cc-backend/5b/26a6e5ff10/0/full.jsonl

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{"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"}
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{"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"}
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{"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,"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 data\n}\n","numLines":1134,"startLine":1,"totalLines":1134}},"sourceToolAssistantUUID":"5d2038c7-8918-48d3-ad30-8bb309e197ed","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":"d3e42f29-d9b9-4e5b-ab97-5f8241c416ec","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LHFrSk7gPr42vNgyYxd8RR","type":"tool_result","content":"     1→package graph\n     2→\n     3→// This file will be automatically regenerated based on the schema, any resolver\n     4→// implementations\n     5→// will be copied through when generating and any unknown code will be moved to the end.\n     6→// Code generated by github.com/99designs/gqlgen version v0.17.87\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 &timestamp, 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 &timestamp, 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 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{"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 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); 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{"parentUuid":"97a1b420-fab3-40a5-887f-c3e910c1f05e","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011sUu45Zq64FG7gzArrJDT9","type":"tool_result","content":"     1→<!--\n     2→  @component Main cluster status view component; renders current system-usage information\n     3→\n     4→  Properties:\n     5→  - `presetCluster String`: The cluster to show status information for\n     6→  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n     7→  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n     8→  - `useAltColors Bool?`: Use alternative color set [Default: false]\n     9→-->\n    10→\n    11→<script>\n    12→  import {\n    13→    Row,\n    14→    Col,\n    15→    Spinner,\n    16→    Card,\n    17→    Table,\n    18→    Icon,\n    19→    Tooltip,\n    20→    Input,\n    21→    InputGroup,\n    22→    InputGroupText,\n    23→  } from \"@sveltestrap/sveltestrap\";\n    24→  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n    25→  import {\n    26→    scramble,\n    27→    scrambleNames,\n    28→    convert2uplot,\n    29→  } from \"../../generic/utils.js\";\n    30→  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n    31→  import Histogram from \"../../generic/plots/Histogram.svelte\";\n    32→  import Refresher from \"../../generic/helper/Refresher.svelte\";\n    33→\n    34→  /* Svelte 5 Props */\n    35→  let {\n    36→    presetCluster,\n    37→    presetSubCluster = null,\n    38→    useCbColors = false,\n    39→    useAltColors = false,\n    40→    loadMe = false,\n    41→  } = $props();\n    42→\n    43→  /* Const Init */\n    44→  const client = getContextClient();\n    45→  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n    46→\n    47→  /* State Init */\n    48→  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n    49→  let selectedHistograms = $state([]); // Dummy For Refresh\n    50→  let colWidthJobs = $state(0);\n    51→  let colWidthNodes = $state(0);\n    52→  let colWidthAccs = $state(0);\n    53→  let numDurationBins = $state(\"1h\");\n    54→\n    55→  /* Derived */\n    56→  const canvasPrefix = $derived(\n    57→    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n    58→  );\n    59→\n    60→  const statusFilter = $derived(\n    61→    presetSubCluster\n    62→      ? [\n    63→          { cluster: { eq: presetCluster } },\n    64→          { subCluster: { eq: presetSubCluster } },\n    65→          { state: [\"running\"] },\n    66→        ]\n    67→      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n    68→  );\n    69→  const topStatsQuery = $derived(\n    70→    loadMe\n    71→      ? queryStore({\n    72→          client: client,\n    73→          query: gql`\n    74→            query ($filter: [JobFilter!]!, $paging: PageRequest!) {\n    75→              topUserJobs: jobsStatistics(\n    76→                filter: $filter\n    77→                page: $paging\n    78→                sortBy: TOTALJOBS\n    79→                groupBy: USER\n    80→              ) {\n    81→                id\n    82→                name\n    83→                totalJobs\n    84→              }\n    85→              topProjectJobs: jobsStatistics(\n    86→                filter: $filter\n    87→                page: $paging\n    88→                sortBy: TOTALJOBS\n    89→                groupBy: PROJECT\n    90→              ) {\n    91→                id\n    92→                totalJobs\n    93→              }\n    94→              topUserNodes: jobsStatistics(\n    95→                filter: $filter\n    96→                page: $paging\n    97→                sortBy: TOTALNODES\n    98→                groupBy: USER\n    99→              ) {\n   100→                id\n   101→                name\n   102→                totalNodes\n   103→              }\n   104→              topProjectNodes: jobsStatistics(\n   105→                filter: $filter\n   106→                page: $paging\n   107→                sortBy: TOTALNODES\n   108→                groupBy: PROJECT\n   109→              ) {\n   110→                id\n   111→                totalNodes\n   112→              }\n   113→              topUserAccs: jobsStatistics(\n   114→                filter: $filter\n   115→                page: $paging\n   116→                sortBy: TOTALACCS\n   117→                groupBy: USER\n   118→              ) {\n   119→                id\n   120→                name\n   121→                totalAccs\n   122→              }\n   123→              topProjectAccs: jobsStatistics(\n   124→                filter: $filter\n   125→                page: $paging\n   126→                sortBy: TOTALACCS\n   127→                groupBy: PROJECT\n   128→              ) {\n   129→                id\n   130→                totalAccs\n   131→              }\n   132→            }\n   133→          `,\n   134→          variables: {\n   135→            filter: statusFilter,\n   136→            paging: pagingState, // Top 10\n   137→          },\n   138→          requestPolicy: \"network-only\",\n   139→        })\n   140→      : null,\n   141→  );\n   142→\n   143→  // Note: nodeMetrics are requested on configured $timestep resolution\n   144→  const nodeStatusQuery = $derived(\n   145→    loadMe\n   146→      ? queryStore({\n   147→          client: client,\n   148→          query: gql`\n   149→            query (\n   150→              $filter: [JobFilter!]!\n   151→              $selectedHistograms: [String!]\n   152→              $numDurationBins: String\n   153→            ) {\n   154→              jobsStatistics(\n   155→                filter: $filter\n   156→                metrics: $selectedHistograms\n   157→                numDurationBins: $numDurationBins\n   158→              ) {\n   159→                histDuration {\n   160→                  count\n   161→                  value\n   162→                }\n   163→                histNumNodes {\n   164→                  count\n   165→                  value\n   166→                }\n   167→                histNumAccs {\n   168→                  count\n   169→                  value\n   170→                }\n   171→              }\n   172→            }\n   173→          `,\n   174→          variables: {\n   175→            filter: statusFilter,\n   176→            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n   177→            numDurationBins: numDurationBins,\n   178→          },\n   179→          requestPolicy: \"network-only\",\n   180→        })\n   181→      : null,\n   182→  );\n   183→\n   184→  /* Functions */\n   185→  function legendColors(targetIdx) {\n   186→    // Reuses first color if targetIdx overflows\n   187→    let c;\n   188→    if (useCbColors) {\n   189→      c = [...colors[\"colorblind\"]];\n   190→    } else if (useAltColors) {\n   191→      c = [...colors[\"alternative\"]];\n   192→    } else {\n   193→      c = [...colors[\"default\"]];\n   194→    }\n   195→    return c[(c.length + targetIdx) % c.length];\n   196→  }\n   197→</script>\n   198→\n   199→<!-- Refresher and space for other options -->\n   200→<Row class=\"justify-content-between\">\n   201→  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n   202→    <InputGroup>\n   203→      <InputGroupText>\n   204→        <Icon name=\"bar-chart-line-fill\" />\n   205→      </InputGroupText>\n   206→      <InputGroupText>Duration Bin Size</InputGroupText>\n   207→      <Input type=\"select\" bind:value={numDurationBins}>\n   208→        {#each durationBinOptions as dbin}\n   209→          <option value={dbin}>{dbin}</option>\n   210→        {/each}\n   211→      </Input>\n   212→    </InputGroup>\n   213→  </Col>\n   214→  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n   215→    <Refresher\n   216→      initially={120}\n   217→      onRefresh={() => {\n   218→        pagingState = { page: 1, itemsPerPage: 10 };\n   219→        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n   220→      }}\n   221→    />\n   222→  </Col>\n   223→</Row>\n   224→\n   225→<hr />\n   226→\n   227→<!-- Job Duration, Top Users and Projects-->\n   228→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n   229→  <Spinner />\n   230→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n   231→  <Row>\n   232→    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n   233→      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n   234→        <Histogram\n   235→          data={convert2uplot(\n   236→            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n   237→          )}\n   238→          title=\"Duration Distribution\"\n   239→          xlabel=\"Current Job Runtimes\"\n   240→          xunit=\"Runtime\"\n   241→          ylabel=\"Number of Jobs\"\n   242→          yunit=\"Jobs\"\n   243→          height=\"275\"\n   244→          usesBins\n   245→          xtime\n   246→          enableFlip\n   247→        />\n   248→      {/key}\n   249→    </Col>\n   250→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   251→      <div bind:clientWidth={colWidthJobs}>\n   252→        <h4 class=\"text-center\">Top Users: Jobs</h4>\n   253→        <Pie\n   254→          {useAltColors}\n   255→          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n   256→          size={colWidthJobs * 0.75}\n   257→          sliceLabel=\"Jobs\"\n   258→          quantities={$topStatsQuery.data.topUserJobs.map(\n   259→            (tu) => 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→      </div>\n   266→    </Col>\n   267→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   268→      <Table>\n   269→        <tr class=\"mb-2\">\n   270→          <th></th>\n   271→          <th style=\"padding-left: 0.5rem;\">User</th>\n   272→          <th>Jobs</th>\n   273→        </tr>\n   274→        {#each $topStatsQuery.data.topUserJobs as tu, i}\n   275→          <tr>\n   276→            <td\n   277→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   278→            >\n   279→            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n   280→              <a\n   281→                target=\"_blank\"\n   282→                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n   283→                  ? '&partition=' + presetSubCluster\n   284→                  : ''}&state=running\"\n   285→                >{scrambleNames ? scramble(tu.id) : tu.id}\n   286→              </a>\n   287→            </td>\n   288→            {#if tu?.name}\n   289→              <Tooltip\n   290→                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n   291→                placement=\"left\"\n   292→                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n   293→              >\n   294→            {/if}\n   295→            <td>{tu[\"totalJobs\"]}</td>\n   296→          </tr>\n   297→        {/each}\n   298→      </Table>\n   299→    </Col>\n   300→\n   301→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   302→      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n   303→      <Pie\n   304→        {useAltColors}\n   305→        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n   306→        size={colWidthJobs * 0.75}\n   307→        sliceLabel={\"Jobs\"}\n   308→        quantities={$topStatsQuery.data.topProjectJobs.map(\n   309→          (tp) => 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→    </Col>\n   316→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   317→      <Table>\n   318→        <tr class=\"mb-2\">\n   319→          <th></th>\n   320→          <th style=\"padding-left: 0.5rem;\">Project</th>\n   321→          <th>Jobs</th>\n   322→        </tr>\n   323→        {#each $topStatsQuery.data.topProjectJobs as tp, i}\n   324→          <tr>\n   325→            <td\n   326→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   327→            >\n   328→            <td>\n   329→              <a\n   330→                target=\"_blank\"\n   331→                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n   332→                  ? '&partition=' + presetSubCluster\n   333→                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n   334→                >{scrambleNames ? scramble(tp.id) : tp.id}\n   335→              </a>\n   336→            </td>\n   337→            <td>{tp[\"totalJobs\"]}</td>\n   338→          </tr>\n   339→        {/each}\n   340→      </Table>\n   341→    </Col>\n   342→  </Row>\n   343→{:else}\n   344→  <Card class=\"mx-4\" body color=\"warning\"\n   345→    >Cannot render job status charts: No data!</Card\n   346→  >\n   347→{/if}\n   348→\n   349→<hr />\n   350→\n   351→<!-- Node Distribution, Top Users and Projects-->\n   352→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n   353→  <Spinner />\n   354→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n   355→  <Row>\n   356→    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n   357→      <Histogram\n   358→        data={convert2uplot(\n   359→          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n   360→        )}\n   361→        title=\"Number of Nodes Distribution\"\n   362→        xlabel=\"Allocated Nodes\"\n   363→        xunit=\"Nodes\"\n   364→        ylabel=\"Number of Jobs\"\n   365→        yunit=\"Jobs\"\n   366→        height=\"275\"\n   367→        enableFlip\n   368→      />\n   369→    </Col>\n   370→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   371→      <div bind:clientWidth={colWidthNodes}>\n   372→        <h4 class=\"text-center\">Top Users: Nodes</h4>\n   373→        <Pie\n   374→          {useAltColors}\n   375→          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n   376→          size={colWidthNodes * 0.75}\n   377→          sliceLabel=\"Nodes\"\n   378→          quantities={$topStatsQuery.data.topUserNodes.map(\n   379→            (tu) => 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→      </div>\n   386→    </Col>\n   387→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   388→      <Table>\n   389→        <tr class=\"mb-2\">\n   390→          <th></th>\n   391→          <th style=\"padding-left: 0.5rem;\">User</th>\n   392→          <th>Nodes</th>\n   393→        </tr>\n   394→        {#each $topStatsQuery.data.topUserNodes as tu, i}\n   395→          <tr>\n   396→            <td\n   397→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   398→            >\n   399→            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n   400→              <a\n   401→                target=\"_blank\"\n   402→                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n   403→                  ? '&partition=' + presetSubCluster\n   404→                  : ''}&state=running\"\n   405→                >{scrambleNames ? scramble(tu.id) : tu.id}\n   406→              </a>\n   407→            </td>\n   408→            {#if tu?.name}\n   409→              <Tooltip\n   410→                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n   411→                placement=\"left\"\n   412→                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n   413→              >\n   414→            {/if}\n   415→            <td>{tu[\"totalNodes\"]}</td>\n   416→          </tr>\n   417→        {/each}\n   418→      </Table>\n   419→    </Col>\n   420→\n   421→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   422→      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n   423→      <Pie\n   424→        {useAltColors}\n   425→        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n   426→        size={colWidthNodes * 0.75}\n   427→        sliceLabel={\"Nodes\"}\n   428→        quantities={$topStatsQuery.data.topProjectNodes.map(\n   429→          (tp) => 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→    </Col>\n   436→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   437→      <Table>\n   438→        <tr class=\"mb-2\">\n   439→          <th></th>\n   440→          <th style=\"padding-left: 0.5rem;\">Project</th>\n   441→          <th>Nodes</th>\n   442→        </tr>\n   443→        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n   444→          <tr>\n   445→            <td\n   446→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   447→            >\n   448→            <td>\n   449→              <a\n   450→                target=\"_blank\"\n   451→                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n   452→                  ? '&partition=' + presetSubCluster\n   453→                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n   454→                >{scrambleNames ? scramble(tp.id) : tp.id}\n   455→              </a>\n   456→            </td>\n   457→            <td>{tp[\"totalNodes\"]}</td>\n   458→          </tr>\n   459→        {/each}\n   460→      </Table>\n   461→    </Col>\n   462→  </Row>\n   463→{:else}\n   464→  <Card class=\"mx-4\" body color=\"warning\"\n   465→    >Cannot render node status charts: No data!</Card\n   466→  >\n   467→{/if}\n   468→\n   469→<hr />\n   470→\n   471→<!-- Acc Distribution, Top Users and Projects-->\n   472→{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n   473→  <Spinner />\n   474→{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n   475→  <Row>\n   476→    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n   477→      <Histogram\n   478→        data={convert2uplot(\n   479→          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n   480→        )}\n   481→        title=\"Number of Accelerators Distribution\"\n   482→        xlabel=\"Allocated Accs\"\n   483→        xunit=\"Accs\"\n   484→        ylabel=\"Number of Jobs\"\n   485→        yunit=\"Jobs\"\n   486→        height=\"275\"\n   487→        enableFlip\n   488→      />\n   489→    </Col>\n   490→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   491→      <div bind:clientWidth={colWidthAccs}>\n   492→        <h4 class=\"text-center\">Top Users: GPUs</h4>\n   493→        <Pie\n   494→          {useAltColors}\n   495→          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n   496→          size={colWidthAccs * 0.75}\n   497→          sliceLabel=\"GPUs\"\n   498→          quantities={$topStatsQuery.data.topUserAccs.map(\n   499→            (tu) => 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→      </div>\n   506→    </Col>\n   507→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   508→      <Table>\n   509→        <tr class=\"mb-2\">\n   510→          <th></th>\n   511→          <th style=\"padding-left: 0.5rem;\">User</th>\n   512→          <th>GPUs</th>\n   513→        </tr>\n   514→        {#each $topStatsQuery.data.topUserAccs as tu, i}\n   515→          <tr>\n   516→            <td\n   517→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   518→            >\n   519→            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n   520→              <a\n   521→                target=\"_blank\"\n   522→                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n   523→                  ? '&partition=' + presetSubCluster\n   524→                  : ''}&state=running\"\n   525→                >{scrambleNames ? scramble(tu.id) : tu.id}\n   526→              </a>\n   527→            </td>\n   528→            {#if tu?.name}\n   529→              <Tooltip\n   530→                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n   531→                placement=\"left\"\n   532→                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n   533→              >\n   534→            {/if}\n   535→            <td>{tu[\"totalAccs\"]}</td>\n   536→          </tr>\n   537→        {/each}\n   538→      </Table>\n   539→    </Col>\n   540→\n   541→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   542→      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n   543→      <Pie\n   544→        {useAltColors}\n   545→        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n   546→        size={colWidthAccs * 0.75}\n   547→        sliceLabel={\"GPUs\"}\n   548→        quantities={$topStatsQuery.data.topProjectAccs.map(\n   549→          (tp) => 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→    </Col>\n   556→    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n   557→      <Table>\n   558→        <tr class=\"mb-2\">\n   559→          <th></th>\n   560→          <th style=\"padding-left: 0.5rem;\">Project</th>\n   561→          <th>GPUs</th>\n   562→        </tr>\n   563→        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n   564→          <tr>\n   565→            <td\n   566→              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n   567→            >\n   568→            <td>\n   569→              <a\n   570→                target=\"_blank\"\n   571→                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n   572→                  ? '&partition=' + presetSubCluster\n   573→                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n   574→                >{scrambleNames ? scramble(tp.id) : tp.id}\n   575→              </a>\n   576→            </td>\n   577→            <td>{tp[\"totalAccs\"]}</td>\n   578→          </tr>\n   579→        {/each}\n   580→      </Table>\n   581→    </Col>\n   582→  </Row>\n   583→{:else}\n   584→  <Card class=\"mx-4\" body color=\"warning\"\n   585→    >Cannot render accelerator status charts: No data!</Card\n   586→  >\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  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={$topStatsQuery.data.topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={$topStatsQuery.data.topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={$topStatsQuery.data.topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={$topStatsQuery.data.topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render accelerator status charts: No data!</Card\n  >\n{/if}\n","numLines":588,"startLine":1,"totalLines":588}},"sourceToolAssistantUUID":"97a1b420-fab3-40a5-887f-c3e910c1f05e","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":"bb4cee48-160d-4e3d-957c-91f58a93a5ef","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XpMPDASZUFur5KWX4TGzFe","type":"tool_result","content":"     1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n     2→// All rights reserved. This file is part of cc-backend.\n     3→// Use of this source code is governed by a MIT-style\n     4→// license that can be found in the LICENSE file.\n     5→\n     6→package graph\n     7→\n     8→import (\n     9→\t\"context\"\n    10→\t\"fmt\"\n    11→\t\"math\"\n    12→\t\"slices\"\n    13→\n    14→\t\"github.com/99designs/gqlgen/graphql\"\n    15→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n    16→\t\"github.com/ClusterCockpit/cc-backend/internal/metricdispatch\"\n    17→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    18→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    19→)\n    20→\n    21→const MAX_JOBS_FOR_ANALYSIS = 500\n    22→\n    23→// Helper function for the rooflineHeatmap GraphQL query placed here so that schema.resolvers.go is not too full.\n    24→func (r *queryResolver) rooflineHeatmap(\n    25→\tctx context.Context,\n    26→\tfilter []*model.JobFilter,\n    27→\trows int, cols int,\n    28→\tminX float64, minY float64, maxX float64, maxY float64,\n    29→) ([][]float64, error) {\n    30→\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n    31→\tif err != nil {\n    32→\t\tcclog.Error(\"Error while querying jobs for roofline\")\n    33→\t\treturn nil, err\n    34→\t}\n    35→\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n    36→\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n    37→\t}\n    38→\n    39→\tfcols, frows := float64(cols), float64(rows)\n    40→\tminX, minY, maxX, maxY = math.Log10(minX), math.Log10(minY), math.Log10(maxX), math.Log10(maxY)\n    41→\ttiles := make([][]float64, rows)\n    42→\tfor i := range tiles {\n    43→\t\ttiles[i] = make([]float64, cols)\n    44→\t}\n    45→\n    46→\tfor _, job := range jobs {\n    47→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n    48→\t\t\tcontinue\n    49→\t\t}\n    50→\n    51→\t\t// metricConfigs := archive.GetCluster(job.Cluster).MetricConfig\n    52→\t\t// resolution := 0\n    53→\n    54→\t\t// for _, mc := range metricConfigs {\n    55→\t\t// \tresolution = max(resolution, mc.Timestep)\n    56→\t\t// }\n    57→\n    58→\t\tjobdata, err := metricdispatch.LoadData(job, []string{\"flops_any\", \"mem_bw\"}, []schema.MetricScope{schema.MetricScopeNode}, ctx, 0)\n    59→\t\tif err != nil {\n    60→\t\t\tcclog.Warnf(\"Error while loading roofline metrics for job %d\", *job.ID)\n    61→\t\t\treturn nil, err\n    62→\t\t}\n    63→\n    64→\t\tflops_, membw_ := jobdata[\"flops_any\"], jobdata[\"mem_bw\"]\n    65→\t\tif flops_ == nil && membw_ == nil {\n    66→\t\t\tcclog.Warnf(\"rooflineHeatmap(): 'flops_any' or 'mem_bw' missing for job %d\", *job.ID)\n    67→\t\t\tcontinue\n    68→\t\t\t// return nil, fmt.Errorf(\"GRAPH/UTIL > 'flops_any' or 'mem_bw' missing for job %d\", job.ID)\n    69→\t\t}\n    70→\n    71→\t\tflops, ok1 := flops_[\"node\"]\n    72→\t\tmembw, ok2 := membw_[\"node\"]\n    73→\t\tif !ok1 || !ok2 {\n    74→\t\t\tcclog.Info(\"rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level\")\n    75→\t\t\tcontinue\n    76→\t\t\t// TODO/FIXME:\n    77→\t\t\t// return nil, errors.New(\"GRAPH/UTIL > todo: rooflineHeatmap() query not implemented for where flops_any or mem_bw not available at 'node' level\")\n    78→\t\t}\n    79→\n    80→\t\tfor n := 0; n < len(flops.Series); n++ {\n    81→\t\t\tflopsSeries, membwSeries := flops.Series[n], membw.Series[n]\n    82→\t\t\tfor i := 0; i < len(flopsSeries.Data); i++ {\n    83→\t\t\t\tif i >= len(membwSeries.Data) {\n    84→\t\t\t\t\tbreak\n    85→\t\t\t\t}\n    86→\n    87→\t\t\t\tx, y := math.Log10(float64(flopsSeries.Data[i]/membwSeries.Data[i])), math.Log10(float64(flopsSeries.Data[i]))\n    88→\t\t\t\tif math.IsNaN(x) || math.IsNaN(y) || x < minX || x >= maxX || y < minY || y > maxY {\n    89→\t\t\t\t\tcontinue\n    90→\t\t\t\t}\n    91→\n    92→\t\t\t\tx, y = math.Floor(((x-minX)/(maxX-minX))*fcols), math.Floor(((y-minY)/(maxY-minY))*frows)\n    93→\t\t\t\tif x < 0 || x >= fcols || y < 0 || y >= frows {\n    94→\t\t\t\t\tcontinue\n    95→\t\t\t\t}\n    96→\n    97→\t\t\t\ttiles[int(y)][int(x)] += 1\n    98→\t\t\t}\n    99→\t\t}\n   100→\t}\n   101→\n   102→\treturn tiles, nil\n   103→}\n   104→\n   105→// Helper function for the jobsFootprints GraphQL query placed here so that schema.resolvers.go is not too full.\n   106→func (r *queryResolver) jobsFootprints(ctx context.Context, filter []*model.JobFilter, metrics []string) (*model.Footprints, error) {\n   107→\tjobs, err := r.Repo.QueryJobs(ctx, filter, &model.PageRequest{Page: 1, ItemsPerPage: MAX_JOBS_FOR_ANALYSIS + 1}, nil)\n   108→\tif err != nil {\n   109→\t\tcclog.Error(\"Error while querying jobs for footprint\")\n   110→\t\treturn nil, err\n   111→\t}\n   112→\tif len(jobs) > MAX_JOBS_FOR_ANALYSIS {\n   113→\t\treturn nil, fmt.Errorf(\"GRAPH/UTIL > too many jobs matched (max: %d)\", MAX_JOBS_FOR_ANALYSIS)\n   114→\t}\n   115→\n   116→\tavgs := make([][]schema.Float, len(metrics))\n   117→\tfor i := range avgs {\n   118→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n   119→\t}\n   120→\n   121→\ttimeweights := new(model.TimeWeights)\n   122→\ttimeweights.NodeHours = make([]schema.Float, 0, len(jobs))\n   123→\ttimeweights.AccHours = make([]schema.Float, 0, len(jobs))\n   124→\ttimeweights.CoreHours = make([]schema.Float, 0, len(jobs))\n   125→\n   126→\tfor _, job := range jobs {\n   127→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n   128→\t\t\tcontinue\n   129→\t\t}\n   130→\n   131→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n   132→\t\t\tcclog.Error(\"Error while loading averages for footprint\")\n   133→\t\t\treturn nil, err\n   134→\t\t}\n   135→\n   136→\t\t// #166 collect arrays: Null values or no null values?\n   137→\t\ttimeweights.NodeHours = append(timeweights.NodeHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumNodes)))\n   138→\t\tif job.NumAcc > 0 {\n   139→\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumAcc)))\n   140→\t\t} else {\n   141→\t\t\ttimeweights.AccHours = append(timeweights.AccHours, schema.Float(1.0))\n   142→\t\t}\n   143→\t\tif job.NumHWThreads > 0 {\n   144→\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(float64(job.Duration)/60.0*float64(job.NumHWThreads))) // SQLite HWThreads == Cores; numCoresForJob(job)\n   145→\t\t} else {\n   146→\t\t\ttimeweights.CoreHours = append(timeweights.CoreHours, schema.Float(1.0))\n   147→\t\t}\n   148→\t}\n   149→\n   150→\tres := make([]*model.MetricFootprints, len(avgs))\n   151→\tfor i, arr := range avgs {\n   152→\t\tres[i] = &model.MetricFootprints{\n   153→\t\t\tMetric: metrics[i],\n   154→\t\t\tData:   arr,\n   155→\t\t}\n   156→\t}\n   157→\n   158→\treturn &model.Footprints{\n   159→\t\tTimeWeights: timeweights,\n   160→\t\tMetrics:     res,\n   161→\t}, nil\n   162→}\n   163→\n   164→// func numCoresForJob(job *schema.Job) (numCores int) {\n   165→\n   166→// \tsubcluster, scerr := archive.GetSubCluster(job.Cluster, job.SubCluster)\n   167→// \tif scerr != nil {\n   168→// \t\treturn 1\n   169→// \t}\n   170→\n   171→// \ttotalJobCores := 0\n   172→// \ttopology := subcluster.Topology\n   173→\n   174→// \tfor _, host := range job.Resources {\n   175→// \t\thwthreads := host.HWThreads\n   176→// \t\tif hwthreads == nil {\n   177→// \t\t\thwthreads = topology.Node\n   178→// \t\t}\n   179→\n   180→// \t\thostCores, _ := topology.GetCoresFromHWThreads(hwthreads)\n   181→// \t\ttotalJobCores += len(hostCores)\n   182→// \t}\n   183→\n   184→// \treturn totalJobCores\n   185→// }\n   186→\n   187→func requireField(ctx context.Context, name string) bool {\n   188→\tfields := graphql.CollectAllFields(ctx)\n   189→\n   190→\treturn slices.Contains(fields, name)\n   191→}\n   192→"}]},"uuid":"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, name)\n}\n","numLines":192,"startLine":1,"totalLines":192}},"sourceToolAssistantUUID":"bb4cee48-160d-4e3d-957c-91f58a93a5ef","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// 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"}
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{"parentUuid":"baf6c3cd-6efa-4688-b896-009e95b689ce","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Mff9BC491Wna1x7Xmo5CPR","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go has been updated successfully."}]},"uuid":"a67b6524-44f4-4584-a05d-caa94055263a","timestamp":"2026-03-13T13:24:51.181Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/jobQuery.go","oldString":"\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 {","newString":"\tif filter.State != nil {\n\t\tif len(filter.State) == 1 {\n\t\t\t// Inline literal value so SQLite can match partial indexes (WHERE job_state = 'running').\n\t\t\t// Safe: values come from validated GraphQL enum (model.JobState).\n\t\t\tsingleStat := string(filter.State[0])\n\t\t\tquery = query.Where(fmt.Sprintf(\"job.job_state = '%s'\", singleStat))\n\t\t} else {","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 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"}
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{"parentUuid":"2ce24c06-01d6-4a1d-b5cd-ab18359a28d4","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01ChG3FEWRdrrsT6ixU62MS1","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/cmd/cc-backend/server.go has been updated successfully."}]},"uuid":"fbc68978-0297-4973-88de-579028c2ffd2","timestamp":"2026-03-13T13:25:09.395Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/cmd/cc-backend/server.go","oldString":"\tgraphQLServer.AddTransport(transport.POST{})","newString":"\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})","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\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"}
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{"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"}
{"parentUuid":"7614be57-18de-43d4-8812-f22a8e194b90","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EfUFviDtEyXqBAmfZ5tmq8","type":"message","role":"assistant","content":[{"type":"text","text":"Now add the `graphql` import in server.go:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":350,"cache_read_input_tokens":81781,"cache_creation":{"ephemeral_5m_input_tokens":350,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ19tcxctRUD5B6GkqFoP","type":"assistant","uuid":"09813721-1b08-4f1b-8b91-a5f7e40bfab7","timestamp":"2026-03-13T13:25:30.522Z","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":"a6793013-5aa1-4d87-a824-43b6009afa64","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PzrJcsrW34E3y19BM8FzMD","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/cmd/cc-backend/server.go has been updated 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\"","   \"github.com/99designs/gqlgen/graphql/handler\"","   \"github.com/99designs/gqlgen/graphql/handler/transport\"","   \"github.com/99designs/gqlgen/graphql/playground\""]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"a6793013-5aa1-4d87-a824-43b6009afa64","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":"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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{"parentUuid":"eac31e9f-039b-463c-bc87-91c1da020980","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DE6W1e535THYg1yPxfhaat","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go has been updated 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 &timestamp, 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"}
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{"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"}
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{"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"}
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{"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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{"parentUuid":"0e037919-ff3a-40ad-92a5-ae71452dc934","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01A9eSBgqs6MPiEUKr19HLcj","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go has been updated 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"}
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{"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"}
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{"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"}
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{"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"}
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{"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  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={$topStatsQuery.data.topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={$topStatsQuery.data.topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={$topStatsQuery.data.topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={$topStatsQuery.data.topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render accelerator status charts: No data!</Card\n  >\n{/if}\n","structuredPatch":[{"oldStart":71,"oldLines":75,"newStart":71,"newLines":68,"lines":["       ? queryStore({","           client: client,","           query: gql`","-            query ($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":"$topStatsQuery.data.topUserJobs","new_string":"topUserJobs"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1252,"cache_read_input_tokens":87924,"cache_creation":{"ephemeral_5m_input_tokens":1252,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1A27ouBKHhKayLKEdw6","type":"assistant","uuid":"ecfb8b92-d249-49e6-a2a2-7f6066ac1a57","timestamp":"2026-03-13T13:27:00.055Z","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"}
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{"parentUuid":"ecfb8b92-d249-49e6-a2a2-7f6066ac1a57","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TxQQJm7gJidvyrWhuADT82","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$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  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={$topStatsQuery.data.topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={$topStatsQuery.data.topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={$topStatsQuery.data.topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={$topStatsQuery.data.topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={$topStatsQuery.data.topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? 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{"parentUuid":"84399fa0-a545-496c-92ca-c3f06e367fbc","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FZTcoDHkyd1rTEfZUbUntn","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topProjectJobs' were successfully replaced with 'topProjectJobs'."}]},"uuid":"def5acef-ff14-4b8c-828a-849d82be48fc","timestamp":"2026-03-13T13:27:01.321Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topProjectJobs","newString":"topProjectJobs","originalFile":"<!--\n  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={$topStatsQuery.data.topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={$topStatsQuery.data.topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? 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'&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? 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{"parentUuid":"e493c9f1-b673-4931-8bbe-110467a23895","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JehtXMUZHtraQNi4nHNxav","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topUserNodes' were successfully replaced with 'topUserNodes'."}]},"uuid":"ec250e48-1916-4dc6-8fec-a5a7e6709909","timestamp":"2026-03-13T13:27:02.211Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topUserNodes","newString":"topUserNodes","originalFile":"<!--\n  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={$topStatsQuery.data.topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={$topStatsQuery.data.topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={$topStatsQuery.data.topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? 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{"parentUuid":"7416010c-0eb5-4526-99b2-bc7d21409862","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018Aa5atSM4pNPvNU7oyXQ4i","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topProjectNodes' were successfully replaced with 'topProjectNodes'."}]},"uuid":"0cea1c9b-7ebf-4096-831f-3ff80851fc3d","timestamp":"2026-03-13T13:27:03.089Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topProjectNodes","newString":"topProjectNodes","originalFile":"<!--\n  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={$topStatsQuery.data.topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={$topStatsQuery.data.topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render accelerator status charts: No data!</Card\n  >\n{/if}\n","structuredPatch":[{"oldStart":418,"oldLines":10,"newStart":418,"newLines":10,"lines":["         canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"","         size={colWidthNodes * 0.75}","         sliceLabel={\"Nodes\"}","-        quantities={$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":["           <th style=\"padding-left: 0.5rem;\">Project</th>","           <th>Nodes</th>","         </tr>","-        {#each $topStatsQuery.data.topProjectNodes as tp, i}","+        {#each topProjectNodes as tp, i}","           <tr>","             <td","               ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td"]}],"userModified":false,"replaceAll":true},"sourceToolAssistantUUID":"7416010c-0eb5-4526-99b2-bc7d21409862","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"}
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{"parentUuid":"8610ac95-a24c-4c79-b6ab-956b8d065dcf","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CMKNNR67KmjdHaMtnuNi4j","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topUserAccs' were successfully replaced with 'topUserAccs'."}]},"uuid":"b3e6f70d-5c6e-4741-a60a-bfa4c7889c8b","timestamp":"2026-03-13T13:27:04.426Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topUserAccs","newString":"topUserAccs","originalFile":"<!--\n  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={$topStatsQuery.data.topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={$topStatsQuery.data.topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? 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{"parentUuid":"cf59e344-e721-4ecc-ac03-a852830ec917","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NkRtgakXsp7iigY87AoYLT","type":"tool_result","content":"The file /Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte has been updated. All occurrences of '$topStatsQuery.data.topProjectAccs' were successfully replaced with 'topProjectAccs'."}]},"uuid":"402e08ae-c29a-470b-991e-6c8e806e2e5b","timestamp":"2026-03-13T13:27:05.077Z","toolUseResult":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend/src/status/dashdetails/UsageDash.svelte","oldString":"$topStatsQuery.data.topProjectAccs","newString":"topProjectAccs","originalFile":"<!--\n  @component Main cluster status view component; renders current system-usage information\n\n  Properties:\n  - `presetCluster String`: The cluster to show status information for\n  - `presetSubCluster String?`: The subCluster to show status information for [Default: null]\n  - `useCbColors Bool?`: Use colorblind friendly colors [Default: false]\n  - `useAltColors Bool?`: Use alternative color set [Default: false]\n-->\n\n<script>\n  import {\n    Row,\n    Col,\n    Spinner,\n    Card,\n    Table,\n    Icon,\n    Tooltip,\n    Input,\n    InputGroup,\n    InputGroupText,\n  } from \"@sveltestrap/sveltestrap\";\n  import { queryStore, gql, getContextClient } from \"@urql/svelte\";\n  import {\n    scramble,\n    scrambleNames,\n    convert2uplot,\n  } from \"../../generic/utils.js\";\n  import Pie, { colors } from \"../../generic/plots/Pie.svelte\";\n  import Histogram from \"../../generic/plots/Histogram.svelte\";\n  import Refresher from \"../../generic/helper/Refresher.svelte\";\n\n  /* Svelte 5 Props */\n  let {\n    presetCluster,\n    presetSubCluster = null,\n    useCbColors = false,\n    useAltColors = false,\n    loadMe = false,\n  } = $props();\n\n  /* Const Init */\n  const client = getContextClient();\n  const durationBinOptions = [\"1m\", \"10m\", \"1h\", \"6h\", \"12h\"];\n\n  /* State Init */\n  let pagingState = $state({ page: 1, itemsPerPage: 10 }); // Top 10\n  let selectedHistograms = $state([]); // Dummy For Refresh\n  let colWidthJobs = $state(0);\n  let colWidthNodes = $state(0);\n  let colWidthAccs = $state(0);\n  let numDurationBins = $state(\"1h\");\n\n  /* Derived */\n  const canvasPrefix = $derived(\n    `${presetCluster}-${presetSubCluster ? presetSubCluster : \"\"}`,\n  );\n\n  const statusFilter = $derived(\n    presetSubCluster\n      ? [\n          { cluster: { eq: presetCluster } },\n          { subCluster: { eq: presetSubCluster } },\n          { state: [\"running\"] },\n        ]\n      : [{ cluster: { eq: presetCluster } }, { state: [\"running\"] }],\n  );\n  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  );\n\n  // Note: nodeMetrics are requested on configured $timestep resolution\n  const nodeStatusQuery = $derived(\n    loadMe\n      ? queryStore({\n          client: client,\n          query: gql`\n            query (\n              $filter: [JobFilter!]!\n              $selectedHistograms: [String!]\n              $numDurationBins: String\n            ) {\n              jobsStatistics(\n                filter: $filter\n                metrics: $selectedHistograms\n                numDurationBins: $numDurationBins\n              ) {\n                histDuration {\n                  count\n                  value\n                }\n                histNumNodes {\n                  count\n                  value\n                }\n                histNumAccs {\n                  count\n                  value\n                }\n              }\n            }\n          `,\n          variables: {\n            filter: statusFilter,\n            selectedHistograms: selectedHistograms, // No Metrics requested for node hardware stats\n            numDurationBins: numDurationBins,\n          },\n          requestPolicy: \"network-only\",\n        })\n      : null,\n  );\n\n  /* Functions */\n  function legendColors(targetIdx) {\n    // Reuses first color if targetIdx overflows\n    let c;\n    if (useCbColors) {\n      c = [...colors[\"colorblind\"]];\n    } else if (useAltColors) {\n      c = [...colors[\"alternative\"]];\n    } else {\n      c = [...colors[\"default\"]];\n    }\n    return c[(c.length + targetIdx) % c.length];\n  }\n</script>\n\n<!-- Refresher and space for other options -->\n<Row class=\"justify-content-between\">\n  <Col class=\"mb-2 mb-md-0\" xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <InputGroup>\n      <InputGroupText>\n        <Icon name=\"bar-chart-line-fill\" />\n      </InputGroupText>\n      <InputGroupText>Duration Bin Size</InputGroupText>\n      <Input type=\"select\" bind:value={numDurationBins}>\n        {#each durationBinOptions as dbin}\n          <option value={dbin}>{dbin}</option>\n        {/each}\n      </Input>\n    </InputGroup>\n  </Col>\n  <Col xs=\"12\" md=\"5\" lg=\"4\" xl=\"3\">\n    <Refresher\n      initially={120}\n      onRefresh={() => {\n        pagingState = { page: 1, itemsPerPage: 10 };\n        selectedHistograms = [...$state.snapshot(selectedHistograms)];\n      }}\n    />\n  </Col>\n</Row>\n\n<hr />\n\n<!-- Job Duration, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      {#key $nodeStatusQuery.data.jobsStatistics[0].histDuration}\n        <Histogram\n          data={convert2uplot(\n            $nodeStatusQuery.data.jobsStatistics[0].histDuration,\n          )}\n          title=\"Duration Distribution\"\n          xlabel=\"Current Job Runtimes\"\n          xunit=\"Runtime\"\n          ylabel=\"Number of Jobs\"\n          yunit=\"Jobs\"\n          height=\"275\"\n          usesBins\n          xtime\n          enableFlip\n        />\n      {/key}\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthJobs}>\n        <h4 class=\"text-center\">Top Users: Jobs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-jobs-users\"\n          size={colWidthJobs * 0.75}\n          sliceLabel=\"Jobs\"\n          quantities={topUserJobs.map(\n            (tu) => tu[\"totalJobs\"],\n          )}\n          entities={topUserJobs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topUserJobs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-jobs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-jobs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Jobs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-jobs-projects\"\n        size={colWidthJobs * 0.75}\n        sliceLabel={\"Jobs\"}\n        quantities={topProjectJobs.map(\n          (tp) => tp[\"totalJobs\"],\n        )}\n        entities={topProjectJobs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Jobs</th>\n        </tr>\n        {#each topProjectJobs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalJobs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render job status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Node Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumNodes,\n        )}\n        title=\"Number of Nodes Distribution\"\n        xlabel=\"Allocated Nodes\"\n        xunit=\"Nodes\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthNodes}>\n        <h4 class=\"text-center\">Top Users: Nodes</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-nodes-users\"\n          size={colWidthNodes * 0.75}\n          sliceLabel=\"Nodes\"\n          quantities={topUserNodes.map(\n            (tu) => tu[\"totalNodes\"],\n          )}\n          entities={topUserNodes.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>Nodes</th>\n        </tr>\n        {#each topUserNodes as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-nodes-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-nodes-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: Nodes</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-nodes-projects\"\n        size={colWidthNodes * 0.75}\n        sliceLabel={\"Nodes\"}\n        quantities={topProjectNodes.map(\n          (tp) => tp[\"totalNodes\"],\n        )}\n        entities={topProjectNodes.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>Nodes</th>\n        </tr>\n        {#each topProjectNodes as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalNodes\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render node status charts: No data!</Card\n  >\n{/if}\n\n<hr />\n\n<!-- Acc Distribution, Top Users and Projects-->\n{#if $topStatsQuery?.fetching || $nodeStatusQuery?.fetching}\n  <Spinner />\n{:else if $topStatsQuery?.data && $nodeStatusQuery?.data}\n  <Row>\n    <Col xs=\"12\" lg=\"4\" class=\"p-2\">\n      <Histogram\n        data={convert2uplot(\n          $nodeStatusQuery.data.jobsStatistics[0].histNumAccs,\n        )}\n        title=\"Number of Accelerators Distribution\"\n        xlabel=\"Allocated Accs\"\n        xunit=\"Accs\"\n        ylabel=\"Number of Jobs\"\n        yunit=\"Jobs\"\n        height=\"275\"\n        enableFlip\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <div bind:clientWidth={colWidthAccs}>\n        <h4 class=\"text-center\">Top Users: GPUs</h4>\n        <Pie\n          {useAltColors}\n          canvasId=\"{canvasPrefix}-hpcpie-accs-users\"\n          size={colWidthAccs * 0.75}\n          sliceLabel=\"GPUs\"\n          quantities={topUserAccs.map(\n            (tu) => tu[\"totalAccs\"],\n          )}\n          entities={topUserAccs.map((tu) =>\n            scrambleNames ? scramble(tu.id) : tu.id,\n          )}\n        />\n      </div>\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">User</th>\n          <th>GPUs</th>\n        </tr>\n        {#each topUserAccs as tu, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td id=\"{canvasPrefix}-topName-accs-{tu.id}\">\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/user/{tu.id}?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running\"\n                >{scrambleNames ? scramble(tu.id) : tu.id}\n              </a>\n            </td>\n            {#if tu?.name}\n              <Tooltip\n                target={`${canvasPrefix}-topName-accs-${tu.id}`}\n                placement=\"left\"\n                >{scrambleNames ? scramble(tu.name) : tu.name}</Tooltip\n              >\n            {/if}\n            <td>{tu[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <h4 class=\"text-center\">Top Projects: GPUs</h4>\n      <Pie\n        {useAltColors}\n        canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"\n        size={colWidthAccs * 0.75}\n        sliceLabel={\"GPUs\"}\n        quantities={$topStatsQuery.data.topProjectAccs.map(\n          (tp) => tp[\"totalAccs\"],\n        )}\n        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>\n          scrambleNames ? scramble(tp.id) : tp.id,\n        )}\n      />\n    </Col>\n    <Col xs=\"6\" md=\"3\" lg=\"2\" class=\"p-2\">\n      <Table>\n        <tr class=\"mb-2\">\n          <th></th>\n          <th style=\"padding-left: 0.5rem;\">Project</th>\n          <th>GPUs</th>\n        </tr>\n        {#each $topStatsQuery.data.topProjectAccs as tp, i}\n          <tr>\n            <td\n              ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td\n            >\n            <td>\n              <a\n                target=\"_blank\"\n                href=\"/monitoring/jobs/?cluster={presetCluster}{presetSubCluster\n                  ? '&partition=' + presetSubCluster\n                  : ''}&state=running&project={tp.id}&projectMatch=eq\"\n                >{scrambleNames ? scramble(tp.id) : tp.id}\n              </a>\n            </td>\n            <td>{tp[\"totalAccs\"]}</td>\n          </tr>\n        {/each}\n      </Table>\n    </Col>\n  </Row>\n{:else}\n  <Card class=\"mx-4\" body color=\"warning\"\n    >Cannot render accelerator status charts: No data!</Card\n  >\n{/if}\n","structuredPatch":[{"oldStart":538,"oldLines":10,"newStart":538,"newLines":10,"lines":["         canvasId=\"{canvasPrefix}-hpcpie-accs-projects\"","         size={colWidthAccs * 0.75}","         sliceLabel={\"GPUs\"}","-        quantities={$topStatsQuery.data.topProjectAccs.map(","+        quantities={topProjectAccs.map(","           (tp) => tp[\"totalAccs\"],","         )}","-        entities={$topStatsQuery.data.topProjectAccs.map((tp) =>","+        entities={topProjectAccs.map((tp) =>","           scrambleNames ? scramble(tp.id) : tp.id,","         )}","       />"]},{"oldStart":553,"oldLines":7,"newStart":553,"newLines":7,"lines":["           <th style=\"padding-left: 0.5rem;\">Project</th>","           <th>GPUs</th>","         </tr>","-        {#each $topStatsQuery.data.topProjectAccs as tp, i}","+        {#each topProjectAccs as tp, i}","           <tr>","             <td","               ><Icon name=\"circle-fill\" style=\"color: {legendColors(i)};\" /></td"]}],"userModified":false,"replaceAll":true},"sourceToolAssistantUUID":"cf59e344-e721-4ecc-ac03-a852830ec917","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":"402e08ae-c29a-470b-991e-6c8e806e2e5b","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_016tRASuTsUjzf41JwZ7ZU75","type":"message","role":"assistant","content":[{"type":"text","text":"Now let's run the verification steps — frontend build and backend build + tests in parallel:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1590,"cache_read_input_tokens":89176,"cache_creation":{"ephemeral_5m_input_tokens":1590,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1A2nfzZXwN8j6cgTWfZ","type":"assistant","uuid":"ceb10195-a576-4621-a736-4dfa0b0ff3e9","timestamp":"2026-03-13T13:27:08.858Z","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":"2e9f7512-1ee1-4623-9d3d-3edb8c5b4664","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019CMwMFkFANRe6LS8PuDuwh","type":"tool_result","content":"node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 37 more\n\u001b[32mcreated \u001b[1mpublic/build/dashpublic.js\u001b[22m in \u001b[1m3.6s\u001b[22m\u001b[39m\n\u001b[36m\n\u001b[1msrc/config.entrypoint.js\u001b[22m → \u001b[1mpublic/build/config.js\u001b[22m...\u001b[39m\n\u001b[1m\u001b[33m(!) Circular dependencies\u001b[39m\u001b[22m\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/runtime.js\nnode_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 37 more\n\u001b[32mcreated \u001b[1mpublic/build/config.js\u001b[22m in \u001b[1m2.7s\u001b[22m\u001b[39m\n\u001b[36m\n\u001b[1msrc/logs.entrypoint.js\u001b[22m → \u001b[1mpublic/build/logs.js\u001b[22m...\u001b[39m\n\u001b[1m\u001b[33m(!) Circular dependencies\u001b[39m\u001b[22m\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/runtime.js\nnode_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 35 more\n\u001b[32mcreated \u001b[1mpublic/build/logs.js\u001b[22m in \u001b[1m1.3s\u001b[22m\u001b[39m","is_error":false}]},"uuid":"430c55e4-d75b-4170-bc4c-d0396d5d5be2","timestamp":"2026-03-13T13:27:57.725Z","toolUseResult":{"stdout":"node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 37 more\n\u001b[32mcreated \u001b[1mpublic/build/dashpublic.js\u001b[22m in \u001b[1m3.6s\u001b[22m\u001b[39m\n\u001b[36m\n\u001b[1msrc/config.entrypoint.js\u001b[22m → \u001b[1mpublic/build/config.js\u001b[22m...\u001b[39m\n\u001b[1m\u001b[33m(!) Circular dependencies\u001b[39m\u001b[22m\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/runtime.js\nnode_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 37 more\n\u001b[32mcreated \u001b[1mpublic/build/config.js\u001b[22m in \u001b[1m2.7s\u001b[22m\u001b[39m\n\u001b[36m\n\u001b[1msrc/logs.entrypoint.js\u001b[22m → \u001b[1mpublic/build/logs.js\u001b[22m...\u001b[39m\n\u001b[1m\u001b[33m(!) Circular dependencies\u001b[39m\u001b[22m\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/runtime.js\nnode_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dom/hydration.js -> node_modules/svelte/src/internal/client/dom/operations.js\nnode_modules/svelte/src/internal/client/runtime.js -> node_modules/svelte/src/internal/client/reactivity/effects.js -> node_modules/svelte/src/internal/client/dom/operations.js -> node_modules/svelte/src/internal/client/dev/equality.js -> node_modules/svelte/src/internal/client/proxy.js -> node_modules/svelte/src/internal/client/runtime.js\n...and 35 more\n\u001b[32mcreated \u001b[1mpublic/build/logs.js\u001b[22m in \u001b[1m1.3s\u001b[22m\u001b[39m","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"2e9f7512-1ee1-4623-9d3d-3edb8c5b4664","userType":"external","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend/web/frontend","sessionId":"889ef150-c6ca-4f35-81e5-c19dc95fe399","version":"2.1.74","gitBranch":"hotfix","slug":"recursive-giggling-volcano"}
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{"parentUuid":"440845ee-072c-4baf-92cd-e27d982cdbb6","isSidechain":false,"promptId":"233387dd-7682-406a-99fd-8b8064a24928","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011qppwyVGH2UgP9PPjGGTeF","type":"tool_result","content":"ok  \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.978s","is_error":false}]},"uuid":"251f9d48-df0b-4066-9ae4-5e662cb6226e","timestamp":"2026-03-13T13:28:13.637Z","toolUseResult":{"stdout":"ok  \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.978s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"440845ee-072c-4baf-92cd-e27d982cdbb6","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":"251f9d48-df0b-4066-9ae4-5e662cb6226e","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_017F2NUYD38dU98Lb1LWMQUo","type":"message","role":"assistant","content":[{"type":"text","text":"All 4 changes are implemented and verified:\n\n1. **Partial indexes** — Migration 14 creates partial covering indexes `WHERE job_state = 'running'` for user/project/subcluster groupings. Version bumped to 14. The `BuildWhereClause` now inlines the literal state value (`job.job_state = 'running'`) so SQLite matches the partial index instead of using a parameterized placeholder.\n\n2. **Request-scoped cache** — `stats_cache.go` provides a `statsGroupCache` injected per GraphQL operation via `AroundOperations` middleware. When the same `(filter, groupBy)` pair is requested multiple times (e.g. topUserJobs, topUserNodes, topUserAccs), the DB query runs only once; sort+page is done in Go.\n\n3. **Parallel histograms** — `AddHistograms` now runs all 4 histogram queries concurrently using `errgroup.WithContext`.\n\n4. **Frontend consolidation** — `UsageDash.svelte` sends 2 GraphQL aliases (allUsers, allProjects) requesting all fields, then derives 6 sorted+sliced top-10 lists client-side via `$derived`."}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":137,"cache_read_input_tokens":92043,"output_tokens":287,"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":137},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1A7qkB8HuoEk6fsa4Xi","type":"assistant","uuid":"099804b7-9b06-4a50-a6cc-6cfaba7c63c2","timestamp":"2026-03-13T13:28:24.534Z","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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{"type":"file-history-snapshot","messageId":"273f8772-393e-43f9-9e8d-009782208e4d","snapshot":{"messageId":"273f8772-393e-43f9-9e8d-009782208e4d","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@v2","version":2,"backupTime":"2026-03-13T13:31:20.070Z"}},"timestamp":"2026-03-13T13:31:20.069Z"},"isSnapshotUpdate":false}
{"parentUuid":"8caed7b7-883b-4636-9159-19905f3f08b6","isSidechain":false,"promptId":"1531f999-3e8d-4bf7-bb85-4592b0d6791f","type":"user","message":{"role":"user","content":"commit it"},"uuid":"273f8772-393e-43f9-9e8d-009782208e4d","timestamp":"2026-03-13T13:31:19.482Z","permissionMode":"acceptEdits","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":"273f8772-393e-43f9-9e8d-009782208e4d","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EqVHditZ6T22Ah73pJhw7f","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nLet me gather the commit info."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":360,"cache_read_input_tokens":92180,"cache_creation":{"ephemeral_5m_input_tokens":360,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1AMao9ZqiKbKsrsxrYX","type":"assistant","uuid":"d96818eb-7d36-45b2-af89-5d7ce16b776f","timestamp":"2026-03-13T13:31:24.639Z","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":"d96818eb-7d36-45b2-af89-5d7ce16b776f","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EqVHditZ6T22Ah73pJhw7f","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_011gfkYhmaQcA57wcC8c81oY","name":"Bash","input":{"command":"git status","description":"Show working tree status"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":360,"cache_read_input_tokens":92180,"cache_creation":{"ephemeral_5m_input_tokens":360,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1AMao9ZqiKbKsrsxrYX","type":"assistant","uuid":"d9a9e730-dc4c-4f7a-bb76-ac63523c7115","timestamp":"2026-03-13T13:31:25.129Z","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":"d9a9e730-dc4c-4f7a-bb76-ac63523c7115","isSidechain":false,"promptId":"1531f999-3e8d-4bf7-bb85-4592b0d6791f","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011gfkYhmaQcA57wcC8c81oY","type":"tool_result","content":"On branch hotfix\nYour branch is behind 'origin/hotfix' by 1 commit, and can be fast-forwarded.\n  (use \"git pull\" to update your local branch)\n\nChanges not staged for commit:\n  (use \"git add <file>...\" to update what will be committed)\n  (use \"git restore <file>...\" 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 <file>...\" 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 -a\")","is_error":false}]},"uuid":"8c38acf0-5730-406e-9bcb-4569e2cc147c","timestamp":"2026-03-13T13:31:25.191Z","toolUseResult":{"stdout":"On branch hotfix\nYour branch is behind 'origin/hotfix' by 1 commit, and can be fast-forwarded.\n  (use \"git pull\" to update your local branch)\n\nChanges not staged for commit:\n  (use \"git add <file>...\" to update what will be committed)\n  (use \"git restore <file>...\" 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 <file>...\" 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 -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 summary"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":360,"cache_read_input_tokens":92180,"cache_creation":{"ephemeral_5m_input_tokens":360,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ1AMao9ZqiKbKsrsxrYX","type":"assistant","uuid":"a14db320-857f-4476-8be0-3429a2a2939f","timestamp":"2026-03-13T13:31:25.639Z","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":"a14db320-857f-4476-8be0-3429a2a2939f","isSidechain":false,"promptId":"1531f999-3e8d-4bf7-bb85-4592b0d6791f","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018XEdEYxNKn8aaiKuPimai3","type":"tool_result","content":" 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 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 deletions(-)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"a14db320-857f-4476-8be0-3429a2a2939f","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":"34def0fd-3190-440e-8478-b886c3b8ff2a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EqVHditZ6T22Ah73pJhw7f","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SgzwLdEGwQgUQYdgE1ro8Y","name":"Bash","input":{"command":"git log --oneline -5","description":"Show recent commits"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":360,"cache_read_input_tokens":92180,"output_tokens":256,"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":360},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ1AMao9ZqiKbKsrsxrYX","type":"assistant","uuid":"c7fff25a-0837-4973-a168-2375bff9a0f5","timestamp":"2026-03-13T13:31:26.169Z","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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