {/each}\n 340→
ProjectJobs
\n 329→ {scrambleNames ? scramble(tp.id) : tp.id}\n 335→ \n 336→ {tp[\"totalJobs\"]}
\n 341→ \n 342→ \n 343→{:else}\n 344→ Cannot render job status charts: No data!\n 347→{/if}\n 348→\n 349→
\n 350→\n 351→\n 352→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n 353→ \n 354→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n 355→ \n 356→ \n 357→ \n 369→ \n 370→ \n 371→
\n 372→

Top Users: Nodes

\n 373→ tu[\"totalNodes\"],\n 380→ )}\n 381→ entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n 382→ scrambleNames ? scramble(tu.id) : tu.id,\n 383→ )}\n 384→ />\n 385→
\n 386→ \n 387→ \n 388→ \n 389→ \n 390→ \n 391→ \n 392→ \n 393→ \n 394→ {#each $topStatsQuery.data.topUserNodes as tu, i}\n 395→ \n 396→ \n 399→ \n 408→ {#if tu?.name}\n 409→ {scrambleNames ? scramble(tu.name) : tu.name}\n 414→ {/if}\n 415→ \n 416→ \n 417→ {/each}\n 418→
UserNodes
\n 400→ {scrambleNames ? scramble(tu.id) : tu.id}\n 406→ \n 407→ {tu[\"totalNodes\"]}
\n 419→ \n 420→\n 421→ \n 422→

Top Projects: Nodes

\n 423→ tp[\"totalNodes\"],\n 430→ )}\n 431→ entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n 432→ scrambleNames ? scramble(tp.id) : tp.id,\n 433→ )}\n 434→ />\n 435→ \n 436→ \n 437→ \n 438→ \n 439→ \n 440→ \n 441→ \n 442→ \n 443→ {#each $topStatsQuery.data.topProjectNodes as tp, i}\n 444→ \n 445→ \n 448→ \n 457→ \n 458→ \n 459→ {/each}\n 460→
ProjectNodes
\n 449→ {scrambleNames ? scramble(tp.id) : tp.id}\n 455→ \n 456→ {tp[\"totalNodes\"]}
\n 461→ \n 462→ \n 463→{:else}\n 464→ Cannot render node status charts: No data!\n 467→{/if}\n 468→\n 469→
\n 470→\n 471→\n 472→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n 473→ \n 474→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n 475→ \n 476→ \n 477→ \n 489→ \n 490→ \n 491→
\n 492→

Top Users: GPUs

\n 493→ tu[\"totalAccs\"],\n 500→ )}\n 501→ entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n 502→ scrambleNames ? scramble(tu.id) : tu.id,\n 503→ )}\n 504→ />\n 505→
\n 506→ \n 507→ \n 508→ \n 509→ \n 510→ \n 511→ \n 512→ \n 513→ \n 514→ {#each $topStatsQuery.data.topUserAccs as tu, i}\n 515→ \n 516→ \n 519→ \n 528→ {#if tu?.name}\n 529→ {scrambleNames ? scramble(tu.name) : tu.name}\n 534→ {/if}\n 535→ \n 536→ \n 537→ {/each}\n 538→
UserGPUs
\n 520→ {scrambleNames ? scramble(tu.id) : tu.id}\n 526→ \n 527→ {tu[\"totalAccs\"]}
\n 539→ \n 540→\n 541→ \n 542→

Top Projects: GPUs

\n 543→ tp[\"totalAccs\"],\n 550→ )}\n 551→ entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n 552→ scrambleNames ? scramble(tp.id) : tp.id,\n 553→ )}\n 554→ />\n 555→ \n 556→ \n 557→ \n 558→ \n 559→ \n 560→ \n 561→ \n 562→ \n 563→ {#each $topStatsQuery.data.topProjectAccs as tp, i}\n 564→ \n 565→ \n 568→ \n 577→ \n 578→ \n 579→ {/each}\n 580→
ProjectGPUs
\n 569→ {scrambleNames ? scramble(tp.id) : tp.id}\n 575→ \n 576→ {tp[\"totalAccs\"]}
\n 581→ \n 582→ \n 583→{:else}\n 584→ Cannot render accelerator status charts: No data!\n 587→{/if}\n 588→"}]},"uuid":"894b1de1-e248-46f0-8847-fbcb87c9e4a2","timestamp":"2026-03-13T13:24:15.924Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","content":"\n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
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+{"parentUuid":"5ca62a38-5bbb-497a-af32-a43d4e8dce5b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01C1o5fH2PijEycKtdrYupHd","toolUseID":"toolu_01C1o5fH2PijEycKtdrYupHd","timestamp":"2026-03-13T13:24:16.091Z","uuid":"4ff0dfea-dbcb-4272-95de-1918c5dd0857","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5ca62a38-5bbb-497a-af32-a43d4e8dce5b","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01C1o5fH2PijEycKtdrYupHd","type":"tool_result","content":" 1→-- Migration 13: Add covering indexes for status/dashboard queries\n 2→-- Column order: cluster (equality), job_state (equality), grouping col, then aggregated columns\n 3→-- These indexes allow the status views to be served entirely from index scans.\n 4→\n 5→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user_stats\n 6→ ON job (cluster, job_state, hpc_user, duration, start_time, num_nodes, num_hwthreads, num_acc);\n 7→\n 8→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project_stats\n 9→ ON job (cluster, job_state, project, duration, start_time, num_nodes, num_hwthreads, num_acc);\n 10→\n 11→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_subcluster_stats\n 12→ ON job (cluster, job_state, subcluster, duration, start_time, num_nodes, num_hwthreads, num_acc);\n 13→\n 14→-- Drop 3-col indexes that are now subsumed by the covering indexes above\n 15→DROP INDEX IF EXISTS jobs_cluster_jobstate_user;\n 16→DROP INDEX IF EXISTS jobs_cluster_jobstate_project;\n 17→\n 18→PRAGMA optimize;\n 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num_acc);\n\n-- Drop 3-col indexes that are now subsumed by the covering indexes above\nDROP INDEX IF EXISTS jobs_cluster_jobstate_user;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_project;\n\nPRAGMA optimize;\n","numLines":19,"startLine":1,"totalLines":19}},"sourceToolAssistantUUID":"5ca62a38-5bbb-497a-af32-a43d4e8dce5b","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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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":"db646daa-34ea-4154-8717-ff7edd8d6297","timestamp":"2026-03-13T13:24:25.772Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/util.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\"math\"\n\t\"slices\"\n\n\t\"github.com/99designs/gqlgen/graphql\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n)\n\nconst MAX_JOBS_FOR_ANALYSIS = 500\n\n// Helper function for the rooflineHeatmap GraphQL query placed here so that schema.resolvers.go is not too full.\nfunc (r *queryResolver) rooflineHeatmap(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\trows int, cols int,\n\tminX float64, minY float64, maxX float64, maxY float64,\n) ([][]float64, error) {\n\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n\tif err != nil {\n\t\tcclog.Error(\"Error while querying jobs for roofline\")\n\t\treturn nil, err\n\t}\n\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n\t}\n\n\tfcols, frows := float64(cols), float64(rows)\n\tminX, minY, maxX, maxY = math.Log10(minX), math.Log10(minY), math.Log10(maxX), math.Log10(maxY)\n\ttiles := make([][]float64, rows)\n\tfor i := range tiles {\n\t\ttiles[i] = make([]float64, cols)\n\t}\n\n\tfor _, job := range jobs {\n\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n\t\t\tcontinue\n\t\t}\n\n\t\t// metricConfigs := archive.GetCluster(job.Cluster).MetricConfig\n\t\t// resolution := 0\n\n\t\t// for _, mc := range metricConfigs {\n\t\t// \tresolution = max(resolution, mc.Timestep)\n\t\t// }\n\n\t\tjobdata, err := metricdispatch.LoadData(job, []string{\"flops_any\", \"mem_bw\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 0)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while loading roofline metrics for job %d\", *job.ID)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tflops_, membw_ := jobdata[\"flops_any\"], jobdata[\"mem_bw\"]\n\t\tif flops_ == nil && membw_ == nil {\n\t\t\tcclog.Warnf(\"rooflineHeatmap(): 'flops_any' or 'mem_bw' missing for job %d\", *job.ID)\n\t\t\tcontinue\n\t\t\t// return nil, fmt.Errorf(\"GRAPH/UTIL > 'flops_any' or 'mem_bw' missing for job %d\", job.ID)\n\t\t}\n\n\t\tflops, ok1 := flops_[\"node\"]\n\t\tmembw, ok2 := membw_[\"node\"]\n\t\tif !ok1 || !ok2 {\n\t\t\tcclog.Info(\"rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level\")\n\t\t\tcontinue\n\t\t\t// TODO/FIXME:\n\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\t\t}\n\n\t\tfor n := 0; n < len(flops.Series); n++ {\n\t\t\tflopsSeries, membwSeries := flops.Series[n], membw.Series[n]\n\t\t\tfor i := 0; i < len(flopsSeries.Data); i++ {\n\t\t\t\tif i >= len(membwSeries.Data) {\n\t\t\t\t\tbreak\n\t\t\t\t}\n\n\t\t\t\tx, y := math.Log10(float64(flopsSeries.Data[i]/membwSeries.Data[i])), math.Log10(float64(flopsSeries.Data[i]))\n\t\t\t\tif math.IsNaN(x) || math.IsNaN(y) || x < minX || x >= maxX || y < minY || y > maxY {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tx, y = math.Floor(((x-minX)/(maxX-minX))*fcols), math.Floor(((y-minY)/(maxY-minY))*frows)\n\t\t\t\tif x < 0 || x >= fcols || y < 0 || y >= frows {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\ttiles[int(y)][int(x)] += 1\n\t\t\t}\n\t\t}\n\t}\n\n\treturn tiles, nil\n}\n\n// Helper function for the jobsFootprints GraphQL query placed here so that schema.resolvers.go is not too full.\nfunc (r *queryResolver) jobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n\tif err != nil {\n\t\tcclog.Error(\"Error while querying jobs for footprint\")\n\t\treturn nil, err\n\t}\n\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n\t}\n\n\tavgs := make([][]schema.Float, len(metrics))\n\tfor i := range avgs {\n\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n\t}\n\n\ttimeweights := new(model.TimeWeights)\n\ttimeweights.NodeHours = make([]schema.Float, 0, len(jobs))\n\ttimeweights.AccHours = make([]schema.Float, 0, len(jobs))\n\ttimeweights.CoreHours = make([]schema.Float, 0, len(jobs))\n\n\tfor _, job := range jobs {\n\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n\t\t\tcontinue\n\t\t}\n\n\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n\t\t\tcclog.Error(\"Error while loading averages for footprint\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\t// #166 collect arrays: Null values or no null values?\n\t\ttimeweights.NodeHours = append(timeweights.NodeHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumNodes)))\n\t\tif job.NumAcc > 0 {\n\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumAcc)))\n\t\t} else {\n\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(1.0))\n\t\t}\n\t\tif job.NumHWThreads > 0 {\n\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumHWThreads))) // SQLite HWThreads == Cores; numCoresForJob(job)\n\t\t} else {\n\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(1.0))\n\t\t}\n\t}\n\n\tres := make([]*model.MetricFootprints, len(avgs))\n\tfor i, arr := range avgs {\n\t\tres[i] = &model.MetricFootprints{\n\t\t\tMetric: metrics[i],\n\t\t\tData: arr,\n\t\t}\n\t}\n\n\treturn &model.Footprints{\n\t\tTimeWeights: timeweights,\n\t\tMetrics: res,\n\t}, nil\n}\n\n// func numCoresForJob(job *schema.Job) (numCores int) {\n\n// \tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n// \tif scerr != nil {\n// \t\treturn 1\n// \t}\n\n// \ttotalJobCores := 0\n// \ttopology := subcluster.Topology\n\n// \tfor _, host := range job.Resources {\n// \t\thwthreads := host.HWThreads\n// \t\tif hwthreads == nil {\n// \t\t\thwthreads = topology.Node\n// \t\t}\n\n// \t\thostCores, _ := topology.GetCoresFromHWThreads(hwthreads)\n// \t\ttotalJobCores += len(hostCores)\n// \t}\n\n// \treturn totalJobCores\n// }\n\nfunc requireField(ctx context.Context, name string) bool {\n\tfields := graphql.CollectAllFields(ctx)\n\n\treturn slices.Contains(fields, 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EXISTS jobs_cluster_jobstate_project_stats;\n 5→DROP INDEX IF EXISTS jobs_cluster_jobstate_subcluster_stats;\n 6→\n 7→-- Restore the original 3-col indexes\n 8→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user\n 9→ ON job (cluster, job_state, hpc_user);\n 10→\n 11→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project\n 12→ ON job (cluster, job_state, project);\n 13→"}]},"uuid":"8c63ac53-7436-4918-9440-ff1f29fd03ca","timestamp":"2026-03-13T13:24:26.843Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migrations/sqlite3/13_status-covering-indexes.down.sql","content":"-- Reverse migration 13: Remove covering status indexes, restore 3-col indexes\n\nDROP INDEX IF EXISTS jobs_cluster_jobstate_user_stats;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_project_stats;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_subcluster_stats;\n\n-- Restore the original 3-col indexes\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user\n ON job (cluster, job_state, hpc_user);\n\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project\n ON job (cluster, job_state, project);\n","numLines":13,"startLine":1,"totalLines":13}},"sourceToolAssistantUUID":"daaf21a6-5ad0-48cc-ba9a-7a6fbe27d9e2","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"8c63ac53-7436-4918-9440-ff1f29fd03ca","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Wbwe2fcD5CLLr1PabXJs9o","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have all the context. Let me implement all 4 changes. I'll work on them in parallel where possible.\n\n**Change 1: Migration files + version bump + inline literal state value**"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3435,"cache_read_input_tokens":75354,"cache_creation":{"ephemeral_5m_input_tokens":3435,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19q87hcEUMnUZKb5HYa","type":"assistant","uuid":"92561e1e-f513-4ee3-a35c-5f31b11fe754","timestamp":"2026-03-13T13:24:32.104Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"type":"file-history-snapshot","messageId":"4e40d80a-73f6-42f9-b603-fc66d2e255ae","snapshot":{"messageId":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","trackedFileBackups":{"internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:24:36.210Z"}},"timestamp":"2026-03-13T13:23:59.403Z"},"isSnapshotUpdate":true} +{"parentUuid":"92561e1e-f513-4ee3-a35c-5f31b11fe754","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Wbwe2fcD5CLLr1PabXJs9o","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VdN8yEKfzDLi1uWrgcFndg","name":"Write","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql","content":"-- Migration 14: Partial covering indexes for running jobs\n-- Only running jobs are in the B-tree, so these indexes are tiny compared to\n-- the full-table indexes from migration 13. SQLite uses them when the query\n-- contains the literal `job_state = 'running'` (not a parameter placeholder).\n\nCREATE INDEX IF NOT EXISTS jobs_running_user_stats\n ON job (cluster, hpc_user, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nCREATE INDEX IF NOT EXISTS jobs_running_project_stats\n ON job (cluster, project, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nCREATE INDEX IF NOT EXISTS jobs_running_subcluster_stats\n ON job (cluster, subcluster, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nPRAGMA optimize;\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3435,"cache_read_input_tokens":75354,"cache_creation":{"ephemeral_5m_input_tokens":3435,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19q87hcEUMnUZKb5HYa","type":"assistant","uuid":"4e40d80a-73f6-42f9-b603-fc66d2e255ae","timestamp":"2026-03-13T13:24:36.202Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"4e40d80a-73f6-42f9-b603-fc66d2e255ae","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Write","command":"callback"},"parentToolUseID":"toolu_01VdN8yEKfzDLi1uWrgcFndg","toolUseID":"toolu_01VdN8yEKfzDLi1uWrgcFndg","timestamp":"2026-03-13T13:24:36.211Z","uuid":"95f5caf0-f3c0-4e9d-b2fa-5f5e31554fb3","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"4e40d80a-73f6-42f9-b603-fc66d2e255ae","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VdN8yEKfzDLi1uWrgcFndg","type":"tool_result","content":"File created successfully at: /Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql"}]},"uuid":"6b556178-372e-467f-88a9-988b0b171353","timestamp":"2026-03-13T13:24:36.211Z","toolUseResult":{"type":"create","filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql","content":"-- Migration 14: Partial covering indexes for running jobs\n-- Only running jobs are in the B-tree, so these indexes are tiny compared to\n-- the full-table indexes from migration 13. SQLite uses them when the query\n-- contains the literal `job_state = 'running'` (not a parameter placeholder).\n\nCREATE INDEX IF NOT EXISTS jobs_running_user_stats\n ON job (cluster, hpc_user, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nCREATE INDEX IF NOT EXISTS jobs_running_project_stats\n ON job (cluster, project, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nCREATE INDEX IF NOT EXISTS jobs_running_subcluster_stats\n ON job (cluster, subcluster, num_nodes, num_hwthreads, num_acc, duration, start_time)\n WHERE job_state = 'running';\n\nPRAGMA optimize;\n","structuredPatch":[],"originalFile":null},"sourceToolAssistantUUID":"4e40d80a-73f6-42f9-b603-fc66d2e255ae","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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to 48)\n// - Version 10: Node table\n//\n// Migration files are embedded at build time from the migrations directory.\nconst Version uint = 14","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 repository\n\nimport (\n\t\"database/sql\"\n\t\"embed\"\n\t\"fmt\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/golang-migrate/migrate/v4\"\n\t\"github.com/golang-migrate/migrate/v4/database/sqlite3\"\n\t\"github.com/golang-migrate/migrate/v4/source/iofs\"\n)\n\n// Version is the current database schema version required by this version of cc-backend.\n// When the database schema changes, this version is incremented and a new migration file\n// is added to internal/repository/migrations/sqlite3/.\n//\n// Version history:\n// - Version 13: Add covering indexes for status/dashboard queries (cluster, job_state, ...)\n// - Version 12: Add covering index for stats queries (cluster, start_time, hpc_user, ...)\n// - Version 11: Optimize job table indexes (reduce from ~78 to 48)\n// - Version 10: Node table\n//\n// Migration files are embedded at build time from the migrations directory.\nconst Version uint = 13\n\n//go:embed migrations/*\nvar migrationFiles embed.FS\n\n// checkDBVersion verifies that the database schema version matches the expected version.\n// This is called automatically during Connect() to ensure schema compatibility.\n//\n// Returns an error if:\n// - Database version is older than expected (needs migration)\n// - Database version is newer than expected (needs app upgrade)\n// - Database is in a dirty state (failed migration)\n//\n// A \"dirty\" database indicates a migration was started but not completed successfully.\n// This requires manual intervention to fix the database and force the version.\nfunc checkDBVersion(db *sql.DB) error {\n\tdriver, err := sqlite3.WithInstance(db, &sqlite3.Config{})\n\tif err != nil {\n\t\treturn err\n\t}\n\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tm, err := migrate.NewWithInstance(\"iofs\", d, \"sqlite3\", driver)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tv, dirty, err := m.Version()\n\tif err != nil {\n\t\tif err == migrate.ErrNilVersion {\n\t\t\tcclog.Warn(\"Legacy database without version or missing database file!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tif v < Version {\n\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n\t} else if v > Version {\n\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease refer to documentation how to downgrade db with external migrate tool\", v, Version)\n\t}\n\n\tif dirty {\n\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n\t}\n\n\treturn nil\n}\n\n// getMigrateInstance creates a new migration instance for the given database file.\n// This is used internally by MigrateDB, RevertDB, and ForceDB.\nfunc getMigrateInstance(db string) (m *migrate.Migrate, err error) {\n\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tm, err = migrate.NewWithSourceInstance(\"iofs\", d, fmt.Sprintf(\"sqlite3://%s?_foreign_keys=on\", db))\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn m, nil\n}\n\n// MigrateDB applies all pending database migrations to bring the schema up to date.\n// This should be run with the -migrate-db flag before starting the application\n// after upgrading to a new version that requires schema changes.\n//\n// Process:\n// 1. Checks current database version\n// 2. Applies all migrations from current version to target Version\n// 3. Updates schema_migrations table to track applied migrations\n//\n// Important:\n// - Always backup your database before running migrations\n// - Migrations are irreversible without manual intervention\n// - If a migration fails, the database is marked \"dirty\" and requires manual fix\n//\n// Usage:\n//\n//\tcc-backend -migrate-db\nfunc MigrateDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tv, dirty, err := m.Version()\n\tif err != nil {\n\t\tif err == migrate.ErrNilVersion {\n\t\t\tcclog.Info(\"Legacy database without version or missing database file!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tif v < Version {\n\t\tcclog.Infof(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n\t}\n\n\tif dirty {\n\t\treturn fmt.Errorf(\"last migration to version %d has failed, please fix the db manually and force version with -force-db flag\", Version)\n\t}\n\n\tif err := m.Up(); err != nil {\n\t\tif err == migrate.ErrNoChange {\n\t\t\tcclog.Info(\"DB already up to date!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tm.Close()\n\treturn nil\n}\n\n// RevertDB rolls back the database schema to the previous version (Version - 1).\n// This is primarily used for testing or emergency rollback scenarios.\n//\n// Warning:\n// - This may cause data loss if newer schema added columns/tables\n// - Always backup before reverting\n// - Not all migrations are safely reversible\n//\n// Usage:\n//\n//\tcc-backend -revert-db\nfunc RevertDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif err := m.Migrate(Version - 1); err != nil {\n\t\tif err == migrate.ErrNoChange {\n\t\t\tcclog.Info(\"DB already up to date!\")\n\t\t} else {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tm.Close()\n\treturn nil\n}\n\n// ForceDB forces the database schema version to the current Version without running migrations.\n// This is only used to recover from failed migrations that left the database in a \"dirty\" state.\n//\n// When to use:\n// - After manually fixing a failed migration\n// - When you've manually applied schema changes and need to update the version marker\n//\n// Warning:\n// - This does NOT apply any schema changes\n// - Only use after manually verifying the schema is correct\n// - Improper use can cause schema/version mismatch\n//\n// Usage:\n//\n//\tcc-backend -force-db\nfunc ForceDB(db string) error {\n\tm, err := getMigrateInstance(db)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif err := m.Force(int(Version)); err != nil {\n\t\treturn err\n\t}\n\n\tm.Close()\n\treturn nil\n}\n","structuredPatch":[{"oldStart":21,"oldLines":13,"newStart":21,"newLines":14,"lines":[" // is added to internal/repository/migrations/sqlite3/."," //"," // Version history:","+// - Version 14: Partial covering indexes for running jobs (tiny B-tree vs millions)"," // - Version 13: Add covering indexes for status/dashboard queries (cluster, job_state, ...)"," // - Version 12: Add covering index for stats queries (cluster, start_time, hpc_user, ...)"," // - Version 11: Optimize job table indexes (reduce from ~78 to 48)"," // - Version 10: Node table"," //"," // Migration files are embedded at build time from the migrations directory.","-const Version uint = 13","+const Version uint = 14"," "," //go:embed migrations/*"," var migrationFiles embed.FS"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"ff233541-cb1b-437d-b5a1-5c4735dc3e48","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"8db79658-fbad-4246-ac37-3f76c1f35785","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WEj69zhEqjxedFRgfHz39g","type":"message","role":"assistant","content":[{"type":"text","text":"Now inline 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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package repository provides job query functionality with filtering, pagination,\n// and security controls. This file contains the main query builders and security\n// checks for job retrieval operations.\npackage repository\n\nimport (\n\t\"context\"\n\t\"errors\"\n\t\"fmt\"\n\t\"regexp\"\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/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n)\n\nconst (\n\t// Default initial capacity for job result slices\n\tdefaultJobsCapacity = 50\n)\n\n// QueryJobs retrieves jobs from the database with optional filtering, pagination,\n// and sorting. Security controls are automatically applied based on the user context.\n//\n// Parameters:\n// - ctx: Context containing user authentication information\n// - filters: Optional job filters (cluster, state, user, time ranges, etc.)\n// - page: Optional pagination parameters (page number and items per page)\n// - order: Optional sorting specification (column or footprint field)\n//\n// Returns a slice of jobs matching the criteria, or an error if the query fails.\n// The function enforces role-based access control through SecurityCheck.\nfunc (r *JobRepository) QueryJobs(\n\tctx context.Context,\n\tfilters []*model.JobFilter,\n\tpage *model.PageRequest,\n\torder *model.OrderByInput,\n) ([]*schema.Job, error) {\n\tquery, qerr := SecurityCheck(ctx, sq.Select(jobColumns...).From(\"job\"))\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tif order != nil {\n\t\tfield := toSnakeCase(order.Field)\n\t\tif order.Type == \"col\" {\n\t\t\tswitch order.Order {\n\t\t\tcase model.SortDirectionEnumAsc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s ASC\", field))\n\t\t\tcase model.SortDirectionEnumDesc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s DESC\", field))\n\t\t\tdefault:\n\t\t\t\treturn nil, errors.New(\"invalid sorting order for column\")\n\t\t\t}\n\t\t} else {\n\t\t\t// Order by footprint JSON field values\n\t\t\tquery = query.Where(\"JSON_VALID(footprint)\")\n\t\t\tswitch order.Order {\n\t\t\tcase model.SortDirectionEnumAsc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") ASC\", field))\n\t\t\tcase model.SortDirectionEnumDesc:\n\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") DESC\", field))\n\t\t\tdefault:\n\t\t\t\treturn nil, errors.New(\"invalid sorting order for footprint\")\n\t\t\t}\n\t\t}\n\t}\n\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tlimit := uint64(page.ItemsPerPage)\n\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.RunWith(r.stmtCache).QueryContext(ctx)\n\tif err != nil {\n\t\tqueryString, queryVars, _ := query.ToSql()\n\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, defaultJobsCapacity)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error scanning job row: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, fmt.Errorf(\"error iterating job rows: %w\", err)\n\t}\n\n\treturn jobs, nil\n}\n\n// CountJobs returns the total number of jobs matching the given filters.\n// Security controls are automatically applied based on the user context.\n// Uses DISTINCT count to handle tag filters correctly (jobs may appear multiple\n// times when joined with the tag table).\nfunc (r *JobRepository) CountJobs(\n\tctx context.Context,\n\tfilters []*model.JobFilter,\n) (int, error) {\n\tquery, qerr := SecurityCheck(ctx, sq.Select(\"count(DISTINCT job.id)\").From(\"job\"))\n\tif qerr != nil {\n\t\treturn 0, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\tvar count int\n\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&count); err != nil {\n\t\treturn 0, fmt.Errorf(\"failed to count jobs: %w\", err)\n\t}\n\n\treturn count, nil\n}\n\n// SecurityCheckWithUser applies role-based access control filters to a job query\n// based on the provided user's roles and permissions.\n//\n// Access rules by role:\n// - API role (exclusive): Full access to all jobs\n// - Admin/Support roles: Full access to all jobs\n// - Manager role: Access to jobs in managed projects plus own jobs\n// - User role: Access only to own jobs\n//\n// Returns an error if the user is nil or has no recognized roles.\nfunc SecurityCheckWithUser(user *schema.User, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n\tif user == nil {\n\t\tvar qnil sq.SelectBuilder\n\t\treturn qnil, fmt.Errorf(\"user context is nil\")\n\t}\n\n\tswitch {\n\tcase len(user.Roles) == 1 && user.HasRole(schema.RoleAPI):\n\t\treturn query, nil\n\tcase user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}):\n\t\treturn query, nil\n\tcase user.HasRole(schema.RoleManager):\n\t\tif len(user.Projects) != 0 {\n\t\t\treturn query.Where(sq.Or{sq.Eq{\"job.project\": user.Projects}, sq.Eq{\"job.hpc_user\": user.Username}}), nil\n\t\t}\n\t\tcclog.Debugf(\"Manager '%s' has no assigned projects, restricting to personal jobs\", user.Username)\n\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n\tcase user.HasRole(schema.RoleUser):\n\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n\tdefault:\n\t\tvar qnil sq.SelectBuilder\n\t\treturn qnil, fmt.Errorf(\"user has no or unknown roles\")\n\t}\n}\n\n// SecurityCheck extracts the user from the context and applies role-based access\n// control filters to the query. This is a convenience wrapper around SecurityCheckWithUser.\nfunc SecurityCheck(ctx context.Context, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n\tuser := GetUserFromContext(ctx)\n\treturn SecurityCheckWithUser(user, query)\n}\n\n// BuildWhereClause constructs SQL WHERE conditions from a JobFilter and applies\n// them to the query. Supports filtering by job properties (cluster, state, user),\n// time ranges, resource usage, tags, and JSON field searches in meta_data,\n// footprint, and resources columns.\nfunc BuildWhereClause(filter *model.JobFilter, query sq.SelectBuilder) sq.SelectBuilder {\n\t// Primary Key\n\tif filter.DbID != nil {\n\t\tdbIDs := make([]string, len(filter.DbID))\n\t\tcopy(dbIDs, filter.DbID)\n\t\tquery = query.Where(sq.Eq{\"job.id\": dbIDs})\n\t}\n\t// Explicit indices\n\tif filter.Cluster != nil {\n\t\tquery = buildStringCondition(\"job.cluster\", filter.Cluster, query)\n\t}\n\tif filter.SubCluster != nil {\n\t\tquery = buildStringCondition(\"job.subcluster\", filter.SubCluster, query)\n\t}\n\tif filter.Partition != nil {\n\t\tquery = buildStringCondition(\"job.cluster_partition\", filter.Partition, query)\n\t}\n\tif filter.State != nil {\n\t\tif len(filter.State) == 1 {\n\t\t\tsingleStat := string(filter.State[0])\n\t\t\tquery = query.Where(\"job.job_state = ?\", singleStat)\n\t\t} else {\n\t\t\tstates := make([]string, len(filter.State))\n\t\t\tfor i, val := range filter.State {\n\t\t\t\tstates[i] = string(val)\n\t\t\t}\n\t\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n\t\t}\n\t}\n\tif filter.Shared != nil {\n\t\tquery = query.Where(\"job.shared = ?\", *filter.Shared)\n\t}\n\tif filter.Project != nil {\n\t\tquery = buildStringCondition(\"job.project\", filter.Project, query)\n\t}\n\tif filter.User != nil {\n\t\tquery = buildStringCondition(\"job.hpc_user\", filter.User, query)\n\t}\n\tif filter.NumNodes != nil {\n\t\tquery = buildIntCondition(\"job.num_nodes\", filter.NumNodes, query)\n\t}\n\tif filter.NumAccelerators != nil {\n\t\tquery = buildIntCondition(\"job.num_acc\", filter.NumAccelerators, query)\n\t}\n\tif filter.NumHWThreads != nil {\n\t\tquery = buildIntCondition(\"job.num_hwthreads\", filter.NumHWThreads, query)\n\t}\n\tif filter.ArrayJobID != nil {\n\t\tquery = query.Where(\"job.array_job_id = ?\", *filter.ArrayJobID)\n\t}\n\tif filter.StartTime != nil {\n\t\tquery = buildTimeCondition(\"job.start_time\", filter.StartTime, query)\n\t}\n\tif filter.Duration != nil {\n\t\tquery = buildIntCondition(\"job.duration\", filter.Duration, query)\n\t}\n\tif filter.Energy != nil {\n\t\tquery = buildFloatCondition(\"job.energy\", filter.Energy, query)\n\t}\n\t// Indices on Tag Table\n\tif filter.Tags != nil {\n\t\t// This is an OR-Logic query: Returns all distinct jobs with at least one of the requested tags; TODO: AND-Logic query?\n\t\tquery = query.Join(\"jobtag ON jobtag.job_id = job.id\").Where(sq.Eq{\"jobtag.tag_id\": filter.Tags}).Distinct()\n\t}\n\t// No explicit Indices\n\tif filter.JobID != nil {\n\t\tquery = buildStringCondition(\"job.job_id\", filter.JobID, query)\n\t}\n\t// Queries Within JSONs\n\tif filter.MetricStats != nil {\n\t\tfor _, ms := range filter.MetricStats {\n\t\t\tquery = buildFloatJSONCondition(ms.MetricName, ms.Range, query)\n\t\t}\n\t}\n\tif filter.Node != nil {\n\t\tquery = buildResourceJSONCondition(\"hostname\", filter.Node, query)\n\t}\n\tif filter.JobName != nil {\n\t\tquery = buildMetaJSONCondition(\"jobName\", filter.JobName, query)\n\t}\n\tif filter.Schedule != nil {\n\t\tinteractiveJobname := \"interactive\"\n\t\tswitch *filter.Schedule {\n\t\tcase \"interactive\":\n\t\t\tiFilter := model.StringInput{Eq: &interactiveJobname}\n\t\t\tquery = buildMetaJSONCondition(\"jobName\", &iFilter, query)\n\t\tcase \"batch\":\n\t\t\tsFilter := model.StringInput{Neq: &interactiveJobname}\n\t\t\tquery = buildMetaJSONCondition(\"jobName\", &sFilter, query)\n\t\t}\n\t}\n\n\t// Configurable Filter to exclude recently started jobs, see config.go: ShortRunningJobsDuration\n\tif filter.MinRunningFor != nil {\n\t\tnow := time.Now().Unix()\n\t\t// Only jobs whose start timestamp is more than MinRunningFor seconds in the past\n\t\t// If a job completed within the configured timeframe, it will still show up after the start_time matches the condition!\n\t\tquery = query.Where(sq.Lt{\"job.start_time\": (now - int64(*filter.MinRunningFor))})\n\t}\n\treturn query\n}\n\n// buildIntCondition creates clauses for integer range filters, using BETWEEN only if required.\nfunc buildIntCondition(field string, cond *config.IntRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != 1 && cond.To != 0 {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1 && cond.To == 0 {\n\t\treturn query.Where(field+\" >= ?\", cond.From)\n\t} else if cond.From == 1 && cond.To != 0 {\n\t\treturn query.Where(field+\" <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\nfunc buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1.0 && cond.To == 0.0 {\n\t\treturn query.Where(field+\" >= ?\", cond.From)\n\t} else if cond.From == 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(field+\" <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildTimeCondition creates time range filters supporting absolute timestamps,\n// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\nfunc buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.From != nil && cond.To != nil {\n\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n\t} else if cond.From != nil {\n\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n\t} else if cond.To != nil {\n\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n\t} else if cond.Range != \"\" {\n\t\tnow := time.Now().Unix()\n\t\tvar then int64\n\t\tswitch cond.Range {\n\t\tcase \"last6h\":\n\t\t\tthen = now - (60 * 60 * 6)\n\t\tcase \"last24h\":\n\t\t\tthen = now - (60 * 60 * 24)\n\t\tcase \"last7d\":\n\t\t\tthen = now - (60 * 60 * 24 * 7)\n\t\tcase \"last30d\":\n\t\t\tthen = now - (60 * 60 * 24 * 30)\n\t\tdefault:\n\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n\t\t\treturn query\n\t\t}\n\t\treturn query.Where(field+\" >= ?\", then)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\nfunc buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(footprint)\")\n\tif cond.From != 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n\t} else if cond.From != 1.0 && cond.To == 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n\t} else if cond.From == 1.0 && cond.To != 0.0 {\n\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n\t} else {\n\t\treturn query\n\t}\n}\n\n// buildStringCondition creates filters for string fields supporting equality,\n// inequality, prefix, suffix, substring, and IN list matching.\nfunc buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tif cond.Eq != nil {\n\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n\t}\n\tif cond.Neq != nil {\n\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\tif cond.In != nil {\n\t\tqueryElements := make([]string, len(cond.In))\n\t\tcopy(queryElements, cond.In)\n\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n\t}\n\treturn query\n}\n\n// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\nfunc buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(meta_data)\")\n\tif cond.Eq != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n\t}\n\tif cond.Neq != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\treturn query\n}\n\n// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n// Uses json_each to search within array elements.\nfunc buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n\tquery = query.Where(\"JSON_VALID(resources)\")\n\tif cond.Eq != nil {\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n\t}\n\tif cond.Neq != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n\t}\n\tif cond.StartsWith != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n\t}\n\tif cond.EndsWith != nil { // Currently Unused\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n\t}\n\tif cond.Contains != nil {\n\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n\t}\n\treturn query\n}\n\nvar (\n\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n)\n\n// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n// Includes security checks to prevent SQL injection attempts.\n// Panics if potentially dangerous characters are detected.\nfunc toSnakeCase(str string) string {\n\tfor _, c := range str {\n\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n\t\t}\n\t}\n\n\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n\treturn strings.ToLower(snake)\n}\n","structuredPatch":[{"oldStart":198,"oldLines":8,"newStart":198,"newLines":10,"lines":[" }"," if filter.State != nil {"," if len(filter.State) == 1 {","+ // Inline literal value so SQLite can match partial indexes (WHERE job_state = 'running').","+ // Safe: values come from validated GraphQL enum (model.JobState)."," singleStat := string(filter.State[0])","- query = query.Where(\"job.job_state = ?\", singleStat)","+ query = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))"," } else {"," states := make([]string, len(filter.State))"," for i, val := range filter.State {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"baf6c3cd-6efa-4688-b896-009e95b689ce","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a67b6524-44f4-4584-a05d-caa94055263a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01CvDFCtvYPhBkgsFKujEt5y","type":"message","role":"assistant","content":[{"type":"text","text":"**Change 2: Request-scoped stats cache**"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":373,"cache_read_input_tokens":80009,"cache_creation":{"ephemeral_5m_input_tokens":373,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19rv9gC4YpooR5SKKxn","type":"assistant","uuid":"70184ed1-de23-4e33-9c5b-8532686a4af2","timestamp":"2026-03-13T13:24:53.881Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"70184ed1-de23-4e33-9c5b-8532686a4af2","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01CvDFCtvYPhBkgsFKujEt5y","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01B3cUuvNUVgsA1QdqpkY8SM","name":"Write","input":{"file_path":"/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\"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"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":373,"cache_read_input_tokens":80009,"output_tokens":791,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":373},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19rv9gC4YpooR5SKKxn","type":"assistant","uuid":"2d24b9f0-17ba-4061-beef-cdbbedaa2699","timestamp":"2026-03-13T13:25:03.438Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"type":"file-history-snapshot","messageId":"2d24b9f0-17ba-4061-beef-cdbbedaa2699","snapshot":{"messageId":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","trackedFileBackups":{"internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:24:36.210Z"},"internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:24:37.402Z"},"internal/repository/migration.go":{"backupFileName":"19a8f1f6575af1e7@v1","version":1,"backupTime":"2026-03-13T13:24:44.807Z"},"internal/repository/jobQuery.go":{"backupFileName":"c64bb1bbdfcfaab5@v1","version":1,"backupTime":"2026-03-13T13:24:51.178Z"},"internal/graph/stats_cache.go":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:25:03.452Z"}},"timestamp":"2026-03-13T13:23:59.403Z"},"isSnapshotUpdate":true} +{"parentUuid":"2d24b9f0-17ba-4061-beef-cdbbedaa2699","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Write","command":"callback"},"parentToolUseID":"toolu_01B3cUuvNUVgsA1QdqpkY8SM","toolUseID":"toolu_01B3cUuvNUVgsA1QdqpkY8SM","timestamp":"2026-03-13T13:25:03.453Z","uuid":"35832531-83f3-4f3f-b96d-59c2bd91a447","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"2d24b9f0-17ba-4061-beef-cdbbedaa2699","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B3cUuvNUVgsA1QdqpkY8SM","type":"tool_result","content":"File created successfully at: /Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go"}]},"uuid":"a042ca02-488c-424e-88b6-069c298261e5","timestamp":"2026-03-13T13:25:03.453Z","toolUseResult":{"type":"create","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\"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","structuredPatch":[],"originalFile":null},"sourceToolAssistantUUID":"2d24b9f0-17ba-4061-beef-cdbbedaa2699","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a042ca02-488c-424e-88b6-069c298261e5","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_012GEWpKRU5Mx73pN747mUiF","type":"message","role":"assistant","content":[{"type":"text","text":"Now add the AroundOperations middleware in 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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package main provides the entry point for the ClusterCockpit backend server.\n// This file contains HTTP server setup, routing configuration, and\n// authentication middleware integration.\npackage main\n\nimport (\n\t\"context\"\n\t\"crypto/tls\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"net\"\n\t\"net/http\"\n\t\"os\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/99designs/gqlgen/graphql/handler\"\n\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n\t\"github.com/99designs/gqlgen/graphql/playground\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/api\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/archiver\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/auth\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/routerConfig\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\t\"github.com/ClusterCockpit/cc-backend/web\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/nats\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/runtime\"\n\t\"github.com/go-chi/chi/v5\"\n\t\"github.com/go-chi/chi/v5/middleware\"\n\t\"github.com/go-chi/cors\"\n\thttpSwagger \"github.com/swaggo/http-swagger\"\n)\n\nvar buildInfo web.Build\n\n// Environment variable names\nconst (\n\tenvDebug = \"DEBUG\"\n)\n\n// Server encapsulates the HTTP server state and dependencies\ntype Server struct {\n\trouter chi.Router\n\tserver *http.Server\n\trestAPIHandle *api.RestAPI\n\tnatsAPIHandle *api.NatsAPI\n}\n\nfunc onFailureResponse(rw http.ResponseWriter, r *http.Request, err error) {\n\trw.Header().Add(\"Content-Type\", \"application/json\")\n\trw.WriteHeader(http.StatusUnauthorized)\n\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\"status\": http.StatusText(http.StatusUnauthorized),\n\t\t\"error\": err.Error(),\n\t})\n}\n\n// NewServer creates and initializes a new Server instance\nfunc NewServer(version, commit, buildDate string) (*Server, error) {\n\tbuildInfo = web.Build{Version: version, Hash: commit, Buildtime: buildDate}\n\n\ts := &Server{\n\t\trouter: chi.NewRouter(),\n\t}\n\n\tif err := s.init(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn s, nil\n}\n\nfunc (s *Server) init() error {\n\t// Setup the http.Handler/Router used by the server\n\tgraph.Init()\n\tresolver := graph.GetResolverInstance()\n\tgraphQLServer := handler.New(\n\t\tgenerated.NewExecutableSchema(generated.Config{Resolvers: resolver}))\n\n\tgraphQLServer.AddTransport(transport.POST{})\n\n\tif os.Getenv(envDebug) != \"1\" {\n\t\t// Having this handler means that a error message is returned via GraphQL instead of the connection simply beeing closed.\n\t\t// The problem with this is that then, no more stacktrace is printed to stderr.\n\t\tgraphQLServer.SetRecoverFunc(func(ctx context.Context, err any) error {\n\t\t\tswitch e := err.(type) {\n\t\t\tcase string:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic: %s\", e)\n\t\t\tcase error:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic caused by: %s\", e.Error())\n\t\t\t}\n\n\t\t\treturn errors.New(\"MAIN > Internal server error (panic)\")\n\t\t})\n\t}\n\n\tauthHandle := auth.GetAuthInstance()\n\n\t// Middleware must be defined before routes in chi\n\ts.router.Use(func(next http.Handler) http.Handler {\n\t\treturn http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tstart := time.Now()\n\t\t\tww := middleware.NewWrapResponseWriter(rw, r.ProtoMajor)\n\t\t\tnext.ServeHTTP(ww, r)\n\t\t\tcclog.Debugf(\"%s %s (%d, %.02fkb, %dms)\",\n\t\t\t\tr.Method, r.URL.RequestURI(),\n\t\t\t\tww.Status(), float32(ww.BytesWritten())/1024,\n\t\t\t\ttime.Since(start).Milliseconds())\n\t\t})\n\t})\n\ts.router.Use(middleware.Compress(5))\n\ts.router.Use(middleware.Recoverer)\n\ts.router.Use(cors.Handler(cors.Options{\n\t\tAllowCredentials: true,\n\t\tAllowedHeaders: []string{\"X-Requested-With\", \"Content-Type\", \"Authorization\", \"Origin\"},\n\t\tAllowedMethods: []string{\"GET\", \"POST\", \"HEAD\", \"OPTIONS\"},\n\t\tAllowedOrigins: []string{\"*\"},\n\t}))\n\n\ts.restAPIHandle = api.New()\n\n\tinfo := map[string]any{}\n\tinfo[\"hasOpenIDConnect\"] = false\n\n\tif auth.Keys.OpenIDConfig != nil {\n\t\topenIDConnect := auth.NewOIDC(authHandle)\n\t\topenIDConnect.RegisterEndpoints(s.router)\n\t\tinfo[\"hasOpenIDConnect\"] = true\n\t}\n\n\ts.router.Get(\"/login\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tcclog.Debugf(\"##%v##\", info)\n\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{Title: \"Login\", Build: buildInfo, Infos: info})\n\t})\n\ts.router.HandleFunc(\"/imprint\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"imprint.tmpl\", &web.Page{Title: \"Imprint\", Build: buildInfo})\n\t})\n\ts.router.HandleFunc(\"/privacy\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"privacy.tmpl\", &web.Page{Title: \"Privacy\", Build: buildInfo})\n\t})\n\n\tif !config.Keys.DisableAuthentication {\n\t\t// Create login failure handler (used by both /login and /jwt-login)\n\t\tloginFailureHandler := func(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\tTitle: \"Login failed - ClusterCockpit\",\n\t\t\t\tMsgType: \"alert-warning\",\n\t\t\t\tMessage: err.Error(),\n\t\t\t\tBuild: buildInfo,\n\t\t\t\tInfos: info,\n\t\t\t})\n\t\t}\n\n\t\ts.router.Post(\"/login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\t\ts.router.HandleFunc(\"/jwt-login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\n\t\ts.router.Post(\"/logout\", authHandle.Logout(\n\t\t\thttp.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\t\trw.WriteHeader(http.StatusOK)\n\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\tTitle: \"Bye - ClusterCockpit\",\n\t\t\t\t\tMsgType: \"alert-info\",\n\t\t\t\t\tMessage: \"Logout successful\",\n\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\tInfos: info,\n\t\t\t\t})\n\t\t\t})).ServeHTTP)\n\t}\n\n\tif flagDev {\n\t\ts.router.Handle(\"/playground\", playground.Handler(\"GraphQL playground\", \"/query\"))\n\t\ts.router.Get(\"/swagger/*\", httpSwagger.Handler(\n\t\t\thttpSwagger.URL(\"http://\"+config.Keys.Addr+\"/swagger/doc.json\")))\n\t}\n\n\t// Secured routes (require authentication)\n\ts.router.Group(func(secured chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tsecured.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.Auth(\n\t\t\t\t\tnext,\n\t\t\t\t\tfunc(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\t\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\t\t\tTitle: \"Authentication failed - ClusterCockpit\",\n\t\t\t\t\t\t\tMsgType: \"alert-danger\",\n\t\t\t\t\t\t\tMessage: err.Error(),\n\t\t\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\t\t\tInfos: info,\n\t\t\t\t\t\t\tRedirect: r.RequestURI,\n\t\t\t\t\t\t})\n\t\t\t\t\t})\n\t\t\t})\n\t\t}\n\n\t\tsecured.Handle(\"/query\", graphQLServer)\n\n\t\tsecured.HandleFunc(\"/search\", func(rw http.ResponseWriter, r *http.Request) {\n\t\t\trouterConfig.HandleSearchBar(rw, r, buildInfo)\n\t\t})\n\n\t\trouterConfig.SetupRoutes(secured, buildInfo)\n\t})\n\n\t// API routes (JWT token auth)\n\ts.router.Route(\"/api\", func(apiRouter chi.Router) {\n\t\t// Main API routes with API auth\n\t\tapiRouter.Group(func(securedapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tsecuredapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountAPIRoutes(securedapi)\n\t\t})\n\n\t\t// Metric store API routes with separate auth\n\t\tapiRouter.Group(func(metricstoreapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tmetricstoreapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthMetricStoreAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountMetricStoreAPIRoutes(metricstoreapi)\n\t\t})\n\t})\n\n\t// User API routes\n\ts.router.Route(\"/userapi\", func(userapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tuserapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthUserAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountUserAPIRoutes(userapi)\n\t})\n\n\t// Config API routes (uses Group with full paths to avoid shadowing\n\t// the /config page route that is registered in the secured group)\n\ts.router.Group(func(configapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tconfigapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthConfigAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountConfigAPIRoutes(configapi)\n\t})\n\n\t// Frontend API routes\n\ts.router.Route(\"/frontend\", func(frontendapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tfrontendapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthFrontendAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountFrontendAPIRoutes(frontendapi)\n\t})\n\n\tif config.Keys.APISubjects != nil {\n\t\ts.natsAPIHandle = api.NewNatsAPI()\n\t\tif err := s.natsAPIHandle.StartSubscriptions(); err != nil {\n\t\t\treturn fmt.Errorf(\"starting NATS subscriptions: %w\", err)\n\t\t}\n\t}\n\n\t// 404 handler for pages and API routes\n\tnotFoundHandler := func(rw http.ResponseWriter, r *http.Request) {\n\t\tif strings.HasPrefix(r.URL.Path, \"/api/\") || strings.HasPrefix(r.URL.Path, \"/userapi/\") ||\n\t\t\tstrings.HasPrefix(r.URL.Path, \"/frontend/\") || strings.HasPrefix(r.URL.Path, \"/config/\") {\n\t\t\trw.Header().Set(\"Content-Type\", \"application/json\")\n\t\t\trw.WriteHeader(http.StatusNotFound)\n\t\t\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\t\t\"status\": \"Resource not found\",\n\t\t\t\t\"error\": \"the requested endpoint does not exist\",\n\t\t\t})\n\t\t\treturn\n\t\t}\n\t\trw.Header().Set(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\trw.WriteHeader(http.StatusNotFound)\n\t\tweb.RenderTemplate(rw, \"404.tmpl\", &web.Page{\n\t\t\tTitle: \"Page Not Found\",\n\t\t\tBuild: buildInfo,\n\t\t})\n\t}\n\n\t// Set NotFound on the router so chi uses it for all unmatched routes,\n\t// including those under subrouters like /api, /userapi, /frontend, etc.\n\ts.router.NotFound(notFoundHandler)\n\n\tif config.Keys.EmbedStaticFiles {\n\t\tif i, err := os.Stat(\"./var/img\"); err == nil {\n\t\t\tif i.IsDir() {\n\t\t\t\tcclog.Info(\"Use local directory for static images\")\n\t\t\t\ts.router.Handle(\"/img/*\", http.StripPrefix(\"/img/\", http.FileServer(http.Dir(\"./var/img\"))))\n\t\t\t}\n\t\t}\n\t\tfileServer := http.StripPrefix(\"/\", web.ServeFiles())\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tif web.StaticFileExists(r.URL.Path) {\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t} else {\n\t\tstaticDir := http.Dir(config.Keys.StaticFiles)\n\t\tfileServer := http.FileServer(staticDir)\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tf, err := staticDir.Open(r.URL.Path)\n\t\t\tif err == nil {\n\t\t\t\tf.Close()\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t}\n\n\treturn nil\n}\n\n// Server timeout defaults (in seconds)\nconst (\n\tdefaultReadTimeout = 20\n\tdefaultWriteTimeout = 20\n)\n\nfunc (s *Server) Start(ctx context.Context) error {\n\t// Use configurable timeouts with defaults\n\treadTimeout := time.Duration(defaultReadTimeout) * time.Second\n\twriteTimeout := time.Duration(defaultWriteTimeout) * time.Second\n\n\ts.server = &http.Server{\n\t\tReadTimeout: readTimeout,\n\t\tWriteTimeout: writeTimeout,\n\t\tHandler: s.router,\n\t\tAddr: config.Keys.Addr,\n\t}\n\n\t// Start http or https server\n\tlistener, err := net.Listen(\"tcp\", config.Keys.Addr)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"starting listener on '%s': %w\", config.Keys.Addr, err)\n\t}\n\n\tif !strings.HasSuffix(config.Keys.Addr, \":80\") && config.Keys.RedirectHTTPTo != \"\" {\n\t\tgo func() {\n\t\t\thttp.ListenAndServe(\":80\", http.RedirectHandler(config.Keys.RedirectHTTPTo, http.StatusMovedPermanently))\n\t\t}()\n\t}\n\n\tif config.Keys.HTTPSCertFile != \"\" && config.Keys.HTTPSKeyFile != \"\" {\n\t\tcert, err := tls.LoadX509KeyPair(\n\t\t\tconfig.Keys.HTTPSCertFile, config.Keys.HTTPSKeyFile)\n\t\tif err != nil {\n\t\t\treturn fmt.Errorf(\"loading X509 keypair (check 'https-cert-file' and 'https-key-file' in config.json): %w\", err)\n\t\t}\n\t\tlistener = tls.NewListener(listener, &tls.Config{\n\t\t\tCertificates: []tls.Certificate{cert},\n\t\t\tCipherSuites: []uint16{\n\t\t\t\ttls.TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256,\n\t\t\t\ttls.TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256,\n\t\t\t},\n\t\t\tMinVersion: tls.VersionTLS12,\n\t\t\tPreferServerCipherSuites: true,\n\t\t})\n\t\tcclog.Infof(\"HTTPS server listening at %s...\", config.Keys.Addr)\n\t} else {\n\t\tcclog.Infof(\"HTTP server listening at %s...\", config.Keys.Addr)\n\t}\n\t//\n\t// Because this program will want to bind to a privileged port (like 80), the listener must\n\t// be established first, then the user can be changed, and after that,\n\t// the actual http server can be started.\n\tif err := runtime.DropPrivileges(config.Keys.Group, config.Keys.User); err != nil {\n\t\treturn fmt.Errorf(\"dropping privileges: %w\", err)\n\t}\n\n\t// Handle context cancellation for graceful shutdown\n\tgo func() {\n\t\t<-ctx.Done()\n\t\tshutdownCtx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n\t\tdefer cancel()\n\t\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n\t\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n\t\t}\n\t}()\n\n\tif err = s.server.Serve(listener); err != nil && err != http.ErrServerClosed {\n\t\treturn fmt.Errorf(\"server failed: %w\", err)\n\t}\n\treturn nil\n}\n\nfunc (s *Server) Shutdown(ctx context.Context) {\n\t// Create a shutdown context with timeout\n\tshutdownCtx, cancel := context.WithTimeout(ctx, 30*time.Second)\n\tdefer cancel()\n\n\tnc := nats.GetClient()\n\tif nc != nil {\n\t\tnc.Close()\n\t}\n\n\t// First shut down the server gracefully (waiting for all ongoing requests)\n\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n\t}\n\n\t// Archive all the metric store data\n\tms := metricstore.GetMemoryStore()\n\n\tif ms != nil {\n\t\tmetricstore.Shutdown()\n\t}\n\n\t// Shutdown archiver with 10 second timeout for fast shutdown\n\tif err := archiver.Shutdown(10 * time.Second); err != nil {\n\t\tcclog.Warnf(\"Archiver shutdown: %v\", err)\n\t}\n}\n","structuredPatch":[{"oldStart":89,"oldLines":6,"newStart":89,"newLines":12,"lines":[" "," graphQLServer.AddTransport(transport.POST{})"," ","+ // Inject a per-request stats cache so that grouped statistics queries","+ // sharing the same (filter, groupBy) pair are executed only once.","+ graphQLServer.AroundOperations(func(ctx context.Context, next graphql.OperationHandler) graphql.ResponseHandler {","+ return next(graph.WithStatsGroupCache(ctx))","+ })","+"," if os.Getenv(envDebug) != \"1\" {"," // Having this handler means that a error message is returned via GraphQL instead of the connection simply beeing closed."," // The problem with this is that then, no more stacktrace is printed to stderr."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"2ce24c06-01d6-4a1d-b5cd-ab18359a28d4","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"fbc68978-0297-4973-88de-579028c2ffd2","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01H1bXsWff85qVjutmuZSNp4","type":"message","role":"assistant","content":[{"type":"text","text":"I need to add the `graphql` import and export the `WithStatsGroupCache` function. Let me fix the export name first:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":564,"cache_read_input_tokens":81217,"cache_creation":{"ephemeral_5m_input_tokens":564,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19tGaXXLjzsv5ttCeYQ","type":"assistant","uuid":"1818b2c6-4c94-4d4a-a532-0249439dba81","timestamp":"2026-03-13T13:25:12.976Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"1818b2c6-4c94-4d4a-a532-0249439dba81","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01H1bXsWff85qVjutmuZSNp4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NqmjnYdvuUCnDUU5z92Ysw","name":"Edit","input":{"replace_all":true,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","old_string":"// withStatsGroupCache injects a new cache into the context.\nfunc withStatsGroupCache(ctx context.Context) context.Context {","new_string":"// WithStatsGroupCache injects a new cache into the context.\nfunc WithStatsGroupCache(ctx context.Context) context.Context {"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":564,"cache_read_input_tokens":81217,"output_tokens":229,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":564},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19tGaXXLjzsv5ttCeYQ","type":"assistant","uuid":"6dba49ee-ead2-4357-a4de-d7b05a30a14f","timestamp":"2026-03-13T13:25:14.266Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"6dba49ee-ead2-4357-a4de-d7b05a30a14f","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01NqmjnYdvuUCnDUU5z92Ysw","toolUseID":"toolu_01NqmjnYdvuUCnDUU5z92Ysw","timestamp":"2026-03-13T13:25:14.291Z","uuid":"5d48dcd7-ac33-4c65-897d-bbd7bee95abd","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"6dba49ee-ead2-4357-a4de-d7b05a30a14f","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NqmjnYdvuUCnDUU5z92Ysw","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go has been updated. All occurrences of '// withStatsGroupCache injects a new cache into the context.\nfunc withStatsGroupCache(ctx context.Context) context.Context {' were successfully replaced with '// WithStatsGroupCache injects a new cache into the context.\nfunc WithStatsGroupCache(ctx context.Context) context.Context {'."}]},"uuid":"7614be57-18de-43d4-8812-f22a8e194b90","timestamp":"2026-03-13T13:25:14.291Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","oldString":"// withStatsGroupCache injects a new cache into the context.\nfunc withStatsGroupCache(ctx context.Context) context.Context {","newString":"// WithStatsGroupCache injects a new cache into the context.\nfunc WithStatsGroupCache(ctx context.Context) context.Context {","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\"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","structuredPatch":[{"oldStart":39,"oldLines":8,"newStart":39,"newLines":8,"lines":[" }"," }"," ","-// withStatsGroupCache injects a new cache into the context.","-func withStatsGroupCache(ctx context.Context) context.Context {","+// WithStatsGroupCache injects a new cache into the context.","+func WithStatsGroupCache(ctx context.Context) context.Context {"," return context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())"," }"," "]}],"userModified":false,"replaceAll":true},"sourceToolAssistantUUID":"6dba49ee-ead2-4357-a4de-d7b05a30a14f","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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successfully."}]},"uuid":"6d6d3ad3-8652-4f69-9bc0-dd5b55b31967","timestamp":"2026-03-13T13:25:32.387Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/cmd/cc-backend/server.go","oldString":"\t\"github.com/99designs/gqlgen/graphql/handler\"\n\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n\t\"github.com/99designs/gqlgen/graphql/playground\"","newString":"\t\"github.com/99designs/gqlgen/graphql\"\n\t\"github.com/99designs/gqlgen/graphql/handler\"\n\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n\t\"github.com/99designs/gqlgen/graphql/playground\"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package main provides the entry point for the ClusterCockpit backend server.\n// This file contains HTTP server setup, routing configuration, and\n// authentication middleware integration.\npackage main\n\nimport (\n\t\"context\"\n\t\"crypto/tls\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"net\"\n\t\"net/http\"\n\t\"os\"\n\t\"strings\"\n\t\"time\"\n\n\t\"github.com/99designs/gqlgen/graphql/handler\"\n\t\"github.com/99designs/gqlgen/graphql/handler/transport\"\n\t\"github.com/99designs/gqlgen/graphql/playground\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/api\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/archiver\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/auth\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/generated\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/routerConfig\"\n\t\"github.com/ClusterCockpit/cc-backend/pkg/metricstore\"\n\t\"github.com/ClusterCockpit/cc-backend/web\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/nats\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/runtime\"\n\t\"github.com/go-chi/chi/v5\"\n\t\"github.com/go-chi/chi/v5/middleware\"\n\t\"github.com/go-chi/cors\"\n\thttpSwagger \"github.com/swaggo/http-swagger\"\n)\n\nvar buildInfo web.Build\n\n// Environment variable names\nconst (\n\tenvDebug = \"DEBUG\"\n)\n\n// Server encapsulates the HTTP server state and dependencies\ntype Server struct {\n\trouter chi.Router\n\tserver *http.Server\n\trestAPIHandle *api.RestAPI\n\tnatsAPIHandle *api.NatsAPI\n}\n\nfunc onFailureResponse(rw http.ResponseWriter, r *http.Request, err error) {\n\trw.Header().Add(\"Content-Type\", \"application/json\")\n\trw.WriteHeader(http.StatusUnauthorized)\n\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\"status\": http.StatusText(http.StatusUnauthorized),\n\t\t\"error\": err.Error(),\n\t})\n}\n\n// NewServer creates and initializes a new Server instance\nfunc NewServer(version, commit, buildDate string) (*Server, error) {\n\tbuildInfo = web.Build{Version: version, Hash: commit, Buildtime: buildDate}\n\n\ts := &Server{\n\t\trouter: chi.NewRouter(),\n\t}\n\n\tif err := s.init(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn s, nil\n}\n\nfunc (s *Server) init() error {\n\t// Setup the http.Handler/Router used by the server\n\tgraph.Init()\n\tresolver := graph.GetResolverInstance()\n\tgraphQLServer := handler.New(\n\t\tgenerated.NewExecutableSchema(generated.Config{Resolvers: resolver}))\n\n\tgraphQLServer.AddTransport(transport.POST{})\n\n\t// Inject a per-request stats cache so that grouped statistics queries\n\t// sharing the same (filter, groupBy) pair are executed only once.\n\tgraphQLServer.AroundOperations(func(ctx context.Context, next graphql.OperationHandler) graphql.ResponseHandler {\n\t\treturn next(graph.WithStatsGroupCache(ctx))\n\t})\n\n\tif os.Getenv(envDebug) != \"1\" {\n\t\t// Having this handler means that a error message is returned via GraphQL instead of the connection simply beeing closed.\n\t\t// The problem with this is that then, no more stacktrace is printed to stderr.\n\t\tgraphQLServer.SetRecoverFunc(func(ctx context.Context, err any) error {\n\t\t\tswitch e := err.(type) {\n\t\t\tcase string:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic: %s\", e)\n\t\t\tcase error:\n\t\t\t\treturn fmt.Errorf(\"MAIN > Panic caused by: %s\", e.Error())\n\t\t\t}\n\n\t\t\treturn errors.New(\"MAIN > Internal server error (panic)\")\n\t\t})\n\t}\n\n\tauthHandle := auth.GetAuthInstance()\n\n\t// Middleware must be defined before routes in chi\n\ts.router.Use(func(next http.Handler) http.Handler {\n\t\treturn http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tstart := time.Now()\n\t\t\tww := middleware.NewWrapResponseWriter(rw, r.ProtoMajor)\n\t\t\tnext.ServeHTTP(ww, r)\n\t\t\tcclog.Debugf(\"%s %s (%d, %.02fkb, %dms)\",\n\t\t\t\tr.Method, r.URL.RequestURI(),\n\t\t\t\tww.Status(), float32(ww.BytesWritten())/1024,\n\t\t\t\ttime.Since(start).Milliseconds())\n\t\t})\n\t})\n\ts.router.Use(middleware.Compress(5))\n\ts.router.Use(middleware.Recoverer)\n\ts.router.Use(cors.Handler(cors.Options{\n\t\tAllowCredentials: true,\n\t\tAllowedHeaders: []string{\"X-Requested-With\", \"Content-Type\", \"Authorization\", \"Origin\"},\n\t\tAllowedMethods: []string{\"GET\", \"POST\", \"HEAD\", \"OPTIONS\"},\n\t\tAllowedOrigins: []string{\"*\"},\n\t}))\n\n\ts.restAPIHandle = api.New()\n\n\tinfo := map[string]any{}\n\tinfo[\"hasOpenIDConnect\"] = false\n\n\tif auth.Keys.OpenIDConfig != nil {\n\t\topenIDConnect := auth.NewOIDC(authHandle)\n\t\topenIDConnect.RegisterEndpoints(s.router)\n\t\tinfo[\"hasOpenIDConnect\"] = true\n\t}\n\n\ts.router.Get(\"/login\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tcclog.Debugf(\"##%v##\", info)\n\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{Title: \"Login\", Build: buildInfo, Infos: info})\n\t})\n\ts.router.HandleFunc(\"/imprint\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"imprint.tmpl\", &web.Page{Title: \"Imprint\", Build: buildInfo})\n\t})\n\ts.router.HandleFunc(\"/privacy\", func(rw http.ResponseWriter, r *http.Request) {\n\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\tweb.RenderTemplate(rw, \"privacy.tmpl\", &web.Page{Title: \"Privacy\", Build: buildInfo})\n\t})\n\n\tif !config.Keys.DisableAuthentication {\n\t\t// Create login failure handler (used by both /login and /jwt-login)\n\t\tloginFailureHandler := func(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\tTitle: \"Login failed - ClusterCockpit\",\n\t\t\t\tMsgType: \"alert-warning\",\n\t\t\t\tMessage: err.Error(),\n\t\t\t\tBuild: buildInfo,\n\t\t\t\tInfos: info,\n\t\t\t})\n\t\t}\n\n\t\ts.router.Post(\"/login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\t\ts.router.HandleFunc(\"/jwt-login\", authHandle.Login(loginFailureHandler).ServeHTTP)\n\n\t\ts.router.Post(\"/logout\", authHandle.Logout(\n\t\t\thttp.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\t\trw.Header().Add(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\t\t\trw.WriteHeader(http.StatusOK)\n\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\tTitle: \"Bye - ClusterCockpit\",\n\t\t\t\t\tMsgType: \"alert-info\",\n\t\t\t\t\tMessage: \"Logout successful\",\n\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\tInfos: info,\n\t\t\t\t})\n\t\t\t})).ServeHTTP)\n\t}\n\n\tif flagDev {\n\t\ts.router.Handle(\"/playground\", playground.Handler(\"GraphQL playground\", \"/query\"))\n\t\ts.router.Get(\"/swagger/*\", httpSwagger.Handler(\n\t\t\thttpSwagger.URL(\"http://\"+config.Keys.Addr+\"/swagger/doc.json\")))\n\t}\n\n\t// Secured routes (require authentication)\n\ts.router.Group(func(secured chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tsecured.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.Auth(\n\t\t\t\t\tnext,\n\t\t\t\t\tfunc(rw http.ResponseWriter, r *http.Request, err error) {\n\t\t\t\t\t\trw.WriteHeader(http.StatusUnauthorized)\n\t\t\t\t\t\tweb.RenderTemplate(rw, \"login.tmpl\", &web.Page{\n\t\t\t\t\t\t\tTitle: \"Authentication failed - ClusterCockpit\",\n\t\t\t\t\t\t\tMsgType: \"alert-danger\",\n\t\t\t\t\t\t\tMessage: err.Error(),\n\t\t\t\t\t\t\tBuild: buildInfo,\n\t\t\t\t\t\t\tInfos: info,\n\t\t\t\t\t\t\tRedirect: r.RequestURI,\n\t\t\t\t\t\t})\n\t\t\t\t\t})\n\t\t\t})\n\t\t}\n\n\t\tsecured.Handle(\"/query\", graphQLServer)\n\n\t\tsecured.HandleFunc(\"/search\", func(rw http.ResponseWriter, r *http.Request) {\n\t\t\trouterConfig.HandleSearchBar(rw, r, buildInfo)\n\t\t})\n\n\t\trouterConfig.SetupRoutes(secured, buildInfo)\n\t})\n\n\t// API routes (JWT token auth)\n\ts.router.Route(\"/api\", func(apiRouter chi.Router) {\n\t\t// Main API routes with API auth\n\t\tapiRouter.Group(func(securedapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tsecuredapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountAPIRoutes(securedapi)\n\t\t})\n\n\t\t// Metric store API routes with separate auth\n\t\tapiRouter.Group(func(metricstoreapi chi.Router) {\n\t\t\tif !config.Keys.DisableAuthentication {\n\t\t\t\tmetricstoreapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\t\treturn authHandle.AuthMetricStoreAPI(next, onFailureResponse)\n\t\t\t\t})\n\t\t\t}\n\t\t\ts.restAPIHandle.MountMetricStoreAPIRoutes(metricstoreapi)\n\t\t})\n\t})\n\n\t// User API routes\n\ts.router.Route(\"/userapi\", func(userapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tuserapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthUserAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountUserAPIRoutes(userapi)\n\t})\n\n\t// Config API routes (uses Group with full paths to avoid shadowing\n\t// the /config page route that is registered in the secured group)\n\ts.router.Group(func(configapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tconfigapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthConfigAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountConfigAPIRoutes(configapi)\n\t})\n\n\t// Frontend API routes\n\ts.router.Route(\"/frontend\", func(frontendapi chi.Router) {\n\t\tif !config.Keys.DisableAuthentication {\n\t\t\tfrontendapi.Use(func(next http.Handler) http.Handler {\n\t\t\t\treturn authHandle.AuthFrontendAPI(next, onFailureResponse)\n\t\t\t})\n\t\t}\n\t\ts.restAPIHandle.MountFrontendAPIRoutes(frontendapi)\n\t})\n\n\tif config.Keys.APISubjects != nil {\n\t\ts.natsAPIHandle = api.NewNatsAPI()\n\t\tif err := s.natsAPIHandle.StartSubscriptions(); err != nil {\n\t\t\treturn fmt.Errorf(\"starting NATS subscriptions: %w\", err)\n\t\t}\n\t}\n\n\t// 404 handler for pages and API routes\n\tnotFoundHandler := func(rw http.ResponseWriter, r *http.Request) {\n\t\tif strings.HasPrefix(r.URL.Path, \"/api/\") || strings.HasPrefix(r.URL.Path, \"/userapi/\") ||\n\t\t\tstrings.HasPrefix(r.URL.Path, \"/frontend/\") || strings.HasPrefix(r.URL.Path, \"/config/\") {\n\t\t\trw.Header().Set(\"Content-Type\", \"application/json\")\n\t\t\trw.WriteHeader(http.StatusNotFound)\n\t\t\tjson.NewEncoder(rw).Encode(map[string]string{\n\t\t\t\t\"status\": \"Resource not found\",\n\t\t\t\t\"error\": \"the requested endpoint does not exist\",\n\t\t\t})\n\t\t\treturn\n\t\t}\n\t\trw.Header().Set(\"Content-Type\", \"text/html; charset=utf-8\")\n\t\trw.WriteHeader(http.StatusNotFound)\n\t\tweb.RenderTemplate(rw, \"404.tmpl\", &web.Page{\n\t\t\tTitle: \"Page Not Found\",\n\t\t\tBuild: buildInfo,\n\t\t})\n\t}\n\n\t// Set NotFound on the router so chi uses it for all unmatched routes,\n\t// including those under subrouters like /api, /userapi, /frontend, etc.\n\ts.router.NotFound(notFoundHandler)\n\n\tif config.Keys.EmbedStaticFiles {\n\t\tif i, err := os.Stat(\"./var/img\"); err == nil {\n\t\t\tif i.IsDir() {\n\t\t\t\tcclog.Info(\"Use local directory for static images\")\n\t\t\t\ts.router.Handle(\"/img/*\", http.StripPrefix(\"/img/\", http.FileServer(http.Dir(\"./var/img\"))))\n\t\t\t}\n\t\t}\n\t\tfileServer := http.StripPrefix(\"/\", web.ServeFiles())\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tif web.StaticFileExists(r.URL.Path) {\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t} else {\n\t\tstaticDir := http.Dir(config.Keys.StaticFiles)\n\t\tfileServer := http.FileServer(staticDir)\n\t\ts.router.Handle(\"/*\", http.HandlerFunc(func(rw http.ResponseWriter, r *http.Request) {\n\t\t\tf, err := staticDir.Open(r.URL.Path)\n\t\t\tif err == nil {\n\t\t\t\tf.Close()\n\t\t\t\tfileServer.ServeHTTP(rw, r)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tnotFoundHandler(rw, r)\n\t\t}))\n\t}\n\n\treturn nil\n}\n\n// Server timeout defaults (in seconds)\nconst (\n\tdefaultReadTimeout = 20\n\tdefaultWriteTimeout = 20\n)\n\nfunc (s *Server) Start(ctx context.Context) error {\n\t// Use configurable timeouts with defaults\n\treadTimeout := time.Duration(defaultReadTimeout) * time.Second\n\twriteTimeout := time.Duration(defaultWriteTimeout) * time.Second\n\n\ts.server = &http.Server{\n\t\tReadTimeout: readTimeout,\n\t\tWriteTimeout: writeTimeout,\n\t\tHandler: s.router,\n\t\tAddr: config.Keys.Addr,\n\t}\n\n\t// Start http or https server\n\tlistener, err := net.Listen(\"tcp\", config.Keys.Addr)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"starting listener on '%s': %w\", config.Keys.Addr, err)\n\t}\n\n\tif !strings.HasSuffix(config.Keys.Addr, \":80\") && config.Keys.RedirectHTTPTo != \"\" {\n\t\tgo func() {\n\t\t\thttp.ListenAndServe(\":80\", http.RedirectHandler(config.Keys.RedirectHTTPTo, http.StatusMovedPermanently))\n\t\t}()\n\t}\n\n\tif config.Keys.HTTPSCertFile != \"\" && config.Keys.HTTPSKeyFile != \"\" {\n\t\tcert, err := tls.LoadX509KeyPair(\n\t\t\tconfig.Keys.HTTPSCertFile, config.Keys.HTTPSKeyFile)\n\t\tif err != nil {\n\t\t\treturn fmt.Errorf(\"loading X509 keypair (check 'https-cert-file' and 'https-key-file' in config.json): %w\", err)\n\t\t}\n\t\tlistener = tls.NewListener(listener, &tls.Config{\n\t\t\tCertificates: []tls.Certificate{cert},\n\t\t\tCipherSuites: []uint16{\n\t\t\t\ttls.TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256,\n\t\t\t\ttls.TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256,\n\t\t\t},\n\t\t\tMinVersion: tls.VersionTLS12,\n\t\t\tPreferServerCipherSuites: true,\n\t\t})\n\t\tcclog.Infof(\"HTTPS server listening at %s...\", config.Keys.Addr)\n\t} else {\n\t\tcclog.Infof(\"HTTP server listening at %s...\", config.Keys.Addr)\n\t}\n\t//\n\t// Because this program will want to bind to a privileged port (like 80), the listener must\n\t// be established first, then the user can be changed, and after that,\n\t// the actual http server can be started.\n\tif err := runtime.DropPrivileges(config.Keys.Group, config.Keys.User); err != nil {\n\t\treturn fmt.Errorf(\"dropping privileges: %w\", err)\n\t}\n\n\t// Handle context cancellation for graceful shutdown\n\tgo func() {\n\t\t<-ctx.Done()\n\t\tshutdownCtx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n\t\tdefer cancel()\n\t\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n\t\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n\t\t}\n\t}()\n\n\tif err = s.server.Serve(listener); err != nil && err != http.ErrServerClosed {\n\t\treturn fmt.Errorf(\"server failed: %w\", err)\n\t}\n\treturn nil\n}\n\nfunc (s *Server) Shutdown(ctx context.Context) {\n\t// Create a shutdown context with timeout\n\tshutdownCtx, cancel := context.WithTimeout(ctx, 30*time.Second)\n\tdefer cancel()\n\n\tnc := nats.GetClient()\n\tif nc != nil {\n\t\tnc.Close()\n\t}\n\n\t// First shut down the server gracefully (waiting for all ongoing requests)\n\tif err := s.server.Shutdown(shutdownCtx); err != nil {\n\t\tcclog.Errorf(\"Server shutdown error: %v\", err)\n\t}\n\n\t// Archive all the metric store data\n\tms := metricstore.GetMemoryStore()\n\n\tif ms != nil {\n\t\tmetricstore.Shutdown()\n\t}\n\n\t// Shutdown archiver with 10 second timeout for fast shutdown\n\tif err := archiver.Shutdown(10 * time.Second); err != nil {\n\t\tcclog.Warnf(\"Archiver shutdown: %v\", err)\n\t}\n}\n","structuredPatch":[{"oldStart":20,"oldLines":6,"newStart":20,"newLines":7,"lines":[" \"strings\""," \"time\""," ","+ \"github.com/99designs/gqlgen/graphql\""," 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continued):"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":437,"cache_read_input_tokens":82131,"cache_creation":{"ephemeral_5m_input_tokens":437,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19uxKyWUqLJaysP3jyx","type":"assistant","uuid":"49f112dc-32cc-47cb-af63-4592d0b45fff","timestamp":"2026-03-13T13:25:35.559Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"49f112dc-32cc-47cb-af63-4592d0b45fff","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0177mfyC6snMWx8enRjuGyAr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01DE6W1e535THYg1yPxfhaat","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","old_string":"\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\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n\t\t}\n\t} else {","new_string":"\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 {"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":437,"cache_read_input_tokens":82131,"output_tokens":576,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":437},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19uxKyWUqLJaysP3jyx","type":"assistant","uuid":"eac31e9f-039b-463c-bc87-91c1da020980","timestamp":"2026-03-13T13:25:41.577Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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successfully."}]},"uuid":"868f10fc-48dc-488e-9133-b1d838599dee","timestamp":"2026-03-13T13:25:41.604Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go","oldString":"\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\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\n\t\t\tcclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))\n\t\t}\n\t} else {","newString":"\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 {","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 v0.17.87\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\tstats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)\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 (\n\tclusterResolver struct{ *Resolver }\n\tjobResolver struct{ *Resolver }\n\tmetricValueResolver struct{ *Resolver }\n\tmutationResolver struct{ *Resolver }\n\tnodeResolver struct{ *Resolver }\n\tqueryResolver struct{ *Resolver }\n\tsubClusterResolver struct{ *Resolver }\n)\n","structuredPatch":[{"oldStart":673,"oldLines":7,"newStart":673,"newLines":20,"lines":[" stats, err = r.Repo.JobsStats(ctx, filter, reqFields)"," } else {"," startGrouped := time.Now()","- stats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)","+ // 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)","+ var allStats []*model.JobsStatistics","+ allStats, err = cache.getOrCompute(key, func() ([]*model.JobsStatistics, error) {","+ return r.Repo.JobsStatsGrouped(ctx, filter, nil, nil, groupBy, nil)","+ })","+ if err == nil {","+ stats = sortAndPageStats(allStats, sortBy, page)","+ }","+ } else {","+ stats, err = r.Repo.JobsStatsGrouped(ctx, filter, page, sortBy, groupBy, reqFields)","+ }"," cclog.Infof(\"Timer JobsStatsGrouped call: %s\", time.Since(startGrouped))"," }"," } else {"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"eac31e9f-039b-463c-bc87-91c1da020980","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"868f10fc-48dc-488e-9133-b1d838599dee","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WD557D88SP67vegFoJ5jCV","type":"message","role":"assistant","content":[{"type":"text","text":"Now I need to add the `sortAndPageStats` helper function. Let me add it to `stats_cache.go`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":622,"cache_read_input_tokens":82568,"cache_creation":{"ephemeral_5m_input_tokens":622,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19vdia6HmiHSu69MCC9","type":"assistant","uuid":"d6b37f45-c7ba-4a42-a354-f2c9c55ae0dc","timestamp":"2026-03-13T13:25:44.663Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"d6b37f45-c7ba-4a42-a354-f2c9c55ae0dc","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WD557D88SP67vegFoJ5jCV","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QUwJ9fpKYTE34wCE1Lt4Cg","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":622,"cache_read_input_tokens":82568,"output_tokens":107,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":622},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19vdia6HmiHSu69MCC9","type":"assistant","uuid":"b54d60aa-bd7f-4739-82c9-1e8d40c9d726","timestamp":"2026-03-13T13:25:44.761Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"b54d60aa-bd7f-4739-82c9-1e8d40c9d726","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01QUwJ9fpKYTE34wCE1Lt4Cg","toolUseID":"toolu_01QUwJ9fpKYTE34wCE1Lt4Cg","timestamp":"2026-03-13T13:25:44.779Z","uuid":"6e102bc2-3188-4ad4-a6af-1a0a4ffd0e72","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"b54d60aa-bd7f-4739-82c9-1e8d40c9d726","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QUwJ9fpKYTE34wCE1Lt4Cg","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\"sync\"\n 12→\n 13→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 14→)\n 15→\n 16→// statsGroupCache is a per-request cache for grouped JobsStatistics results.\n 17→// It deduplicates identical (filter+groupBy) SQL queries that arise when the\n 18→// frontend requests multiple sort/page slices of the same underlying data\n 19→// (e.g. topUserJobs, topUserNodes, topUserAccs all group by USER).\n 20→type statsGroupCache struct {\n 21→\tmu sync.Mutex\n 22→\tentries map[string]*cacheEntry\n 23→}\n 24→\n 25→type cacheEntry struct {\n 26→\tonce sync.Once\n 27→\tresult []*model.JobsStatistics\n 28→\terr error\n 29→}\n 30→\n 31→type ctxKey int\n 32→\n 33→const statsGroupCacheKey ctxKey = iota\n 34→\n 35→// newStatsGroupCache creates a new empty cache.\n 36→func newStatsGroupCache() *statsGroupCache {\n 37→\treturn &statsGroupCache{\n 38→\t\tentries: make(map[string]*cacheEntry),\n 39→\t}\n 40→}\n 41→\n 42→// WithStatsGroupCache injects a new cache into the context.\n 43→func WithStatsGroupCache(ctx context.Context) context.Context {\n 44→\treturn context.WithValue(ctx, statsGroupCacheKey, newStatsGroupCache())\n 45→}\n 46→\n 47→// getStatsGroupCache retrieves the cache from context, or nil if absent.\n 48→func getStatsGroupCache(ctx context.Context) *statsGroupCache {\n 49→\tif c, ok := ctx.Value(statsGroupCacheKey).(*statsGroupCache); ok {\n 50→\t\treturn c\n 51→\t}\n 52→\treturn nil\n 53→}\n 54→\n 55→// cacheKey builds a deterministic string key from filter + groupBy.\n 56→func statsCacheKey(filter []*model.JobFilter, groupBy *model.Aggregate) string {\n 57→\treturn fmt.Sprintf(\"%v|%v\", filter, *groupBy)\n 58→}\n 59→\n 60→// getOrCompute returns cached results for the given key, computing them on\n 61→// first access via the provided function.\n 62→func (c *statsGroupCache) getOrCompute(\n 63→\tkey string,\n 64→\tcompute func() ([]*model.JobsStatistics, error),\n 65→) ([]*model.JobsStatistics, error) {\n 66→\tc.mu.Lock()\n 67→\tentry, ok := c.entries[key]\n 68→\tif !ok {\n 69→\t\tentry = &cacheEntry{}\n 70→\t\tc.entries[key] = entry\n 71→\t}\n 72→\tc.mu.Unlock()\n 73→\n 74→\tentry.once.Do(func() {\n 75→\t\tentry.result, entry.err = compute()\n 76→\t})\n 77→\treturn entry.result, entry.err\n 78→}\n 79→"}]},"uuid":"2a42853d-2db7-46b7-9aef-ffa9af84f034","timestamp":"2026-03-13T13:25:44.779Z","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\"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","numLines":79,"startLine":1,"totalLines":79}},"sourceToolAssistantUUID":"b54d60aa-bd7f-4739-82c9-1e8d40c9d726","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"2a42853d-2db7-46b7-9aef-ffa9af84f034","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PnHsnU6gt2LhjfXhTEZjDR","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013toWZ6WkCsL4eQ5sKan4Ji","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","old_string":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n)","new_string":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"slices\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n)"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1741,"cache_read_input_tokens":82568,"output_tokens":222,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1741},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19vsJ8tk4gF7rPLFDyq","type":"assistant","uuid":"0b9df822-27a7-4a89-8b3a-7d2090e64fc7","timestamp":"2026-03-13T13:25:49.219Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"0b9df822-27a7-4a89-8b3a-7d2090e64fc7","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_013toWZ6WkCsL4eQ5sKan4Ji","toolUseID":"toolu_013toWZ6WkCsL4eQ5sKan4Ji","timestamp":"2026-03-13T13:25:49.256Z","uuid":"b6bc947a-7db4-4b1b-afd4-da33f15aa784","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"0b9df822-27a7-4a89-8b3a-7d2090e64fc7","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013toWZ6WkCsL4eQ5sKan4Ji","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go has been updated successfully."}]},"uuid":"3df9fb40-d43e-441b-a54d-327d01d7d5ca","timestamp":"2026-03-13T13:25:49.256Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","oldString":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n)","newString":"import (\n\t\"context\"\n\t\"fmt\"\n\t\"slices\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\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\"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","structuredPatch":[{"oldStart":8,"oldLines":6,"newStart":8,"newLines":7,"lines":[" import ("," \"context\""," \"fmt\"","+ \"slices\""," \"sync\""," "," \"github.com/ClusterCockpit/cc-backend/internal/graph/model\""]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"0b9df822-27a7-4a89-8b3a-7d2090e64fc7","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"3df9fb40-d43e-441b-a54d-327d01d7d5ca","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01QAa4fwohhpymL9HqVikZH5","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Y8crQvfpZ2nJrQyvZ5LPN9","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","old_string":"\treturn entry.result, entry.err\n}","new_string":"\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}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":267,"cache_read_input_tokens":84309,"output_tokens":918,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":267},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19wCRKxfGtevGTc85v1","type":"assistant","uuid":"edf51814-e2de-4d4f-9baa-2741808df2db","timestamp":"2026-03-13T13:26:01.047Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"edf51814-e2de-4d4f-9baa-2741808df2db","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01Y8crQvfpZ2nJrQyvZ5LPN9","toolUseID":"toolu_01Y8crQvfpZ2nJrQyvZ5LPN9","timestamp":"2026-03-13T13:26:01.069Z","uuid":"d9abe7ec-fb44-449a-9f18-f86e4c55ff14","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"edf51814-e2de-4d4f-9baa-2741808df2db","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Y8crQvfpZ2nJrQyvZ5LPN9","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go has been updated successfully."}]},"uuid":"d11ac660-7a96-420c-8886-d5b6cc230188","timestamp":"2026-03-13T13:26:01.068Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/stats_cache.go","oldString":"\treturn entry.result, entry.err\n}","newString":"\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}","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","structuredPatch":[{"oldStart":77,"oldLines":3,"newStart":77,"newLines":59,"lines":[" })"," return entry.result, entry.err"," }","+","+// sortAndPageStats sorts a copy of allStats by the given sortBy field (descending)","+// and returns the requested page slice.","+func sortAndPageStats(allStats []*model.JobsStatistics, sortBy *model.SortByAggregate, page *model.PageRequest) []*model.JobsStatistics {","+ // Work on a shallow copy so the cached slice order is not mutated.","+ sorted := make([]*model.JobsStatistics, len(allStats))","+ copy(sorted, allStats)","+","+ if sortBy != nil {","+ getter := statsFieldGetter(*sortBy)","+ slices.SortFunc(sorted, func(a, b *model.JobsStatistics) int {","+ return getter(b) - getter(a) // descending","+ })","+ }","+","+ if page != nil && page.ItemsPerPage != -1 {","+ start := (page.Page - 1) * page.ItemsPerPage","+ if start >= len(sorted) {","+ return nil","+ }","+ end := start + page.ItemsPerPage","+ if end > len(sorted) {","+ end = len(sorted)","+ }","+ sorted = sorted[start:end]","+ }","+","+ return sorted","+}","+","+// statsFieldGetter returns a function that extracts the sortable int field","+// from a JobsStatistics struct for the given sort key.","+func statsFieldGetter(sortBy model.SortByAggregate) func(*model.JobsStatistics) int {","+ switch sortBy {","+ case model.SortByAggregateTotaljobs:","+ return func(s *model.JobsStatistics) int { return s.TotalJobs }","+ case model.SortByAggregateTotalusers:","+ return func(s *model.JobsStatistics) int { return s.TotalUsers }","+ case model.SortByAggregateTotalwalltime:","+ return func(s *model.JobsStatistics) int { return s.TotalWalltime }","+ case model.SortByAggregateTotalnodes:","+ return func(s *model.JobsStatistics) int { return s.TotalNodes }","+ case model.SortByAggregateTotalnodehours:","+ return func(s *model.JobsStatistics) int { return s.TotalNodeHours }","+ case model.SortByAggregateTotalcores:","+ return func(s *model.JobsStatistics) int { return s.TotalCores }","+ case model.SortByAggregateTotalcorehours:","+ return func(s *model.JobsStatistics) int { return s.TotalCoreHours }","+ case model.SortByAggregateTotalaccs:","+ return func(s *model.JobsStatistics) int { return s.TotalAccs }","+ case model.SortByAggregateTotalacchours:","+ return func(s *model.JobsStatistics) int { return s.TotalAccHours }","+ default:","+ return func(s *model.JobsStatistics) int { return s.TotalJobs }","+ }","+}"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"edf51814-e2de-4d4f-9baa-2741808df2db","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"d11ac660-7a96-420c-8886-d5b6cc230188","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NLCdYJwwkVDxX1H5LKY4kq","type":"message","role":"assistant","content":[{"type":"text","text":"The `slices` import: I'm using `slices.SortFunc` so it should be used. Let me check the Go version:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1033,"cache_read_input_tokens":84576,"cache_creation":{"ephemeral_5m_input_tokens":1033,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19x5CHG7jrP7jojRgxg","type":"assistant","uuid":"581a1b83-1054-4e6f-9183-7042df0a5d5c","timestamp":"2026-03-13T13:26:04.185Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"581a1b83-1054-4e6f-9183-7042df0a5d5c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NLCdYJwwkVDxX1H5LKY4kq","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CtJHadHZrKMTKNrRPwmvQe","name":"Bash","input":{"command":"head -5 /Users/jan/prg/ClusterCockpit/cc-backend/go.mod","description":"Check Go version"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1033,"cache_read_input_tokens":84576,"output_tokens":127,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1033},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19x5CHG7jrP7jojRgxg","type":"assistant","uuid":"5c01da7e-23a7-4646-b6bd-fe07c5f354e0","timestamp":"2026-03-13T13:26:04.767Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5c01da7e-23a7-4646-b6bd-fe07c5f354e0","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CtJHadHZrKMTKNrRPwmvQe","type":"tool_result","content":"module github.com/ClusterCockpit/cc-backend\n\ngo 1.25.0\n\ntool (","is_error":false}]},"uuid":"1afcd351-1304-42de-a50c-2f7f6b3aca8b","timestamp":"2026-03-13T13:26:04.820Z","toolUseResult":{"stdout":"module github.com/ClusterCockpit/cc-backend\n\ngo 1.25.0\n\ntool (","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"5c01da7e-23a7-4646-b6bd-fe07c5f354e0","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"1afcd351-1304-42de-a50c-2f7f6b3aca8b","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01HDHc7VBGMXFPoRqByAWShB","type":"message","role":"assistant","content":[{"type":"text","text":"Go 1.25 should have `slices` in stdlib. The diagnostic might be stale. Let me verify the build compiles. But first let me do **Change 3: Parallelize histogram queries**."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":229,"cache_read_input_tokens":85609,"cache_creation":{"ephemeral_5m_input_tokens":229,"ephemeral_1h_input_tokens":0},"output_tokens":7,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19xLyJWgjbjAw7uhUFh","type":"assistant","uuid":"a0e65154-c7c8-45d8-8963-75c4f08c116a","timestamp":"2026-03-13T13:26:08.786Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a0e65154-c7c8-45d8-8963-75c4f08c116a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01HDHc7VBGMXFPoRqByAWShB","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015ABCLJxD54VJdQ4434Xb1T","name":"Bash","input":{"command":"grep 'golang.org/x/sync' go.mod","description":"Check if x/sync is a dependency"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":229,"cache_read_input_tokens":85609,"output_tokens":155,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":229},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19xLyJWgjbjAw7uhUFh","type":"assistant","uuid":"753a9235-bde6-405f-b6f4-72e439b7159b","timestamp":"2026-03-13T13:26:09.488Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"753a9235-bde6-405f-b6f4-72e439b7159b","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015ABCLJxD54VJdQ4434Xb1T","type":"tool_result","content":"\tgolang.org/x/sync v0.19.0 // indirect","is_error":false}]},"uuid":"efe5c323-499c-4de2-8de9-e4f2dc6fc53b","timestamp":"2026-03-13T13:26:09.534Z","toolUseResult":{"stdout":"\tgolang.org/x/sync v0.19.0 // indirect","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"753a9235-bde6-405f-b6f4-72e439b7159b","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"efe5c323-499c-4de2-8de9-e4f2dc6fc53b","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SxgSrbZviAMYahS9ihhLra","type":"message","role":"assistant","content":[{"type":"text","text":"Good, `errgroup` is available. Now parallelize the histogram queries in `AddHistograms`:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":274,"cache_read_input_tokens":85838,"cache_creation":{"ephemeral_5m_input_tokens":274,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19xhAVSmTVBLFWNDEDi","type":"assistant","uuid":"8002f7f9-74b5-44f4-ad05-82b438d15718","timestamp":"2026-03-13T13:26:12.772Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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successfully."}]},"uuid":"18180edc-dbac-4031-afea-d6b8212ff2ed","timestamp":"2026-03-13T13:26:16.260Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go","oldString":"\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\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/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"","newString":"\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\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/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"golang.org/x/sync/errgroup\"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file contains job statistics and histogram generation functionality for the JobRepository.\n//\n// # Job Statistics\n//\n// The statistics methods provide aggregated metrics about jobs including total jobs, users,\n// walltime, and resource usage (nodes, cores, accelerators). Statistics can be computed:\n// - Overall (JobsStats): Single aggregate across all matching jobs\n// - Grouped (JobsStatsGrouped): Aggregated by user, project, cluster, or subcluster\n// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n//\n// All statistics methods support filtering via JobFilter and respect security contexts.\n//\n// # Histograms\n//\n// Histogram methods generate distribution data for visualization:\n// - Duration, nodes, cores, accelerators (AddHistograms)\n// - Job metrics like CPU load, memory usage (AddMetricHistograms)\n//\n// Histograms use intelligent binning:\n// - Duration: Variable bin sizes (1m, 10m, 1h, 6h, 12h, 24h) with zero-padding\n// - Resources: Natural value-based bins\n// - Metrics: Normalized to peak values with configurable bin counts\n//\n// # Running vs. Completed Jobs\n//\n// Statistics handle running jobs specially:\n// - Duration calculated as (now - start_time) for running jobs\n// - Metric histograms for running jobs load data from metric backend instead of footprint\n// - Job state filtering distinguishes running/completed jobs\n//\n// # Performance Considerations\n//\n// - All queries use prepared statements via stmtCache\n// - Complex aggregations use SQL for efficiency\n// - Histogram pre-initialization ensures consistent bin ranges\n// - Metric histogram queries limited to 5000 jobs for running job analysis\n\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"fmt\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\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/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n)\n\n// groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names.\n// Used by JobsStatsGrouped and JobCountGrouped to translate user-facing grouping dimensions\n// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\nvar groupBy2column = map[model.Aggregate]string{\n\tmodel.AggregateUser: \"job.hpc_user\",\n\tmodel.AggregateProject: \"job.project\",\n\tmodel.AggregateCluster: \"job.cluster\",\n\tmodel.AggregateSubcluster: \"job.subcluster\",\n}\n\n// sortBy2column maps GraphQL SortByAggregate enum values to their corresponding computed column names.\n// Used by JobsStatsGrouped to translate sort preferences into SQL ORDER BY clauses.\n// Column names match the AS aliases used in buildStatsQuery.\nvar sortBy2column = map[model.SortByAggregate]string{\n\tmodel.SortByAggregateTotaljobs: \"totalJobs\",\n\tmodel.SortByAggregateTotalusers: \"totalUsers\",\n\tmodel.SortByAggregateTotalwalltime: \"totalWalltime\",\n\tmodel.SortByAggregateTotalnodes: \"totalNodes\",\n\tmodel.SortByAggregateTotalnodehours: \"totalNodeHours\",\n\tmodel.SortByAggregateTotalcores: \"totalCores\",\n\tmodel.SortByAggregateTotalcorehours: \"totalCoreHours\",\n\tmodel.SortByAggregateTotalaccs: \"totalAccs\",\n\tmodel.SortByAggregateTotalacchours: \"totalAccHours\",\n}\n\n// buildCountQuery constructs a SQL query to count jobs with optional grouping and filtering.\n//\n// Parameters:\n// - filter: Job filters to apply (cluster, user, time range, etc.)\n// - kind: Special filter - \"running\" for running jobs only, \"short\" for jobs under threshold\n// - col: Column name to GROUP BY; empty string for total count without grouping\n//\n// Returns a SelectBuilder that produces either:\n// - Single count: COUNT(job.id) when col is empty\n// - Grouped counts: col, COUNT(job.id) when col is specified\n//\n// The kind parameter enables counting specific job categories:\n// - \"running\": Only jobs with job_state = 'running'\n// - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n// - empty: All jobs matching filters\nfunc (r *JobRepository) buildCountQuery(\n\tfilter []*model.JobFilter,\n\tkind string,\n\tcol string,\n) sq.SelectBuilder {\n\tvar query sq.SelectBuilder\n\n\tif col != \"\" {\n\t\tquery = sq.Select(col, \"COUNT(*)\").From(\"job\").GroupBy(col)\n\t} else {\n\t\tquery = sq.Select(\"COUNT(*)\").From(\"job\")\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n\tcase \"short\":\n\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n\t}\n\n\tfor _, f := range filter {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\treturn query\n}\n\n// buildStatsQuery constructs a SQL query to compute job statistics with optional grouping.\n// Only requested columns are computed; unrequested columns select 0 as placeholder.\n//\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\") && col != \"job.hpc_user\" {\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}\n\n// JobsStatsGrouped computes job statistics grouped by a dimension (user, project, cluster, or subcluster).\n// Only columns listed in reqFields are computed; others return 0. User display names are looked up\n// in a separate lightweight query to avoid JOIN overhead on the main aggregation.\nfunc (r *JobRepository) JobsStatsGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tpage *model.PageRequest,\n\tsortBy *model.SortByAggregate,\n\tgroupBy *model.Aggregate,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildStatsQuery(filter, col, config.Keys.ShortRunningJobsDuration, reqFields)\n\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif sortBy != nil {\n\t\tsortBy := sortBy2column[*sortBy]\n\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n\t}\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tlimit := uint64(page.ItemsPerPage)\n\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n\t}\n\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\t\tif err := rows.Scan(&id, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\t\tTotalNodes: int(nodes.Int64),\n\t\t\t\t\tTotalNodeHours: int(nodeHours.Int64),\n\t\t\t\t\tTotalCores: int(cores.Int64),\n\t\t\t\t\tTotalCoreHours: int(coreHours.Int64),\n\t\t\t\t\tTotalAccs: int(accs.Int64),\n\t\t\t\t\tTotalAccHours: int(accHours.Int64),\n\t\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\t// Post-query name lookup for user grouping (avoids LEFT JOIN on aggregation query)\n\tif col == \"job.hpc_user\" && len(stats) > 0 {\n\t\tusernames := make([]any, len(stats))\n\t\tfor i, s := range stats {\n\t\t\tusernames[i] = s.ID\n\t\t}\n\n\t\tnameQuery := sq.Select(\"username\", \"name\").From(\"hpc_user\").Where(sq.Eq{\"username\": usernames})\n\t\tnameRows, err := nameQuery.RunWith(r.DB).QueryContext(ctx)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error looking up user names: %s\", err.Error())\n\t\t\t// Non-fatal: stats are still valid without display names\n\t\t} else {\n\t\t\tdefer nameRows.Close()\n\t\t\tnameMap := make(map[string]string, len(stats))\n\t\t\tfor nameRows.Next() {\n\t\t\t\tvar username, name string\n\t\t\t\tif err := nameRows.Scan(&username, &name); err == nil {\n\t\t\t\t\tnameMap[username] = name\n\t\t\t\t}\n\t\t\t}\n\t\t\tfor _, s := range stats {\n\t\t\t\tif name, ok := nameMap[s.ID]; ok {\n\t\t\t\t\ts.Name = name\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// JobsStats computes overall job statistics across all matching jobs without grouping.\n//\n// This method provides a single aggregate view of job metrics, useful for dashboard\n// summaries and overall system utilization reports.\n//\n// Parameters:\n// - ctx: Context for security checks and cancellation\n// - filter: Filters to apply (time range, cluster, job state, etc.)\n//\n// Returns a single-element slice containing aggregate statistics:\n// - totalJobs, totalUsers, totalWalltime\n// - totalNodeHours, totalCoreHours, totalAccHours\n//\n// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n// Security checks are applied via SecurityCheck to respect user access levels.\nfunc (r *JobRepository) JobsStats(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildStatsQuery(filter, \"\", config.Keys.ShortRunningJobsDuration, reqFields)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\trow := query.RunWith(r.DB).QueryRowContext(ctx)\n\tstats := make([]*model.JobsStatistics, 0, 1)\n\n\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\tcclog.Warn(\"Error while scanning rows\")\n\t\treturn nil, err\n\t}\n\n\tif jobs.Valid {\n\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n\n\t\tif nodeHours.Valid {\n\t\t\ttotalNodeHours = int(nodeHours.Int64)\n\t\t}\n\t\tif coreHours.Valid {\n\t\t\ttotalCoreHours = int(coreHours.Int64)\n\t\t}\n\t\tif accHours.Valid {\n\t\t\ttotalAccHours = int(accHours.Int64)\n\t\t}\n\t\tstats = append(stats,\n\t\t\t&model.JobsStatistics{\n\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\tTotalNodeHours: totalNodeHours,\n\t\t\t\tTotalCoreHours: totalCoreHours,\n\t\t\t\tTotalAccHours: totalAccHours,\n\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t})\n\t}\n\n\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n// Returns 0.0 if the metric is not found or statType is invalid.\n//\n// Parameters:\n// - job: Job struct with populated Statistics field\n// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n//\n// Returns the requested statistic value or 0.0 if not found.\nfunc LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n\tif stats, ok := job.Statistics[metric]; ok {\n\t\tswitch statType {\n\t\tcase \"avg\":\n\t\t\treturn stats.Avg\n\t\tcase \"max\":\n\t\t\treturn stats.Max\n\t\tcase \"min\":\n\t\t\treturn stats.Min\n\t\tdefault:\n\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n\t\t}\n\t}\n\n\treturn 0.0\n}\n\n// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n//\n// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n// avoiding the overhead of calculating walltime and resource usage metrics.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n//\n// Returns JobsStatistics with only ID and TotalJobs populated for each group.\nfunc (r *JobRepository) JobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, \"\", col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(cnt.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCountGrouped augments existing statistics with additional job counts by category.\n//\n// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n// - stats: Existing statistics to augment (modified in-place by ID matching)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n// Groups without matching jobs will have 0 for the added field.\nfunc (r *JobRepository) AddJobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, kind, col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tcounts := make(map[string]int)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tcounts[id.String] = int(cnt.Int64)\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = counts[s.ID]\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = counts[s.ID]\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCount augments existing overall statistics with additional job counts by category.\n//\n// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n// to all statistics entries (typically just one).\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - stats: Existing statistics to augment (modified in-place)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\nfunc (r *JobRepository) AddJobCount(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildCountQuery(filter, kind, \"\")\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tvar cnt sql.NullInt64\n\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&cnt); err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job count\")\n\t\treturn nil, err\n\t}\n\n\tcount := int(cnt.Int64)\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = count\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = count\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddHistograms augments statistics with distribution histograms for job properties.\n//\n// Generates histogram data for visualization of job duration, node count, core count,\n// and accelerator count distributions. Duration histogram uses intelligent binning based\n// on the requested resolution.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply to jobs included in histograms\n// - stat: Statistics struct to augment (modified in-place)\n// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n//\n// Populates these fields in stat:\n// - HistDuration: Job duration distribution (zero-padded bins)\n// - HistNumNodes: Node count distribution\n// - HistNumCores: Core (hwthread) count distribution\n// - HistNumAccs: Accelerator count distribution\n//\n// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\nfunc (r *JobRepository) AddHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstat *model.JobsStatistics,\n\tdurationBins *string,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\tvar targetBinCount int\n\tvar targetBinSize int\n\tswitch *durationBins {\n\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n\t\ttargetBinCount = 60\n\t\ttargetBinSize = 60\n\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n\t\ttargetBinCount = 72\n\t\ttargetBinSize = 600\n\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n\t\ttargetBinCount = 48\n\t\ttargetBinSize = 3600\n\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n\t\ttargetBinCount = 12\n\t\ttargetBinSize = 21600\n\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n\t\ttargetBinCount = 14\n\t\ttargetBinSize = 43200\n\tdefault: // 24h\n\t\ttargetBinCount = 24\n\t\ttargetBinSize = 3600\n\t}\n\n\tvar err error\n\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n//\n// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n// and completed jobs differently: running jobs load data from metric backend, completed jobs\n// use footprint data from database.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply (MUST contain State filter for running jobs)\n// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n// - stat: Statistics struct to augment (modified in-place)\n// - targetBinCount: Number of histogram bins (default: 10)\n//\n// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n//\n// Binning algorithm:\n// - Values normalized to metric's peak value from cluster configuration\n// - Bins evenly distributed from 0 to peak\n// - Pre-initialized with zeros for consistent visualization\n//\n// Limitations:\n// - Running jobs: Limited to 5000 jobs for performance\n// - Requires valid cluster configuration with metric peak values\n// - Uses footprint statistic (avg/max/min) configured per metric\nfunc (r *JobRepository) AddMetricHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tmetrics []string,\n\tstat *model.JobsStatistics,\n\ttargetBinCount *int,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n\tfor _, f := range filter {\n\t\tif f.State != nil {\n\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\t\t\t\treturn stat, nil\n\t\t\t}\n\t\t}\n\t}\n\n\t// All other cases: Query and make bins in sqlite directly\n\tfor _, m := range metrics {\n\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n\t\t\tcontinue\n\t\t}\n\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n\t}\n\n\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n//\n// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n//\n// Parameters:\n// - value: SQL expression that produces the histogram value, aliased as \"value\"\n// - filters: Job filters to apply\n//\n// Returns histogram points with Value (from column) and Count (number of jobs).\nfunc (r *JobRepository) jobsStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tpoints := make([]*model.HistoPoint, 0)\n\t// is it possible to introduce zero values here? requires info about bincount\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tpoints = append(points, &point)\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n//\n// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n// histograms which only return bins with data. The value parameter should compute\n// the bin number from job duration.\n//\n// Parameters:\n// - value: SQL expression computing bin number from duration, aliased as \"value\"\n// - filters: Job filters to apply\n// - binSizeSeconds: Width of each bin in seconds\n// - targetBinCount: Number of bins to pre-initialize\n//\n// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n//\n// Algorithm:\n// 1. Pre-initialize targetBinCount bins with zero counts\n// 2. Query database for actual counts per bin\n// 3. Match query results to pre-initialized bins by value\n// 4. Bins without matches remain at zero\nfunc (r *JobRepository) jobsDurationStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n\tbinSizeSeconds int,\n\ttargetBinCount *int,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n\tpoints := make([]*model.HistoPoint, 0, *targetBinCount)\n\tfor i := 1; i <= *targetBinCount; i++ {\n\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n\t\tpoints = append(points, &point)\n\t}\n\n\t// Build a map from bin value (seconds) to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tbinMap[p.Value] = i\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Match query results to pre-initialized bins using map lookup.\n\t// point.Value from query is the bin number; multiply by binSizeSeconds to get bin key.\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif idx, ok := binMap[point.Value*binSizeSeconds]; ok {\n\t\t\tpoints[idx].Count = point.Count\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n//\n// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n// and computing bin assignments in SQL.\n//\n// Parameters:\n// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n// - filters: Job filters to apply\n// - bins: Number of bins to generate\n//\n// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n//\n// Algorithm:\n// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n// 3. Pre-initialize bins with min/max ranges based on peak value\n// 4. Query database for counts per bin\n// 5. Match results to pre-initialized bins\n//\n// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n// peak by 0.999999999 to avoid creating an extra bin.\nfunc (r *JobRepository) jobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetric string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) (*model.MetricHistoPoints, error) {\n\t// Peak value defines the upper bound for binning: values are distributed across\n\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n\t// scan all clusters to find the maximum peak value.\n\tvar metricConfig *schema.MetricConfig\n\tvar peak float64\n\tvar unit string\n\tvar footprintStat string\n\n\t// Try to get metric config from filtered cluster\n\tfor _, f := range filters {\n\t\tif f.Cluster != nil {\n\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\tpeak = metricConfig.Peak\n\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\tfootprintStat = metricConfig.Footprint\n\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n\t\t}\n\t}\n\n\t// If no cluster filter or peak not found, find largest peak across all clusters\n\t// This ensures histogram can accommodate all possible values\n\tif peak == 0.0 {\n\t\tfor _, c := range archive.Clusters {\n\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\tif m.Name == metric {\n\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t}\n\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t}\n\t\t\t\t\tif footprintStat == \"\" {\n\t\t\t\t\t\tfootprintStat = m.Footprint\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\t// Construct SQL histogram bins using normalized values.\n\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n\tstart := time.Now()\n\n\t// Bin calculation formula:\n\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n\t// Special case: value == peak would create bin N+1, so we test for equality\n\t// and multiply peak by 0.999999999 to force it into bin N.\n\tbinQuery := fmt.Sprintf(`CAST(\n\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n\t\t* %v as INTEGER )`,\n\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n\n\tmainQuery := sq.Select(\n\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n\t\t`count(*) as count`,\n\t).From(\"job\").Where(\n\t\t\"JSON_VALID(footprint)\",\n\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n\n\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tmainQuery = BuildWhereClause(f, mainQuery)\n\t}\n\n\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n\n\trows, err := mainQuery.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Pre-initialize bins with calculated min/max ranges.\n\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n\tpoints := make([]*model.MetricHistoPoint, 0, *bins)\n\tbinStep := int(peak) / *bins\n\tfor i := 1; i <= *bins; i++ {\n\t\tbinMin := (binStep * (i - 1))\n\t\tbinMax := (binStep * i)\n\t\tidx := i\n\t\tepoint := model.MetricHistoPoint{Bin: &idx, Count: 0, Min: &binMin, Max: &binMax}\n\t\tpoints = append(points, &epoint)\n\t}\n\n\t// Build a map from bin number to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tif p.Bin != nil {\n\t\t\tbinMap[*p.Bin] = i\n\t\t}\n\t}\n\n\t// Match query results to pre-initialized bins using map lookup.\n\tfor rows.Next() {\n\t\trpoint := model.MetricHistoPoint{}\n\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif rpoint.Bin != nil {\n\t\t\tif idx, ok := binMap[*rpoint.Bin]; ok {\n\t\t\t\tpoints[idx].Count = rpoint.Count\n\t\t\t}\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn &result, nil\n}\n\n// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n//\n// Unlike completed jobs which use footprint data from the database, running jobs require\n// fetching current metric averages from the metric backend (via metricdispatch).\n//\n// Parameters:\n// - metrics: List of metric names\n// - filters: Job filters (should filter to running jobs only)\n// - bins: Number of histogram bins\n//\n// Returns slice of MetricHistoPoints, one per metric.\n//\n// Limitations:\n// - Maximum 5000 jobs (returns nil if more jobs match)\n// - Requires metric backend availability\n// - Bins based on metric peak values from cluster configuration\n//\n// Algorithm:\n// 1. Query first 5001 jobs to check count limit\n// 2. Load metric averages for all jobs via metricdispatch\n// 3. For each metric, create bins based on peak value\n// 4. Iterate averages and count jobs per bin\nfunc (r *JobRepository) runningJobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetrics []string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) []*model.MetricHistoPoints {\n\t// Get Jobs\n\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n\t\treturn nil\n\t}\n\tif len(jobs) > 5000 {\n\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n\t\treturn nil\n\t}\n\n\t// Get AVGs from metric repo\n\tavgs := make([][]schema.Float, len(metrics))\n\tfor i := range avgs {\n\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n\t}\n\n\tfor _, job := range jobs {\n\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n\t\t\tcontinue\n\t\t}\n\n\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n\t\t\treturn nil\n\t\t}\n\t}\n\n\t// Iterate metrics to fill endresult\n\tdata := make([]*model.MetricHistoPoints, 0)\n\tfor idx, metric := range metrics {\n\t\t// Get specific Peak or largest Peak\n\t\tvar metricConfig *schema.MetricConfig\n\t\tvar peak float64\n\t\tvar unit string\n\n\t\tfor _, f := range filters {\n\t\t\tif f.Cluster != nil {\n\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\t\tpeak = metricConfig.Peak\n\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\t}\n\t\t}\n\n\t\tif peak == 0.0 {\n\t\t\tfor _, c := range archive.Clusters {\n\t\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\t\tif m.Name == metric {\n\t\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// Make and fill bins\n\t\tpeakBin := int(peak) / *bins\n\n\t\tpoints := make([]*model.MetricHistoPoint, 0)\n\t\tfor b := 0; b < *bins; b++ {\n\t\t\tcount := 0\n\t\t\tbindex := b + 1\n\t\t\tbmin := peakBin * b\n\t\t\tbmax := peakBin * (b + 1)\n\n\t\t\t// Iterate AVG values for indexed metric and count for bins\n\t\t\tfor _, val := range avgs[idx] {\n\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n\t\t\t\t\tcount += 1\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// Append Bin to Metric Result Array\n\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n\t\t\tpoints = append(points, &point)\n\t\t}\n\n\t\t// Append Metric Result Array to final results array\n\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n\t\tdata = append(data, &result)\n\t}\n\n\treturn data\n}\n","structuredPatch":[{"oldStart":55,"oldLines":6,"newStart":55,"newLines":7,"lines":[" cclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\""," \"github.com/ClusterCockpit/cc-lib/v2/schema\""," sq \"github.com/Masterminds/squirrel\"","+ \"golang.org/x/sync/errgroup\""," )"," "," // groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"0e037919-ff3a-40ad-92a5-ae71452dc934","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"18180edc-dbac-4031-afea-d6b8212ff2ed","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AKWtDviLW2M9zkNF5BKY1r","type":"message","role":"assistant","content":[{"type":"text","text":"Now replace the sequential histogram calls with parallel ones:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":518,"cache_read_input_tokens":86112,"cache_creation":{"ephemeral_5m_input_tokens":518,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19yBxrUUdRvoX6L1dNE","type":"assistant","uuid":"220a991e-e26f-4040-9ea2-9834aa852105","timestamp":"2026-03-13T13:26:19.141Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"220a991e-e26f-4040-9ea2-9834aa852105","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AKWtDviLW2M9zkNF5BKY1r","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BBxZWSii8bhD1q6UKReDX2","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go","old_string":"\tvar err error\n\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\treturn nil, err\n\t}","new_string":"\t// Run all 4 histogram queries in parallel — each writes a distinct struct field.\n\tg, gctx := errgroup.WithContext(ctx)\n\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(gctx, value, filter, targetBinSize, &targetBinCount)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(gctx, \"job.num_nodes as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumCores, err = r.jobsStatisticsHistogram(gctx, \"job.num_hwthreads as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(gctx, \"job.num_acc as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\t}\n\t\treturn err\n\t})\n\n\tif err := g.Wait(); err != nil {\n\t\treturn nil, err\n\t}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":518,"cache_read_input_tokens":86112,"output_tokens":1008,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":518},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19yBxrUUdRvoX6L1dNE","type":"assistant","uuid":"6f3e3876-3c98-41b5-b64a-64c6d537e940","timestamp":"2026-03-13T13:26:35.219Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"6f3e3876-3c98-41b5-b64a-64c6d537e940","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01BBxZWSii8bhD1q6UKReDX2","toolUseID":"toolu_01BBxZWSii8bhD1q6UKReDX2","timestamp":"2026-03-13T13:26:35.248Z","uuid":"8e20f7f2-24f9-4d71-b275-79561ea268d7","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"6f3e3876-3c98-41b5-b64a-64c6d537e940","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BBxZWSii8bhD1q6UKReDX2","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go has been updated successfully."}]},"uuid":"61223990-72cc-412c-a85d-bb62dd9936f9","timestamp":"2026-03-13T13:26:35.248Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go","oldString":"\tvar err error\n\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\treturn nil, err\n\t}","newString":"\t// Run all 4 histogram queries in parallel — each writes a distinct struct field.\n\tg, gctx := errgroup.WithContext(ctx)\n\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(gctx, value, filter, targetBinSize, &targetBinCount)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(gctx, \"job.num_nodes as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumCores, err = r.jobsStatisticsHistogram(gctx, \"job.num_hwthreads as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\t}\n\t\treturn err\n\t})\n\tg.Go(func() error {\n\t\tvar err error\n\t\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(gctx, \"job.num_acc as value\", filter)\n\t\tif err != nil {\n\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\t}\n\t\treturn err\n\t})\n\n\tif err := g.Wait(); err != nil {\n\t\treturn nil, err\n\t}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// This file contains job statistics and histogram generation functionality for the JobRepository.\n//\n// # Job Statistics\n//\n// The statistics methods provide aggregated metrics about jobs including total jobs, users,\n// walltime, and resource usage (nodes, cores, accelerators). Statistics can be computed:\n// - Overall (JobsStats): Single aggregate across all matching jobs\n// - Grouped (JobsStatsGrouped): Aggregated by user, project, cluster, or subcluster\n// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n//\n// All statistics methods support filtering via JobFilter and respect security contexts.\n//\n// # Histograms\n//\n// Histogram methods generate distribution data for visualization:\n// - Duration, nodes, cores, accelerators (AddHistograms)\n// - Job metrics like CPU load, memory usage (AddMetricHistograms)\n//\n// Histograms use intelligent binning:\n// - Duration: Variable bin sizes (1m, 10m, 1h, 6h, 12h, 24h) with zero-padding\n// - Resources: Natural value-based bins\n// - Metrics: Normalized to peak values with configurable bin counts\n//\n// # Running vs. Completed Jobs\n//\n// Statistics handle running jobs specially:\n// - Duration calculated as (now - start_time) for running jobs\n// - Metric histograms for running jobs load data from metric backend instead of footprint\n// - Job state filtering distinguishes running/completed jobs\n//\n// # Performance Considerations\n//\n// - All queries use prepared statements via stmtCache\n// - Complex aggregations use SQL for efficiency\n// - Histogram pre-initialization ensures consistent bin ranges\n// - Metric histogram queries limited to 5000 jobs for running job analysis\n\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"fmt\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\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/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"golang.org/x/sync/errgroup\"\n)\n\n// groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names.\n// Used by JobsStatsGrouped and JobCountGrouped to translate user-facing grouping dimensions\n// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\nvar groupBy2column = map[model.Aggregate]string{\n\tmodel.AggregateUser: \"job.hpc_user\",\n\tmodel.AggregateProject: \"job.project\",\n\tmodel.AggregateCluster: \"job.cluster\",\n\tmodel.AggregateSubcluster: \"job.subcluster\",\n}\n\n// sortBy2column maps GraphQL SortByAggregate enum values to their corresponding computed column names.\n// Used by JobsStatsGrouped to translate sort preferences into SQL ORDER BY clauses.\n// Column names match the AS aliases used in buildStatsQuery.\nvar sortBy2column = map[model.SortByAggregate]string{\n\tmodel.SortByAggregateTotaljobs: \"totalJobs\",\n\tmodel.SortByAggregateTotalusers: \"totalUsers\",\n\tmodel.SortByAggregateTotalwalltime: \"totalWalltime\",\n\tmodel.SortByAggregateTotalnodes: \"totalNodes\",\n\tmodel.SortByAggregateTotalnodehours: \"totalNodeHours\",\n\tmodel.SortByAggregateTotalcores: \"totalCores\",\n\tmodel.SortByAggregateTotalcorehours: \"totalCoreHours\",\n\tmodel.SortByAggregateTotalaccs: \"totalAccs\",\n\tmodel.SortByAggregateTotalacchours: \"totalAccHours\",\n}\n\n// buildCountQuery constructs a SQL query to count jobs with optional grouping and filtering.\n//\n// Parameters:\n// - filter: Job filters to apply (cluster, user, time range, etc.)\n// - kind: Special filter - \"running\" for running jobs only, \"short\" for jobs under threshold\n// - col: Column name to GROUP BY; empty string for total count without grouping\n//\n// Returns a SelectBuilder that produces either:\n// - Single count: COUNT(job.id) when col is empty\n// - Grouped counts: col, COUNT(job.id) when col is specified\n//\n// The kind parameter enables counting specific job categories:\n// - \"running\": Only jobs with job_state = 'running'\n// - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n// - empty: All jobs matching filters\nfunc (r *JobRepository) buildCountQuery(\n\tfilter []*model.JobFilter,\n\tkind string,\n\tcol string,\n) sq.SelectBuilder {\n\tvar query sq.SelectBuilder\n\n\tif col != \"\" {\n\t\tquery = sq.Select(col, \"COUNT(*)\").From(\"job\").GroupBy(col)\n\t} else {\n\t\tquery = sq.Select(\"COUNT(*)\").From(\"job\")\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n\tcase \"short\":\n\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n\t}\n\n\tfor _, f := range filter {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\treturn query\n}\n\n// buildStatsQuery constructs a SQL query to compute job statistics with optional grouping.\n// Only requested columns are computed; unrequested columns select 0 as placeholder.\n//\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\") && col != \"job.hpc_user\" {\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}\n\n// JobsStatsGrouped computes job statistics grouped by a dimension (user, project, cluster, or subcluster).\n// Only columns listed in reqFields are computed; others return 0. User display names are looked up\n// in a separate lightweight query to avoid JOIN overhead on the main aggregation.\nfunc (r *JobRepository) JobsStatsGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tpage *model.PageRequest,\n\tsortBy *model.SortByAggregate,\n\tgroupBy *model.Aggregate,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildStatsQuery(filter, col, config.Keys.ShortRunningJobsDuration, reqFields)\n\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif sortBy != nil {\n\t\tsortBy := sortBy2column[*sortBy]\n\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n\t}\n\tif page != nil && page.ItemsPerPage != -1 {\n\t\tlimit := uint64(page.ItemsPerPage)\n\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n\t}\n\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\t\tif err := rows.Scan(&id, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\t\tTotalNodes: int(nodes.Int64),\n\t\t\t\t\tTotalNodeHours: int(nodeHours.Int64),\n\t\t\t\t\tTotalCores: int(cores.Int64),\n\t\t\t\t\tTotalCoreHours: int(coreHours.Int64),\n\t\t\t\t\tTotalAccs: int(accs.Int64),\n\t\t\t\t\tTotalAccHours: int(accHours.Int64),\n\t\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\t// Post-query name lookup for user grouping (avoids LEFT JOIN on aggregation query)\n\tif col == \"job.hpc_user\" && len(stats) > 0 {\n\t\tusernames := make([]any, len(stats))\n\t\tfor i, s := range stats {\n\t\t\tusernames[i] = s.ID\n\t\t}\n\n\t\tnameQuery := sq.Select(\"username\", \"name\").From(\"hpc_user\").Where(sq.Eq{\"username\": usernames})\n\t\tnameRows, err := nameQuery.RunWith(r.DB).QueryContext(ctx)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error looking up user names: %s\", err.Error())\n\t\t\t// Non-fatal: stats are still valid without display names\n\t\t} else {\n\t\t\tdefer nameRows.Close()\n\t\t\tnameMap := make(map[string]string, len(stats))\n\t\t\tfor nameRows.Next() {\n\t\t\t\tvar username, name string\n\t\t\t\tif err := nameRows.Scan(&username, &name); err == nil {\n\t\t\t\t\tnameMap[username] = name\n\t\t\t\t}\n\t\t\t}\n\t\t\tfor _, s := range stats {\n\t\t\t\tif name, ok := nameMap[s.ID]; ok {\n\t\t\t\t\ts.Name = name\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\treturn stats, nil\n}\n\n// JobsStats computes overall job statistics across all matching jobs without grouping.\n//\n// This method provides a single aggregate view of job metrics, useful for dashboard\n// summaries and overall system utilization reports.\n//\n// Parameters:\n// - ctx: Context for security checks and cancellation\n// - filter: Filters to apply (time range, cluster, job state, etc.)\n//\n// Returns a single-element slice containing aggregate statistics:\n// - totalJobs, totalUsers, totalWalltime\n// - totalNodeHours, totalCoreHours, totalAccHours\n//\n// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n// Security checks are applied via SecurityCheck to respect user access levels.\nfunc (r *JobRepository) JobsStats(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\treqFields map[string]bool,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildStatsQuery(filter, \"\", config.Keys.ShortRunningJobsDuration, reqFields)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\trow := query.RunWith(r.DB).QueryRowContext(ctx)\n\tstats := make([]*model.JobsStatistics, 0, 1)\n\n\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n\t\tcclog.Warn(\"Error while scanning rows\")\n\t\treturn nil, err\n\t}\n\n\tif jobs.Valid {\n\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n\n\t\tif nodeHours.Valid {\n\t\t\ttotalNodeHours = int(nodeHours.Int64)\n\t\t}\n\t\tif coreHours.Valid {\n\t\t\ttotalCoreHours = int(coreHours.Int64)\n\t\t}\n\t\tif accHours.Valid {\n\t\t\ttotalAccHours = int(accHours.Int64)\n\t\t}\n\t\tstats = append(stats,\n\t\t\t&model.JobsStatistics{\n\t\t\t\tTotalJobs: int(jobs.Int64),\n\t\t\t\tTotalUsers: int(users.Int64),\n\t\t\t\tTotalWalltime: int(walltime.Int64),\n\t\t\t\tTotalNodeHours: totalNodeHours,\n\t\t\t\tTotalCoreHours: totalCoreHours,\n\t\t\t\tTotalAccHours: totalAccHours,\n\t\t\t\tRunningJobs: int(runningJobs.Int64),\n\t\t\t\tShortJobs: int(shortJobs.Int64),\n\t\t\t})\n\t}\n\n\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n// Returns 0.0 if the metric is not found or statType is invalid.\n//\n// Parameters:\n// - job: Job struct with populated Statistics field\n// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n//\n// Returns the requested statistic value or 0.0 if not found.\nfunc LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n\tif stats, ok := job.Statistics[metric]; ok {\n\t\tswitch statType {\n\t\tcase \"avg\":\n\t\t\treturn stats.Avg\n\t\tcase \"max\":\n\t\t\treturn stats.Max\n\t\tcase \"min\":\n\t\t\treturn stats.Min\n\t\tdefault:\n\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n\t\t}\n\t}\n\n\treturn 0.0\n}\n\n// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n//\n// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n// avoiding the overhead of calculating walltime and resource usage metrics.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n//\n// Returns JobsStatistics with only ID and TotalJobs populated for each group.\nfunc (r *JobRepository) JobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, \"\", col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tstats := make([]*model.JobsStatistics, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tstats = append(stats,\n\t\t\t\t&model.JobsStatistics{\n\t\t\t\t\tID: id.String,\n\t\t\t\t\tTotalJobs: int(cnt.Int64),\n\t\t\t\t})\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCountGrouped augments existing statistics with additional job counts by category.\n//\n// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n// - stats: Existing statistics to augment (modified in-place by ID matching)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n// Groups without matching jobs will have 0 for the added field.\nfunc (r *JobRepository) AddJobCountGrouped(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tgroupBy *model.Aggregate,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tcol := groupBy2column[*groupBy]\n\tquery := r.buildCountQuery(filter, kind, col)\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tcounts := make(map[string]int)\n\n\tfor rows.Next() {\n\t\tvar id sql.NullString\n\t\tvar cnt sql.NullInt64\n\t\tif err := rows.Scan(&id, &cnt); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\t\tif id.Valid {\n\t\t\tcounts[id.String] = int(cnt.Int64)\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = counts[s.ID]\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = counts[s.ID]\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddJobCount augments existing overall statistics with additional job counts by category.\n//\n// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n// to all statistics entries (typically just one).\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply\n// - stats: Existing statistics to augment (modified in-place)\n// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n//\n// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\nfunc (r *JobRepository) AddJobCount(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstats []*model.JobsStatistics,\n\tkind string,\n) ([]*model.JobsStatistics, error) {\n\tstart := time.Now()\n\tquery := r.buildCountQuery(filter, kind, \"\")\n\tquery, err := SecurityCheck(ctx, query)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tvar cnt sql.NullInt64\n\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&cnt); err != nil {\n\t\tcclog.Warn(\"Error while querying DB for job count\")\n\t\treturn nil, err\n\t}\n\n\tcount := int(cnt.Int64)\n\n\tswitch kind {\n\tcase \"running\":\n\t\tfor _, s := range stats {\n\t\t\ts.RunningJobs = count\n\t\t}\n\tcase \"short\":\n\t\tfor _, s := range stats {\n\t\t\ts.ShortJobs = count\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n\treturn stats, nil\n}\n\n// AddHistograms augments statistics with distribution histograms for job properties.\n//\n// Generates histogram data for visualization of job duration, node count, core count,\n// and accelerator count distributions. Duration histogram uses intelligent binning based\n// on the requested resolution.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply to jobs included in histograms\n// - stat: Statistics struct to augment (modified in-place)\n// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n//\n// Populates these fields in stat:\n// - HistDuration: Job duration distribution (zero-padded bins)\n// - HistNumNodes: Node count distribution\n// - HistNumCores: Core (hwthread) count distribution\n// - HistNumAccs: Accelerator count distribution\n//\n// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\nfunc (r *JobRepository) AddHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tstat *model.JobsStatistics,\n\tdurationBins *string,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\tvar targetBinCount int\n\tvar targetBinSize int\n\tswitch *durationBins {\n\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n\t\ttargetBinCount = 60\n\t\ttargetBinSize = 60\n\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n\t\ttargetBinCount = 72\n\t\ttargetBinSize = 600\n\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n\t\ttargetBinCount = 48\n\t\ttargetBinSize = 3600\n\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n\t\ttargetBinCount = 12\n\t\ttargetBinSize = 21600\n\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n\t\ttargetBinCount = 14\n\t\ttargetBinSize = 43200\n\tdefault: // 24h\n\t\ttargetBinCount = 24\n\t\ttargetBinSize = 3600\n\t}\n\n\tvar err error\n\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n\t\treturn nil, err\n\t}\n\n\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n//\n// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n// and completed jobs differently: running jobs load data from metric backend, completed jobs\n// use footprint data from database.\n//\n// Parameters:\n// - ctx: Context for security checks\n// - filter: Filters to apply (MUST contain State filter for running jobs)\n// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n// - stat: Statistics struct to augment (modified in-place)\n// - targetBinCount: Number of histogram bins (default: 10)\n//\n// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n//\n// Binning algorithm:\n// - Values normalized to metric's peak value from cluster configuration\n// - Bins evenly distributed from 0 to peak\n// - Pre-initialized with zeros for consistent visualization\n//\n// Limitations:\n// - Running jobs: Limited to 5000 jobs for performance\n// - Requires valid cluster configuration with metric peak values\n// - Uses footprint statistic (avg/max/min) configured per metric\nfunc (r *JobRepository) AddMetricHistograms(\n\tctx context.Context,\n\tfilter []*model.JobFilter,\n\tmetrics []string,\n\tstat *model.JobsStatistics,\n\ttargetBinCount *int,\n) (*model.JobsStatistics, error) {\n\tstart := time.Now()\n\n\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n\tfor _, f := range filter {\n\t\tif f.State != nil {\n\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\t\t\t\treturn stat, nil\n\t\t\t}\n\t\t}\n\t}\n\n\t// All other cases: Query and make bins in sqlite directly\n\tfor _, m := range metrics {\n\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n\t\t\tcontinue\n\t\t}\n\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n\t}\n\n\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n\treturn stat, nil\n}\n\n// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n//\n// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n//\n// Parameters:\n// - value: SQL expression that produces the histogram value, aliased as \"value\"\n// - filters: Job filters to apply\n//\n// Returns histogram points with Value (from column) and Count (number of jobs).\nfunc (r *JobRepository) jobsStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tpoints := make([]*model.HistoPoint, 0)\n\t// is it possible to introduce zero values here? requires info about bincount\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tpoints = append(points, &point)\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n//\n// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n// histograms which only return bins with data. The value parameter should compute\n// the bin number from job duration.\n//\n// Parameters:\n// - value: SQL expression computing bin number from duration, aliased as \"value\"\n// - filters: Job filters to apply\n// - binSizeSeconds: Width of each bin in seconds\n// - targetBinCount: Number of bins to pre-initialize\n//\n// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n//\n// Algorithm:\n// 1. Pre-initialize targetBinCount bins with zero counts\n// 2. Query database for actual counts per bin\n// 3. Match query results to pre-initialized bins by value\n// 4. Bins without matches remain at zero\nfunc (r *JobRepository) jobsDurationStatisticsHistogram(\n\tctx context.Context,\n\tvalue string,\n\tfilters []*model.JobFilter,\n\tbinSizeSeconds int,\n\ttargetBinCount *int,\n) ([]*model.HistoPoint, error) {\n\tstart := time.Now()\n\tquery, qerr := SecurityCheck(ctx,\n\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n\tpoints := make([]*model.HistoPoint, 0, *targetBinCount)\n\tfor i := 1; i <= *targetBinCount; i++ {\n\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n\t\tpoints = append(points, &point)\n\t}\n\n\t// Build a map from bin value (seconds) to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tbinMap[p.Value] = i\n\t}\n\n\tfor _, f := range filters {\n\t\tquery = BuildWhereClause(f, query)\n\t}\n\n\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Error(\"Error while running query\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Match query results to pre-initialized bins using map lookup.\n\t// point.Value from query is the bin number; multiply by binSizeSeconds to get bin key.\n\tfor rows.Next() {\n\t\tpoint := model.HistoPoint{}\n\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning rows\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif idx, ok := binMap[point.Value*binSizeSeconds]; ok {\n\t\t\tpoints[idx].Count = point.Count\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn points, nil\n}\n\n// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n//\n// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n// and computing bin assignments in SQL.\n//\n// Parameters:\n// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n// - filters: Job filters to apply\n// - bins: Number of bins to generate\n//\n// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n//\n// Algorithm:\n// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n// 3. Pre-initialize bins with min/max ranges based on peak value\n// 4. Query database for counts per bin\n// 5. Match results to pre-initialized bins\n//\n// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n// peak by 0.999999999 to avoid creating an extra bin.\nfunc (r *JobRepository) jobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetric string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) (*model.MetricHistoPoints, error) {\n\t// Peak value defines the upper bound for binning: values are distributed across\n\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n\t// scan all clusters to find the maximum peak value.\n\tvar metricConfig *schema.MetricConfig\n\tvar peak float64\n\tvar unit string\n\tvar footprintStat string\n\n\t// Try to get metric config from filtered cluster\n\tfor _, f := range filters {\n\t\tif f.Cluster != nil {\n\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\tpeak = metricConfig.Peak\n\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\tfootprintStat = metricConfig.Footprint\n\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n\t\t}\n\t}\n\n\t// If no cluster filter or peak not found, find largest peak across all clusters\n\t// This ensures histogram can accommodate all possible values\n\tif peak == 0.0 {\n\t\tfor _, c := range archive.Clusters {\n\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\tif m.Name == metric {\n\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t}\n\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t}\n\t\t\t\t\tif footprintStat == \"\" {\n\t\t\t\t\t\tfootprintStat = m.Footprint\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\n\t// Construct SQL histogram bins using normalized values.\n\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n\tstart := time.Now()\n\n\t// Bin calculation formula:\n\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n\t// Special case: value == peak would create bin N+1, so we test for equality\n\t// and multiply peak by 0.999999999 to force it into bin N.\n\tbinQuery := fmt.Sprintf(`CAST(\n\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n\t\t* %v as INTEGER )`,\n\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n\n\tmainQuery := sq.Select(\n\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n\t\t`count(*) as count`,\n\t).From(\"job\").Where(\n\t\t\"JSON_VALID(footprint)\",\n\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n\n\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n\tif qerr != nil {\n\t\treturn nil, qerr\n\t}\n\n\tfor _, f := range filters {\n\t\tmainQuery = BuildWhereClause(f, mainQuery)\n\t}\n\n\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n\n\trows, err := mainQuery.RunWith(r.DB).QueryContext(ctx)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\t// Pre-initialize bins with calculated min/max ranges.\n\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n\tpoints := make([]*model.MetricHistoPoint, 0, *bins)\n\tbinStep := int(peak) / *bins\n\tfor i := 1; i <= *bins; i++ {\n\t\tbinMin := (binStep * (i - 1))\n\t\tbinMax := (binStep * i)\n\t\tidx := i\n\t\tepoint := model.MetricHistoPoint{Bin: &idx, Count: 0, Min: &binMin, Max: &binMax}\n\t\tpoints = append(points, &epoint)\n\t}\n\n\t// Build a map from bin number to slice index for O(1) lookup.\n\tbinMap := make(map[int]int, len(points))\n\tfor i, p := range points {\n\t\tif p.Bin != nil {\n\t\t\tbinMap[*p.Bin] = i\n\t\t}\n\t}\n\n\t// Match query results to pre-initialized bins using map lookup.\n\tfor rows.Next() {\n\t\trpoint := model.MetricHistoPoint{}\n\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif rpoint.Bin != nil {\n\t\t\tif idx, ok := binMap[*rpoint.Bin]; ok {\n\t\t\t\tpoints[idx].Count = rpoint.Count\n\t\t\t}\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n\n\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n\treturn &result, nil\n}\n\n// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n//\n// Unlike completed jobs which use footprint data from the database, running jobs require\n// fetching current metric averages from the metric backend (via metricdispatch).\n//\n// Parameters:\n// - metrics: List of metric names\n// - filters: Job filters (should filter to running jobs only)\n// - bins: Number of histogram bins\n//\n// Returns slice of MetricHistoPoints, one per metric.\n//\n// Limitations:\n// - Maximum 5000 jobs (returns nil if more jobs match)\n// - Requires metric backend availability\n// - Bins based on metric peak values from cluster configuration\n//\n// Algorithm:\n// 1. Query first 5001 jobs to check count limit\n// 2. Load metric averages for all jobs via metricdispatch\n// 3. For each metric, create bins based on peak value\n// 4. Iterate averages and count jobs per bin\nfunc (r *JobRepository) runningJobsMetricStatisticsHistogram(\n\tctx context.Context,\n\tmetrics []string,\n\tfilters []*model.JobFilter,\n\tbins *int,\n) []*model.MetricHistoPoints {\n\t// Get Jobs\n\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n\t\treturn nil\n\t}\n\tif len(jobs) > 5000 {\n\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n\t\treturn nil\n\t}\n\n\t// Get AVGs from metric repo\n\tavgs := make([][]schema.Float, len(metrics))\n\tfor i := range avgs {\n\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n\t}\n\n\tfor _, job := range jobs {\n\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n\t\t\tcontinue\n\t\t}\n\n\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n\t\t\treturn nil\n\t\t}\n\t}\n\n\t// Iterate metrics to fill endresult\n\tdata := make([]*model.MetricHistoPoints, 0)\n\tfor idx, metric := range metrics {\n\t\t// Get specific Peak or largest Peak\n\t\tvar metricConfig *schema.MetricConfig\n\t\tvar peak float64\n\t\tvar unit string\n\n\t\tfor _, f := range filters {\n\t\t\tif f.Cluster != nil {\n\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n\t\t\t\tpeak = metricConfig.Peak\n\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n\t\t\t}\n\t\t}\n\n\t\tif peak == 0.0 {\n\t\t\tfor _, c := range archive.Clusters {\n\t\t\t\tfor _, m := range c.MetricConfig {\n\t\t\t\t\tif m.Name == metric {\n\t\t\t\t\t\tif m.Peak > peak {\n\t\t\t\t\t\t\tpeak = m.Peak\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif unit == \"\" {\n\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// Make and fill bins\n\t\tpeakBin := int(peak) / *bins\n\n\t\tpoints := make([]*model.MetricHistoPoint, 0)\n\t\tfor b := 0; b < *bins; b++ {\n\t\t\tcount := 0\n\t\t\tbindex := b + 1\n\t\t\tbmin := peakBin * b\n\t\t\tbmax := peakBin * (b + 1)\n\n\t\t\t// Iterate AVG values for indexed metric and count for bins\n\t\t\tfor _, val := range avgs[idx] {\n\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n\t\t\t\t\tcount += 1\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// Append Bin to Metric Result Array\n\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n\t\t\tpoints = append(points, &point)\n\t\t}\n\n\t\t// Append Metric Result Array to final results array\n\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n\t\tdata = append(data, &result)\n\t}\n\n\treturn data\n}\n","structuredPatch":[{"oldStart":641,"oldLines":33,"newStart":641,"newLines":48,"lines":[" targetBinSize = 3600"," }"," ","- var err error","- // Return X-Values always as seconds, will be formatted into minutes and hours in frontend","+ // Run all 4 histogram queries in parallel — each writes a distinct struct field.","+ g, gctx := errgroup.WithContext(ctx)","+"," value := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)","- stat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)","- if err != nil {","- cclog.Warn(\"Error while loading job statistics histogram: job duration\")","- return nil, err","- }"," ","- stat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)","- if err != nil {","- cclog.Warn(\"Error while loading job statistics histogram: num nodes\")","- return nil, err","- }","+ g.Go(func() error {","+ var err error","+ stat.HistDuration, err = r.jobsDurationStatisticsHistogram(gctx, value, filter, targetBinSize, &targetBinCount)","+ if err != nil {","+ cclog.Warn(\"Error while loading job statistics histogram: job duration\")","+ }","+ return err","+ })","+ g.Go(func() error {","+ var err error","+ stat.HistNumNodes, err = r.jobsStatisticsHistogram(gctx, \"job.num_nodes as value\", filter)","+ if err != nil {","+ cclog.Warn(\"Error while loading job statistics histogram: num nodes\")","+ }","+ return err","+ })","+ g.Go(func() error {","+ var err error","+ stat.HistNumCores, err = r.jobsStatisticsHistogram(gctx, \"job.num_hwthreads as value\", filter)","+ if err != nil {","+ cclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")","+ }","+ return err","+ })","+ g.Go(func() error {","+ var err error","+ stat.HistNumAccs, err = r.jobsStatisticsHistogram(gctx, \"job.num_acc as value\", filter)","+ if err != nil {","+ cclog.Warn(\"Error while loading job statistics histogram: num acc\")","+ }","+ return err","+ })"," ","- stat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)","- if err != nil {","- cclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")","+ if err := g.Wait(); err != nil {"," return nil, err"," }"," ","- stat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)","- if err != nil {","- cclog.Warn(\"Error while loading job statistics histogram: num acc\")","- return nil, err","- }","-"," cclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))"," return stat, nil"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"6f3e3876-3c98-41b5-b64a-64c6d537e940","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"61223990-72cc-412c-a85d-bb62dd9936f9","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_017163t2tE4E7gxDMFD9oMLg","type":"message","role":"assistant","content":[{"type":"text","text":"The LSP says errgroup is unused but it should be used by the code I just added. Let me run `go mod tidy` and verify compilation:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1162,"cache_read_input_tokens":86630,"cache_creation":{"ephemeral_5m_input_tokens":1162,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19zbXiRYsQfm1yc8txp","type":"assistant","uuid":"4d84dd1b-9ff6-42a9-9c2b-a2453ff49e72","timestamp":"2026-03-13T13:26:39.269Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"4d84dd1b-9ff6-42a9-9c2b-a2453ff49e72","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_017163t2tE4E7gxDMFD9oMLg","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Rw7skoVoDUZGtMQMNpMT2w","name":"Bash","input":{"command":"go mod tidy 2>&1","description":"Tidy go modules"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1162,"cache_read_input_tokens":86630,"output_tokens":133,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1162},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19zbXiRYsQfm1yc8txp","type":"assistant","uuid":"6a8b9cf3-a221-4cf5-b01c-71e62675622d","timestamp":"2026-03-13T13:26:39.718Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"6a8b9cf3-a221-4cf5-b01c-71e62675622d","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Rw7skoVoDUZGtMQMNpMT2w","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"uuid":"48f1c453-5abc-404d-a54a-10c240c7de17","timestamp":"2026-03-13T13:26:39.975Z","toolUseResult":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"6a8b9cf3-a221-4cf5-b01c-71e62675622d","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"48f1c453-5abc-404d-a54a-10c240c7de17","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Q2Y5cQd61W7EwmSMHAmsoD","type":"message","role":"assistant","content":[{"type":"text","text":"**Change 4: Frontend consolidated query**\n\nNow update the UsageDash.svelte to use 2 aliases instead of 6:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":132,"cache_read_input_tokens":87792,"cache_creation":{"ephemeral_5m_input_tokens":132,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19zwH7SVwnw9hgta1pN","type":"assistant","uuid":"ca0e02b0-1771-4fd7-9271-cca56552cd1d","timestamp":"2026-03-13T13:26:43.648Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"ca0e02b0-1771-4fd7-9271-cca56552cd1d","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Q2Y5cQd61W7EwmSMHAmsoD","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CwcFBCq4WgLeXJHwPGskj3","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","old_string":" const topStatsQuery = $derived(\n loadMe\n ? queryStore({\n client: client,\n query: gql`\n query ($filter: [JobFilter!]!, $paging: PageRequest!) {\n topUserJobs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALJOBS\n groupBy: USER\n ) {\n id\n name\n totalJobs\n }\n topProjectJobs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALJOBS\n groupBy: PROJECT\n ) {\n id\n totalJobs\n }\n topUserNodes: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALNODES\n groupBy: USER\n ) {\n id\n name\n totalNodes\n }\n topProjectNodes: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALNODES\n groupBy: PROJECT\n ) {\n id\n totalNodes\n }\n topUserAccs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALACCS\n groupBy: USER\n ) {\n id\n name\n totalAccs\n }\n topProjectAccs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALACCS\n groupBy: PROJECT\n ) {\n id\n totalAccs\n }\n }\n `,\n variables: {\n filter: statusFilter,\n paging: pagingState, // Top 10\n },\n requestPolicy: \"network-only\",\n })\n : null,\n );","new_string":" const topStatsQuery = $derived(\n loadMe\n ? queryStore({\n client: client,\n query: gql`\n query ($filter: [JobFilter!]!) {\n allUsers: jobsStatistics(\n filter: $filter\n groupBy: USER\n ) {\n id\n name\n totalJobs\n totalNodes\n totalAccs\n }\n allProjects: jobsStatistics(\n filter: $filter\n groupBy: PROJECT\n ) {\n id\n totalJobs\n totalNodes\n totalAccs\n }\n }\n `,\n variables: {\n filter: statusFilter,\n },\n requestPolicy: \"network-only\",\n })\n : null,\n );\n\n // Sort + slice top-10 from the full results in the frontend\n const topUserJobs = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalJobs - a.totalJobs)\n .slice(0, 10) ?? [],\n );\n const topProjectJobs = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalJobs - a.totalJobs)\n .slice(0, 10) ?? [],\n );\n const topUserNodes = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalNodes - a.totalNodes)\n .slice(0, 10) ?? [],\n );\n const topProjectNodes = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalNodes - a.totalNodes)\n .slice(0, 10) ?? [],\n );\n const topUserAccs = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalAccs - a.totalAccs)\n .slice(0, 10) ?? [],\n );\n const topProjectAccs = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalAccs - a.totalAccs)\n .slice(0, 10) ?? [],\n );"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":132,"cache_read_input_tokens":87792,"output_tokens":1197,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":132},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ19zwH7SVwnw9hgta1pN","type":"assistant","uuid":"a36a94c9-929c-424a-b35a-b5d956132a5b","timestamp":"2026-03-13T13:26:55.968Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"type":"file-history-snapshot","messageId":"a36a94c9-929c-424a-b35a-b5d956132a5b","snapshot":{"messageId":"0dd2f17c-9b90-4281-95e5-a244d3659bb9","trackedFileBackups":{"internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:24:36.210Z"},"internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:24:37.402Z"},"internal/repository/migration.go":{"backupFileName":"19a8f1f6575af1e7@v1","version":1,"backupTime":"2026-03-13T13:24:44.807Z"},"internal/repository/jobQuery.go":{"backupFileName":"c64bb1bbdfcfaab5@v1","version":1,"backupTime":"2026-03-13T13:24:51.178Z"},"internal/graph/stats_cache.go":{"backupFileName":null,"version":1,"backupTime":"2026-03-13T13:25:03.452Z"},"cmd/cc-backend/server.go":{"backupFileName":"52a9e99169bfa641@v1","version":1,"backupTime":"2026-03-13T13:25:09.393Z"},"internal/graph/schema.resolvers.go":{"backupFileName":"117e2419c7a90363@v1","version":1,"backupTime":"2026-03-13T13:25:41.602Z"},"internal/repository/stats.go":{"backupFileName":"37b1ab532d191fe8@v1","version":1,"backupTime":"2026-03-13T13:26:16.258Z"},"web/frontend/src/status/dashdetails/UsageDash.svelte":{"backupFileName":"0992f74d3d8ab349@v1","version":1,"backupTime":"2026-03-13T13:26:55.999Z"}},"timestamp":"2026-03-13T13:23:59.403Z"},"isSnapshotUpdate":true} +{"parentUuid":"a36a94c9-929c-424a-b35a-b5d956132a5b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01CwcFBCq4WgLeXJHwPGskj3","toolUseID":"toolu_01CwcFBCq4WgLeXJHwPGskj3","timestamp":"2026-03-13T13:26:56.002Z","uuid":"6c61ab56-2675-4f57-8ed3-df99e5e9ebdb","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a36a94c9-929c-424a-b35a-b5d956132a5b","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CwcFBCq4WgLeXJHwPGskj3","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated successfully."}]},"uuid":"a02e96ec-1ecc-473d-9605-dddd28731c35","timestamp":"2026-03-13T13:26:56.002Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":" const topStatsQuery = $derived(\n loadMe\n ? queryStore({\n client: client,\n query: gql`\n query ($filter: [JobFilter!]!, $paging: PageRequest!) {\n topUserJobs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALJOBS\n groupBy: USER\n ) {\n id\n name\n totalJobs\n }\n topProjectJobs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALJOBS\n groupBy: PROJECT\n ) {\n id\n totalJobs\n }\n topUserNodes: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALNODES\n groupBy: USER\n ) {\n id\n name\n totalNodes\n }\n topProjectNodes: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALNODES\n groupBy: PROJECT\n ) {\n id\n totalNodes\n }\n topUserAccs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALACCS\n groupBy: USER\n ) {\n id\n name\n totalAccs\n }\n topProjectAccs: jobsStatistics(\n filter: $filter\n page: $paging\n sortBy: TOTALACCS\n groupBy: PROJECT\n ) {\n id\n totalAccs\n }\n }\n `,\n variables: {\n filter: statusFilter,\n paging: pagingState, // Top 10\n },\n requestPolicy: \"network-only\",\n })\n : null,\n );","newString":" const topStatsQuery = $derived(\n loadMe\n ? queryStore({\n client: client,\n query: gql`\n query ($filter: [JobFilter!]!) {\n allUsers: jobsStatistics(\n filter: $filter\n groupBy: USER\n ) {\n id\n name\n totalJobs\n totalNodes\n totalAccs\n }\n allProjects: jobsStatistics(\n filter: $filter\n groupBy: PROJECT\n ) {\n id\n totalJobs\n totalNodes\n totalAccs\n }\n }\n `,\n variables: {\n filter: statusFilter,\n },\n requestPolicy: \"network-only\",\n })\n : null,\n );\n\n // Sort + slice top-10 from the full results in the frontend\n const topUserJobs = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalJobs - a.totalJobs)\n .slice(0, 10) ?? [],\n );\n const topProjectJobs = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalJobs - a.totalJobs)\n .slice(0, 10) ?? [],\n );\n const topUserNodes = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalNodes - a.totalNodes)\n .slice(0, 10) ?? [],\n );\n const topProjectNodes = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalNodes - a.totalNodes)\n .slice(0, 10) ?? [],\n );\n const topUserAccs = $derived(\n $topStatsQuery?.data?.allUsers\n ?.toSorted((a, b) => b.totalAccs - a.totalAccs)\n .slice(0, 10) ?? [],\n );\n const topProjectAccs = $derived(\n $topStatsQuery?.data?.allProjects\n ?.toSorted((a, b) => b.totalAccs - a.totalAccs)\n .slice(0, 10) ?? [],\n );","originalFile":"\n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":71,"oldLines":75,"newStart":71,"newLines":68,"lines":[" ? queryStore({"," client: client,"," query: gql`","- query ($filter: [JobFilter!]!, $paging: PageRequest!) {","- topUserJobs: jobsStatistics(","+ query ($filter: [JobFilter!]!) {","+ allUsers: jobsStatistics("," filter: $filter","- page: $paging","- sortBy: TOTALJOBS"," groupBy: USER"," ) {"," id"," name"," totalJobs","+ totalNodes","+ totalAccs"," }","- topProjectJobs: jobsStatistics(","+ allProjects: jobsStatistics("," filter: $filter","- page: $paging","- sortBy: TOTALJOBS"," groupBy: PROJECT"," ) {"," id"," totalJobs","- }","- topUserNodes: jobsStatistics(","- filter: $filter","- page: $paging","- sortBy: TOTALNODES","- groupBy: USER","- ) {","- id","- name"," totalNodes","- }","- topProjectNodes: jobsStatistics(","- filter: $filter","- page: $paging","- sortBy: TOTALNODES","- groupBy: PROJECT","- ) {","- id","- totalNodes","- }","- topUserAccs: jobsStatistics(","- filter: $filter","- page: $paging","- sortBy: TOTALACCS","- groupBy: USER","- ) {","- id","- name"," totalAccs"," }","- topProjectAccs: jobsStatistics(","- filter: $filter","- page: $paging","- sortBy: TOTALACCS","- groupBy: PROJECT","- ) {","- id","- totalAccs","- }"," }"," `,"," variables: {"," filter: statusFilter,","- paging: pagingState, // Top 10"," },"," requestPolicy: \"network-only\","," })"," : null,"," );"," ","+ // Sort + slice top-10 from the full results in the frontend","+ const topUserJobs = $derived(","+ $topStatsQuery?.data?.allUsers","+ ?.toSorted((a, b) => b.totalJobs - a.totalJobs)","+ .slice(0, 10) ?? [],","+ );","+ const topProjectJobs = $derived(","+ $topStatsQuery?.data?.allProjects","+ ?.toSorted((a, b) => b.totalJobs - a.totalJobs)","+ .slice(0, 10) ?? [],","+ );","+ const topUserNodes = $derived(","+ $topStatsQuery?.data?.allUsers","+ ?.toSorted((a, b) => b.totalNodes - a.totalNodes)","+ .slice(0, 10) ?? [],","+ );","+ const topProjectNodes = $derived(","+ $topStatsQuery?.data?.allProjects","+ ?.toSorted((a, b) => b.totalNodes - a.totalNodes)","+ .slice(0, 10) ?? [],","+ );","+ const topUserAccs = $derived(","+ $topStatsQuery?.data?.allUsers","+ ?.toSorted((a, b) => b.totalAccs - a.totalAccs)","+ .slice(0, 10) ?? [],","+ );","+ const topProjectAccs = $derived(","+ $topStatsQuery?.data?.allProjects","+ ?.toSorted((a, b) => b.totalAccs - a.totalAccs)","+ .slice(0, 10) ?? [],","+ );","+"," // Note: nodeMetrics are requested on configured $timestep resolution"," const nodeStatusQuery = $derived("," loadMe"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a36a94c9-929c-424a-b35a-b5d956132a5b","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a02e96ec-1ecc-473d-9605-dddd28731c35","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WH4iM1EzgCXabo7xs6jddi","type":"message","role":"assistant","content":[{"type":"text","text":"Now update all template references from `$topStatsQuery.data.topUserJobs` to `topUserJobs`, etc.:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1252,"cache_read_input_tokens":87924,"cache_creation":{"ephemeral_5m_input_tokens":1252,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1A27ouBKHhKayLKEdw6","type":"assistant","uuid":"08ff14dd-c478-4566-be11-19e1b6a9aa2f","timestamp":"2026-03-13T13:26:59.034Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"08ff14dd-c478-4566-be11-19e1b6a9aa2f","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WH4iM1EzgCXabo7xs6jddi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01TxQQJm7gJidvyrWhuADT82","name":"Edit","input":{"replace_all":true,"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","old_string":"$topStatsQuery.data.topUserJobs","new_string":"topUserJobs"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1252,"cache_read_input_tokens":87924,"cache_creation":{"ephemeral_5m_input_tokens":1252,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1A27ouBKHhKayLKEdw6","type":"assistant","uuid":"ecfb8b92-d249-49e6-a2a2-7f6066ac1a57","timestamp":"2026-03-13T13:27:00.055Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"ecfb8b92-d249-49e6-a2a2-7f6066ac1a57","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01TxQQJm7gJidvyrWhuADT82","toolUseID":"toolu_01TxQQJm7gJidvyrWhuADT82","timestamp":"2026-03-13T13:27:00.076Z","uuid":"4f47b0b4-6795-4f14-9c3c-e589f9243cb5","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"ecfb8b92-d249-49e6-a2a2-7f6066ac1a57","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TxQQJm7gJidvyrWhuADT82","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topUserJobs' were successfully replaced with 'topUserJobs'."}]},"uuid":"37f50ab8-2134-46b5-af9a-4846b80c1385","timestamp":"2026-03-13T13:27:00.076Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topUserJobs","newString":"topUserJobs","originalFile":"\n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":248,"oldLines":10,"newStart":248,"newLines":10,"lines":[" canvasId=\"{canvasPrefix}-hpcpie-jobs-users\""," size={colWidthJobs * 0.75}"," sliceLabel=\"Jobs\"","- quantities={$topStatsQuery.data.topUserJobs.map(","+ quantities={topUserJobs.map("," (tu) => tu[\"totalJobs\"],"," )}","- entities={$topStatsQuery.data.topUserJobs.map((tu) =>","+ entities={topUserJobs.map((tu) =>"," scrambleNames ? scramble(tu.id) : tu.id,"," )}"," />"]},{"oldStart":264,"oldLines":7,"newStart":264,"newLines":7,"lines":[" User"," Jobs"," ","- {#each $topStatsQuery.data.topUserJobs as tu, i}","+ {#each topUserJobs as tu, i}"," "," \n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":298,"oldLines":10,"newStart":298,"newLines":10,"lines":[" canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\""," size={colWidthJobs * 0.75}"," sliceLabel={\"Jobs\"}","- quantities={$topStatsQuery.data.topProjectJobs.map(","+ quantities={topProjectJobs.map("," (tp) => tp[\"totalJobs\"],"," )}","- entities={$topStatsQuery.data.topProjectJobs.map((tp) =>","+ entities={topProjectJobs.map((tp) =>"," scrambleNames ? scramble(tp.id) : tp.id,"," )}"," />"]},{"oldStart":313,"oldLines":7,"newStart":313,"newLines":7,"lines":[" Project"," Jobs"," ","- {#each $topStatsQuery.data.topProjectJobs as tp, i}","+ {#each topProjectJobs as tp, i}"," "," \n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":368,"oldLines":10,"newStart":368,"newLines":10,"lines":[" canvasId=\"{canvasPrefix}-hpcpie-nodes-users\""," size={colWidthNodes * 0.75}"," sliceLabel=\"Nodes\"","- quantities={$topStatsQuery.data.topUserNodes.map(","+ quantities={topUserNodes.map("," (tu) => tu[\"totalNodes\"],"," )}","- entities={$topStatsQuery.data.topUserNodes.map((tu) =>","+ entities={topUserNodes.map((tu) =>"," scrambleNames ? scramble(tu.id) : tu.id,"," )}"," />"]},{"oldStart":384,"oldLines":7,"newStart":384,"newLines":7,"lines":[" User"," Nodes"," ","- {#each $topStatsQuery.data.topUserNodes as tu, i}","+ {#each topUserNodes as tu, i}"," "," \n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":418,"oldLines":10,"newStart":418,"newLines":10,"lines":[" canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\""," size={colWidthNodes * 0.75}"," sliceLabel={\"Nodes\"}","- quantities={$topStatsQuery.data.topProjectNodes.map(","+ quantities={topProjectNodes.map("," (tp) => tp[\"totalNodes\"],"," )}","- entities={$topStatsQuery.data.topProjectNodes.map((tp) =>","+ entities={topProjectNodes.map((tp) =>"," scrambleNames ? scramble(tp.id) : tp.id,"," )}"," />"]},{"oldStart":433,"oldLines":7,"newStart":433,"newLines":7,"lines":[" Project"," Nodes"," ","- {#each $topStatsQuery.data.topProjectNodes as tp, i}","+ {#each topProjectNodes as tp, i}"," "," \n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
\n \n \n{:else}\n Cannot render accelerator status charts: No data!\n{/if}\n","structuredPatch":[{"oldStart":488,"oldLines":10,"newStart":488,"newLines":10,"lines":[" canvasId=\"{canvasPrefix}-hpcpie-accs-users\""," size={colWidthAccs * 0.75}"," sliceLabel=\"GPUs\"","- quantities={$topStatsQuery.data.topUserAccs.map(","+ quantities={topUserAccs.map("," (tu) => tu[\"totalAccs\"],"," )}","- entities={$topStatsQuery.data.topUserAccs.map((tu) =>","+ entities={topUserAccs.map((tu) =>"," scrambleNames ? scramble(tu.id) : tu.id,"," )}"," />"]},{"oldStart":504,"oldLines":7,"newStart":504,"newLines":7,"lines":[" User"," GPUs"," ","- {#each $topStatsQuery.data.topUserAccs as tu, i}","+ {#each topUserAccs as tu, i}"," "," \n\n\n\n\n\n \n \n \n \n \n Duration Bin Size\n \n {#each durationBinOptions as dbin}\n \n {/each}\n \n \n \n \n {\n pagingState = { page: 1, itemsPerPage: 10 };\n selectedHistograms = [...$state.snapshot(selectedHistograms)];\n }}\n />\n \n\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n \n {/key}\n \n \n
\n

Top Users: Jobs

\n tu[\"totalJobs\"],\n )}\n entities={topUserJobs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserJobs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserJobs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalJobs\"]}
\n \n\n \n

Top Projects: Jobs

\n tp[\"totalJobs\"],\n )}\n entities={topProjectJobs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectJobs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectJobs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalJobs\"]}
\n \n \n{:else}\n Cannot render job status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: Nodes

\n tu[\"totalNodes\"],\n )}\n entities={topUserNodes.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserNodes as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserNodes
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalNodes\"]}
\n \n\n \n

Top Projects: Nodes

\n tp[\"totalNodes\"],\n )}\n entities={topProjectNodes.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each topProjectNodes as tp, i}\n \n \n \n \n \n {/each}\n
ProjectNodes
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalNodes\"]}
\n \n \n{:else}\n Cannot render node status charts: No data!\n{/if}\n\n
\n\n\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n \n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n \n \n \n \n \n
\n

Top Users: GPUs

\n tu[\"totalAccs\"],\n )}\n entities={topUserAccs.map((tu) =>\n scrambleNames ? scramble(tu.id) : tu.id,\n )}\n />\n
\n \n \n \n \n \n \n \n \n {#each topUserAccs as tu, i}\n \n \n \n {#if tu?.name}\n {scrambleNames ? scramble(tu.name) : tu.name}\n {/if}\n \n \n {/each}\n
UserGPUs
\n {scrambleNames ? scramble(tu.id) : tu.id}\n \n {tu[\"totalAccs\"]}
\n \n\n \n

Top Projects: GPUs

\n tp[\"totalAccs\"],\n )}\n entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n scrambleNames ? scramble(tp.id) : tp.id,\n )}\n />\n \n \n \n \n \n \n \n \n {#each $topStatsQuery.data.topProjectAccs as tp, i}\n \n \n \n \n \n {/each}\n
ProjectGPUs
\n {scrambleNames ? scramble(tp.id) : tp.id}\n \n {tp[\"totalAccs\"]}
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and can be fast-forwarded.\n (use \"git pull\" to update your local branch)\n\nChanges not staged for commit:\n (use \"git add ...\" to update what will be committed)\n (use \"git restore ...\" to discard changes in working directory)\n\tmodified: cmd/cc-backend/server.go\n\tmodified: go.mod\n\tmodified: internal/graph/schema.resolvers.go\n\tmodified: internal/repository/jobQuery.go\n\tmodified: internal/repository/migration.go\n\tmodified: internal/repository/stats.go\n\tmodified: web/frontend/src/status/dashdetails/UsageDash.svelte\n\nUntracked files:\n (use \"git add ...\" to include in what will be committed)\n\tinternal/graph/stats_cache.go\n\tinternal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql\n\tinternal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql\n\nno changes added to commit (use \"git add\" and/or \"git commit 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committed)\n\tinternal/graph/stats_cache.go\n\tinternal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql\n\tinternal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"d9a9e730-dc4c-4f7a-bb76-ac63523c7115","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"8c38acf0-5730-406e-9bcb-4569e2cc147c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EqVHditZ6T22Ah73pJhw7f","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018XEdEYxNKn8aaiKuPimai3","name":"Bash","input":{"command":"git diff --stat","description":"Show diff 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internal/graph/schema.resolvers.go | 15 ++-\n internal/repository/jobQuery.go | 4 +-\n internal/repository/migration.go | 3 +-\n internal/repository/stats.go | 58 ++++++----\n .../src/status/dashdetails/UsageDash.svelte | 117 ++++++++++-----------\n 7 files changed, 119 insertions(+), 87 deletions(-)","is_error":false}]},"uuid":"34def0fd-3190-440e-8478-b886c3b8ff2a","timestamp":"2026-03-13T13:31:25.694Z","toolUseResult":{"stdout":" cmd/cc-backend/server.go | 7 ++\n go.mod | 2 +-\n internal/graph/schema.resolvers.go | 15 ++-\n internal/repository/jobQuery.go | 4 +-\n internal/repository/migration.go | 3 +-\n internal/repository/stats.go | 58 ++++++----\n .../src/status/dashdetails/UsageDash.svelte | 117 ++++++++++-----------\n 7 files changed, 119 insertions(+), 87 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+{"parentUuid":"c8a9689e-b6ab-473e-8908-bdcbcc4bb7d6","isSidechain":false,"promptId":"cef5abc9-1504-479e-870d-845cb284bb17","type":"user","message":{"role":"user","content":"Does it make sense to also inline the literal state value in other places?"},"uuid":"161d4ccc-0537-4700-a10d-f7a8534ef7f4","timestamp":"2026-03-13T14:10:51.396Z","permissionMode":"plan","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"161d4ccc-0537-4700-a10d-f7a8534ef7f4","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01LadQ1AxETvXziMrYBqj9ps","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nGood question. Let me explore where `job_state` is filtered with parameterized values across the codebase to see if there are other hot paths that would benefit."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":82126,"cache_read_input_tokens":14321,"cache_creation":{"ephemeral_5m_input_tokens":82126,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1DNSxjVjbYfyBxWUgBg","type":"assistant","uuid":"d5e13524-c651-4d20-b025-783abd83517c","timestamp":"2026-03-13T14:10:57.740Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"d5e13524-c651-4d20-b025-783abd83517c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01LadQ1AxETvXziMrYBqj9ps","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01EDotFfP7XFHmDSwtCzpTYi","name":"Agent","input":{"description":"Find all job_state filter sites","subagent_type":"Explore","prompt":"Search the codebase for all places where `job_state` or `job.job_state` is used in SQL query construction (not in migration files). I need to find every place where a WHERE clause on job_state is built, whether via squirrel (sq.Where, query.Where) or raw SQL strings. \n\nFor each occurrence, note:\n1. The file and line number\n2. Whether the value is parameterized (using `?` placeholder) or inlined as a literal\n3. The context — what function it's in and what it's used for (e.g., counting running jobs, building stats queries, etc.)\n4. Whether it filters for a single known state value (like 'running') from a validated/hardcoded source, or from user input\n\nFocus on:\n- internal/repository/stats.go\n- internal/repository/jobQuery.go \n- internal/repository/job.go\n- Any other files in internal/repository/\n- internal/graph/ resolvers\n\nDo NOT look at migration SQL files."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":82126,"cache_read_input_tokens":14321,"output_tokens":364,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":82126},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1DNSxjVjbYfyBxWUgBg","type":"assistant","uuid":"8cbf0c52-c5b0-4c92-a63e-ba22eb7416fd","timestamp":"2026-03-13T14:11:04.386Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"8cbf0c52-c5b0-4c92-a63e-ba22eb7416fd","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PreToolUse","hookName":"PreToolUse:Agent","command":"entire hooks claude-code pre-task"},"toolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"0452f0e0-bc7d-4e99-a6ef-5e905225bd95","timestamp":"2026-03-13T14:11:04.391Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"0452f0e0-bc7d-4e99-a6ef-5e905225bd95","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"Search the codebase for all places where `job_state` or `job.job_state` is used in SQL query construction (not in migration files). I need to find every place where a WHERE clause on job_state is built, whether via squirrel (sq.Where, query.Where) or raw SQL strings. \n\nFor each occurrence, note:\n1. The file and line number\n2. Whether the value is parameterized (using `?` placeholder) or inlined as a literal\n3. The context — what function it's in and what it's used for (e.g., counting running jobs, building stats queries, etc.)\n4. Whether it filters for a single known state value (like 'running') from a validated/hardcoded source, or from user input\n\nFocus on:\n- internal/repository/stats.go\n- internal/repository/jobQuery.go \n- internal/repository/job.go\n- Any other files in internal/repository/\n- internal/graph/ resolvers\n\nDo NOT look at migration SQL files."}]},"uuid":"708853b8-ac7f-487a-aee8-1feebb810dae","timestamp":"2026-03-13T14:11:04.707Z"},"type":"agent_progress","prompt":"Search the codebase for all places where `job_state` or `job.job_state` is used in SQL query construction (not in migration files). I need to find every place where a WHERE clause on job_state is built, whether via squirrel (sq.Where, query.Where) or raw SQL strings. \n\nFor each occurrence, note:\n1. The file and line number\n2. Whether the value is parameterized (using `?` placeholder) or inlined as a literal\n3. The context — what function it's in and what it's used for (e.g., counting running jobs, building stats queries, etc.)\n4. Whether it filters for a single known state value (like 'running') from a validated/hardcoded source, or from user input\n\nFocus on:\n- internal/repository/stats.go\n- internal/repository/jobQuery.go \n- internal/repository/job.go\n- Any other files in internal/repository/\n- internal/graph/ resolvers\n\nDo NOT look at migration SQL files.","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"d9698125-af00-4dd3-a1fa-2a66f5bb7e46","timestamp":"2026-03-13T14:11:04.707Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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files\ninternal/repository/stats.go\ninternal/repository/jobQuery.go\ninternal/repository/migration.go\ninternal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql\ninternal/repository/migrations/sqlite3/13_status-covering-indexes.down.sql\ninternal/repository/migrations/sqlite3/13_status-covering-indexes.up.sql\ninternal/repository/jobCreate.go\ninternal/repository/migrations/sqlite3/12_stats-covering-index.up.sql\ninternal/repository/migrations/sqlite3/09_add-job-cache.up.sql\ninternal/repository/migrations/sqlite3/11_optimize-indexes.down.sql\ninternal/repository/jobFind.go\ninternal/repository/jobCreate_test.go\ninternal/repository/job.go\ninternal/repository/migrations/sqlite3/04_add-constraints.up.sql\ninternal/repository/migrations/sqlite3/08_add-footprint.up.sql\ninternal/repository/migrations/sqlite3/01_init-schema.up.sql\ninternal/repository/migrations/sqlite3/02_add-index.up.sql\ninternal/repository/migrations/sqlite3/04_add-constraints.down.sql"}]},"uuid":"4043e45a-a9ac-4776-b305-696aa7f31504","timestamp":"2026-03-13T14:11:07.046Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"989db38d-4a17-4739-ab6b-1699a99e48d6","timestamp":"2026-03-13T14:11:07.079Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"188d4f7a-5686-49d2-bc3d-3fb00bddd033","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Wp14PSnNiLjZX1qTuT4YyH","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// This file contains job statistics and histogram generation functionality for the JobRepository.\n 7→//\n 8→// # Job Statistics\n 9→//\n 10→// The statistics methods provide aggregated metrics about jobs including total jobs, users,\n 11→// walltime, and resource usage (nodes, cores, accelerators). Statistics can be computed:\n 12→// - Overall (JobsStats): Single aggregate across all matching jobs\n 13→// - Grouped (JobsStatsGrouped): Aggregated by user, project, cluster, or subcluster\n 14→// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n 15→//\n 16→// All statistics methods support filtering via JobFilter and respect security contexts.\n 17→//\n 18→// # Histograms\n 19→//\n 20→// Histogram methods generate distribution data for visualization:\n 21→// - Duration, nodes, cores, accelerators (AddHistograms)\n 22→// - Job metrics like CPU load, memory usage (AddMetricHistograms)\n 23→//\n 24→// Histograms use intelligent binning:\n 25→// - Duration: Variable bin sizes (1m, 10m, 1h, 6h, 12h, 24h) with zero-padding\n 26→// - Resources: Natural value-based bins\n 27→// - Metrics: Normalized to peak values with configurable bin counts\n 28→//\n 29→// # Running vs. Completed Jobs\n 30→//\n 31→// Statistics handle running jobs specially:\n 32→// - Duration calculated as (now - start_time) for running jobs\n 33→// - Metric histograms for running jobs load data from metric backend instead of footprint\n 34→// - Job state filtering distinguishes running/completed jobs\n 35→//\n 36→// # Performance Considerations\n 37→//\n 38→// - All queries use prepared statements via stmtCache\n 39→// - Complex aggregations use SQL for efficiency\n 40→// - Histogram pre-initialization ensures consistent bin ranges\n 41→// - Metric histogram queries limited to 5000 jobs for running job analysis\n 42→\n 43→package repository\n 44→\n 45→import (\n 46→\t\"context\"\n 47→\t\"database/sql\"\n 48→\t\"fmt\"\n 49→\t\"time\"\n 50→\n 51→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n 52→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 53→\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n 54→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 55→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 56→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 57→\tsq \"github.com/Masterminds/squirrel\"\n 58→\t\"golang.org/x/sync/errgroup\"\n 59→)\n 60→\n 61→// groupBy2column maps GraphQL Aggregate enum values to their corresponding database column names.\n 62→// Used by JobsStatsGrouped and JobCountGrouped to translate user-facing grouping dimensions\n 63→// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\n 64→var groupBy2column = map[model.Aggregate]string{\n 65→\tmodel.AggregateUser: \"job.hpc_user\",\n 66→\tmodel.AggregateProject: \"job.project\",\n 67→\tmodel.AggregateCluster: \"job.cluster\",\n 68→\tmodel.AggregateSubcluster: \"job.subcluster\",\n 69→}\n 70→\n 71→// sortBy2column maps GraphQL SortByAggregate enum values to their corresponding computed column names.\n 72→// Used by JobsStatsGrouped to translate sort preferences into SQL ORDER BY clauses.\n 73→// Column names match the AS aliases used in buildStatsQuery.\n 74→var sortBy2column = map[model.SortByAggregate]string{\n 75→\tmodel.SortByAggregateTotaljobs: \"totalJobs\",\n 76→\tmodel.SortByAggregateTotalusers: \"totalUsers\",\n 77→\tmodel.SortByAggregateTotalwalltime: \"totalWalltime\",\n 78→\tmodel.SortByAggregateTotalnodes: \"totalNodes\",\n 79→\tmodel.SortByAggregateTotalnodehours: \"totalNodeHours\",\n 80→\tmodel.SortByAggregateTotalcores: \"totalCores\",\n 81→\tmodel.SortByAggregateTotalcorehours: \"totalCoreHours\",\n 82→\tmodel.SortByAggregateTotalaccs: \"totalAccs\",\n 83→\tmodel.SortByAggregateTotalacchours: \"totalAccHours\",\n 84→}\n 85→\n 86→// buildCountQuery constructs a SQL query to count jobs with optional grouping and filtering.\n 87→//\n 88→// Parameters:\n 89→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 90→// - kind: Special filter - \"running\" for running jobs only, \"short\" for jobs under threshold\n 91→// - col: Column name to GROUP BY; empty string for total count without grouping\n 92→//\n 93→// Returns a SelectBuilder that produces either:\n 94→// - Single count: COUNT(job.id) when col is empty\n 95→// - Grouped counts: col, COUNT(job.id) when col is specified\n 96→//\n 97→// The kind parameter enables counting specific job categories:\n 98→// - \"running\": Only jobs with job_state = 'running'\n 99→// - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n 100→// - empty: All jobs matching filters\n 101→func (r *JobRepository) buildCountQuery(\n 102→\tfilter []*model.JobFilter,\n 103→\tkind string,\n 104→\tcol string,\n 105→) sq.SelectBuilder {\n 106→\tvar query sq.SelectBuilder\n 107→\n 108→\tif col != \"\" {\n 109→\t\tquery = sq.Select(col, \"COUNT(*)\").From(\"job\").GroupBy(col)\n 110→\t} else {\n 111→\t\tquery = sq.Select(\"COUNT(*)\").From(\"job\")\n 112→\t}\n 113→\n 114→\tswitch kind {\n 115→\tcase \"running\":\n 116→\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n 117→\tcase \"short\":\n 118→\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n 119→\t}\n 120→\n 121→\tfor _, f := range filter {\n 122→\t\tquery = BuildWhereClause(f, query)\n 123→\t}\n 124→\n 125→\treturn query\n 126→}\n 127→\n 128→// buildStatsQuery constructs a SQL query to compute job statistics with optional grouping.\n 129→// Only requested columns are computed; unrequested columns select 0 as placeholder.\n 130→//\n 131→// Parameters:\n 132→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 133→// - col: Column name to GROUP BY; 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\") && col != \"job.hpc_user\" {\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→}\n 230→\n 231→// JobsStatsGrouped computes job statistics grouped by a dimension (user, project, cluster, or subcluster).\n 232→// Only columns listed in reqFields are computed; others return 0. User display names are looked up\n 233→// in a separate lightweight query to avoid JOIN overhead on the main aggregation.\n 234→func (r *JobRepository) JobsStatsGrouped(\n 235→\tctx context.Context,\n 236→\tfilter []*model.JobFilter,\n 237→\tpage *model.PageRequest,\n 238→\tsortBy *model.SortByAggregate,\n 239→\tgroupBy *model.Aggregate,\n 240→\treqFields map[string]bool,\n 241→) ([]*model.JobsStatistics, error) {\n 242→\tcol := groupBy2column[*groupBy]\n 243→\tquery := r.buildStatsQuery(filter, col, config.Keys.ShortRunningJobsDuration, reqFields)\n 244→\n 245→\tquery, err := SecurityCheck(ctx, query)\n 246→\tif err != nil {\n 247→\t\treturn nil, err\n 248→\t}\n 249→\n 250→\tif sortBy != nil {\n 251→\t\tsortBy := sortBy2column[*sortBy]\n 252→\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n 253→\t}\n 254→\tif page != nil && page.ItemsPerPage != -1 {\n 255→\t\tlimit := uint64(page.ItemsPerPage)\n 256→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 257→\t}\n 258→\n 259→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 260→\tif err != nil {\n 261→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 262→\t\treturn nil, err\n 263→\t}\n 264→\tdefer rows.Close()\n 265→\n 266→\tstats := make([]*model.JobsStatistics, 0, 100)\n 267→\n 268→\tfor rows.Next() {\n 269→\t\tvar id sql.NullString\n 270→\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n 271→\t\tif err := rows.Scan(&id, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n 272→\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n 273→\t\t\treturn nil, err\n 274→\t\t}\n 275→\n 276→\t\tif id.Valid {\n 277→\t\t\tstats = append(stats,\n 278→\t\t\t\t&model.JobsStatistics{\n 279→\t\t\t\t\tID: id.String,\n 280→\t\t\t\t\tTotalJobs: int(jobs.Int64),\n 281→\t\t\t\t\tTotalUsers: int(users.Int64),\n 282→\t\t\t\t\tTotalWalltime: int(walltime.Int64),\n 283→\t\t\t\t\tTotalNodes: int(nodes.Int64),\n 284→\t\t\t\t\tTotalNodeHours: int(nodeHours.Int64),\n 285→\t\t\t\t\tTotalCores: int(cores.Int64),\n 286→\t\t\t\t\tTotalCoreHours: int(coreHours.Int64),\n 287→\t\t\t\t\tTotalAccs: int(accs.Int64),\n 288→\t\t\t\t\tTotalAccHours: int(accHours.Int64),\n 289→\t\t\t\t\tRunningJobs: int(runningJobs.Int64),\n 290→\t\t\t\t\tShortJobs: int(shortJobs.Int64),\n 291→\t\t\t\t})\n 292→\t\t}\n 293→\t}\n 294→\n 295→\tif err := rows.Err(); err != nil {\n 296→\t\treturn nil, err\n 297→\t}\n 298→\n 299→\t// Post-query name lookup for user grouping (avoids LEFT JOIN on aggregation query)\n 300→\tif col == \"job.hpc_user\" && len(stats) > 0 {\n 301→\t\tusernames := make([]any, len(stats))\n 302→\t\tfor i, s := range stats {\n 303→\t\t\tusernames[i] = s.ID\n 304→\t\t}\n 305→\n 306→\t\tnameQuery := sq.Select(\"username\", \"name\").From(\"hpc_user\").Where(sq.Eq{\"username\": usernames})\n 307→\t\tnameRows, err := nameQuery.RunWith(r.DB).QueryContext(ctx)\n 308→\t\tif err != nil {\n 309→\t\t\tcclog.Warnf(\"Error looking up user names: %s\", err.Error())\n 310→\t\t\t// Non-fatal: stats are still valid without display names\n 311→\t\t} else {\n 312→\t\t\tdefer nameRows.Close()\n 313→\t\t\tnameMap := make(map[string]string, len(stats))\n 314→\t\t\tfor nameRows.Next() {\n 315→\t\t\t\tvar username, name string\n 316→\t\t\t\tif err := nameRows.Scan(&username, &name); err == nil {\n 317→\t\t\t\t\tnameMap[username] = name\n 318→\t\t\t\t}\n 319→\t\t\t}\n 320→\t\t\tfor _, s := range stats {\n 321→\t\t\t\tif name, ok := nameMap[s.ID]; ok {\n 322→\t\t\t\t\ts.Name = name\n 323→\t\t\t\t}\n 324→\t\t\t}\n 325→\t\t}\n 326→\t}\n 327→\n 328→\treturn stats, nil\n 329→}\n 330→\n 331→// JobsStats computes overall job statistics across all matching jobs without grouping.\n 332→//\n 333→// This method provides a single aggregate view of job metrics, useful for dashboard\n 334→// summaries and overall system utilization reports.\n 335→//\n 336→// Parameters:\n 337→// - ctx: Context for security checks and cancellation\n 338→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 339→//\n 340→// Returns a single-element slice containing aggregate statistics:\n 341→// - totalJobs, totalUsers, totalWalltime\n 342→// - totalNodeHours, totalCoreHours, totalAccHours\n 343→//\n 344→// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n 345→// Security checks are applied via SecurityCheck to respect user access levels.\n 346→func (r *JobRepository) JobsStats(\n 347→\tctx context.Context,\n 348→\tfilter []*model.JobFilter,\n 349→\treqFields map[string]bool,\n 350→) ([]*model.JobsStatistics, error) {\n 351→\tstart := time.Now()\n 352→\tquery := r.buildStatsQuery(filter, \"\", config.Keys.ShortRunningJobsDuration, reqFields)\n 353→\tquery, err := SecurityCheck(ctx, query)\n 354→\tif err != nil {\n 355→\t\treturn nil, err\n 356→\t}\n 357→\n 358→\trow := query.RunWith(r.DB).QueryRowContext(ctx)\n 359→\tstats := make([]*model.JobsStatistics, 0, 1)\n 360→\n 361→\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours, runningJobs, shortJobs sql.NullInt64\n 362→\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours, &runningJobs, &shortJobs); err != nil {\n 363→\t\tcclog.Warn(\"Error while scanning rows\")\n 364→\t\treturn nil, err\n 365→\t}\n 366→\n 367→\tif jobs.Valid {\n 368→\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n 369→\n 370→\t\tif nodeHours.Valid {\n 371→\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 372→\t\t}\n 373→\t\tif coreHours.Valid {\n 374→\t\t\ttotalCoreHours = int(coreHours.Int64)\n 375→\t\t}\n 376→\t\tif accHours.Valid {\n 377→\t\t\ttotalAccHours = int(accHours.Int64)\n 378→\t\t}\n 379→\t\tstats = append(stats,\n 380→\t\t\t&model.JobsStatistics{\n 381→\t\t\t\tTotalJobs: int(jobs.Int64),\n 382→\t\t\t\tTotalUsers: int(users.Int64),\n 383→\t\t\t\tTotalWalltime: int(walltime.Int64),\n 384→\t\t\t\tTotalNodeHours: totalNodeHours,\n 385→\t\t\t\tTotalCoreHours: totalCoreHours,\n 386→\t\t\t\tTotalAccHours: totalAccHours,\n 387→\t\t\t\tRunningJobs: int(runningJobs.Int64),\n 388→\t\t\t\tShortJobs: int(shortJobs.Int64),\n 389→\t\t\t})\n 390→\t}\n 391→\n 392→\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n 393→\treturn stats, nil\n 394→}\n 395→\n 396→// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n 397→// Returns 0.0 if the metric is not found or statType is invalid.\n 398→//\n 399→// Parameters:\n 400→// - job: Job struct with populated Statistics field\n 401→// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n 402→// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n 403→//\n 404→// Returns the requested statistic value or 0.0 if not found.\n 405→func LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n 406→\tif stats, ok := job.Statistics[metric]; ok {\n 407→\t\tswitch statType {\n 408→\t\tcase \"avg\":\n 409→\t\t\treturn stats.Avg\n 410→\t\tcase \"max\":\n 411→\t\t\treturn stats.Max\n 412→\t\tcase \"min\":\n 413→\t\t\treturn stats.Min\n 414→\t\tdefault:\n 415→\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n 416→\t\t}\n 417→\t}\n 418→\n 419→\treturn 0.0\n 420→}\n 421→\n 422→// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n 423→//\n 424→// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n 425→// avoiding the overhead of calculating walltime and resource usage metrics.\n 426→//\n 427→// Parameters:\n 428→// - ctx: Context for security checks\n 429→// - filter: Filters to apply\n 430→// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n 431→//\n 432→// Returns JobsStatistics with only ID and TotalJobs populated for each group.\n 433→func (r *JobRepository) JobCountGrouped(\n 434→\tctx context.Context,\n 435→\tfilter []*model.JobFilter,\n 436→\tgroupBy *model.Aggregate,\n 437→) ([]*model.JobsStatistics, error) {\n 438→\tstart := time.Now()\n 439→\tcol := groupBy2column[*groupBy]\n 440→\tquery := r.buildCountQuery(filter, \"\", col)\n 441→\tquery, err := SecurityCheck(ctx, query)\n 442→\tif err != nil {\n 443→\t\treturn nil, err\n 444→\t}\n 445→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 446→\tif err != nil {\n 447→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 448→\t\treturn nil, err\n 449→\t}\n 450→\tdefer rows.Close()\n 451→\n 452→\tstats := make([]*model.JobsStatistics, 0, 100)\n 453→\n 454→\tfor rows.Next() {\n 455→\t\tvar id sql.NullString\n 456→\t\tvar cnt sql.NullInt64\n 457→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 458→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 459→\t\t\treturn nil, err\n 460→\t\t}\n 461→\t\tif id.Valid {\n 462→\t\t\tstats = append(stats,\n 463→\t\t\t\t&model.JobsStatistics{\n 464→\t\t\t\t\tID: id.String,\n 465→\t\t\t\t\tTotalJobs: int(cnt.Int64),\n 466→\t\t\t\t})\n 467→\t\t}\n 468→\t}\n 469→\n 470→\tif err := rows.Err(); err != nil {\n 471→\t\treturn nil, err\n 472→\t}\n 473→\n 474→\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n 475→\treturn stats, nil\n 476→}\n 477→\n 478→// AddJobCountGrouped augments existing statistics with additional job counts by category.\n 479→//\n 480→// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n 481→// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n 482→//\n 483→// Parameters:\n 484→// - ctx: Context for security checks\n 485→// - filter: Filters to apply\n 486→// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n 487→// - stats: Existing statistics to augment (modified in-place by ID matching)\n 488→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 489→//\n 490→// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n 491→// Groups without matching jobs will have 0 for the added field.\n 492→func (r *JobRepository) AddJobCountGrouped(\n 493→\tctx context.Context,\n 494→\tfilter []*model.JobFilter,\n 495→\tgroupBy *model.Aggregate,\n 496→\tstats []*model.JobsStatistics,\n 497→\tkind string,\n 498→) ([]*model.JobsStatistics, error) {\n 499→\tstart := time.Now()\n 500→\tcol := groupBy2column[*groupBy]\n 501→\tquery := r.buildCountQuery(filter, kind, col)\n 502→\tquery, err := SecurityCheck(ctx, query)\n 503→\tif err != nil {\n 504→\t\treturn nil, err\n 505→\t}\n 506→\trows, err := query.RunWith(r.DB).QueryContext(ctx)\n 507→\tif err != nil {\n 508→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 509→\t\treturn nil, err\n 510→\t}\n 511→\tdefer rows.Close()\n 512→\n 513→\tcounts := make(map[string]int)\n 514→\n 515→\tfor rows.Next() {\n 516→\t\tvar id sql.NullString\n 517→\t\tvar cnt sql.NullInt64\n 518→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 519→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 520→\t\t\treturn nil, err\n 521→\t\t}\n 522→\t\tif id.Valid {\n 523→\t\t\tcounts[id.String] = int(cnt.Int64)\n 524→\t\t}\n 525→\t}\n 526→\n 527→\tif err := rows.Err(); err != nil {\n 528→\t\treturn nil, err\n 529→\t}\n 530→\n 531→\tswitch kind {\n 532→\tcase \"running\":\n 533→\t\tfor _, s := range stats {\n 534→\t\t\ts.RunningJobs = counts[s.ID]\n 535→\t\t}\n 536→\tcase \"short\":\n 537→\t\tfor _, s := range stats {\n 538→\t\t\ts.ShortJobs = counts[s.ID]\n 539→\t\t}\n 540→\t}\n 541→\n 542→\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n 543→\treturn stats, nil\n 544→}\n 545→\n 546→// AddJobCount augments existing overall statistics with additional job counts by category.\n 547→//\n 548→// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n 549→// to all statistics entries (typically just one).\n 550→//\n 551→// Parameters:\n 552→// - ctx: Context for security checks\n 553→// - filter: Filters to apply\n 554→// - stats: Existing statistics to augment (modified in-place)\n 555→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 556→//\n 557→// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\n 558→func (r *JobRepository) AddJobCount(\n 559→\tctx context.Context,\n 560→\tfilter []*model.JobFilter,\n 561→\tstats []*model.JobsStatistics,\n 562→\tkind string,\n 563→) ([]*model.JobsStatistics, error) {\n 564→\tstart := time.Now()\n 565→\tquery := r.buildCountQuery(filter, kind, \"\")\n 566→\tquery, err := SecurityCheck(ctx, query)\n 567→\tif err != nil {\n 568→\t\treturn nil, err\n 569→\t}\n 570→\tvar cnt sql.NullInt64\n 571→\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&cnt); err != nil {\n 572→\t\tcclog.Warn(\"Error while querying DB for job count\")\n 573→\t\treturn nil, err\n 574→\t}\n 575→\n 576→\tcount := int(cnt.Int64)\n 577→\n 578→\tswitch kind {\n 579→\tcase \"running\":\n 580→\t\tfor _, s := range stats {\n 581→\t\t\ts.RunningJobs = count\n 582→\t\t}\n 583→\tcase \"short\":\n 584→\t\tfor _, s := range stats {\n 585→\t\t\ts.ShortJobs = count\n 586→\t\t}\n 587→\t}\n 588→\n 589→\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n 590→\treturn stats, nil\n 591→}\n 592→\n 593→// AddHistograms augments statistics with distribution histograms for job properties.\n 594→//\n 595→// Generates histogram data for visualization of job duration, node count, core count,\n 596→// and accelerator count distributions. Duration histogram uses intelligent binning based\n 597→// on the requested resolution.\n 598→//\n 599→// Parameters:\n 600→// - ctx: Context for security checks\n 601→// - filter: Filters to apply to jobs included in histograms\n 602→// - stat: Statistics struct to augment (modified in-place)\n 603→// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n 604→//\n 605→// Populates these fields in stat:\n 606→// - HistDuration: Job duration distribution (zero-padded bins)\n 607→// - HistNumNodes: Node count distribution\n 608→// - HistNumCores: Core (hwthread) count distribution\n 609→// - HistNumAccs: Accelerator count distribution\n 610→//\n 611→// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n 612→// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\n 613→func (r *JobRepository) AddHistograms(\n 614→\tctx context.Context,\n 615→\tfilter []*model.JobFilter,\n 616→\tstat *model.JobsStatistics,\n 617→\tdurationBins *string,\n 618→) (*model.JobsStatistics, error) {\n 619→\tstart := time.Now()\n 620→\n 621→\tvar targetBinCount int\n 622→\tvar targetBinSize int\n 623→\tswitch *durationBins {\n 624→\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n 625→\t\ttargetBinCount = 60\n 626→\t\ttargetBinSize = 60\n 627→\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n 628→\t\ttargetBinCount = 72\n 629→\t\ttargetBinSize = 600\n 630→\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n 631→\t\ttargetBinCount = 48\n 632→\t\ttargetBinSize = 3600\n 633→\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n 634→\t\ttargetBinCount = 12\n 635→\t\ttargetBinSize = 21600\n 636→\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n 637→\t\ttargetBinCount = 14\n 638→\t\ttargetBinSize = 43200\n 639→\tdefault: // 24h\n 640→\t\ttargetBinCount = 24\n 641→\t\ttargetBinSize = 3600\n 642→\t}\n 643→\n 644→\t// Run all 4 histogram queries in parallel — each writes a distinct struct field.\n 645→\tg, gctx := errgroup.WithContext(ctx)\n 646→\n 647→\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n 648→\n 649→\tg.Go(func() error {\n 650→\t\tvar err error\n 651→\t\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(gctx, value, filter, targetBinSize, &targetBinCount)\n 652→\t\tif err != nil {\n 653→\t\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n 654→\t\t}\n 655→\t\treturn err\n 656→\t})\n 657→\tg.Go(func() error {\n 658→\t\tvar err error\n 659→\t\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(gctx, \"job.num_nodes as value\", filter)\n 660→\t\tif err != nil {\n 661→\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n 662→\t\t}\n 663→\t\treturn err\n 664→\t})\n 665→\tg.Go(func() error {\n 666→\t\tvar err error\n 667→\t\tstat.HistNumCores, err = r.jobsStatisticsHistogram(gctx, \"job.num_hwthreads as value\", filter)\n 668→\t\tif err != nil {\n 669→\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n 670→\t\t}\n 671→\t\treturn err\n 672→\t})\n 673→\tg.Go(func() error {\n 674→\t\tvar err error\n 675→\t\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(gctx, \"job.num_acc as value\", filter)\n 676→\t\tif err != nil {\n 677→\t\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n 678→\t\t}\n 679→\t\treturn err\n 680→\t})\n 681→\n 682→\tif err := g.Wait(); err != nil {\n 683→\t\treturn nil, err\n 684→\t}\n 685→\n 686→\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n 687→\treturn stat, nil\n 688→}\n 689→\n 690→// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n 691→//\n 692→// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n 693→// and completed jobs differently: running jobs load data from metric backend, completed jobs\n 694→// use footprint data from database.\n 695→//\n 696→// Parameters:\n 697→// - ctx: Context for security checks\n 698→// - filter: Filters to apply (MUST contain State filter for running jobs)\n 699→// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n 700→// - stat: Statistics struct to augment (modified in-place)\n 701→// - targetBinCount: Number of histogram bins (default: 10)\n 702→//\n 703→// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n 704→//\n 705→// Binning algorithm:\n 706→// - Values normalized to metric's peak value from cluster configuration\n 707→// - Bins evenly distributed from 0 to peak\n 708→// - Pre-initialized with zeros for consistent visualization\n 709→//\n 710→// Limitations:\n 711→// - Running jobs: Limited to 5000 jobs for performance\n 712→// - Requires valid cluster configuration with metric peak values\n 713→// - Uses footprint statistic (avg/max/min) configured per metric\n 714→func (r *JobRepository) AddMetricHistograms(\n 715→\tctx context.Context,\n 716→\tfilter []*model.JobFilter,\n 717→\tmetrics []string,\n 718→\tstat *model.JobsStatistics,\n 719→\ttargetBinCount *int,\n 720→) (*model.JobsStatistics, error) {\n 721→\tstart := time.Now()\n 722→\n 723→\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n 724→\tfor _, f := range filter {\n 725→\t\tif f.State != nil {\n 726→\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n 727→\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n 728→\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 729→\t\t\t\treturn stat, nil\n 730→\t\t\t}\n 731→\t\t}\n 732→\t}\n 733→\n 734→\t// All other cases: Query and make bins in sqlite directly\n 735→\tfor _, m := range metrics {\n 736→\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n 737→\t\tif err != nil {\n 738→\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n 739→\t\t\tcontinue\n 740→\t\t}\n 741→\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n 742→\t}\n 743→\n 744→\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 745→\treturn stat, nil\n 746→}\n 747→\n 748→// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n 749→//\n 750→// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n 751→// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n 752→//\n 753→// Parameters:\n 754→// - value: SQL expression that produces the histogram value, aliased as \"value\"\n 755→// - filters: Job filters to apply\n 756→//\n 757→// Returns histogram points with Value (from column) and Count (number of jobs).\n 758→func (r *JobRepository) jobsStatisticsHistogram(\n 759→\tctx context.Context,\n 760→\tvalue string,\n 761→\tfilters []*model.JobFilter,\n 762→) ([]*model.HistoPoint, error) {\n 763→\tstart := time.Now()\n 764→\tquery, qerr := SecurityCheck(ctx,\n 765→\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n 766→\n 767→\tif qerr != nil {\n 768→\t\treturn nil, qerr\n 769→\t}\n 770→\n 771→\tfor _, f := range filters {\n 772→\t\tquery = BuildWhereClause(f, query)\n 773→\t}\n 774→\n 775→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n 776→\tif err != nil {\n 777→\t\tcclog.Error(\"Error while running query\")\n 778→\t\treturn nil, err\n 779→\t}\n 780→\tdefer rows.Close()\n 781→\n 782→\tpoints := make([]*model.HistoPoint, 0)\n 783→\t// is it possible to introduce zero values here? requires info about bincount\n 784→\tfor rows.Next() {\n 785→\t\tpoint := model.HistoPoint{}\n 786→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 787→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 788→\t\t\treturn nil, err\n 789→\t\t}\n 790→\n 791→\t\tpoints = append(points, &point)\n 792→\t}\n 793→\n 794→\tif err := rows.Err(); err != nil {\n 795→\t\treturn nil, err\n 796→\t}\n 797→\n 798→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 799→\treturn points, nil\n 800→}\n 801→\n 802→// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n 803→//\n 804→// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n 805→// histograms which only return bins with data. The value parameter should compute\n 806→// the bin number from job duration.\n 807→//\n 808→// Parameters:\n 809→// - value: SQL expression computing bin number from duration, aliased as \"value\"\n 810→// - filters: Job filters to apply\n 811→// - binSizeSeconds: Width of each bin in seconds\n 812→// - targetBinCount: Number of bins to pre-initialize\n 813→//\n 814→// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n 815→// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n 816→//\n 817→// Algorithm:\n 818→// 1. Pre-initialize targetBinCount bins with zero counts\n 819→// 2. Query database for actual counts per bin\n 820→// 3. Match query results to pre-initialized bins by value\n 821→// 4. Bins without matches remain at zero\n 822→func (r *JobRepository) jobsDurationStatisticsHistogram(\n 823→\tctx context.Context,\n 824→\tvalue string,\n 825→\tfilters []*model.JobFilter,\n 826→\tbinSizeSeconds int,\n 827→\ttargetBinCount *int,\n 828→) ([]*model.HistoPoint, error) {\n 829→\tstart := time.Now()\n 830→\tquery, qerr := SecurityCheck(ctx,\n 831→\t\tsq.Select(value, \"COUNT(*) AS count\").From(\"job\"))\n 832→\n 833→\tif qerr != nil {\n 834→\t\treturn nil, qerr\n 835→\t}\n 836→\n 837→\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n 838→\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n 839→\tpoints := make([]*model.HistoPoint, 0, *targetBinCount)\n 840→\tfor i := 1; i <= *targetBinCount; i++ {\n 841→\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n 842→\t\tpoints = append(points, &point)\n 843→\t}\n 844→\n 845→\t// Build a map from bin value (seconds) to slice index for O(1) lookup.\n 846→\tbinMap := make(map[int]int, len(points))\n 847→\tfor i, p := range points {\n 848→\t\tbinMap[p.Value] = i\n 849→\t}\n 850→\n 851→\tfor _, f := range filters {\n 852→\t\tquery = BuildWhereClause(f, query)\n 853→\t}\n 854→\n 855→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).QueryContext(ctx)\n 856→\tif err != nil {\n 857→\t\tcclog.Error(\"Error while running query\")\n 858→\t\treturn nil, err\n 859→\t}\n 860→\tdefer rows.Close()\n 861→\n 862→\t// Match query results to pre-initialized bins using map lookup.\n 863→\t// point.Value from query is the bin number; multiply by binSizeSeconds to get bin key.\n 864→\tfor rows.Next() {\n 865→\t\tpoint := model.HistoPoint{}\n 866→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 867→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 868→\t\t\treturn nil, err\n 869→\t\t}\n 870→\n 871→\t\tif idx, ok := binMap[point.Value*binSizeSeconds]; ok {\n 872→\t\t\tpoints[idx].Count = point.Count\n 873→\t\t}\n 874→\t}\n 875→\n 876→\tif err := rows.Err(); err != nil {\n 877→\t\treturn nil, err\n 878→\t}\n 879→\n 880→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 881→\treturn points, nil\n 882→}\n 883→\n 884→// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n 885→//\n 886→// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n 887→// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n 888→// and computing bin assignments in SQL.\n 889→//\n 890→// Parameters:\n 891→// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n 892→// - filters: Job filters to apply\n 893→// - bins: Number of bins to generate\n 894→//\n 895→// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n 896→//\n 897→// Algorithm:\n 898→// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n 899→// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n 900→// 3. Pre-initialize bins with min/max ranges based on peak value\n 901→// 4. Query database for counts per bin\n 902→// 5. Match results to pre-initialized bins\n 903→//\n 904→// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n 905→// peak by 0.999999999 to avoid creating an extra bin.\n 906→func (r *JobRepository) jobsMetricStatisticsHistogram(\n 907→\tctx context.Context,\n 908→\tmetric string,\n 909→\tfilters []*model.JobFilter,\n 910→\tbins *int,\n 911→) (*model.MetricHistoPoints, error) {\n 912→\t// Peak value defines the upper bound for binning: values are distributed across\n 913→\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n 914→\t// scan all clusters to find the maximum peak value.\n 915→\tvar metricConfig *schema.MetricConfig\n 916→\tvar peak float64\n 917→\tvar unit string\n 918→\tvar footprintStat string\n 919→\n 920→\t// Try to get metric config from filtered cluster\n 921→\tfor _, f := range filters {\n 922→\t\tif f.Cluster != nil {\n 923→\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 924→\t\t\tpeak = metricConfig.Peak\n 925→\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 926→\t\t\tfootprintStat = metricConfig.Footprint\n 927→\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n 928→\t\t}\n 929→\t}\n 930→\n 931→\t// If no cluster filter or peak not found, find largest peak across all clusters\n 932→\t// This ensures histogram can accommodate all possible values\n 933→\tif peak == 0.0 {\n 934→\t\tfor _, c := range archive.Clusters {\n 935→\t\t\tfor _, m := range c.MetricConfig {\n 936→\t\t\t\tif m.Name == metric {\n 937→\t\t\t\t\tif m.Peak > peak {\n 938→\t\t\t\t\t\tpeak = m.Peak\n 939→\t\t\t\t\t}\n 940→\t\t\t\t\tif unit == \"\" {\n 941→\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 942→\t\t\t\t\t}\n 943→\t\t\t\t\tif footprintStat == \"\" {\n 944→\t\t\t\t\t\tfootprintStat = m.Footprint\n 945→\t\t\t\t\t}\n 946→\t\t\t\t}\n 947→\t\t\t}\n 948→\t\t}\n 949→\t}\n 950→\n 951→\t// Construct SQL histogram bins using normalized values.\n 952→\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n 953→\tstart := time.Now()\n 954→\n 955→\t// Bin calculation formula:\n 956→\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n 957→\t// Special case: value == peak would create bin N+1, so we test for equality\n 958→\t// and multiply peak by 0.999999999 to force it into bin N.\n 959→\tbinQuery := fmt.Sprintf(`CAST(\n 960→\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n 961→\t\t* %v as INTEGER )`,\n 962→\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n 963→\n 964→\tmainQuery := sq.Select(\n 965→\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n 966→\t\t`count(*) as count`,\n 967→\t).From(\"job\").Where(\n 968→\t\t\"JSON_VALID(footprint)\",\n 969→\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n 970→\n 971→\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n 972→\tif qerr != nil {\n 973→\t\treturn nil, qerr\n 974→\t}\n 975→\n 976→\tfor _, f := range filters {\n 977→\t\tmainQuery = BuildWhereClause(f, mainQuery)\n 978→\t}\n 979→\n 980→\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n 981→\n 982→\trows, err := mainQuery.RunWith(r.DB).QueryContext(ctx)\n 983→\tif err != nil {\n 984→\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n 985→\t\treturn nil, err\n 986→\t}\n 987→\tdefer rows.Close()\n 988→\n 989→\t// Pre-initialize bins with calculated min/max ranges.\n 990→\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n 991→\tpoints := make([]*model.MetricHistoPoint, 0, *bins)\n 992→\tbinStep := int(peak) / *bins\n 993→\tfor i := 1; i <= *bins; i++ {\n 994→\t\tbinMin := (binStep * (i - 1))\n 995→\t\tbinMax := (binStep * i)\n 996→\t\tidx := i\n 997→\t\tepoint := model.MetricHistoPoint{Bin: &idx, Count: 0, Min: &binMin, Max: &binMax}\n 998→\t\tpoints = append(points, &epoint)\n 999→\t}\n 1000→\n 1001→\t// Build a map from bin number to slice index for O(1) lookup.\n 1002→\tbinMap := make(map[int]int, len(points))\n 1003→\tfor i, p := range points {\n 1004→\t\tif p.Bin != nil {\n 1005→\t\t\tbinMap[*p.Bin] = i\n 1006→\t\t}\n 1007→\t}\n 1008→\n 1009→\t// Match query results to pre-initialized bins using map lookup.\n 1010→\tfor rows.Next() {\n 1011→\t\trpoint := model.MetricHistoPoint{}\n 1012→\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n 1013→\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n 1014→\t\t\treturn nil, err\n 1015→\t\t}\n 1016→\n 1017→\t\tif rpoint.Bin != nil {\n 1018→\t\t\tif idx, ok := binMap[*rpoint.Bin]; ok {\n 1019→\t\t\t\tpoints[idx].Count = rpoint.Count\n 1020→\t\t\t}\n 1021→\t\t}\n 1022→\t}\n 1023→\n 1024→\tif err := rows.Err(); err != nil {\n 1025→\t\treturn nil, err\n 1026→\t}\n 1027→\n 1028→\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n 1029→\n 1030→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 1031→\treturn &result, nil\n 1032→}\n 1033→\n 1034→// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n 1035→//\n 1036→// Unlike completed jobs which use footprint data from the database, running jobs require\n 1037→// fetching current metric averages from the metric backend (via metricdispatch).\n 1038→//\n 1039→// Parameters:\n 1040→// - metrics: List of metric names\n 1041→// - filters: Job filters (should filter to running jobs only)\n 1042→// - bins: Number of histogram bins\n 1043→//\n 1044→// Returns slice of MetricHistoPoints, one per metric.\n 1045→//\n 1046→// Limitations:\n 1047→// - Maximum 5000 jobs (returns nil if more jobs match)\n 1048→// - Requires metric backend availability\n 1049→// - Bins based on metric peak values from cluster configuration\n 1050→//\n 1051→// Algorithm:\n 1052→// 1. Query first 5001 jobs to check count limit\n 1053→// 2. Load metric averages for all jobs via metricdispatch\n 1054→// 3. For each metric, create bins based on peak value\n 1055→// 4. Iterate averages and count jobs per bin\n 1056→func (r *JobRepository) runningJobsMetricStatisticsHistogram(\n 1057→\tctx context.Context,\n 1058→\tmetrics []string,\n 1059→\tfilters []*model.JobFilter,\n 1060→\tbins *int,\n 1061→) []*model.MetricHistoPoints {\n 1062→\t// Get Jobs\n 1063→\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n 1064→\tif err != nil {\n 1065→\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n 1066→\t\treturn nil\n 1067→\t}\n 1068→\tif len(jobs) > 5000 {\n 1069→\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n 1070→\t\treturn nil\n 1071→\t}\n 1072→\n 1073→\t// Get AVGs from metric repo\n 1074→\tavgs := make([][]schema.Float, len(metrics))\n 1075→\tfor i := range avgs {\n 1076→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n 1077→\t}\n 1078→\n 1079→\tfor _, job := range jobs {\n 1080→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 1081→\t\t\tcontinue\n 1082→\t\t}\n 1083→\n 1084→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n 1085→\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n 1086→\t\t\treturn nil\n 1087→\t\t}\n 1088→\t}\n 1089→\n 1090→\t// Iterate metrics to fill endresult\n 1091→\tdata := make([]*model.MetricHistoPoints, 0)\n 1092→\tfor idx, metric := range metrics {\n 1093→\t\t// Get specific Peak or largest Peak\n 1094→\t\tvar metricConfig *schema.MetricConfig\n 1095→\t\tvar peak float64\n 1096→\t\tvar unit string\n 1097→\n 1098→\t\tfor _, f := range filters {\n 1099→\t\t\tif f.Cluster != nil {\n 1100→\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 1101→\t\t\t\tpeak = metricConfig.Peak\n 1102→\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 1103→\t\t\t}\n 1104→\t\t}\n 1105→\n 1106→\t\tif peak == 0.0 {\n 1107→\t\t\tfor _, c := range archive.Clusters {\n 1108→\t\t\t\tfor _, m := range c.MetricConfig {\n 1109→\t\t\t\t\tif m.Name == metric {\n 1110→\t\t\t\t\t\tif m.Peak > peak {\n 1111→\t\t\t\t\t\t\tpeak = m.Peak\n 1112→\t\t\t\t\t\t}\n 1113→\t\t\t\t\t\tif unit == \"\" {\n 1114→\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 1115→\t\t\t\t\t\t}\n 1116→\t\t\t\t\t}\n 1117→\t\t\t\t}\n 1118→\t\t\t}\n 1119→\t\t}\n 1120→\n 1121→\t\t// Make and fill bins\n 1122→\t\tpeakBin := int(peak) / *bins\n 1123→\n 1124→\t\tpoints := make([]*model.MetricHistoPoint, 0)\n 1125→\t\tfor b := 0; b < *bins; b++ {\n 1126→\t\t\tcount := 0\n 1127→\t\t\tbindex := b + 1\n 1128→\t\t\tbmin := peakBin * b\n 1129→\t\t\tbmax := peakBin * (b + 1)\n 1130→\n 1131→\t\t\t// Iterate AVG values for indexed metric and count for bins\n 1132→\t\t\tfor _, val := range avgs[idx] {\n 1133→\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n 1134→\t\t\t\t\tcount += 1\n 1135→\t\t\t\t}\n 1136→\t\t\t}\n 1137→\n 1138→\t\t\t// Append Bin to Metric Result Array\n 1139→\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n 1140→\t\t\tpoints = append(points, &point)\n 1141→\t\t}\n 1142→\n 1143→\t\t// Append Metric Result Array to final results array\n 1144→\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n 1145→\t\tdata = append(data, &result)\n 1146→\t}\n 1147→\n 1148→\treturn data\n 1149→}\n 1150→"}]},"uuid":"dd0b639f-6949-4db5-855d-6824ea0f9458","timestamp":"2026-03-13T14:11:09.514Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"5e272231-8f96-456b-843f-3ea00519dfbf","timestamp":"2026-03-13T14:11:09.575Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5e272231-8f96-456b-843f-3ea00519dfbf","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WFwXZph4GrZ6BiX1xQZmYK","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 repository provides job query functionality with filtering, pagination,\n 7→// and security controls. This file contains the main query builders and security\n 8→// checks for job retrieval operations.\n 9→package repository\n 10→\n 11→import (\n 12→\t\"context\"\n 13→\t\"errors\"\n 14→\t\"fmt\"\n 15→\t\"regexp\"\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/model\"\n 21→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 22→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 23→\tsq \"github.com/Masterminds/squirrel\"\n 24→)\n 25→\n 26→const (\n 27→\t// Default initial capacity for job result slices\n 28→\tdefaultJobsCapacity = 50\n 29→)\n 30→\n 31→// QueryJobs retrieves jobs from the database with optional filtering, pagination,\n 32→// and sorting. Security controls are automatically applied based on the user context.\n 33→//\n 34→// Parameters:\n 35→// - ctx: Context containing user authentication information\n 36→// - filters: Optional job filters (cluster, state, user, time ranges, etc.)\n 37→// - page: Optional pagination parameters (page number and items per page)\n 38→// - order: Optional sorting specification (column or footprint field)\n 39→//\n 40→// Returns a slice of jobs matching the criteria, or an error if the query fails.\n 41→// The function enforces role-based access control through SecurityCheck.\n 42→func (r *JobRepository) QueryJobs(\n 43→\tctx context.Context,\n 44→\tfilters []*model.JobFilter,\n 45→\tpage *model.PageRequest,\n 46→\torder *model.OrderByInput,\n 47→) ([]*schema.Job, error) {\n 48→\tquery, qerr := SecurityCheck(ctx, sq.Select(jobColumns...).From(\"job\"))\n 49→\tif qerr != nil {\n 50→\t\treturn nil, qerr\n 51→\t}\n 52→\n 53→\tif order != nil {\n 54→\t\tfield := toSnakeCase(order.Field)\n 55→\t\tif order.Type == \"col\" {\n 56→\t\t\tswitch order.Order {\n 57→\t\t\tcase model.SortDirectionEnumAsc:\n 58→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s ASC\", field))\n 59→\t\t\tcase model.SortDirectionEnumDesc:\n 60→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s DESC\", field))\n 61→\t\t\tdefault:\n 62→\t\t\t\treturn nil, errors.New(\"invalid sorting order for column\")\n 63→\t\t\t}\n 64→\t\t} else {\n 65→\t\t\t// Order by footprint JSON field values\n 66→\t\t\tquery = query.Where(\"JSON_VALID(footprint)\")\n 67→\t\t\tswitch order.Order {\n 68→\t\t\tcase model.SortDirectionEnumAsc:\n 69→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") ASC\", field))\n 70→\t\t\tcase model.SortDirectionEnumDesc:\n 71→\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") DESC\", field))\n 72→\t\t\tdefault:\n 73→\t\t\t\treturn nil, errors.New(\"invalid sorting order for footprint\")\n 74→\t\t\t}\n 75→\t\t}\n 76→\t}\n 77→\n 78→\tif page != nil && page.ItemsPerPage != -1 {\n 79→\t\tlimit := uint64(page.ItemsPerPage)\n 80→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 81→\t}\n 82→\n 83→\tfor _, f := range filters {\n 84→\t\tquery = BuildWhereClause(f, query)\n 85→\t}\n 86→\n 87→\trows, err := query.RunWith(r.stmtCache).QueryContext(ctx)\n 88→\tif err != nil {\n 89→\t\tqueryString, queryVars, _ := query.ToSql()\n 90→\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n 91→\t}\n 92→\tdefer rows.Close()\n 93→\n 94→\tjobs := make([]*schema.Job, 0, defaultJobsCapacity)\n 95→\tfor rows.Next() {\n 96→\t\tjob, err := scanJob(rows)\n 97→\t\tif err != nil {\n 98→\t\t\tcclog.Warnf(\"Error scanning job row: %v\", err)\n 99→\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n 100→\t\t}\n 101→\t\tjobs = append(jobs, job)\n 102→\t}\n 103→\n 104→\tif err := rows.Err(); err != nil {\n 105→\t\treturn nil, fmt.Errorf(\"error iterating job rows: %w\", err)\n 106→\t}\n 107→\n 108→\treturn jobs, nil\n 109→}\n 110→\n 111→// CountJobs returns the total number of jobs matching the given filters.\n 112→// Security controls are automatically applied based on the user context.\n 113→// Uses DISTINCT count to handle tag filters correctly (jobs may appear multiple\n 114→// times when joined with the tag table).\n 115→func (r *JobRepository) CountJobs(\n 116→\tctx context.Context,\n 117→\tfilters []*model.JobFilter,\n 118→) (int, error) {\n 119→\tquery, qerr := SecurityCheck(ctx, sq.Select(\"count(DISTINCT job.id)\").From(\"job\"))\n 120→\tif qerr != nil {\n 121→\t\treturn 0, qerr\n 122→\t}\n 123→\n 124→\tfor _, f := range filters {\n 125→\t\tquery = BuildWhereClause(f, query)\n 126→\t}\n 127→\n 128→\tvar count int\n 129→\tif err := query.RunWith(r.DB).QueryRowContext(ctx).Scan(&count); err != nil {\n 130→\t\treturn 0, fmt.Errorf(\"failed to count jobs: %w\", err)\n 131→\t}\n 132→\n 133→\treturn count, nil\n 134→}\n 135→\n 136→// SecurityCheckWithUser applies role-based access control filters to a job query\n 137→// based on the provided user's roles and permissions.\n 138→//\n 139→// Access rules by role:\n 140→// - API role (exclusive): Full access to all jobs\n 141→// - Admin/Support roles: Full access to all jobs\n 142→// - Manager role: Access to jobs in managed projects plus own jobs\n 143→// - User role: Access only to own jobs\n 144→//\n 145→// Returns an error if the user is nil or has no recognized roles.\n 146→func SecurityCheckWithUser(user *schema.User, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n 147→\tif user == nil {\n 148→\t\tvar qnil sq.SelectBuilder\n 149→\t\treturn qnil, fmt.Errorf(\"user context is nil\")\n 150→\t}\n 151→\n 152→\tswitch {\n 153→\tcase len(user.Roles) == 1 && user.HasRole(schema.RoleAPI):\n 154→\t\treturn query, nil\n 155→\tcase user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}):\n 156→\t\treturn query, nil\n 157→\tcase user.HasRole(schema.RoleManager):\n 158→\t\tif len(user.Projects) != 0 {\n 159→\t\t\treturn query.Where(sq.Or{sq.Eq{\"job.project\": user.Projects}, sq.Eq{\"job.hpc_user\": user.Username}}), nil\n 160→\t\t}\n 161→\t\tcclog.Debugf(\"Manager '%s' has no assigned projects, restricting to personal jobs\", user.Username)\n 162→\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n 163→\tcase user.HasRole(schema.RoleUser):\n 164→\t\treturn query.Where(\"job.hpc_user = ?\", user.Username), nil\n 165→\tdefault:\n 166→\t\tvar qnil sq.SelectBuilder\n 167→\t\treturn qnil, fmt.Errorf(\"user has no or unknown roles\")\n 168→\t}\n 169→}\n 170→\n 171→// SecurityCheck extracts the user from the context and applies role-based access\n 172→// control filters to the query. This is a convenience wrapper around SecurityCheckWithUser.\n 173→func SecurityCheck(ctx context.Context, query sq.SelectBuilder) (sq.SelectBuilder, error) {\n 174→\tuser := GetUserFromContext(ctx)\n 175→\treturn SecurityCheckWithUser(user, query)\n 176→}\n 177→\n 178→// BuildWhereClause constructs SQL WHERE conditions from a JobFilter and applies\n 179→// them to the query. Supports filtering by job properties (cluster, state, user),\n 180→// time ranges, resource usage, tags, and JSON field searches in meta_data,\n 181→// footprint, and resources columns.\n 182→func BuildWhereClause(filter *model.JobFilter, query sq.SelectBuilder) sq.SelectBuilder {\n 183→\t// Primary Key\n 184→\tif filter.DbID != nil {\n 185→\t\tdbIDs := make([]string, len(filter.DbID))\n 186→\t\tcopy(dbIDs, filter.DbID)\n 187→\t\tquery = query.Where(sq.Eq{\"job.id\": dbIDs})\n 188→\t}\n 189→\t// Explicit indices\n 190→\tif filter.Cluster != nil {\n 191→\t\tquery = buildStringCondition(\"job.cluster\", filter.Cluster, query)\n 192→\t}\n 193→\tif filter.SubCluster != nil {\n 194→\t\tquery = buildStringCondition(\"job.subcluster\", filter.SubCluster, query)\n 195→\t}\n 196→\tif filter.Partition != nil {\n 197→\t\tquery = buildStringCondition(\"job.cluster_partition\", filter.Partition, query)\n 198→\t}\n 199→\tif filter.State != nil {\n 200→\t\tif len(filter.State) == 1 {\n 201→\t\t\t// Inline literal value so SQLite can match partial indexes (WHERE job_state = 'running').\n 202→\t\t\t// Safe: values come from validated GraphQL enum (model.JobState).\n 203→\t\t\tsingleStat := string(filter.State[0])\n 204→\t\t\tquery = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))\n 205→\t\t} else {\n 206→\t\t\tstates := make([]string, len(filter.State))\n 207→\t\t\tfor i, val := range filter.State {\n 208→\t\t\t\tstates[i] = string(val)\n 209→\t\t\t}\n 210→\t\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n 211→\t\t}\n 212→\t}\n 213→\tif filter.Shared != nil {\n 214→\t\tquery = query.Where(\"job.shared = ?\", *filter.Shared)\n 215→\t}\n 216→\tif filter.Project != nil {\n 217→\t\tquery = buildStringCondition(\"job.project\", filter.Project, query)\n 218→\t}\n 219→\tif filter.User != nil {\n 220→\t\tquery = buildStringCondition(\"job.hpc_user\", filter.User, query)\n 221→\t}\n 222→\tif filter.NumNodes != nil {\n 223→\t\tquery = buildIntCondition(\"job.num_nodes\", filter.NumNodes, query)\n 224→\t}\n 225→\tif filter.NumAccelerators != nil {\n 226→\t\tquery = buildIntCondition(\"job.num_acc\", filter.NumAccelerators, query)\n 227→\t}\n 228→\tif filter.NumHWThreads != nil {\n 229→\t\tquery = buildIntCondition(\"job.num_hwthreads\", filter.NumHWThreads, query)\n 230→\t}\n 231→\tif filter.ArrayJobID != nil {\n 232→\t\tquery = query.Where(\"job.array_job_id = ?\", *filter.ArrayJobID)\n 233→\t}\n 234→\tif filter.StartTime != nil {\n 235→\t\tquery = buildTimeCondition(\"job.start_time\", filter.StartTime, query)\n 236→\t}\n 237→\tif filter.Duration != nil {\n 238→\t\tquery = buildIntCondition(\"job.duration\", filter.Duration, query)\n 239→\t}\n 240→\tif filter.Energy != nil {\n 241→\t\tquery = buildFloatCondition(\"job.energy\", filter.Energy, query)\n 242→\t}\n 243→\t// Indices on Tag Table\n 244→\tif filter.Tags != nil {\n 245→\t\t// This is an OR-Logic query: Returns all distinct jobs with at least one of the requested tags; TODO: AND-Logic query?\n 246→\t\tquery = query.Join(\"jobtag ON jobtag.job_id = job.id\").Where(sq.Eq{\"jobtag.tag_id\": filter.Tags}).Distinct()\n 247→\t}\n 248→\t// No explicit Indices\n 249→\tif filter.JobID != nil {\n 250→\t\tquery = buildStringCondition(\"job.job_id\", filter.JobID, query)\n 251→\t}\n 252→\t// Queries Within JSONs\n 253→\tif filter.MetricStats != nil {\n 254→\t\tfor _, ms := range filter.MetricStats {\n 255→\t\t\tquery = buildFloatJSONCondition(ms.MetricName, ms.Range, query)\n 256→\t\t}\n 257→\t}\n 258→\tif filter.Node != nil {\n 259→\t\tquery = buildResourceJSONCondition(\"hostname\", filter.Node, query)\n 260→\t}\n 261→\tif filter.JobName != nil {\n 262→\t\tquery = buildMetaJSONCondition(\"jobName\", filter.JobName, query)\n 263→\t}\n 264→\tif filter.Schedule != nil {\n 265→\t\tinteractiveJobname := \"interactive\"\n 266→\t\tswitch *filter.Schedule {\n 267→\t\tcase \"interactive\":\n 268→\t\t\tiFilter := model.StringInput{Eq: &interactiveJobname}\n 269→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &iFilter, query)\n 270→\t\tcase \"batch\":\n 271→\t\t\tsFilter := model.StringInput{Neq: &interactiveJobname}\n 272→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &sFilter, query)\n 273→\t\t}\n 274→\t}\n 275→\n 276→\t// Configurable Filter to exclude recently started jobs, see config.go: ShortRunningJobsDuration\n 277→\tif filter.MinRunningFor != nil {\n 278→\t\tnow := time.Now().Unix()\n 279→\t\t// Only jobs whose start timestamp is more than MinRunningFor seconds in the past\n 280→\t\t// If a job completed within the configured timeframe, it will still show up after the start_time matches the condition!\n 281→\t\tquery = query.Where(sq.Lt{\"job.start_time\": (now - int64(*filter.MinRunningFor))})\n 282→\t}\n 283→\treturn query\n 284→}\n 285→\n 286→// buildIntCondition creates clauses for integer range filters, using BETWEEN only if required.\n 287→func buildIntCondition(field string, cond *config.IntRange, query sq.SelectBuilder) sq.SelectBuilder {\n 288→\tif cond.From != 1 && cond.To != 0 {\n 289→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 290→\t} else if cond.From != 1 && cond.To == 0 {\n 291→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 292→\t} else if cond.From == 1 && cond.To != 0 {\n 293→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 294→\t} else {\n 295→\t\treturn query\n 296→\t}\n 297→}\n 298→\n 299→// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\n 300→func buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 301→\tif cond.From != 1.0 && cond.To != 0.0 {\n 302→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 303→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 304→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 305→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 306→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 307→\t} else {\n 308→\t\treturn query\n 309→\t}\n 310→}\n 311→\n 312→// buildTimeCondition creates time range filters supporting absolute timestamps,\n 313→// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n 314→// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\n 315→func buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n 316→\tif cond.From != nil && cond.To != nil {\n 317→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n 318→\t} else if cond.From != nil {\n 319→\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n 320→\t} else if cond.To != nil {\n 321→\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n 322→\t} else if cond.Range != \"\" {\n 323→\t\tnow := time.Now().Unix()\n 324→\t\tvar then int64\n 325→\t\tswitch cond.Range {\n 326→\t\tcase \"last6h\":\n 327→\t\t\tthen = now - (60 * 60 * 6)\n 328→\t\tcase \"last24h\":\n 329→\t\t\tthen = now - (60 * 60 * 24)\n 330→\t\tcase \"last7d\":\n 331→\t\t\tthen = now - (60 * 60 * 24 * 7)\n 332→\t\tcase \"last30d\":\n 333→\t\t\tthen = now - (60 * 60 * 24 * 30)\n 334→\t\tdefault:\n 335→\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n 336→\t\t\treturn query\n 337→\t\t}\n 338→\t\treturn query.Where(field+\" >= ?\", then)\n 339→\t} else {\n 340→\t\treturn query\n 341→\t}\n 342→}\n 343→\n 344→// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\n 345→func buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 346→\tquery = query.Where(\"JSON_VALID(footprint)\")\n 347→\tif cond.From != 1.0 && cond.To != 0.0 {\n 348→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n 349→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 350→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n 351→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 352→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n 353→\t} else {\n 354→\t\treturn query\n 355→\t}\n 356→}\n 357→\n 358→// buildStringCondition creates filters for string fields supporting equality,\n 359→// inequality, prefix, suffix, substring, and IN list matching.\n 360→func buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 361→\tif cond.Eq != nil {\n 362→\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n 363→\t}\n 364→\tif cond.Neq != nil {\n 365→\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n 366→\t}\n 367→\tif cond.StartsWith != nil {\n 368→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 369→\t}\n 370→\tif cond.EndsWith != nil {\n 371→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 372→\t}\n 373→\tif cond.Contains != nil {\n 374→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 375→\t}\n 376→\tif cond.In != nil {\n 377→\t\tqueryElements := make([]string, len(cond.In))\n 378→\t\tcopy(queryElements, cond.In)\n 379→\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n 380→\t}\n 381→\treturn query\n 382→}\n 383→\n 384→// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\n 385→func buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 386→\tquery = query.Where(\"JSON_VALID(meta_data)\")\n 387→\tif cond.Eq != nil {\n 388→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n 389→\t}\n 390→\tif cond.Neq != nil {\n 391→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n 392→\t}\n 393→\tif cond.StartsWith != nil {\n 394→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 395→\t}\n 396→\tif cond.EndsWith != nil {\n 397→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 398→\t}\n 399→\tif cond.Contains != nil {\n 400→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 401→\t}\n 402→\treturn query\n 403→}\n 404→\n 405→// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n 406→// Uses json_each to search within array elements.\n 407→func buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 408→\tquery = query.Where(\"JSON_VALID(resources)\")\n 409→\tif cond.Eq != nil {\n 410→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n 411→\t}\n 412→\tif cond.Neq != nil { // Currently Unused\n 413→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n 414→\t}\n 415→\tif cond.StartsWith != nil { // Currently Unused\n 416→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 417→\t}\n 418→\tif cond.EndsWith != nil { // Currently Unused\n 419→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n 420→\t}\n 421→\tif cond.Contains != nil {\n 422→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 423→\t}\n 424→\treturn query\n 425→}\n 426→\n 427→var (\n 428→\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n 429→\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n 430→)\n 431→\n 432→// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n 433→// Includes security checks to prevent SQL injection attempts.\n 434→// Panics if potentially dangerous characters are detected.\n 435→func toSnakeCase(str string) string {\n 436→\tfor _, c := range str {\n 437→\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n 438→\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n 439→\t\t}\n 440→\t}\n 441→\n 442→\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n 443→\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n 444→\treturn strings.ToLower(snake)\n 445→}\n 446→"}]},"uuid":"b51ae835-87b1-4eb2-a538-fccddaec12df","timestamp":"2026-03-13T14:11:09.347Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"016af23b-9293-4b33-81b2-287a8e5b408f","timestamp":"2026-03-13T14:11:09.576Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"939a2696-b97a-4b6a-abf9-d5285b66653a","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01X9F3YaGF9o8Ujnkz4pWCH9","type":"tool_result","content":"\nOutput too large (49.5KB). Full output saved to: /Users/jan/.claude/projects/-Users-jan-prg-ClusterCockpit-cc-backend/889ef150-c6ca-4f35-81e5-c19dc95fe399/tool-results/REDACTED.txt\n\nPreview (first 2KB):\n 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// Package repository provides the data access layer for cc-backend using the repository pattern.\n 7→//\n 8→// The repository pattern abstracts database operations and provides a clean interface for\n 9→// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n 10→// operations and specialized queries.\n 11→//\n 12→// # Database Connection\n 13→//\n 14→// Initialize the database connection before using any repository:\n 15→//\n 16→//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n 17→//\n 18→// # Configuration\n 19→//\n 20→// Optional: Configure repository settings before initialization:\n 21→//\n 22→//\trepository.SetConfig(&repository.RepositoryConfig{\n 23→//\t CacheSize: 2 * 1024 * 1024, // 2MB cache\n 24→//\t MaxOpenConnections: 8, // Connection pool size\n 25→//\t MinRunningJobDuration: 300, // Filter threshold\n 26→//\t})\n 27→//\n 28→// If not configured, sensible defaults are used automatically.\n 29→//\n 30→// # Repositories\n 31→//\n 32→// - JobRepository: Job lifecycle management and querying\n 33→// - UserRepository: User management and authentication\n 34→// - NodeRepository: Cluster node state tracking\n 35→// - Tags: Job tagging and categorization\n 36→//\n 37→// # Caching\n 38→//\n 39→// Repositories use LRU caching to improve performance. Cache keys are constructed\n 40→// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n 41→// mutations to maintain consistency.\n 42→//\n 43→// # Transaction Support\n 44→//\n 45→// For batch operations, use transactions:\n 46→//\n 47→//\tt, err := jobRepo.TransactionInit()\n...\n"}]},"uuid":"17f0f64f-0891-48a3-94b8-7930d3ed96fb","timestamp":"2026-03-13T14:11:09.796Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"5c9114de-0408-440c-80b8-a10a3384e92c","timestamp":"2026-03-13T14:11:09.799Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"5c9114de-0408-440c-80b8-a10a3384e92c","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-13T14:11:09.799Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01Fhfb93Fhobxx5SVNqmGBrG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_019zZLoPC9GPMR4LVYfm78mD","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobCreate.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":869,"cache_read_input_tokens":17392,"cache_creation":{"ephemeral_5m_input_tokens":869,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ1DPZA5cvSxMGtyDmgvH","uuid":"5ae01326-7a22-470d-abb0-b29f19a27835"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"a272b4ea-9d3e-418f-b098-e45c8c7d263a","timestamp":"2026-03-13T14:11:09.799Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a272b4ea-9d3e-418f-b098-e45c8c7d263a","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019zZLoPC9GPMR4LVYfm78mD","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 repository\n 7→\n 8→import (\n 9→\t\"encoding/json\"\n 10→\t\"fmt\"\n 11→\n 12→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 13→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 14→\tsq \"github.com/Masterminds/squirrel\"\n 15→)\n 16→\n 17→const NamedJobCacheInsert string = `INSERT INTO job_cache (\n 18→\tjob_id, hpc_user, project, cluster, subcluster, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc,\n 19→\tshared, monitoring_status, smt, job_state, start_time, duration, walltime, footprint, energy, energy_footprint, resources, meta_data\n 20→) VALUES (\n 21→\t:job_id, :hpc_user, :project, :cluster, :subcluster, :cluster_partition, :array_job_id, :num_nodes, :num_hwthreads, :num_acc,\n 22→ :shared, :monitoring_status, :smt, :job_state, :start_time, :duration, :walltime, :footprint, :energy, :energy_footprint, :resources, :meta_data\n 23→);`\n 24→\n 25→const NamedJobInsert string = `INSERT INTO job (\n 26→\tjob_id, hpc_user, project, cluster, subcluster, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc,\n 27→\tshared, monitoring_status, smt, job_state, start_time, duration, walltime, footprint, energy, energy_footprint, resources, meta_data\n 28→) VALUES (\n 29→\t:job_id, :hpc_user, :project, :cluster, :subcluster, :cluster_partition, :array_job_id, :num_nodes, :num_hwthreads, :num_acc,\n 30→ :shared, :monitoring_status, :smt, :job_state, :start_time, :duration, :walltime, :footprint, :energy, :energy_footprint, :resources, :meta_data\n 31→);`\n 32→\n 33→// InsertJobDirect inserts a job directly into the job table (not job_cache).\n 34→// Use this when the returned ID will be used for operations on the job table\n 35→// (e.g., adding tags), or for imported jobs that are already completed.\n 36→func (r *JobRepository) InsertJobDirect(job *schema.Job) (int64, error) {\n 37→\tr.Mutex.Lock()\n 38→\tdefer r.Mutex.Unlock()\n 39→\n 40→\tres, err := r.DB.NamedExec(NamedJobInsert, job)\n 41→\tif err != nil {\n 42→\t\tcclog.Warn(\"Error while NamedJobInsert (direct)\")\n 43→\t\treturn 0, err\n 44→\t}\n 45→\tid, err := res.LastInsertId()\n 46→\tif err != nil {\n 47→\t\tcclog.Warn(\"Error while getting last insert ID (direct)\")\n 48→\t\treturn 0, err\n 49→\t}\n 50→\n 51→\treturn id, nil\n 52→}\n 53→\n 54→func (r *JobRepository) InsertJob(job *schema.Job) (int64, error) {\n 55→\tr.Mutex.Lock()\n 56→\tdefer r.Mutex.Unlock()\n 57→\n 58→\tres, err := r.DB.NamedExec(NamedJobCacheInsert, job)\n 59→\tif err != nil {\n 60→\t\tcclog.Warn(\"Error while NamedJobInsert\")\n 61→\t\treturn 0, err\n 62→\t}\n 63→\tid, err := res.LastInsertId()\n 64→\tif err != nil {\n 65→\t\tcclog.Warn(\"Error while getting last insert ID\")\n 66→\t\treturn 0, err\n 67→\t}\n 68→\n 69→\treturn id, nil\n 70→}\n 71→\n 72→func (r *JobRepository) SyncJobs() ([]*schema.Job, error) {\n 73→\tr.Mutex.Lock()\n 74→\tdefer r.Mutex.Unlock()\n 75→\n 76→\tquery := sq.Select(jobCacheColumns...).From(\"job_cache\")\n 77→\n 78→\trows, err := query.RunWith(r.stmtCache).Query()\n 79→\tif err != nil {\n 80→\t\tcclog.Errorf(\"Error while running query %v\", err)\n 81→\t\treturn nil, err\n 82→\t}\n 83→\tdefer rows.Close()\n 84→\n 85→\tjobs := make([]*schema.Job, 0, 50)\n 86→\tfor rows.Next() {\n 87→\t\tjob, err := scanJob(rows)\n 88→\t\tif err != nil {\n 89→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 90→\t\t\treturn nil, err\n 91→\t\t}\n 92→\t\tjobs = append(jobs, job)\n 93→\t}\n 94→\n 95→\t// Use INSERT OR IGNORE to skip jobs already transferred by the stop path\n 96→\t_, err = r.DB.Exec(\n 97→\t\t\"INSERT OR IGNORE INTO job (job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data) SELECT job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data FROM job_cache\")\n 98→\tif err != nil {\n 99→\t\tcclog.Errorf(\"Error while Job sync: %v\", err)\n 100→\t\treturn nil, err\n 101→\t}\n 102→\n 103→\t_, err = r.DB.Exec(\"DELETE FROM job_cache\")\n 104→\tif err != nil {\n 105→\t\tcclog.Errorf(\"Error while Job cache clean: %v\", err)\n 106→\t\treturn nil, err\n 107→\t}\n 108→\n 109→\t// Resolve correct job.id from the job table. The IDs read from job_cache\n 110→\t// are from a different auto-increment sequence and must not be used to\n 111→\t// query the job table.\n 112→\tfor _, job := range jobs {\n 113→\t\tvar newID int64\n 114→\t\tif err := sq.Select(\"job.id\").From(\"job\").\n 115→\t\t\tWhere(\"job.job_id = ? AND job.cluster = ? AND job.start_time = ?\",\n 116→\t\t\t\tjob.JobID, job.Cluster, job.StartTime).\n 117→\t\t\tRunWith(r.stmtCache).QueryRow().Scan(&newID); err != nil {\n 118→\t\t\tcclog.Warnf(\"SyncJobs: could not resolve job table id for job %d on %s: %v\",\n 119→\t\t\t\tjob.JobID, job.Cluster, err)\n 120→\t\t\tcontinue\n 121→\t\t}\n 122→\t\tjob.ID = &newID\n 123→\t}\n 124→\n 125→\treturn jobs, nil\n 126→}\n 127→\n 128→// TransferCachedJobToMain moves a job from job_cache to the job table.\n 129→// Caller must hold r.Mutex. Returns the new job table ID.\n 130→func (r *JobRepository) TransferCachedJobToMain(cacheID int64) (int64, error) {\n 131→\tres, err := r.DB.Exec(\n 132→\t\t\"INSERT INTO job (job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data) SELECT job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data FROM job_cache WHERE id = ?\",\n 133→\t\tcacheID)\n 134→\tif err != nil {\n 135→\t\treturn 0, fmt.Errorf(\"transferring cached job %d to main table failed: %w\", cacheID, err)\n 136→\t}\n 137→\n 138→\tnewID, err := res.LastInsertId()\n 139→\tif err != nil {\n 140→\t\treturn 0, fmt.Errorf(\"getting new job ID after transfer failed: %w\", err)\n 141→\t}\n 142→\n 143→\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", cacheID)\n 144→\tif err != nil {\n 145→\t\treturn 0, fmt.Errorf(\"deleting cached job %d after transfer failed: %w\", cacheID, err)\n 146→\t}\n 147→\n 148→\treturn newID, nil\n 149→}\n 150→\n 151→// Start inserts a new job in the table, returning the unique job ID.\n 152→// Statistics are not transfered!\n 153→func (r *JobRepository) Start(job *schema.Job) (id int64, err error) {\n 154→\tjob.RawFootprint, err = json.Marshal(job.Footprint)\n 155→\tif err != nil {\n 156→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding footprint field failed: %w\", err)\n 157→\t}\n 158→\n 159→\tjob.RawResources, err = json.Marshal(job.Resources)\n 160→\tif err != nil {\n 161→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding resources field failed: %w\", err)\n 162→\t}\n 163→\n 164→\tjob.RawMetaData, err = json.Marshal(job.MetaData)\n 165→\tif err != nil {\n 166→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding metaData field failed: %w\", err)\n 167→\t}\n 168→\n 169→\treturn r.InsertJob(job)\n 170→}\n 171→\n 172→// StartDirect inserts a new job directly into the job table (not job_cache).\n 173→// Use this when the returned ID will immediately be used for job table\n 174→// operations such as adding tags.\n 175→func (r *JobRepository) StartDirect(job *schema.Job) (id int64, err error) {\n 176→\tjob.RawFootprint, err = json.Marshal(job.Footprint)\n 177→\tif err != nil {\n 178→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding footprint field failed: %w\", err)\n 179→\t}\n 180→\n 181→\tjob.RawResources, err = json.Marshal(job.Resources)\n 182→\tif err != nil {\n 183→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding resources field failed: %w\", err)\n 184→\t}\n 185→\n 186→\tjob.RawMetaData, err = json.Marshal(job.MetaData)\n 187→\tif err != nil {\n 188→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding metaData field failed: %w\", err)\n 189→\t}\n 190→\n 191→\treturn r.InsertJobDirect(job)\n 192→}\n 193→\n 194→// Stop updates the job with the database id jobId using the provided arguments.\n 195→func (r *JobRepository) Stop(\n 196→\tjobID int64,\n 197→\tduration int32,\n 198→\tstate schema.JobState,\n 199→\tmonitoringStatus int32,\n 200→) (err error) {\n 201→\t// Invalidate cache entries as job state is changing\n 202→\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", jobID))\n 203→\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", jobID))\n 204→\n 205→\tstmt := sq.Update(\"job\").\n 206→\t\tSet(\"job_state\", state).\n 207→\t\tSet(\"duration\", duration).\n 208→\t\tSet(\"monitoring_status\", monitoringStatus).\n 209→\t\tWhere(\"job.id = ?\", jobID)\n 210→\n 211→\t_, err = stmt.RunWith(r.stmtCache).Exec()\n 212→\treturn err\n 213→}\n 214→"}]},"uuid":"208e9674-2c54-4170-a0df-e976f24b2dd3","timestamp":"2026-03-13T14:11:09.812Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"a1e1ee7b-7dfb-4e17-bb5d-c1cac3e716a1","timestamp":"2026-03-13T14:11:09.981Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"a1e1ee7b-7dfb-4e17-bb5d-c1cac3e716a1","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-13T14:11:10.001Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01Fhfb93Fhobxx5SVNqmGBrG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01A3ib8hMenZRABoGGvobf7k","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":869,"cache_read_input_tokens":17392,"cache_creation":{"ephemeral_5m_input_tokens":869,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ1DPZA5cvSxMGtyDmgvH","uuid":"13f69735-0ab2-4365-94c0-d8ea10c81d44"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"93c5bcd0-f24a-4705-857c-15bca8910681","timestamp":"2026-03-13T14:11:10.002Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"93c5bcd0-f24a-4705-857c-15bca8910681","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01A3ib8hMenZRABoGGvobf7k","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 repository\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"database/sql\"\n 11→\t\"fmt\"\n 12→\t\"time\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 15→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 16→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 17→\tsq \"github.com/Masterminds/squirrel\"\n 18→)\n 19→\n 20→// Find executes a SQL query to find a specific batch job.\n 21→// The job is queried using the batch job id, the cluster name,\n 22→// and the start time of the job in UNIX epoch time seconds.\n 23→// It returns a pointer to a schema.Job data structure and an error variable.\n 24→// To check if no job was found test err == sql.ErrNoRows\n 25→func (r *JobRepository) Find(\n 26→\tjobID *int64,\n 27→\tcluster *string,\n 28→\tstartTime *int64,\n 29→) (*schema.Job, error) {\n 30→\tif jobID == nil {\n 31→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 32→\t}\n 33→\n 34→\tstart := time.Now()\n 35→\tq := sq.Select(jobColumns...).From(\"job\").\n 36→\t\tWhere(\"job.job_id = ?\", *jobID)\n 37→\n 38→\tif cluster != nil {\n 39→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 40→\t}\n 41→\tif startTime != nil {\n 42→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 43→\t}\n 44→\n 45→\tq = q.OrderBy(\"job.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 46→\n 47→\tcclog.Debugf(\"Timer Find %s\", time.Since(start))\n 48→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 49→}\n 50→\n 51→// FindCached executes a SQL query to find a specific batch job from the job_cache table.\n 52→// The job is queried using the batch job id, and optionally filtered by cluster name\n 53→// and start time (UNIX epoch time seconds). This method uses cached job data which\n 54→// may be stale but provides faster access than Find().\n 55→// It returns a pointer to a schema.Job data structure and an error variable.\n 56→// To check if no job was found test err == sql.ErrNoRows\n 57→func (r *JobRepository) FindCached(\n 58→\tjobID *int64,\n 59→\tcluster *string,\n 60→\tstartTime *int64,\n 61→) (*schema.Job, error) {\n 62→\tif jobID == nil {\n 63→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 64→\t}\n 65→\n 66→\tq := sq.Select(jobCacheColumns...).From(\"job_cache\").\n 67→\t\tWhere(\"job_cache.job_id = ?\", *jobID)\n 68→\n 69→\tif cluster != nil {\n 70→\t\tq = q.Where(\"job_cache.cluster = ?\", *cluster)\n 71→\t}\n 72→\tif startTime != nil {\n 73→\t\tq = q.Where(\"job_cache.start_time = ?\", *startTime)\n 74→\t}\n 75→\n 76→\tq = q.OrderBy(\"job_cache.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 77→\n 78→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 79→}\n 80→\n 81→// FindAll executes a SQL query to find all batch jobs matching the given criteria.\n 82→// Jobs are queried using the batch job id, and optionally filtered by cluster name\n 83→// and start time (UNIX epoch time seconds).\n 84→// It returns a slice of pointers to schema.Job data structures and an error variable.\n 85→// An empty slice is returned if no matching jobs are found.\n 86→func (r *JobRepository) FindAll(\n 87→\tjobID *int64,\n 88→\tcluster *string,\n 89→\tstartTime *int64,\n 90→) ([]*schema.Job, error) {\n 91→\tif jobID == nil {\n 92→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 93→\t}\n 94→\n 95→\tstart := time.Now()\n 96→\tq := sq.Select(jobColumns...).From(\"job\").\n 97→\t\tWhere(\"job.job_id = ?\", *jobID)\n 98→\n 99→\tif cluster != nil {\n 100→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 101→\t}\n 102→\tif startTime != nil {\n 103→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 104→\t}\n 105→\n 106→\trows, err := q.RunWith(r.stmtCache).Query()\n 107→\tif err != nil {\n 108→\t\tcclog.Errorf(\"Error while running FindAll query for jobID=%d: %v\", *jobID, err)\n 109→\t\treturn nil, fmt.Errorf(\"failed to execute FindAll query: %w\", err)\n 110→\t}\n 111→\tdefer rows.Close()\n 112→\n 113→\tjobs := make([]*schema.Job, 0, 10)\n 114→\tfor rows.Next() {\n 115→\t\tjob, err := scanJob(rows)\n 116→\t\tif err != nil {\n 117→\t\t\tcclog.Warnf(\"Error while scanning rows in FindAll: %v\", err)\n 118→\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n 119→\t\t}\n 120→\t\tjobs = append(jobs, job)\n 121→\t}\n 122→\tcclog.Debugf(\"Timer FindAll %s\", time.Since(start))\n 123→\treturn jobs, nil\n 124→}\n 125→\n 126→// GetJobList returns job IDs for non-running jobs.\n 127→// This is useful to process large job counts and intended to be used\n 128→// together with FindById to process jobs one by one.\n 129→// Use limit and offset for pagination. Use limit=0 to get all results (not recommended for large datasets).\n 130→func (r *JobRepository) GetJobList(limit int, offset int) ([]int64, error) {\n 131→\tquery := sq.Select(\"id\").From(\"job\").\n 132→\t\tWhere(\"job.job_state != 'running'\")\n 133→\n 134→\t// Add pagination if limit is specified\n 135→\tif limit > 0 {\n 136→\t\tquery = query.Limit(uint64(limit)).Offset(uint64(offset))\n 137→\t}\n 138→\n 139→\trows, err := query.RunWith(r.stmtCache).Query()\n 140→\tif err != nil {\n 141→\t\tcclog.Errorf(\"Error while running GetJobList query (limit=%d, offset=%d): %v\", limit, offset, err)\n 142→\t\treturn nil, fmt.Errorf(\"failed to execute GetJobList query: %w\", err)\n 143→\t}\n 144→\tdefer rows.Close()\n 145→\n 146→\tjl := make([]int64, 0, 1000)\n 147→\tfor rows.Next() {\n 148→\t\tvar id int64\n 149→\t\terr := rows.Scan(&id)\n 150→\t\tif err != nil {\n 151→\t\t\tcclog.Warnf(\"Error while scanning rows in GetJobList: %v\", err)\n 152→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID: %w\", err)\n 153→\t\t}\n 154→\t\tjl = append(jl, id)\n 155→\t}\n 156→\n 157→\tcclog.Debugf(\"JobRepository.GetJobList(): Return job count %d\", len(jl))\n 158→\treturn jl, nil\n 159→}\n 160→\n 161→// FindByID executes a SQL query to find a specific batch job.\n 162→// The job is queried using the database id.\n 163→// It returns a pointer to a schema.Job data structure and an error variable.\n 164→// To check if no job was found test err == sql.ErrNoRows\n 165→func (r *JobRepository) FindByID(ctx context.Context, jobID int64) (*schema.Job, error) {\n 166→\tq := sq.Select(jobColumns...).\n 167→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 168→\n 169→\tq, qerr := SecurityCheck(ctx, q)\n 170→\tif qerr != nil {\n 171→\t\treturn nil, qerr\n 172→\t}\n 173→\n 174→\treturn scanJob(q.RunWith(r.stmtCache).QueryRowContext(ctx))\n 175→}\n 176→\n 177→// FindByIDWithUser executes a SQL query to find a specific batch job.\n 178→// The job is queried using the database id. The user is passed directly,\n 179→// instead as part of the context.\n 180→// It returns a pointer to a schema.Job data structure and an error variable.\n 181→// To check if no job was found test err == sql.ErrNoRows\n 182→func (r *JobRepository) FindByIDWithUser(user *schema.User, jobID int64) (*schema.Job, error) {\n 183→\tq := sq.Select(jobColumns...).\n 184→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 185→\n 186→\tq, qerr := SecurityCheckWithUser(user, q)\n 187→\tif qerr != nil {\n 188→\t\treturn nil, qerr\n 189→\t}\n 190→\n 191→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 192→}\n 193→\n 194→// FindByIDDirect executes a SQL query to find a specific batch job.\n 195→// The job is queried using the database id.\n 196→// It returns a pointer to a schema.Job data structure and an error variable.\n 197→// To check if no job was found test err == sql.ErrNoRows\n 198→func (r *JobRepository) FindByIDDirect(jobID int64) (*schema.Job, error) {\n 199→\tq := sq.Select(jobColumns...).\n 200→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 201→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 202→}\n 203→\n 204→// FindByJobID executes a SQL query to find a specific batch job.\n 205→// The job is queried using the slurm id and the clustername.\n 206→// It returns a pointer to a schema.Job data structure and an error variable.\n 207→// To check if no job was found test err == sql.ErrNoRows\n 208→func (r *JobRepository) FindByJobID(ctx context.Context, jobID int64, startTime int64, cluster string) (*schema.Job, error) {\n 209→\tq := sq.Select(jobColumns...).\n 210→\t\tFrom(\"job\").\n 211→\t\tWhere(\"job.job_id = ?\", jobID).\n 212→\t\tWhere(\"job.cluster = ?\", cluster).\n 213→\t\tWhere(\"job.start_time = ?\", startTime)\n 214→\n 215→\tq, qerr := SecurityCheck(ctx, q)\n 216→\tif qerr != nil {\n 217→\t\treturn nil, qerr\n 218→\t}\n 219→\n 220→\treturn scanJob(q.RunWith(r.stmtCache).QueryRowContext(ctx))\n 221→}\n 222→\n 223→// IsJobOwner checks if the specified user owns the batch job identified by jobID,\n 224→// startTime, and cluster. Returns true if the user is the owner, false otherwise.\n 225→// This method does not return errors; it returns false for both non-existent jobs\n 226→// and jobs owned by other users.\n 227→func (r *JobRepository) IsJobOwner(jobID int64, startTime int64, user string, cluster string) bool {\n 228→\tq := sq.Select(\"id\").\n 229→\t\tFrom(\"job\").\n 230→\t\tWhere(\"job.job_id = ?\", jobID).\n 231→\t\tWhere(\"job.hpc_user = ?\", user).\n 232→\t\tWhere(\"job.cluster = ?\", cluster).\n 233→\t\tWhere(\"job.start_time = ?\", startTime)\n 234→\n 235→\t_, err := scanJob(q.RunWith(r.stmtCache).QueryRow())\n 236→\tif err != nil && err != sql.ErrNoRows {\n 237→\t\tcclog.Warnf(\"IsJobOwner: unexpected error for jobID=%d, user=%s, cluster=%s: %v\", jobID, user, cluster, err)\n 238→\t}\n 239→\treturn err != sql.ErrNoRows\n 240→}\n 241→\n 242→func (r *JobRepository) FindConcurrentJobs(\n 243→\tctx context.Context,\n 244→\tjob *schema.Job,\n 245→) (*model.JobLinkResultList, error) {\n 246→\tif job == nil {\n 247→\t\treturn nil, nil\n 248→\t}\n 249→\n 250→\tquery, qerr := SecurityCheck(ctx, sq.Select(\"job.id\", \"job.job_id\", \"job.start_time\").From(\"job\"))\n 251→\tif qerr != nil {\n 252→\t\treturn nil, qerr\n 253→\t}\n 254→\n 255→\tquery = query.Where(\"cluster = ?\", job.Cluster)\n 256→\n 257→\tif len(job.Resources) == 0 {\n 258→\t\treturn nil, fmt.Errorf(\"job has no resources defined\")\n 259→\t}\n 260→\n 261→\tvar startTime int64\n 262→\tvar stopTime int64\n 263→\n 264→\tstartTime = job.StartTime\n 265→\thostname := job.Resources[0].Hostname\n 266→\n 267→\tif job.State == schema.JobStateRunning {\n 268→\t\tstopTime = time.Now().Unix()\n 269→\t} else {\n 270→\t\tstopTime = startTime + int64(job.Duration)\n 271→\t}\n 272→\n 273→\t// Time buffer constant for finding overlapping jobs\n 274→\t// overlapBufferEnd: 200s buffer at job end to account for scheduling/cleanup overlap\n 275→\tconst overlapBufferEnd = 200\n 276→\n 277→\tstopTimeTail := stopTime - overlapBufferEnd\n 278→\tstartTimeFront := startTime + overlapBufferEnd\n 279→\n 280→\tqueryRunning := query.Where(\"job.job_state = ?\", \"running\").\n 281→\t\tWhere(\"job.start_time <= ?\", stopTimeTail)\n 282→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 283→\tqueryRunning = queryRunning.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 284→\n 285→\tquery = query.Where(\"job.job_state != ?\", \"running\").\n 286→\t\tWhere(\"job.start_time < ?\", stopTimeTail).\n 287→\t\tWhere(\"(job.start_time + job.duration) > ?\", startTimeFront)\n 288→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 289→\tquery = query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 290→\n 291→\trows, err := query.RunWith(r.stmtCache).Query()\n 292→\tif err != nil {\n 293→\t\tcclog.Errorf(\"Error while running concurrent jobs query: %v\", err)\n 294→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent jobs query: %w\", err)\n 295→\t}\n 296→\tdefer rows.Close()\n 297→\n 298→\titems := make([]*model.JobLink, 0, 10)\n 299→\tqueryString := fmt.Sprintf(\"cluster=%s\", job.Cluster)\n 300→\n 301→\tfor rows.Next() {\n 302→\t\tvar id, jobID, startTime sql.NullInt64\n 303→\n 304→\t\tif err = rows.Scan(&id, &jobID, &startTime); err != nil {\n 305→\t\t\tcclog.Warnf(\"Error while scanning concurrent job rows: %v\", err)\n 306→\t\t\treturn nil, fmt.Errorf(\"failed to scan concurrent job row: %w\", err)\n 307→\t\t}\n 308→\n 309→\t\tif id.Valid {\n 310→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 311→\t\t\titems = append(items,\n 312→\t\t\t\t&model.JobLink{\n 313→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 314→\t\t\t\t\tJobID: int(jobID.Int64),\n 315→\t\t\t\t})\n 316→\t\t}\n 317→\t}\n 318→\n 319→\trows, err = queryRunning.RunWith(r.stmtCache).Query()\n 320→\tif err != nil {\n 321→\t\tcclog.Errorf(\"Error while running concurrent running jobs query: %v\", err)\n 322→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent running jobs query: %w\", err)\n 323→\t}\n 324→\tdefer rows.Close()\n 325→\n 326→\tfor rows.Next() {\n 327→\t\tvar id, jobID, startTime sql.NullInt64\n 328→\n 329→\t\tif err := rows.Scan(&id, &jobID, &startTime); err != nil {\n 330→\t\t\tcclog.Warnf(\"Error while scanning running concurrent job rows: %v\", err)\n 331→\t\t\treturn nil, fmt.Errorf(\"failed to scan running concurrent job row: %w\", err)\n 332→\t\t}\n 333→\n 334→\t\tif id.Valid {\n 335→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 336→\t\t\titems = append(items,\n 337→\t\t\t\t&model.JobLink{\n 338→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 339→\t\t\t\t\tJobID: int(jobID.Int64),\n 340→\t\t\t\t})\n 341→\t\t}\n 342→\t}\n 343→\n 344→\tcnt := len(items)\n 345→\n 346→\treturn &model.JobLinkResultList{\n 347→\t\tListQuery: &queryString,\n 348→\t\tItems: items,\n 349→\t\tCount: &cnt,\n 350→\t}, nil\n 351→}\n 352→"}]},"uuid":"5b596ba1-32f5-456c-9283-84c772345ab6","timestamp":"2026-03-13T14:11:10.005Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"13f7ed9e-592d-4462-899b-045e7a88c3a5","timestamp":"2026-03-13T14:11:10.007Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"c54541fe-b8df-4009-ba27-f3cf101f2e6a","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01YSUsYeEVVPftAf54wRbPar","type":"tool_result","content":"96-//\n97-/ The kind parameter enables counting specific job categories:\n98:// - \"running\": Only jobs with job_state = 'running'\n99-/ - \"short\": Only jobs with duration < ShortRunningJobsDuration config value\n100-/ - empty: All jobs matching filters\n--\n114-\tswitch kind {\n115-\tcase \"running\":\n116:\t\tquery = query.Where(\"job.job_state = ?\", \"running\")\n117-\tcase \"short\":\n118-\t\tquery = query.Where(\"job.duration < ?\", config.Keys.ShortRunningJobsDuration)\n--\n146-\t\treturn reqFields == nil || reqFields[field]\n147-\t}\n148:\tdurationExpr := fmt.Sprintf(`(CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END)`, now)\n149-\n150-\t// Build column list\n--\n206-\n207-\tif need(\"runningJobs\") {\n208:\t\tcolumns = append(columns, `COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs`)\n209-\t} else {\n210-\t\tcolumns = append(columns, \"0 as runningJobs\")\n--\n645-\tg, gctx := errgroup.WithContext(ctx)\n646-\n647:\tvalue := fmt.Sprintf(`CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value`, time.Now().Unix(), targetBinSize)\n648-\n649-\tg.Go(func() error {"}]},"uuid":"c1e34ce6-68a7-4a7c-b470-42aefabf2a56","timestamp":"2026-03-13T14:11:12.366Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"6e7e6f6f-2b8e-4747-b182-f636138220bb","timestamp":"2026-03-13T14:11:12.522Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"d08e6460-130f-4c09-9476-a6dca6dae2e0","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014ryNAkGhdtC1MnwpTadLyu","type":"tool_result","content":"199-\tif filter.State != nil {\n200-\t\tif len(filter.State) == 1 {\n201:\t\t\t// Inline literal value so SQLite can match partial indexes (WHERE job_state = 'running').\n202-\t\t\t/ Safe: values come from validated GraphQL enum (model.JobState).\n203-\t\t\tsingleStat := string(filter.State[0])\n204:\t\t\tquery = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))\n205-\t\t} else {\n206-\t\t\tstates := make([]string, len(filter.State))\n--\n208-\t\t\t\tstates[i] = string(val)\n209-\t\t\t}\n210:\t\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n211-\t\t}\n212-\t}"}]},"uuid":"19f8f6f8-b48d-4e5c-8b28-ccfd433578b7","timestamp":"2026-03-13T14:11:12.777Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"27e63fd8-d055-4a25-9f3a-b306dfc9dbcc","timestamp":"2026-03-13T14:11:12.947Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"71c682e8-b0ca-459d-a64c-b6eb651c7df9","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01D1ZZpevMFkv2QdourhvYiu","type":"tool_result","content":" 650→\t}\n 651→\tcclog.Debugf(\"Timer Partitions %s\", time.Since(start))\n 652→\treturn partitions.([]string), nil\n 653→}\n 654→\n 655→// AllocatedNodes returns a map of all subclusters to a map of hostnames to the amount of jobs running on that host.\n 656→// Hosts with zero jobs running on them will not show up!\n 657→func (r *JobRepository) AllocatedNodes(cluster string) (map[string]map[string]int, error) {\n 658→\tstart := time.Now()\n 659→\tsubclusters := make(map[string]map[string]int)\n 660→\trows, err := sq.Select(\"resources\", \"subcluster\").From(\"job\").\n 661→\t\tWhere(\"job.job_state = 'running'\").\n 662→\t\tWhere(\"job.cluster = ?\", cluster).\n 663→\t\tRunWith(r.stmtCache).Query()\n 664→\tif err != nil {\n 665→\t\tcclog.Errorf(\"Error while running AllocatedNodes query for cluster=%s: %v\", cluster, err)\n 666→\t\treturn nil, fmt.Errorf(\"failed to query allocated nodes for cluster %s: %w\", cluster, err)\n 667→\t}\n 668→\n 669→\tvar raw []byte\n 670→\tdefer rows.Close()\n 671→\tfor rows.Next() {\n 672→\t\traw = raw[0:0]\n 673→\t\tvar resources []*schema.Resource\n 674→\t\tvar subcluster string\n 675→\t\tif err := rows.Scan(&raw, &subcluster); err != nil {\n 676→\t\t\tcclog.Warnf(\"Error while scanning rows in AllocatedNodes: %v\", err)\n 677→\t\t\treturn nil, fmt.Errorf(\"failed to scan allocated nodes row: %w\", err)\n 678→\t\t}\n 679→\t\tif err := json.Unmarshal(raw, &resources); err != nil {\n 680→\t\t\tcclog.Warnf(\"Error while unmarshaling raw resources json in AllocatedNodes: %v\", err)\n 681→\t\t\treturn nil, fmt.Errorf(\"failed to unmarshal resources in AllocatedNodes: %w\", err)\n 682→\t\t}\n 683→\n 684→\t\thosts, ok := subclusters[subcluster]\n 685→\t\tif !ok {\n 686→\t\t\thosts = make(map[string]int)\n 687→\t\t\tsubclusters[subcluster] = hosts\n 688→\t\t}\n 689→\n 690→\t\tfor _, resource := range resources {\n 691→\t\t\thosts[resource.Hostname] += 1\n 692→\t\t}\n 693→\t}\n 694→\n 695→\tcclog.Debugf(\"Timer AllocatedNodes %s\", time.Since(start))\n 696→\treturn subclusters, nil\n 697→}\n 698→\n 699→// StopJobsExceedingWalltimeBy marks running jobs as failed if they exceed their walltime limit.\n 700→// This is typically called periodically to clean up stuck or orphaned jobs.\n 701→//\n 702→// Jobs are marked with:\n 703→// - monitoring_status: MonitoringStatusArchivingFailed\n 704→// - duration: 0\n 705→// - job_state: JobStateFailed\n 706→//\n 707→// Parameters:\n 708→// - seconds: Grace period beyond walltime before marking as failed\n 709→//\n 710→// Returns an error if the database update fails.\n 711→// Logs the number of jobs marked as failed if any were affected.\n 712→func (r *JobRepository) StopJobsExceedingWalltimeBy(seconds int) error {\n 713→\tstart := time.Now()\n 714→\tcurrentTime := time.Now().Unix()\n 715→\tres, err := sq.Update(\"job\").\n 716→\t\tSet(\"monitoring_status\", schema.MonitoringStatusArchivingFailed).\n 717→\t\tSet(\"duration\", 0).\n 718→\t\tSet(\"job_state\", schema.JobStateFailed).\n 719→\t\tWhere(\"job.job_state = 'running'\").\n 720→\t\tWhere(\"job.walltime > 0\").\n 721→\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\n 722→\t\tRunWith(r.DB).Exec()\n 723→\tif err != nil {\n 724→\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n 725→\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n 726→\t}\n 727→\n 728→\trowsAffected, err := res.RowsAffected()\n 729→\tif err != nil {\n 730→\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n 731→\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n 732→\t}\n 733→\n 734→\tif rowsAffected > 0 {\n 735→\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n 736→\t}\n 737→\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n 738→\treturn nil\n 739→}\n 740→\n 741→// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n 742→//\n 743→// Parameters:\n 744→// - tagID: Database ID of the tag to search for\n 745→//\n 746→// Returns a slice of job IDs or an error if the query fails.\n 747→func (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n 748→\tquery := sq.Select(\"job.id\").From(\"job\").\n 749→\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n 750→\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n 751→\trows, err := query.RunWith(r.stmtCache).Query()\n 752→\tif err != nil {\n 753→\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n 754→\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n 755→\t}\n 756→\tdefer rows.Close()\n 757→\n 758→\tjobIds := make([]int64, 0, 100)\n 759→\n 760→\tfor rows.Next() {\n 761→\t\tvar jobID int64\n 762→\n 763→\t\tif err := rows.Scan(&jobID); err != nil {\n 764→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n 765→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n 766→\t\t}\n 767→\n 768→\t\tjobIds = append(jobIds, jobID)\n 769→\t}\n 770→\n 771→\treturn jobIds, nil\n 772→}\n 773→\n 774→// FindRunningJobs returns all currently running jobs for a specific cluster.\n 775→// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n 776→//\n 777→// Parameters:\n 778→// - cluster: Cluster name to filter jobs\n 779→//\n 780→// Returns a slice of running job objects or an error if the query fails.\n 781→func (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n 782→\tquery := sq.Select(jobColumns...).From(\"job\").\n 783→\t\tWhere(\"job.cluster = ?\", cluster).\n 784→\t\tWhere(\"job.job_state = 'running'\").\n 785→\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n 786→\n 787→\trows, err := query.RunWith(r.stmtCache).Query()\n 788→\tif err != nil {\n 789→\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n 790→\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n 791→\t}\n 792→\tdefer rows.Close()\n 793→\n 794→\tjobs := make([]*schema.Job, 0, 50)\n 795→\tfor rows.Next() {\n 796→\t\tjob, err := scanJob(rows)\n 797→\t\tif err != nil {\n 798→\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n 799→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n 800→\t\t}\n 801→\t\tjobs = append(jobs, job)\n 802→\t}\n 803→\n 804→\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n 805→\treturn jobs, nil\n 806→}\n 807→\n 808→// UpdateDuration recalculates and updates the duration field for all running jobs.\n 809→// Called periodically to keep job durations current without querying individual jobs.\n 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally 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sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {"}]},"uuid":"a537c474-390f-40dc-8a0c-23c77f2dc65f","timestamp":"2026-03-13T14:11:30.365Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"a05ba4c8-605c-4216-8e7e-ee658720d43a","timestamp":"2026-03-13T14:11:30.559Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} 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+{"parentUuid":"76aafb68-f966-421a-ab8d-7f5131da7e79","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WsidkZ8Zwnh45fE2jsg49t","type":"tool_result","content":" 700→// This is typically called periodically to clean up stuck or orphaned jobs.\n 701→//\n 702→// Jobs are marked with:\n 703→// - monitoring_status: MonitoringStatusArchivingFailed\n 704→// - duration: 0\n 705→// - job_state: JobStateFailed\n 706→//\n 707→// Parameters:\n 708→// - seconds: Grace period beyond walltime before marking as failed\n 709→//\n 710→// Returns an error if the database update fails.\n 711→// Logs the number of jobs marked as failed if any were affected.\n 712→func (r *JobRepository) StopJobsExceedingWalltimeBy(seconds int) error {\n 713→\tstart := time.Now()\n 714→\tcurrentTime := time.Now().Unix()\n 715→\tres, err := sq.Update(\"job\").\n 716→\t\tSet(\"monitoring_status\", schema.MonitoringStatusArchivingFailed).\n 717→\t\tSet(\"duration\", 0).\n 718→\t\tSet(\"job_state\", schema.JobStateFailed).\n 719→\t\tWhere(\"job.job_state = 'running'\").\n 720→\t\tWhere(\"job.walltime > 0\").\n 721→\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\n 722→\t\tRunWith(r.DB).Exec()\n 723→\tif err != nil {\n 724→\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n 725→\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n 726→\t}\n 727→\n 728→\trowsAffected, err := res.RowsAffected()\n 729→\tif err != nil {\n 730→\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n 731→\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n 732→\t}\n 733→\n 734→\tif rowsAffected > 0 {\n 735→\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n 736→\t}\n 737→\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n 738→\treturn nil\n 739→}\n 740→\n 741→// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n 742→//\n 743→// Parameters:\n 744→// - tagID: Database ID of the tag to search for\n 745→//\n 746→// Returns a slice of job IDs or an error if the query fails.\n 747→func (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n 748→\tquery := sq.Select(\"job.id\").From(\"job\").\n 749→\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n 750→\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n 751→\trows, err := query.RunWith(r.stmtCache).Query()\n 752→\tif err != nil {\n 753→\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n 754→\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n 755→\t}\n 756→\tdefer rows.Close()\n 757→\n 758→\tjobIds := make([]int64, 0, 100)\n 759→\n 760→\tfor rows.Next() {\n 761→\t\tvar jobID int64\n 762→\n 763→\t\tif err := rows.Scan(&jobID); err != nil {\n 764→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n 765→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n 766→\t\t}\n 767→\n 768→\t\tjobIds = append(jobIds, jobID)\n 769→\t}\n 770→\n 771→\treturn jobIds, nil\n 772→}\n 773→\n 774→// FindRunningJobs returns all currently running jobs for a specific cluster.\n 775→// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n 776→//\n 777→// Parameters:\n 778→// - cluster: Cluster name to filter jobs\n 779→//\n 780→// Returns a slice of running job objects or an error if the query fails.\n 781→func (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n 782→\tquery := sq.Select(jobColumns...).From(\"job\").\n 783→\t\tWhere(\"job.cluster = ?\", cluster).\n 784→\t\tWhere(\"job.job_state = 'running'\").\n 785→\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n 786→\n 787→\trows, err := query.RunWith(r.stmtCache).Query()\n 788→\tif err != nil {\n 789→\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n 790→\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n 791→\t}\n 792→\tdefer rows.Close()\n 793→\n 794→\tjobs := make([]*schema.Job, 0, 50)\n 795→\tfor rows.Next() {\n 796→\t\tjob, err := scanJob(rows)\n 797→\t\tif err != nil {\n 798→\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n 799→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n 800→\t\t}\n 801→\t\tjobs = append(jobs, job)\n 802→\t}\n 803→\n 804→\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n 805→\treturn jobs, nil\n 806→}\n 807→\n 808→// UpdateDuration recalculates and updates the duration field for all running jobs.\n 809→// Called periodically to keep job durations current without querying individual jobs.\n 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally excludes tagged jobs from results.\n 831→//\n 832→// Parameters:\n 833→// - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n 834→// - startTimeEnd: Unix timestamp for range end\n 835→// - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n 836→// \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 837→//\n 838→// Returns a slice of jobs or an error if the time range is invalid or query fails.\n 839→func (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n 840→\tvar query sq.SelectBuilder\n 841→\n 842→\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n 843→\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n 844→\t}\n 845→\n 846→\tif startTimeBegin == 0 {\n 847→\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n 848→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {"}]},"uuid":"ee8da5df-cc13-4034-b4c0-086f87d6f70d","timestamp":"2026-03-13T14:11:30.584Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"ba3c4f26-3e95-4f0f-9c94-86b88127cd50","timestamp":"2026-03-13T14:11:30.770Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"ba3c4f26-3e95-4f0f-9c94-86b88127cd50","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-13T14:11:30.986Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_014dWntQKguGty8r7M9bwWcr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016EzxEsAxyAkYY3CRF3BudW","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go","offset":775,"limit":80},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":4,"cache_creation_input_tokens":377,"cache_read_input_tokens":53445,"cache_creation":{"ephemeral_5m_input_tokens":377,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ1DQu89fTPJZynurGgpB","uuid":"2ee8932e-e136-4653-9a5a-408e61da6dac"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"9b9a26dc-4c69-4070-915b-bab0588b2ed7","timestamp":"2026-03-13T14:11:30.986Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"9b9a26dc-4c69-4070-915b-bab0588b2ed7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016EzxEsAxyAkYY3CRF3BudW","type":"tool_result","content":" 775→// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n 776→//\n 777→// Parameters:\n 778→// - cluster: Cluster name to filter jobs\n 779→//\n 780→// Returns a slice of running job objects or an error if the query fails.\n 781→func (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n 782→\tquery := sq.Select(jobColumns...).From(\"job\").\n 783→\t\tWhere(\"job.cluster = ?\", cluster).\n 784→\t\tWhere(\"job.job_state = 'running'\").\n 785→\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n 786→\n 787→\trows, err := query.RunWith(r.stmtCache).Query()\n 788→\tif err != nil {\n 789→\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n 790→\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n 791→\t}\n 792→\tdefer rows.Close()\n 793→\n 794→\tjobs := make([]*schema.Job, 0, 50)\n 795→\tfor rows.Next() {\n 796→\t\tjob, err := scanJob(rows)\n 797→\t\tif err != nil {\n 798→\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n 799→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n 800→\t\t}\n 801→\t\tjobs = append(jobs, job)\n 802→\t}\n 803→\n 804→\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n 805→\treturn jobs, nil\n 806→}\n 807→\n 808→// UpdateDuration recalculates and updates the duration field for all running jobs.\n 809→// Called periodically to keep job durations current without querying individual jobs.\n 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally excludes tagged jobs from results.\n 831→//\n 832→// Parameters:\n 833→// - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n 834→// - startTimeEnd: Unix timestamp for range end\n 835→// - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n 836→// \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 837→//\n 838→// Returns a slice of jobs or an error if the time range is invalid or query fails.\n 839→func (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n 840→\tvar query sq.SelectBuilder\n 841→\n 842→\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n 843→\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n 844→\t}\n 845→\n 846→\tif startTimeBegin == 0 {\n 847→\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n 848→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {\n 850→\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n 851→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n 852→\t}\n 853→\n 854→\tswitch omitTagged {"}]},"uuid":"2366f563-e3f2-42c4-9d48-4282e834f53a","timestamp":"2026-03-13T14:11:31.004Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"2c4e7d36-5198-4631-8626-f08cb8dfca0a","timestamp":"2026-03-13T14:11:31.193Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"2c4e7d36-5198-4631-8626-f08cb8dfca0a","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-13T14:11:31.427Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_014dWntQKguGty8r7M9bwWcr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01L5C3J4gfQiFcBcFeRgNAtZ","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go","offset":810,"limit":70},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":4,"cache_creation_input_tokens":377,"cache_read_input_tokens":53445,"cache_creation":{"ephemeral_5m_input_tokens":377,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ1DQu89fTPJZynurGgpB","uuid":"d6ffe93e-d138-4cb4-9d21-a2fcd10c7f89"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"850e46fa-3d6a-4dd5-a2d2-69d800b7f46d","timestamp":"2026-03-13T14:11:31.427Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"850e46fa-3d6a-4dd5-a2d2-69d800b7f46d","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01L5C3J4gfQiFcBcFeRgNAtZ","type":"tool_result","content":" 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally excludes tagged jobs from results.\n 831→//\n 832→// Parameters:\n 833→// - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n 834→// - startTimeEnd: Unix timestamp for range end\n 835→// - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n 836→// \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 837→//\n 838→// Returns a slice of jobs or an error if the time range is invalid or query fails.\n 839→func (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n 840→\tvar query sq.SelectBuilder\n 841→\n 842→\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n 843→\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n 844→\t}\n 845→\n 846→\tif startTimeBegin == 0 {\n 847→\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n 848→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {\n 850→\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n 851→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n 852→\t}\n 853→\n 854→\tswitch omitTagged {\n 855→\tcase \"all\":\n 856→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 857→\tcase \"user\":\n 858→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 859→\t}\n 860→\n 861→\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\n 862→\n 863→\trows, err := query.RunWith(r.stmtCache).Query()\n 864→\tif err != nil {\n 865→\t\tcclog.Errorf(\"Error while running FindJobsBetween query: %v\", err)\n 866→\t\treturn nil, fmt.Errorf(\"failed to find jobs between %d and %d: %w\", startTimeBegin, startTimeEnd, err)\n 867→\t}\n 868→\tdefer rows.Close()\n 869→\n 870→\tjobs := make([]*schema.Job, 0, 50)\n 871→\tfor rows.Next() {\n 872→\t\tjob, err := scanJob(rows)\n 873→\t\tif err != nil {\n 874→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobsBetween: %v\", err)\n 875→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindJobsBetween: %w\", err)\n 876→\t\t}\n 877→\t\tjobs = append(jobs, job)\n 878→\t}\n 879→"}]},"uuid":"2ce8a2c7-bb58-43e8-8783-3734a983376e","timestamp":"2026-03-13T14:11:31.433Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"7ef1ae30-b504-4797-9a83-dc5ddfb6d5b2","timestamp":"2026-03-13T14:11:31.434Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"7ef1ae30-b504-4797-9a83-dc5ddfb6d5b2","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-13T14:11:31.602Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_014dWntQKguGty8r7M9bwWcr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SHLuweraH1NnZkZs9RJyoR","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go","offset":1060,"limit":30},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":4,"cache_creation_input_tokens":377,"cache_read_input_tokens":53445,"cache_creation":{"ephemeral_5m_input_tokens":377,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ1DQu89fTPJZynurGgpB","uuid":"0f27e56d-9795-4f54-bc99-8889a875b91e"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"b9e03118-b10e-4c53-acd9-bf6e330530a0","timestamp":"2026-03-13T14:11:31.603Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"b9e03118-b10e-4c53-acd9-bf6e330530a0","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SHLuweraH1NnZkZs9RJyoR","type":"tool_result","content":" 1060→//\n 1061→// The timestamp parameter (ts) is compared against job.start_time to find\n 1062→// relevant jobs. Returns an error if the database query fails or row iteration\n 1063→// encounters errors. Individual row parsing errors are logged but don't fail\n 1064→// the entire operation.\n 1065→func (r *JobRepository) GetUsedNodes(ts int64) (map[string][]string, error) {\n 1066→\t// Note: Query expects index on (job_state, start_time) for optimal performance\n 1067→\tq := sq.Select(\"job.cluster\", \"job.resources\").From(\"job\").\n 1068→\t\tWhere(\"job.start_time < ?\", ts).\n 1069→\t\tWhere(sq.Eq{\"job.job_state\": \"running\"})\n 1070→\n 1071→\trows, err := q.RunWith(r.stmtCache).Query()\n 1072→\tif err != nil {\n 1073→\t\tqueryString, queryVars, _ := q.ToSql()\n 1074→\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n 1075→\t}\n 1076→\tdefer rows.Close()\n 1077→\n 1078→\t// Use a map of sets for efficient deduplication\n 1079→\tnodeSet := make(map[string]map[string]struct{})\n 1080→\n 1081→\tvar (\n 1082→\t\tcluster string\n 1083→\t\trawResources []byte\n 1084→\t\tresources []*schema.Resource\n 1085→\t\tskippedRows int\n 1086→\t)\n 1087→\n 1088→\tfor rows.Next() {\n 1089→\t\tif err := rows.Scan(&cluster, &rawResources); err != nil {"}]},"uuid":"90f85031-94bc-4a0f-8bfd-bb4eff8fbea6","timestamp":"2026-03-13T14:11:31.611Z"},"type":"agent_progress","prompt":"","agentId":"a7c36c0986477581c"},"toolUseID":"agent_msg_01LadQ1AxETvXziMrYBqj9ps","parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","uuid":"dc75125c-f284-40fb-bdd1-a3360661db17","timestamp":"2026-03-13T14:11:31.631Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"dc75125c-f284-40fb-bdd1-a3360661db17","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","toolUseID":"toolu_01EDotFfP7XFHmDSwtCzpTYi","timestamp":"2026-03-13T14:11:58.098Z","uuid":"b2eb28ab-8b07-4fac-b449-57cb5a409c8c","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"8cbf0c52-c5b0-4c92-a63e-ba22eb7416fd","isSidechain":false,"promptId":"cef5abc9-1504-479e-870d-845cb284bb17","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01EDotFfP7XFHmDSwtCzpTYi","type":"tool_result","content":[{"type":"text","text":"Perfect! Now I have all the information. Let me compile the comprehensive report:\n\n## Summary of `job_state` SQL Query Usage\n\nI've found **11 occurrences** of `job_state` in WHERE clauses across the repository layer. Here's the complete breakdown:\n\n### 1. **stats.go - Line 116** (buildCountQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:116`\n- **Function**: `buildCountQuery()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `query = query.Where(\"job.job_state = ?\", \"running\")`\n- **Parameterization**: YES - uses `?` placeholder with \"running\" passed as parameter\n- **Context**: Counts jobs by kind; filters for running jobs when kind=\"running\". Used by AddJobCount, AddJobCountGrouped\n- **Source**: Validated - hardcoded constant \"running\" from switch statement\n\n### 2. **stats.go - Line 148** (buildStatsQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:148`\n- **Function**: `buildStatsQuery()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `durationExpr := fmt.Sprintf(\"(CASE WHEN job.job_state = 'running' THEN ...\")`\n- **Parameterization**: NO - hardcoded literal 'running' in string\n- **Context**: Builds dynamic SQL for calculating duration. For running jobs: (now - start_time); for completed: duration field. Used in statistics aggregations\n- **Source**: Validated - hardcoded constant in comparison expression\n\n### 3. **stats.go - Line 208** (buildStatsQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:208`\n- **Function**: `buildStatsQuery()`\n- **SQL Pattern**: Raw SQL string via SELECT clause\n- **Code**: `columns = append(columns, \"COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs\")`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Counts running jobs as part of statistics aggregation\n- **Source**: Validated - hardcoded constant\n\n### 4. **stats.go - Line 647** (AddHistograms)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:647`\n- **Function**: `AddHistograms()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `value := fmt.Sprintf(\"CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value\"...)`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Duration histogram calculation; same as buildStatsQuery logic for running vs completed jobs\n- **Source**: Validated - hardcoded constant\n\n### 5. **jobQuery.go - Line 204** (BuildWhereClause)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go:204`\n- **Function**: `BuildWhereClause()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `query = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))`\n- **Parameterization**: NO - inlined literal using fmt.Sprintf\n- **Context**: User filter for job state. When single state value requested, inlines for SQLite partial index matching. Comment explicitly notes this is safe because values come from GraphQL enum validation\n- **Source**: Validated - values from `filter.State[0]` which is model.JobState enum (validated GraphQL type)\n- **Security**: Comment at line 201-202 documents this is intentional for partial index optimization\n\n### 6. **jobQuery.go - Line 210** (BuildWhereClause)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go:210`\n- **Function**: `BuildWhereClause()`\n- **SQL Pattern**: Squirrel sq.Eq\n- **Code**: `query = query.Where(sq.Eq{\"job.job_state\": states})`\n- **Parameterization**: YES - Squirrel parameterizes this with ? placeholders\n- **Context**: Multiple state filter (IN clause); when filter has multiple state values\n- **Source**: Validated - values from filter.State which is model.JobState enum array\n\n### 7. **jobFind.go - Line 132** (GetJobList)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:132`\n- **Function**: `GetJobList()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state != 'running'\")`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Gets list of non-running (completed) jobs for batch processing. Returns paginated IDs\n- **Source**: Validated - hardcoded constant\n\n### 8. **jobFind.go - Line 280** (FindConcurrentJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:280`\n- **Function**: `FindConcurrentJobs()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `queryRunning := query.Where(\"job.job_state = ?\", \"running\")`\n- **Parameterization**: YES - uses ? placeholder with \"running\" as parameter\n- **Context**: Finds running jobs overlapping with specified job's time range (for concurrent job analysis)\n- **Source**: Validated - hardcoded constant \"running\"\n\n### 9. **jobFind.go - Line 285** (FindConcurrentJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:285`\n- **Function**: `FindConcurrentJobs()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `query = query.Where(\"job.job_state != ?\", \"running\")`\n- **Parameterization**: YES - uses ? placeholder with \"running\" as parameter\n- **Context**: Finds completed jobs (not running) overlapping with specified job's time range\n- **Source**: Validated - hardcoded constant \"running\"\n\n### 10. **job.go - Line 661** (AllocatedNodes)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:661`\n- **Function**: `AllocatedNodes()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Gets all currently allocated nodes across running jobs on a cluster\n- **Source**: Validated - hardcoded constant\n\n### 11. **job.go - Line 719** (StopJobsExceedingWalltimeBy)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:719`\n- **Function**: `StopJobsExceedingWalltimeBy()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Marks stuck/orphaned jobs as failed if they exceed walltime. Filters to only running jobs\n- **Source**: Validated - hardcoded constant\n\n### 12. **job.go - Line 784** (FindRunningJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:784`\n- **Function**: `FindRunningJobs()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Retrieves all running jobs for a cluster, filters by MinRunningJobDuration threshold\n- **Source**: Validated - hardcoded constant\n\n### 13. **job.go - Line 817** (UpdateDuration)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:817`\n- **Function**: `UpdateDuration()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job_state = 'running'\")` (note: missing \"job.\" prefix)\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Updates duration for all running jobs periodically (current_time - start_time)\n- **Source**: Validated - hardcoded constant\n- **Note**: Missing table prefix (\"job.\" is omitted)\n\n### 14. **job.go - Line 1069** (GetUsedNodes)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:1069`\n- **Function**: `GetUsedNodes()`\n- **SQL Pattern**: Squirrel sq.Eq\n- **Code**: `Where(sq.Eq{\"job.job_state\": \"running\"})`\n- **Parameterization**: YES - Squirrel parameterizes this with ? placeholder\n- **Context**: Gets nodes in use for running jobs before a timestamp. Comment notes performance requires index on (job_state, start_time)\n- **Source**: Validated - hardcoded constant \"running\"\n\n---\n\n## Summary Table\n\n| File | Line | Function | Parameterized | Value Source | Filter Type |\n|------|------|----------|----------------|-------------|------------|\n| stats.go | 116 | buildCountQuery | YES (?) | hardcoded \"running\" | Single known value |\n| stats.go | 148 | buildStatsQuery | NO (inlined) | hardcoded 'running' | Single known value |\n| stats.go | 208 | buildStatsQuery | NO (inlined) | hardcoded 'running' | Single known value |\n| stats.go | 647 | AddHistograms | NO (inlined) | hardcoded 'running' | Single known value |\n| jobQuery.go | 204 | BuildWhereClause | NO (fmt.Sprintf) | GraphQL enum validated | Single known value |\n| jobQuery.go | 210 | BuildWhereClause | YES (sq.Eq) | GraphQL enum validated | Multiple values |\n| jobFind.go | 132 | GetJobList | NO (inlined) | hardcoded 'running' | Single known value |\n| jobFind.go | 280 | FindConcurrentJobs | YES (?) | hardcoded \"running\" | Single known value |\n| jobFind.go | 285 | FindConcurrentJobs | YES (?) | hardcoded \"running\" | Single known value |\n| job.go | 661 | AllocatedNodes | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 719 | StopJobsExceedingWalltimeBy | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 784 | FindRunningJobs | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 817 | UpdateDuration | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 1069 | GetUsedNodes | YES (sq.Eq) | hardcoded \"running\" | Single known value |\n\n---\n\n## Key Findings\n\n1. **No user input flows directly into job_state filters** - All values come from either hardcoded constants or validated GraphQL enums\n2. **Mixed parameterization approach** - 5 use parameterized queries (Squirrel with ?), 9 use inlined literals\n3. **Intentional inlining in jobQuery.go:204** - Comment documents this is safe for SQLite partial index optimization\n4. **Consistent \"running\" state usage** - Almost all filters target the hardcoded \"running\" state for specific queries\n5. **One minor issue in job.go:817** - Missing \"job.\" table prefix in UpdateDuration query (though still safe as it's unambiguous)"},{"type":"text","text":"agentId: a7c36c0986477581c (for resuming to continue this agent's work if needed)\ntotal_tokens: 66263\ntool_uses: 17\nduration_ms: 53390"}]}]},"uuid":"eab5e799-0172-4a96-ad80-8a9ebe391648","timestamp":"2026-03-13T14:11:58.097Z","toolUseResult":{"status":"completed","prompt":"Search the codebase for all places where `job_state` or `job.job_state` is used in SQL query construction (not in migration files). I need to find every place where a WHERE clause on job_state is built, whether via squirrel (sq.Where, query.Where) or raw SQL strings. \n\nFor each occurrence, note:\n1. The file and line number\n2. Whether the value is parameterized (using `?` placeholder) or inlined as a literal\n3. The context — what function it's in and what it's used for (e.g., counting running jobs, building stats queries, etc.)\n4. Whether it filters for a single known state value (like 'running') from a validated/hardcoded source, or from user input\n\nFocus on:\n- internal/repository/stats.go\n- internal/repository/jobQuery.go \n- internal/repository/job.go\n- Any other files in internal/repository/\n- internal/graph/ resolvers\n\nDo NOT look at migration SQL files.","agentId":"a7c36c0986477581c","content":[{"type":"text","text":"Perfect! Now I have all the information. Let me compile the comprehensive report:\n\n## Summary of `job_state` SQL Query Usage\n\nI've found **11 occurrences** of `job_state` in WHERE clauses across the repository layer. Here's the complete breakdown:\n\n### 1. **stats.go - Line 116** (buildCountQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:116`\n- **Function**: `buildCountQuery()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `query = query.Where(\"job.job_state = ?\", \"running\")`\n- **Parameterization**: YES - uses `?` placeholder with \"running\" passed as parameter\n- **Context**: Counts jobs by kind; filters for running jobs when kind=\"running\". Used by AddJobCount, AddJobCountGrouped\n- **Source**: Validated - hardcoded constant \"running\" from switch statement\n\n### 2. **stats.go - Line 148** (buildStatsQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:148`\n- **Function**: `buildStatsQuery()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `durationExpr := fmt.Sprintf(\"(CASE WHEN job.job_state = 'running' THEN ...\")`\n- **Parameterization**: NO - hardcoded literal 'running' in string\n- **Context**: Builds dynamic SQL for calculating duration. For running jobs: (now - start_time); for completed: duration field. Used in statistics aggregations\n- **Source**: Validated - hardcoded constant in comparison expression\n\n### 3. **stats.go - Line 208** (buildStatsQuery)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:208`\n- **Function**: `buildStatsQuery()`\n- **SQL Pattern**: Raw SQL string via SELECT clause\n- **Code**: `columns = append(columns, \"COUNT(CASE WHEN job.job_state = 'running' THEN 1 END) as runningJobs\")`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Counts running jobs as part of statistics aggregation\n- **Source**: Validated - hardcoded constant\n\n### 4. **stats.go - Line 647** (AddHistograms)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:647`\n- **Function**: `AddHistograms()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `value := fmt.Sprintf(\"CAST(ROUND(((CASE WHEN job.job_state = 'running' THEN %d - job.start_time ELSE job.duration END) / %d) + 1) as int) as value\"...)`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Duration histogram calculation; same as buildStatsQuery logic for running vs completed jobs\n- **Source**: Validated - hardcoded constant\n\n### 5. **jobQuery.go - Line 204** (BuildWhereClause)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go:204`\n- **Function**: `BuildWhereClause()`\n- **SQL Pattern**: Raw SQL string via fmt.Sprintf (inlined literal)\n- **Code**: `query = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))`\n- **Parameterization**: NO - inlined literal using fmt.Sprintf\n- **Context**: User filter for job state. When single state value requested, inlines for SQLite partial index matching. Comment explicitly notes this is safe because values come from GraphQL enum validation\n- **Source**: Validated - values from `filter.State[0]` which is model.JobState enum (validated GraphQL type)\n- **Security**: Comment at line 201-202 documents this is intentional for partial index optimization\n\n### 6. **jobQuery.go - Line 210** (BuildWhereClause)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go:210`\n- **Function**: `BuildWhereClause()`\n- **SQL Pattern**: Squirrel sq.Eq\n- **Code**: `query = query.Where(sq.Eq{\"job.job_state\": states})`\n- **Parameterization**: YES - Squirrel parameterizes this with ? placeholders\n- **Context**: Multiple state filter (IN clause); when filter has multiple state values\n- **Source**: Validated - values from filter.State which is model.JobState enum array\n\n### 7. **jobFind.go - Line 132** (GetJobList)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:132`\n- **Function**: `GetJobList()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state != 'running'\")`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Gets list of non-running (completed) jobs for batch processing. Returns paginated IDs\n- **Source**: Validated - hardcoded constant\n\n### 8. **jobFind.go - Line 280** (FindConcurrentJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:280`\n- **Function**: `FindConcurrentJobs()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `queryRunning := query.Where(\"job.job_state = ?\", \"running\")`\n- **Parameterization**: YES - uses ? placeholder with \"running\" as parameter\n- **Context**: Finds running jobs overlapping with specified job's time range (for concurrent job analysis)\n- **Source**: Validated - hardcoded constant \"running\"\n\n### 9. **jobFind.go - Line 285** (FindConcurrentJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobFind.go:285`\n- **Function**: `FindConcurrentJobs()`\n- **SQL Pattern**: Squirrel with parameterized placeholder\n- **Code**: `query = query.Where(\"job.job_state != ?\", \"running\")`\n- **Parameterization**: YES - uses ? placeholder with \"running\" as parameter\n- **Context**: Finds completed jobs (not running) overlapping with specified job's time range\n- **Source**: Validated - hardcoded constant \"running\"\n\n### 10. **job.go - Line 661** (AllocatedNodes)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:661`\n- **Function**: `AllocatedNodes()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Gets all currently allocated nodes across running jobs on a cluster\n- **Source**: Validated - hardcoded constant\n\n### 11. **job.go - Line 719** (StopJobsExceedingWalltimeBy)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:719`\n- **Function**: `StopJobsExceedingWalltimeBy()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Marks stuck/orphaned jobs as failed if they exceed walltime. Filters to only running jobs\n- **Source**: Validated - hardcoded constant\n\n### 12. **job.go - Line 784** (FindRunningJobs)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:784`\n- **Function**: `FindRunningJobs()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job.job_state = 'running'\").`\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Retrieves all running jobs for a cluster, filters by MinRunningJobDuration threshold\n- **Source**: Validated - hardcoded constant\n\n### 13. **job.go - Line 817** (UpdateDuration)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:817`\n- **Function**: `UpdateDuration()`\n- **SQL Pattern**: Raw SQL string (inlined literal)\n- **Code**: `Where(\"job_state = 'running'\")` (note: missing \"job.\" prefix)\n- **Parameterization**: NO - hardcoded literal 'running'\n- **Context**: Updates duration for all running jobs periodically (current_time - start_time)\n- **Source**: Validated - hardcoded constant\n- **Note**: Missing table prefix (\"job.\" is omitted)\n\n### 14. **job.go - Line 1069** (GetUsedNodes)\n- **Location**: `/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:1069`\n- **Function**: `GetUsedNodes()`\n- **SQL Pattern**: Squirrel sq.Eq\n- **Code**: `Where(sq.Eq{\"job.job_state\": \"running\"})`\n- **Parameterization**: YES - Squirrel parameterizes this with ? placeholder\n- **Context**: Gets nodes in use for running jobs before a timestamp. Comment notes performance requires index on (job_state, start_time)\n- **Source**: Validated - hardcoded constant \"running\"\n\n---\n\n## Summary Table\n\n| File | Line | Function | Parameterized | Value Source | Filter Type |\n|------|------|----------|----------------|-------------|------------|\n| stats.go | 116 | buildCountQuery | YES (?) | hardcoded \"running\" | Single known value |\n| stats.go | 148 | buildStatsQuery | NO (inlined) | hardcoded 'running' | Single known value |\n| stats.go | 208 | buildStatsQuery | NO (inlined) | hardcoded 'running' | Single known value |\n| stats.go | 647 | AddHistograms | NO (inlined) | hardcoded 'running' | Single known value |\n| jobQuery.go | 204 | BuildWhereClause | NO (fmt.Sprintf) | GraphQL enum validated | Single known value |\n| jobQuery.go | 210 | BuildWhereClause | YES (sq.Eq) | GraphQL enum validated | Multiple values |\n| jobFind.go | 132 | GetJobList | NO (inlined) | hardcoded 'running' | Single known value |\n| jobFind.go | 280 | FindConcurrentJobs | YES (?) | hardcoded \"running\" | Single known value |\n| jobFind.go | 285 | FindConcurrentJobs | YES (?) | hardcoded \"running\" | Single known value |\n| job.go | 661 | AllocatedNodes | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 719 | StopJobsExceedingWalltimeBy | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 784 | FindRunningJobs | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 817 | UpdateDuration | NO (inlined) | hardcoded 'running' | Single known value |\n| job.go | 1069 | GetUsedNodes | YES (sq.Eq) | hardcoded \"running\" | Single known value |\n\n---\n\n## Key Findings\n\n1. **No user input flows directly into job_state filters** - All values come from either hardcoded constants or validated GraphQL enums\n2. **Mixed parameterization approach** - 5 use parameterized queries (Squirrel with ?), 9 use inlined literals\n3. **Intentional inlining in jobQuery.go:204** - Comment documents this is safe for SQLite partial index optimization\n4. **Consistent \"running\" state usage** - Almost all filters target the hardcoded \"running\" state for specific queries\n5. **One minor issue in job.go:817** - Missing \"job.\" table prefix in UpdateDuration query (though still safe as it's unambiguous)"}],"totalDurationMs":53390,"totalTokens":66263,"totalToolUseCount":17,"usage":{"input_tokens":5,"cache_creation_input_tokens":9264,"cache_read_input_tokens":53822,"output_tokens":3172,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":9264},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"8cbf0c52-c5b0-4c92-a63e-ba22eb7416fd","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"eab5e799-0172-4a96-ad80-8a9ebe391648","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01LunFsBm6KQMnHbRchWL5Qj","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016KHumoJ75SUh7X9K1dBwVa","name":"Read","input":{"file_path":"/Users/jan/.claude/plans/recursive-giggling-volcano.md"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3603,"cache_read_input_tokens":96447,"output_tokens":69,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":3603},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1DTLFJVo71xZC2C7HHC","type":"assistant","uuid":"1da6cc18-dc56-4b07-a55d-7c7ec3c68593","timestamp":"2026-03-13T14:12:02.412Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"1da6cc18-dc56-4b07-a55d-7c7ec3c68593","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_016KHumoJ75SUh7X9K1dBwVa","toolUseID":"toolu_016KHumoJ75SUh7X9K1dBwVa","timestamp":"2026-03-13T14:12:02.443Z","uuid":"cd5ff376-d254-40fb-8a96-f6c329a0d77d","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"1da6cc18-dc56-4b07-a55d-7c7ec3c68593","isSidechain":false,"promptId":"cef5abc9-1504-479e-870d-845cb284bb17","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016KHumoJ75SUh7X9K1dBwVa","type":"tool_result","content":" 1→# Usage Dashboard Query Optimization\n 2→\n 3→## Change 1: Partial indexes for running jobs\n 4→\n 5→- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).\n 6→- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.\n 7→- **`internal/repository/migration.go:30`** — `Version` 13 → 14.\n 8→- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.\n 9→\n 10→## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)\n 11→\n 12→- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.\n 13→- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.\n 14→- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.\n 15→\n 16→## Change 3: Parallelize histogram queries\n 17→\n 18→- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.\n 19→\n 20→## Change 4: Frontend uses consolidated results\n 21→\n 22→- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. Update template refs.\n 23→\n 24→## Verification\n 25→```bash\n 26→cd web/frontend && npm run build && cd ../.. && go build ./... && go test ./internal/repository/...\n 27→```\n 28→"}]},"uuid":"c7e28a29-2dbd-47c9-bb33-66828a28b0a1","timestamp":"2026-03-13T14:12:02.442Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/.claude/plans/recursive-giggling-volcano.md","content":"# Usage Dashboard Query Optimization\n\n## Change 1: Partial indexes for running jobs\n\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.\n- **`internal/repository/migration.go:30`** — `Version` 13 → 14.\n- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.\n\n## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)\n\n- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.\n- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.\n- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.\n\n## Change 3: Parallelize histogram queries\n\n- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.\n\n## Change 4: Frontend uses consolidated results\n\n- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. Update template refs.\n\n## Verification\n```bash\ncd web/frontend && npm run build && cd ../.. && go build ./... && go test ./internal/repository/...\n```\n","numLines":28,"startLine":1,"totalLines":28}},"sourceToolAssistantUUID":"1da6cc18-dc56-4b07-a55d-7c7ec3c68593","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"c7e28a29-2dbd-47c9-bb33-66828a28b0a1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01TZ5r3uFwnQk5WH4h6DjiNV","type":"message","role":"assistant","content":[{"type":"text","text":"The exploration found **4 parameterized sites** that filter on a hardcoded `\"running\"` value where inlining could help SQLite use the partial indexes:\n\n| File | Line | Function | Currently |\n|------|------|----------|-----------|\n| `stats.go` | 116 | `buildCountQuery` | `\"job.job_state = ?\", \"running\"` |\n| `jobFind.go` | 280 | `FindConcurrentJobs` | `\"job.job_state = ?\", \"running\"` |\n| `jobFind.go` | 285 | `FindConcurrentJobs` | `\"job.job_state != ?\", \"running\"` |\n| `job.go` | 1069 | `GetUsedNodes` | `sq.Eq{\"job.job_state\": \"running\"}` |\n\nHowever, the benefit is uneven:\n\n- **`stats.go:116` (`buildCountQuery`)** — this is the strongest candidate. It's called by `AddJobCount`/`AddJobCountGrouped` on the dashboard. Inlining here lets SQLite use the partial indexes we just created.\n- **`job.go:1069` (`GetUsedNodes`)** — also queries running jobs, could benefit.\n- **`jobFind.go:280/285` (`FindConcurrentJobs`)** — these query by specific resources/time overlap, so the partial index is less likely to be chosen by the planner (the equality on `job_state` isn't the leading selectivity driver).\n\nThe remaining 8 sites already use inlined literals (`'running'` directly in SQL strings), so they're fine."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4375,"cache_read_input_tokens":96447,"cache_creation":{"ephemeral_5m_input_tokens":4375,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1DTd3r1FoaFXoLinP98","type":"assistant","uuid":"b483fbdc-1d1b-4602-9cad-0e2962d9bc73","timestamp":"2026-03-13T14:12:13.883Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"type":"file-history-snapshot","messageId":"973ed897-bf9f-44d8-9d47-1cb82259cfee","snapshot":{"messageId":"161d4ccc-0537-4700-a10d-f7a8534ef7f4","trackedFileBackups":{"internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql":{"backupFileName":"39f0a8ec00eef836@v2","version":2,"backupTime":"2026-03-13T13:31:20.069Z"},"internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql":{"backupFileName":"cccfd468ffeeb12d@v2","version":2,"backupTime":"2026-03-13T13:31:20.069Z"},"internal/repository/migration.go":{"backupFileName":"19a8f1f6575af1e7@v2","version":2,"backupTime":"2026-03-13T13:31:20.069Z"},"internal/repository/jobQuery.go":{"backupFileName":"c64bb1bbdfcfaab5@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"},"internal/graph/stats_cache.go":{"backupFileName":"192476250d06317a@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"},"cmd/cc-backend/server.go":{"backupFileName":"52a9e99169bfa641@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"},"internal/graph/schema.resolvers.go":{"backupFileName":"117e2419c7a90363@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"},"internal/repository/stats.go":{"backupFileName":"37b1ab532d191fe8@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"},"web/frontend/src/status/dashdetails/UsageDash.svelte":{"backupFileName":"0992f74d3d8ab349@v3","version":3,"backupTime":"2026-03-13T14:10:52.135Z"},"/Users/jan/.claude/plans/recursive-giggling-volcano.md":{"backupFileName":"199cf438c5ea258b@v1","version":1,"backupTime":"2026-03-13T14:12:20.753Z"}},"timestamp":"2026-03-13T14:10:52.134Z"},"isSnapshotUpdate":true} +{"parentUuid":"b483fbdc-1d1b-4602-9cad-0e2962d9bc73","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01TZ5r3uFwnQk5WH4h6DjiNV","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PNU1pDvBtV95Wihx8mcR3j","name":"Write","input":{"file_path":"/Users/jan/.claude/plans/recursive-giggling-volcano.md","content":"# Inline literal job_state in remaining parameterized sites\n\n## Files to change\n\n- **`internal/repository/stats.go:116`** (`buildCountQuery`) — change `query.Where(\"job.job_state = ?\", \"running\")` → `query.Where(\"job.job_state = 'running'\")`. Highest impact: called by dashboard count queries.\n- **`internal/repository/job.go:1069`** (`GetUsedNodes`) — change `sq.Eq{\"job.job_state\": \"running\"}` → `query.Where(\"job.job_state = 'running'\")`. Benefits node allocation queries.\n\n## Sites intentionally NOT changed\n\n- **`jobFind.go:280,285`** (`FindConcurrentJobs`) — equality/inequality on job_state isn't the leading filter here (time overlap + resources dominate), so partial index unlikely to help. Also uses `!=` which doesn't match `WHERE job_state = 'running'` partial indexes.\n\n## Verification\n```bash\ngo build ./cmd/cc-backend && go test ./internal/repository/...\n```\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4375,"cache_read_input_tokens":96447,"output_tokens":730,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":4375},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1DTd3r1FoaFXoLinP98","type":"assistant","uuid":"973ed897-bf9f-44d8-9d47-1cb82259cfee","timestamp":"2026-03-13T14:12:20.734Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"973ed897-bf9f-44d8-9d47-1cb82259cfee","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Write","command":"callback"},"parentToolUseID":"toolu_01PNU1pDvBtV95Wihx8mcR3j","toolUseID":"toolu_01PNU1pDvBtV95Wihx8mcR3j","timestamp":"2026-03-13T14:12:20.755Z","uuid":"17905a2f-c9b5-42e4-aacd-26361f2d8016","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"973ed897-bf9f-44d8-9d47-1cb82259cfee","isSidechain":false,"promptId":"cef5abc9-1504-479e-870d-845cb284bb17","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PNU1pDvBtV95Wihx8mcR3j","type":"tool_result","content":"The file /Users/jan/.claude/plans/recursive-giggling-volcano.md has been updated successfully."}]},"uuid":"9ea40fde-6dd4-40db-93fe-93da8108dea8","timestamp":"2026-03-13T14:12:20.755Z","toolUseResult":{"type":"update","filePath":"/Users/jan/.claude/plans/recursive-giggling-volcano.md","content":"# Inline literal job_state in remaining parameterized sites\n\n## Files to change\n\n- **`internal/repository/stats.go:116`** (`buildCountQuery`) — change `query.Where(\"job.job_state = ?\", \"running\")` → `query.Where(\"job.job_state = 'running'\")`. Highest impact: called by dashboard count queries.\n- **`internal/repository/job.go:1069`** (`GetUsedNodes`) — change `sq.Eq{\"job.job_state\": \"running\"}` → `query.Where(\"job.job_state = 'running'\")`. Benefits node allocation queries.\n\n## Sites intentionally NOT changed\n\n- **`jobFind.go:280,285`** (`FindConcurrentJobs`) — equality/inequality on job_state isn't the leading filter here (time overlap + resources dominate), so partial index unlikely to help. Also uses `!=` which doesn't match `WHERE job_state = 'running'` partial indexes.\n\n## Verification\n```bash\ngo build ./cmd/cc-backend && go test ./internal/repository/...\n```\n","structuredPatch":[{"oldStart":1,"oldLines":27,"newStart":1,"newLines":15,"lines":["-# Usage Dashboard Query Optimization","+# Inline literal job_state in remaining parameterized sites"," ","-## Change 1: Partial indexes for running jobs","+## Files to change"," ","-- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).","-- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.","-- **`internal/repository/migration.go:30`** — `Version` 13 → 14.","-- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.","+- **`internal/repository/stats.go:116`** (`buildCountQuery`) — change `query.Where(\"job.job_state = ?\", \"running\")` → `query.Where(\"job.job_state = 'running'\")`. Highest impact: called by dashboard count queries.","+- **`internal/repository/job.go:1069`** (`GetUsedNodes`) — change `sq.Eq{\"job.job_state\": \"running\"}` → `query.Where(\"job.job_state = 'running'\")`. Benefits node allocation queries."," ","-## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)","+## Sites intentionally NOT changed"," ","-- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.","-- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.","-- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.","+- **`jobFind.go:280,285`** (`FindConcurrentJobs`) — equality/inequality on job_state isn't the leading filter here (time overlap + resources dominate), so partial index unlikely to help. Also uses `!=` which doesn't match `WHERE job_state = 'running'` partial indexes."," ","-## Change 3: Parallelize histogram queries","-","-- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.","-","-## Change 4: Frontend uses consolidated results","-","-- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. Update template refs.","-"," ## Verification"," ```bash","-cd web/frontend && npm run build && cd ../.. && go build ./... && go test ./internal/repository/...","+go build ./cmd/cc-backend && go test ./internal/repository/..."," ```"]}],"originalFile":"# Usage Dashboard Query Optimization\n\n## Change 1: Partial indexes for running jobs\n\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.up.sql`** — partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Only running jobs in B-tree (tiny vs millions).\n- **New `internal/repository/migrations/sqlite3/14_running-partial-indexes.down.sql`** — drop them.\n- **`internal/repository/migration.go:30`** — `Version` 13 → 14.\n- **`internal/repository/jobQuery.go:200-202`** — inline literal state value (`fmt.Sprintf(\"job.job_state = '%s'\", singleStat)`) so SQLite matches partial indexes. Safe: values from validated GraphQL enum.\n\n## Change 2: Request-scoped cache for grouped stats (6 SQL → 2)\n\n- **`internal/graph/stats_cache.go`** (new) — define `statsGroupCache` type (wraps `sync.Map`), context key, `getOrCompute` method using `sync.Once` per cache entry.\n- **`cmd/cc-backend/server.go:87-88`** — add `graphQLServer.AroundOperations` middleware to inject empty cache into context per request.\n- **`internal/graph/schema.resolvers.go:671-678`** — in `JobsStatistics`, when `groupBy != nil`: check cache for (filter+groupBy) key → on miss, call `JobsStatsGrouped` with nil sortBy/page (all results), cache them → sort+slice in Go per caller's sortBy/page.\n\n## Change 3: Parallelize histogram queries\n\n- **`internal/repository/stats.go:643-668`** — replace 4 sequential histogram calls in `AddHistograms` with `errgroup.WithContext`. Import `golang.org/x/sync/errgroup`. Each goroutine writes distinct struct field.\n\n## Change 4: Frontend uses consolidated results\n\n- **`web/frontend/src/status/dashdetails/UsageDash.svelte`** — replace 6-alias topStatsQuery with 2 aliases (USER, PROJECT) requesting all fields, no sort/page. Add 6 `$derived` vars to sort+slice top-10. 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Highest impact: called by dashboard count queries.\n- **`internal/repository/job.go:1069`** (`GetUsedNodes`) — change `sq.Eq{\"job.job_state\": \"running\"}` → `query.Where(\"job.job_state = 'running'\")`. Benefits node allocation queries.\n\n## Sites intentionally NOT changed\n\n- **`jobFind.go:280,285`** (`FindConcurrentJobs`) — equality/inequality on job_state isn't the leading filter here (time overlap + resources dominate), so partial index unlikely to help. Also uses `!=` which doesn't match `WHERE job_state = 'running'` partial indexes.\n\n## Verification\n```bash\ngo build ./cmd/cc-backend && go test ./internal/repository/...\n```\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":847,"cache_read_input_tokens":101680,"output_tokens":93,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":847},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1DVCivmtJg9s3QZDwFb","type":"assistant","uuid":"57e16369-4d3f-448d-a795-88a884d5bbc0","timestamp":"2026-03-13T14:12:27.819Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"} +{"parentUuid":"57e16369-4d3f-448d-a795-88a884d5bbc0","isSidechain":false,"promptId":"cef5abc9-1504-479e-870d-845cb284bb17","type":"user","message":{"role":"user","content":[{"type":"tool_result","content":"The user doesn't want to proceed with this tool use. 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