diff --git a/.entire/logs/entire.log b/.entire/logs/entire.log
index 4c5a9fb6..fe99ba74 100644
--- a/.entire/logs/entire.log
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@@ -22,3 +22,26 @@
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diff --git a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/full.jsonl b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/full.jsonl
index de8ba740..fad8cdf2 100644
--- a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/full.jsonl
+++ b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/full.jsonl
@@ -273,3 +273,140 @@
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{"parentUuid":"8d9b5a96-061e-41d1-875d-ece946bde5ba","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"hotfix","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01DbpCZXtRAf9H7QrxWqZ5gE","type":"message","role":"assistant","content":[{"type":"text","text":"All passes. Here's a summary of findings and fixes:\n\n---\n\n## Findings\n\n### Bug 1: Missing `defer rows.Close()` in `user.go:GetLdapUsernames()` (line 100)\n**Fixed.** Every call leaked a database connection and its buffers.\n\n### Bug 2: SQLite never runs `ANALYZE` — wrong index selection\n**Fixed.** Added `ANALYZE` to `setupSqlite()` in `dbConnection.go`.\n\nWithout statistics in `sqlite_stat1`, SQLite's query planner **guessed** and chose `jobs_jobstate_energy` (a terrible index for this query) instead of scanning `jobs_starttime` in reverse. The result:\n\n| | Before ANALYZE | After ANALYZE |\n|---|---|---|\n| Index used | `jobs_jobstate_energy` | `jobs_starttime` |\n| Sort | **TEMP B-TREE** (materializes ALL rows) | None (index order) |\n| Memory | Proportional to total matching rows | Constant |\n| I/O | Full scan of all matching rows | Stops at OFFSET+LIMIT |\n\n### Bug 3: `IN` clause + `ORDER BY` is fundamentally incompatible with composite indexes\n\nEven with the \"correct\" index `(job_state, start_time)`, SQLite **cannot** merge-sort across 3 separate index range scans for `IN ('completed','running','failed')`. It always falls back to a temp B-tree sort. The only efficient plan is to use the standalone `jobs_starttime` index — which SQLite does automatically **after ANALYZE** because it realizes the 3 states cover virtually all rows, making the WHERE clause nearly a no-op.\n\n### Observation: 79 indexes on the `job` table\nThis is excessive and actively harmful — it confuses the query planner (especially without ANALYZE) and slows writes. The `jobs_jobstate_starttime` index from migration 08 is also missing from the actual DB (only the 3-column `jobs_jobstate_starttime_duration` exists). This is worth investigating separately but is a schema/migration concern, not a code bug."}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":153,"cache_read_input_tokens":120540,"output_tokens":500,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":153,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYveq9QSvRtPQukPDHvUy","type":"assistant","uuid":"09019982-a241-40fa-b6cb-6b8920303b5c","timestamp":"2026-03-11T04:22:02.158Z"}
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+{"parentUuid":"6735f33e-7963-4666-9db2-5a3d57535c54","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":"What optimal index selection do you suggest? The job table contains almost 20 million jobs in production causing timouts on any filter query that does not use and index."},"uuid":"8b150e09-f7cd-42c9-8c52-ac10bb0e4955","timestamp":"2026-03-11T04:31:33.107Z","permissionMode":"plan"}
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+{"parentUuid":"cc849b03-4ad6-4cd1-9f8c-a165de6eeead","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016pyzp8PNn1akjaTANZvC96","type":"tool_result","content":" 1→# Fix Missing `rows.Close()` Memory Leaks in SQLite3 Queries\n 2→\n 3→## Context\n 4→\n 5→Production memory leaks traced to queries that do full table scans (e.g., job state list sorted by `start_time` on all jobs). The root cause is `sql.Rows` objects not being closed after query execution. In Go's `database/sql`, every `rows` returned by `.Query()` holds a database connection and associated buffers until `rows.Close()` is called. Without `defer rows.Close()`, these leak on every code path (both success and error returns).\n 6→\n 7→## Part 1: Missing `defer rows.Close()` (16 locations)\n 8→\n 9→**22 total `.Query()` calls** across the repository layer. **15 have `defer rows.Close()`**. **7 do not** (plus additional in tags/node). Additionally, 1 `Queryx` call in `tags.go` is also missing close.\n 10→\n 11→### 1a. `internal/repository/stats.go` — 7 functions\n 12→\n 13→Add `defer rows.Close()` immediately after the `if err != nil` check for each:\n 14→\n 15→| Line | Function |\n 16→|------|----------|\n 17→| 237 | `JobsStatsGrouped` |\n 18→| 442 | `JobCountGrouped` |\n 19→| 498 | `AddJobCountGrouped` |\n 20→| 557 | `AddJobCount` |\n 21→| 757 | `jobsStatisticsHistogram` |\n 22→| 825 | `jobsDurationStatisticsHistogram` |\n 23→| 950 | `jobsMetricStatisticsHistogram` |\n 24→\n 25→### 1b. `internal/repository/tags.go` — 5 locations\n 26→\n 27→| Line | Function | Detail |\n 28→|------|----------|--------|\n 29→| 284 | `CountTags` | Add `defer xrows.Close()` after Queryx error check |\n 30→| 336 | `CountTags` | Add `defer rows.Close()` after Query error check |\n 31→| 513 | `GetTags` | Add `defer rows.Close()` |\n 32→| 546 | `GetTagsDirect` | Add `defer rows.Close()` |\n 33→| 584 | `getArchiveTags` | Add `defer rows.Close()` |\n 34→\n 35→### 1c. `internal/repository/node.go` — 4 functions\n 36→\n 37→Replace manual `rows.Close()` in error-only paths with `defer rows.Close()`:\n 38→\n 39→| Line | Function | Also remove manual close at |\n 40→|------|----------|----|\n 41→| 368 | `QueryNodes` | L375 |\n 42→| 417 | `QueryNodesWithMeta` | L427 |\n 43→| 563 | `CountStates` | L569 |\n 44→| 625 | `CountStatesTimed` | L633 |\n 45→\n 46→## Part 2: Missing `rows.Err()` Checks\n 47→\n 48→After a `rows.Next()` loop, `rows.Err()` should be checked to detect iteration errors (e.g., connection lost mid-scan). Currently only 3 of ~22 query sites check it.\n 49→\n 50→Add `rows.Err()` check after the scan loop in every function touched by Part 1. Pattern:\n 51→\n 52→```go\n 53→for rows.Next() {\n 54→ // ... scan ...\n 55→}\n 56→if err := rows.Err(); err != nil {\n 57→ return nil, err\n 58→}\n 59→```\n 60→\n 61→Functions needing this (same 16 locations as Part 1 — all functions listed above).\n 62→\n 63→## Part 3: Unbounded Query Optimization\n 64→\n 65→### 3a. `CountStates` in `node.go:546` — counting in Go instead of SQL\n 66→\n 67→Currently fetches every individual row (`SELECT column FROM node ...`) and counts in Go with a map. Should use SQL aggregation instead:\n 68→\n 69→```go\n 70→// BEFORE: fetches N rows, counts in Go\n 71→sq.Select(column).From(\"node\")...\n 72→\n 73→// AFTER: let SQL do the counting\n 74→sq.Select(column, \"COUNT(*) as count\").From(\"node\")...GroupBy(column)\n 75→```\n 76→\n 77→This changes the scan from `rows.Scan(&state)` to `rows.Scan(&state, &count)` and eliminates the Go-side counting loop. Reduces rows transferred from N (number of nodes) to ~5 (number of distinct states).\n 78→\n 79→### 3b. `AddJobCount` in `stats.go:541` — uses `.Query()` instead of `.QueryRow()`\n 80→\n 81→`AddJobCount` builds a count query without GROUP BY (returns a single row) but uses `.Query()` + loop instead of `.QueryRow()`. Should be simplified to `QueryRow().Scan()` like `JobsStats` does. This eliminates the rows object entirely.\n 82→\n 83→## Summary of All Edits\n 84→\n 85→| File | Function | Actions |\n 86→|------|----------|---------|\n 87→| `stats.go` | `JobsStatsGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n 88→| `stats.go` | `JobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n 89→| `stats.go` | `AddJobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n 90→| `stats.go` | `AddJobCount` | Rewrite to use `QueryRow` instead of `Query` |\n 91→| `stats.go` | `jobsStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n 92→| `stats.go` | `jobsDurationStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n 93→| `stats.go` | `jobsMetricStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n 94→| `tags.go` | `CountTags` (xrows) | + `defer xrows.Close()`, + `xrows.Err()` after loop |\n 95→| `tags.go` | `CountTags` (rows) | + `defer rows.Close()` (already has `rows.Err()`) |\n 96→| `tags.go` | `GetTags` | + `defer rows.Close()`, + `rows.Err()` |\n 97→| `tags.go` | `GetTagsDirect` | + `defer rows.Close()`, + `rows.Err()` |\n 98→| `tags.go` | `getArchiveTags` | + `defer rows.Close()`, + `rows.Err()` |\n 99→| `node.go` | `QueryNodes` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n 100→| `node.go` | `QueryNodesWithMeta` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n 101→| `node.go` | `CountStates` | Rewrite to use SQL `COUNT(*)...GROUP BY`, + `defer rows.Close()`, remove manual close |\n 102→| `node.go` | `CountStatesTimed` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n 103→\n 104→## Verification\n 105→\n 106→1. `go build ./...` — ensure it compiles\n 107→2. `go test ./internal/repository/...` — run repository tests\n 108→3. `go vet ./internal/repository/...` — static analysis\n 109→"}]},"uuid":"d5ebf711-1743-47e7-819f-a97d6b07ae3c","timestamp":"2026-03-11T04:31:37.789Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/.claude/plans/refactored-wishing-journal.md","content":"# Fix Missing `rows.Close()` Memory Leaks in SQLite3 Queries\n\n## Context\n\nProduction memory leaks traced to queries that do full table scans (e.g., job state list sorted by `start_time` on all jobs). The root cause is `sql.Rows` objects not being closed after query execution. In Go's `database/sql`, every `rows` returned by `.Query()` holds a database connection and associated buffers until `rows.Close()` is called. Without `defer rows.Close()`, these leak on every code path (both success and error returns).\n\n## Part 1: Missing `defer rows.Close()` (16 locations)\n\n**22 total `.Query()` calls** across the repository layer. **15 have `defer rows.Close()`**. **7 do not** (plus additional in tags/node). Additionally, 1 `Queryx` call in `tags.go` is also missing close.\n\n### 1a. `internal/repository/stats.go` — 7 functions\n\nAdd `defer rows.Close()` immediately after the `if err != nil` check for each:\n\n| Line | Function |\n|------|----------|\n| 237 | `JobsStatsGrouped` |\n| 442 | `JobCountGrouped` |\n| 498 | `AddJobCountGrouped` |\n| 557 | `AddJobCount` |\n| 757 | `jobsStatisticsHistogram` |\n| 825 | `jobsDurationStatisticsHistogram` |\n| 950 | `jobsMetricStatisticsHistogram` |\n\n### 1b. `internal/repository/tags.go` — 5 locations\n\n| Line | Function | Detail |\n|------|----------|--------|\n| 284 | `CountTags` | Add `defer xrows.Close()` after Queryx error check |\n| 336 | `CountTags` | Add `defer rows.Close()` after Query error check |\n| 513 | `GetTags` | Add `defer rows.Close()` |\n| 546 | `GetTagsDirect` | Add `defer rows.Close()` |\n| 584 | `getArchiveTags` | Add `defer rows.Close()` |\n\n### 1c. `internal/repository/node.go` — 4 functions\n\nReplace manual `rows.Close()` in error-only paths with `defer rows.Close()`:\n\n| Line | Function | Also remove manual close at |\n|------|----------|----|\n| 368 | `QueryNodes` | L375 |\n| 417 | `QueryNodesWithMeta` | L427 |\n| 563 | `CountStates` | L569 |\n| 625 | `CountStatesTimed` | L633 |\n\n## Part 2: Missing `rows.Err()` Checks\n\nAfter a `rows.Next()` loop, `rows.Err()` should be checked to detect iteration errors (e.g., connection lost mid-scan). Currently only 3 of ~22 query sites check it.\n\nAdd `rows.Err()` check after the scan loop in every function touched by Part 1. Pattern:\n\n```go\nfor rows.Next() {\n // ... scan ...\n}\nif err := rows.Err(); err != nil {\n return nil, err\n}\n```\n\nFunctions needing this (same 16 locations as Part 1 — all functions listed above).\n\n## Part 3: Unbounded Query Optimization\n\n### 3a. `CountStates` in `node.go:546` — counting in Go instead of SQL\n\nCurrently fetches every individual row (`SELECT column FROM node ...`) and counts in Go with a map. Should use SQL aggregation instead:\n\n```go\n// BEFORE: fetches N rows, counts in Go\nsq.Select(column).From(\"node\")...\n\n// AFTER: let SQL do the counting\nsq.Select(column, \"COUNT(*) as count\").From(\"node\")...GroupBy(column)\n```\n\nThis changes the scan from `rows.Scan(&state)` to `rows.Scan(&state, &count)` and eliminates the Go-side counting loop. Reduces rows transferred from N (number of nodes) to ~5 (number of distinct states).\n\n### 3b. `AddJobCount` in `stats.go:541` — uses `.Query()` instead of `.QueryRow()`\n\n`AddJobCount` builds a count query without GROUP BY (returns a single row) but uses `.Query()` + loop instead of `.QueryRow()`. Should be simplified to `QueryRow().Scan()` like `JobsStats` does. This eliminates the rows object entirely.\n\n## Summary of All Edits\n\n| File | Function | Actions |\n|------|----------|---------|\n| `stats.go` | `JobsStatsGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `JobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `AddJobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `AddJobCount` | Rewrite to use `QueryRow` instead of `Query` |\n| `stats.go` | `jobsStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `jobsDurationStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `jobsMetricStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `CountTags` (xrows) | + `defer xrows.Close()`, + `xrows.Err()` after loop |\n| `tags.go` | `CountTags` (rows) | + `defer rows.Close()` (already has `rows.Err()`) |\n| `tags.go` | `GetTags` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `GetTagsDirect` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `getArchiveTags` | + `defer rows.Close()`, + `rows.Err()` |\n| `node.go` | `QueryNodes` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n| `node.go` | `QueryNodesWithMeta` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n| `node.go` | `CountStates` | Rewrite to use SQL `COUNT(*)...GROUP BY`, + `defer rows.Close()`, remove manual close |\n| `node.go` | `CountStatesTimed` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n\n## Verification\n\n1. `go build ./...` — ensure it compiles\n2. `go test ./internal/repository/...` — run repository tests\n3. `go vet ./internal/repository/...` — static analysis\n","numLines":109,"startLine":1,"totalLines":109}},"sourceToolAssistantUUID":"cc849b03-4ad6-4cd1-9f8c-a165de6eeead"}
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+{"parentUuid":"690b6940-e879-4e12-b927-17bd3339299c","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-11T04:31:52.401Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01R3QkDQBAVB6DF6PkpxSuc2","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018QkQ8ennWzkgVLFjVHpDPq","name":"Grep","input":{"pattern":"\\.From\\(\"job\"\\)|FROM\\s+job|from\\(\"job\"\\)","path":"/Users/jan/prg/CC/cc-backend/internal/repository","type":"go","output_mode":"files_with_matches"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":16728,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":16728,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CYvfbdLwQ4Y4qBfiScNHG","uuid":"6c070919-56c3-45d4-8fb3-848cc5752c64"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"b10358fa-fada-41b4-bb17-e5cede031538","timestamp":"2026-03-11T04:31:52.402Z"}
+{"parentUuid":"b10358fa-fada-41b4-bb17-e5cede031538","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018QkQ8ennWzkgVLFjVHpDPq","type":"tool_result","content":"Found 9 files\ninternal/repository/stats.go\ninternal/repository/tags.go\ninternal/repository/jobQuery.go\ninternal/repository/stats_test.go\ninternal/repository/jobCreate_test.go\ninternal/repository/jobCreate.go\ninternal/repository/jobFind.go\ninternal/repository/hooks_test.go\ninternal/repository/job.go"}]},"uuid":"60162acb-8de9-4717-8c03-0aa8b2bd5433","timestamp":"2026-03-11T04:31:52.423Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"e22cac72-2982-4744-883c-bc3c57d12e3e","timestamp":"2026-03-11T04:31:52.521Z"}
+{"parentUuid":"e22cac72-2982-4744-883c-bc3c57d12e3e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-11T04:31:52.546Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01R3QkDQBAVB6DF6PkpxSuc2","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013PworAAF6cehN2ut9qEybB","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":16728,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":16728,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CYvfbdLwQ4Y4qBfiScNHG","uuid":"f4f8ab67-21d8-486a-b8fd-c94cc2c11274"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"61305c81-2055-4699-ab1c-4ac0d7ec6179","timestamp":"2026-03-11T04:31:52.547Z"}
+{"parentUuid":"61305c81-2055-4699-ab1c-4ac0d7ec6179","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013PworAAF6cehN2ut9qEybB","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).Query()\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).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\tstates := make([]string, len(filter.State))\n 201→\t\tfor i, val := range filter.State {\n 202→\t\t\tstates[i] = string(val)\n 203→\t\t}\n 204→\t\tquery = query.Where(sq.Eq{\"job.job_state\": states})\n 205→\t}\n 206→\tif filter.Shared != nil {\n 207→\t\tquery = query.Where(\"job.shared = ?\", *filter.Shared)\n 208→\t}\n 209→\tif filter.Project != nil {\n 210→\t\tquery = buildStringCondition(\"job.project\", filter.Project, query)\n 211→\t}\n 212→\tif filter.User != nil {\n 213→\t\tquery = buildStringCondition(\"job.hpc_user\", filter.User, query)\n 214→\t}\n 215→\tif filter.NumNodes != nil {\n 216→\t\tquery = buildIntCondition(\"job.num_nodes\", filter.NumNodes, query)\n 217→\t}\n 218→\tif filter.NumAccelerators != nil {\n 219→\t\tquery = buildIntCondition(\"job.num_acc\", filter.NumAccelerators, query)\n 220→\t}\n 221→\tif filter.NumHWThreads != nil {\n 222→\t\tquery = buildIntCondition(\"job.num_hwthreads\", filter.NumHWThreads, query)\n 223→\t}\n 224→\tif filter.ArrayJobID != nil {\n 225→\t\tquery = query.Where(\"job.array_job_id = ?\", *filter.ArrayJobID)\n 226→\t}\n 227→\tif filter.StartTime != nil {\n 228→\t\tquery = buildTimeCondition(\"job.start_time\", filter.StartTime, query)\n 229→\t}\n 230→\tif filter.Duration != nil {\n 231→\t\tquery = buildIntCondition(\"job.duration\", filter.Duration, query)\n 232→\t}\n 233→\tif filter.Energy != nil {\n 234→\t\tquery = buildFloatCondition(\"job.energy\", filter.Energy, query)\n 235→\t}\n 236→\t// Indices on Tag Table\n 237→\tif filter.Tags != nil {\n 238→\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 239→\t\tquery = query.Join(\"jobtag ON jobtag.job_id = job.id\").Where(sq.Eq{\"jobtag.tag_id\": filter.Tags}).Distinct()\n 240→\t}\n 241→\t// No explicit Indices\n 242→\tif filter.JobID != nil {\n 243→\t\tquery = buildStringCondition(\"job.job_id\", filter.JobID, query)\n 244→\t}\n 245→\t// Queries Within JSONs\n 246→\tif filter.MetricStats != nil {\n 247→\t\tfor _, ms := range filter.MetricStats {\n 248→\t\t\tquery = buildFloatJSONCondition(ms.MetricName, ms.Range, query)\n 249→\t\t}\n 250→\t}\n 251→\tif filter.Node != nil {\n 252→\t\tquery = buildResourceJSONCondition(\"hostname\", filter.Node, query)\n 253→\t}\n 254→\tif filter.JobName != nil {\n 255→\t\tquery = buildMetaJSONCondition(\"jobName\", filter.JobName, query)\n 256→\t}\n 257→\tif filter.Schedule != nil {\n 258→\t\tinteractiveJobname := \"interactive\"\n 259→\t\tswitch *filter.Schedule {\n 260→\t\tcase \"interactive\":\n 261→\t\t\tiFilter := model.StringInput{Eq: &interactiveJobname}\n 262→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &iFilter, query)\n 263→\t\tcase \"batch\":\n 264→\t\t\tsFilter := model.StringInput{Neq: &interactiveJobname}\n 265→\t\t\tquery = buildMetaJSONCondition(\"jobName\", &sFilter, query)\n 266→\t\t}\n 267→\t}\n 268→\n 269→\t// Configurable Filter to exclude recently started jobs, see config.go: ShortRunningJobsDuration\n 270→\tif filter.MinRunningFor != nil {\n 271→\t\tnow := time.Now().Unix()\n 272→\t\t// Only jobs whose start timestamp is more than MinRunningFor seconds in the past\n 273→\t\t// If a job completed within the configured timeframe, it will still show up after the start_time matches the condition!\n 274→\t\tquery = query.Where(sq.Lt{\"job.start_time\": (now - int64(*filter.MinRunningFor))})\n 275→\t}\n 276→\treturn query\n 277→}\n 278→\n 279→// buildIntCondition creates clauses for integer range filters, using BETWEEN only if required.\n 280→func buildIntCondition(field string, cond *config.IntRange, query sq.SelectBuilder) sq.SelectBuilder {\n 281→\tif cond.From != 1 && cond.To != 0 {\n 282→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 283→\t} else if cond.From != 1 && cond.To == 0 {\n 284→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 285→\t} else if cond.From == 1 && cond.To != 0 {\n 286→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 287→\t} else {\n 288→\t\treturn query\n 289→\t}\n 290→}\n 291→\n 292→// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\n 293→func buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 294→\tif cond.From != 1.0 && cond.To != 0.0 {\n 295→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 296→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 297→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 298→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 299→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 300→\t} else {\n 301→\t\treturn query\n 302→\t}\n 303→}\n 304→\n 305→// buildTimeCondition creates time range filters supporting absolute timestamps,\n 306→// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n 307→// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\n 308→func buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n 309→\tif cond.From != nil && cond.To != nil {\n 310→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n 311→\t} else if cond.From != nil {\n 312→\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n 313→\t} else if cond.To != nil {\n 314→\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n 315→\t} else if cond.Range != \"\" {\n 316→\t\tnow := time.Now().Unix()\n 317→\t\tvar then int64\n 318→\t\tswitch cond.Range {\n 319→\t\tcase \"last6h\":\n 320→\t\t\tthen = now - (60 * 60 * 6)\n 321→\t\tcase \"last24h\":\n 322→\t\t\tthen = now - (60 * 60 * 24)\n 323→\t\tcase \"last7d\":\n 324→\t\t\tthen = now - (60 * 60 * 24 * 7)\n 325→\t\tcase \"last30d\":\n 326→\t\t\tthen = now - (60 * 60 * 24 * 30)\n 327→\t\tdefault:\n 328→\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n 329→\t\t\treturn query\n 330→\t\t}\n 331→\t\treturn query.Where(field+\" >= ?\", then)\n 332→\t} else {\n 333→\t\treturn query\n 334→\t}\n 335→}\n 336→\n 337→// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\n 338→func buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 339→\tquery = query.Where(\"JSON_VALID(footprint)\")\n 340→\tif cond.From != 1.0 && cond.To != 0.0 {\n 341→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n 342→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 343→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n 344→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 345→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n 346→\t} else {\n 347→\t\treturn query\n 348→\t}\n 349→}\n 350→\n 351→// buildStringCondition creates filters for string fields supporting equality,\n 352→// inequality, prefix, suffix, substring, and IN list matching.\n 353→func buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 354→\tif cond.Eq != nil {\n 355→\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n 356→\t}\n 357→\tif cond.Neq != nil {\n 358→\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n 359→\t}\n 360→\tif cond.StartsWith != nil {\n 361→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 362→\t}\n 363→\tif cond.EndsWith != nil {\n 364→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 365→\t}\n 366→\tif cond.Contains != nil {\n 367→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 368→\t}\n 369→\tif cond.In != nil {\n 370→\t\tqueryElements := make([]string, len(cond.In))\n 371→\t\tcopy(queryElements, cond.In)\n 372→\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n 373→\t}\n 374→\treturn query\n 375→}\n 376→\n 377→// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\n 378→func buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 379→\tquery = query.Where(\"JSON_VALID(meta_data)\")\n 380→\tif cond.Eq != nil {\n 381→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n 382→\t}\n 383→\tif cond.Neq != nil {\n 384→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n 385→\t}\n 386→\tif cond.StartsWith != nil {\n 387→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 388→\t}\n 389→\tif cond.EndsWith != nil {\n 390→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 391→\t}\n 392→\tif cond.Contains != nil {\n 393→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 394→\t}\n 395→\treturn query\n 396→}\n 397→\n 398→// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n 399→// Uses json_each to search within array elements.\n 400→func buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 401→\tquery = query.Where(\"JSON_VALID(resources)\")\n 402→\tif cond.Eq != nil {\n 403→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n 404→\t}\n 405→\tif cond.Neq != nil { // Currently Unused\n 406→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n 407→\t}\n 408→\tif cond.StartsWith != nil { // Currently Unused\n 409→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 410→\t}\n 411→\tif cond.EndsWith != nil { // Currently Unused\n 412→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n 413→\t}\n 414→\tif cond.Contains != nil {\n 415→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 416→\t}\n 417→\treturn query\n 418→}\n 419→\n 420→var (\n 421→\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n 422→\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n 423→)\n 424→\n 425→// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n 426→// Includes security checks to prevent SQL injection attempts.\n 427→// Panics if potentially dangerous characters are detected.\n 428→func toSnakeCase(str string) string {\n 429→\tfor _, c := range str {\n 430→\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n 431→\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n 432→\t\t}\n 433→\t}\n 434→\n 435→\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n 436→\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n 437→\treturn strings.ToLower(snake)\n 438→}\n 439→"}]},"uuid":"d7d837fe-27e0-4163-aae9-7845794dc247","timestamp":"2026-03-11T04:31:52.551Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"f47aff90-2d35-4116-a9c5-72dd4887888f","timestamp":"2026-03-11T04:31:52.556Z"}
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+{"parentUuid":"04f095b0-19a0-4279-9146-1ecf70d9aa7a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-11T04:31:55.107Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01SM5yMbj5zg2mhprsomprZR","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BGMnaad1YCJeDuX64te1yt","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":8163,"cache_read_input_tokens":16728,"cache_creation":{"ephemeral_5m_input_tokens":8163,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CYvfbovBHHA4pTaAEN5fU","uuid":"ac03a5aa-2168-4289-ae97-2d24911046ef"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"bde56468-9c74-47ef-8418-642d7dd23373","timestamp":"2026-03-11T04:31:55.107Z"}
+{"parentUuid":"bde56468-9c74-47ef-8418-642d7dd23373","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BGMnaad1YCJeDuX64te1yt","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→package repository\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"database/sql\"\n 11→\t\"fmt\"\n 12→\t\"time\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 15→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 16→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 17→\tsq \"github.com/Masterminds/squirrel\"\n 18→)\n 19→\n 20→// Find executes a SQL query to find a specific batch job.\n 21→// The job is queried using the batch job id, the cluster name,\n 22→// and the start time of the job in UNIX epoch time seconds.\n 23→// It returns a pointer to a schema.Job data structure and an error variable.\n 24→// To check if no job was found test err == sql.ErrNoRows\n 25→func (r *JobRepository) Find(\n 26→\tjobID *int64,\n 27→\tcluster *string,\n 28→\tstartTime *int64,\n 29→) (*schema.Job, error) {\n 30→\tif jobID == nil {\n 31→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 32→\t}\n 33→\n 34→\tstart := time.Now()\n 35→\tq := sq.Select(jobColumns...).From(\"job\").\n 36→\t\tWhere(\"job.job_id = ?\", *jobID)\n 37→\n 38→\tif cluster != nil {\n 39→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 40→\t}\n 41→\tif startTime != nil {\n 42→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 43→\t}\n 44→\n 45→\tq = q.OrderBy(\"job.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 46→\n 47→\tcclog.Debugf(\"Timer Find %s\", time.Since(start))\n 48→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 49→}\n 50→\n 51→// FindCached executes a SQL query to find a specific batch job from the job_cache table.\n 52→// The job is queried using the batch job id, and optionally filtered by cluster name\n 53→// and start time (UNIX epoch time seconds). This method uses cached job data which\n 54→// may be stale but provides faster access than Find().\n 55→// It returns a pointer to a schema.Job data structure and an error variable.\n 56→// To check if no job was found test err == sql.ErrNoRows\n 57→func (r *JobRepository) FindCached(\n 58→\tjobID *int64,\n 59→\tcluster *string,\n 60→\tstartTime *int64,\n 61→) (*schema.Job, error) {\n 62→\tif jobID == nil {\n 63→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 64→\t}\n 65→\n 66→\tq := sq.Select(jobCacheColumns...).From(\"job_cache\").\n 67→\t\tWhere(\"job_cache.job_id = ?\", *jobID)\n 68→\n 69→\tif cluster != nil {\n 70→\t\tq = q.Where(\"job_cache.cluster = ?\", *cluster)\n 71→\t}\n 72→\tif startTime != nil {\n 73→\t\tq = q.Where(\"job_cache.start_time = ?\", *startTime)\n 74→\t}\n 75→\n 76→\tq = q.OrderBy(\"job_cache.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 77→\n 78→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 79→}\n 80→\n 81→// FindAll executes a SQL query to find all batch jobs matching the given criteria.\n 82→// Jobs are queried using the batch job id, and optionally filtered by cluster name\n 83→// and start time (UNIX epoch time seconds).\n 84→// It returns a slice of pointers to schema.Job data structures and an error variable.\n 85→// An empty slice is returned if no matching jobs are found.\n 86→func (r *JobRepository) FindAll(\n 87→\tjobID *int64,\n 88→\tcluster *string,\n 89→\tstartTime *int64,\n 90→) ([]*schema.Job, error) {\n 91→\tif jobID == nil {\n 92→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 93→\t}\n 94→\n 95→\tstart := time.Now()\n 96→\tq := sq.Select(jobColumns...).From(\"job\").\n 97→\t\tWhere(\"job.job_id = ?\", *jobID)\n 98→\n 99→\tif cluster != nil {\n 100→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 101→\t}\n 102→\tif startTime != nil {\n 103→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 104→\t}\n 105→\n 106→\trows, err := q.RunWith(r.stmtCache).Query()\n 107→\tif err != nil {\n 108→\t\tcclog.Errorf(\"Error while running FindAll query for jobID=%d: %v\", *jobID, err)\n 109→\t\treturn nil, fmt.Errorf(\"failed to execute FindAll query: %w\", err)\n 110→\t}\n 111→\tdefer rows.Close()\n 112→\n 113→\tjobs := make([]*schema.Job, 0, 10)\n 114→\tfor rows.Next() {\n 115→\t\tjob, err := scanJob(rows)\n 116→\t\tif err != nil {\n 117→\t\t\tcclog.Warnf(\"Error while scanning rows in FindAll: %v\", err)\n 118→\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n 119→\t\t}\n 120→\t\tjobs = append(jobs, job)\n 121→\t}\n 122→\tcclog.Debugf(\"Timer FindAll %s\", time.Since(start))\n 123→\treturn jobs, nil\n 124→}\n 125→\n 126→// GetJobList returns job IDs for non-running jobs.\n 127→// This is useful to process large job counts and intended to be used\n 128→// together with FindById to process jobs one by one.\n 129→// Use limit and offset for pagination. Use limit=0 to get all results (not recommended for large datasets).\n 130→func (r *JobRepository) GetJobList(limit int, offset int) ([]int64, error) {\n 131→\tquery := sq.Select(\"id\").From(\"job\").\n 132→\t\tWhere(\"job.job_state != 'running'\")\n 133→\n 134→\t// Add pagination if limit is specified\n 135→\tif limit > 0 {\n 136→\t\tquery = query.Limit(uint64(limit)).Offset(uint64(offset))\n 137→\t}\n 138→\n 139→\trows, err := query.RunWith(r.stmtCache).Query()\n 140→\tif err != nil {\n 141→\t\tcclog.Errorf(\"Error while running GetJobList query (limit=%d, offset=%d): %v\", limit, offset, err)\n 142→\t\treturn nil, fmt.Errorf(\"failed to execute GetJobList query: %w\", err)\n 143→\t}\n 144→\tdefer rows.Close()\n 145→\n 146→\tjl := make([]int64, 0, 1000)\n 147→\tfor rows.Next() {\n 148→\t\tvar id int64\n 149→\t\terr := rows.Scan(&id)\n 150→\t\tif err != nil {\n 151→\t\t\tcclog.Warnf(\"Error while scanning rows in GetJobList: %v\", err)\n 152→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID: %w\", err)\n 153→\t\t}\n 154→\t\tjl = append(jl, id)\n 155→\t}\n 156→\n 157→\tcclog.Debugf(\"JobRepository.GetJobList(): Return job count %d\", len(jl))\n 158→\treturn jl, nil\n 159→}\n 160→\n 161→// FindByID executes a SQL query to find a specific batch job.\n 162→// The job is queried using the database id.\n 163→// It returns a pointer to a schema.Job data structure and an error variable.\n 164→// To check if no job was found test err == sql.ErrNoRows\n 165→func (r *JobRepository) FindByID(ctx context.Context, jobID int64) (*schema.Job, error) {\n 166→\tq := sq.Select(jobColumns...).\n 167→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 168→\n 169→\tq, qerr := SecurityCheck(ctx, q)\n 170→\tif qerr != nil {\n 171→\t\treturn nil, qerr\n 172→\t}\n 173→\n 174→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 175→}\n 176→\n 177→// FindByIDWithUser executes a SQL query to find a specific batch job.\n 178→// The job is queried using the database id. The user is passed directly,\n 179→// instead as part of the context.\n 180→// It returns a pointer to a schema.Job data structure and an error variable.\n 181→// To check if no job was found test err == sql.ErrNoRows\n 182→func (r *JobRepository) FindByIDWithUser(user *schema.User, jobID int64) (*schema.Job, error) {\n 183→\tq := sq.Select(jobColumns...).\n 184→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 185→\n 186→\tq, qerr := SecurityCheckWithUser(user, q)\n 187→\tif qerr != nil {\n 188→\t\treturn nil, qerr\n 189→\t}\n 190→\n 191→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 192→}\n 193→\n 194→// FindByIDDirect executes a SQL query to find a specific batch job.\n 195→// The job is queried using the database id.\n 196→// It returns a pointer to a schema.Job data structure and an error variable.\n 197→// To check if no job was found test err == sql.ErrNoRows\n 198→func (r *JobRepository) FindByIDDirect(jobID int64) (*schema.Job, error) {\n 199→\tq := sq.Select(jobColumns...).\n 200→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 201→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 202→}\n 203→\n 204→// FindByJobID executes a SQL query to find a specific batch job.\n 205→// The job is queried using the slurm id and the clustername.\n 206→// It returns a pointer to a schema.Job data structure and an error variable.\n 207→// To check if no job was found test err == sql.ErrNoRows\n 208→func (r *JobRepository) FindByJobID(ctx context.Context, jobID int64, startTime int64, cluster string) (*schema.Job, error) {\n 209→\tq := sq.Select(jobColumns...).\n 210→\t\tFrom(\"job\").\n 211→\t\tWhere(\"job.job_id = ?\", jobID).\n 212→\t\tWhere(\"job.cluster = ?\", cluster).\n 213→\t\tWhere(\"job.start_time = ?\", startTime)\n 214→\n 215→\tq, qerr := SecurityCheck(ctx, q)\n 216→\tif qerr != nil {\n 217→\t\treturn nil, qerr\n 218→\t}\n 219→\n 220→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 221→}\n 222→\n 223→// IsJobOwner checks if the specified user owns the batch job identified by jobID,\n 224→// startTime, and cluster. Returns true if the user is the owner, false otherwise.\n 225→// This method does not return errors; it returns false for both non-existent jobs\n 226→// and jobs owned by other users.\n 227→func (r *JobRepository) IsJobOwner(jobID int64, startTime int64, user string, cluster string) bool {\n 228→\tq := sq.Select(\"id\").\n 229→\t\tFrom(\"job\").\n 230→\t\tWhere(\"job.job_id = ?\", jobID).\n 231→\t\tWhere(\"job.hpc_user = ?\", user).\n 232→\t\tWhere(\"job.cluster = ?\", cluster).\n 233→\t\tWhere(\"job.start_time = ?\", startTime)\n 234→\n 235→\t_, err := scanJob(q.RunWith(r.stmtCache).QueryRow())\n 236→\tif err != nil && err != sql.ErrNoRows {\n 237→\t\tcclog.Warnf(\"IsJobOwner: unexpected error for jobID=%d, user=%s, cluster=%s: %v\", jobID, user, cluster, err)\n 238→\t}\n 239→\treturn err != sql.ErrNoRows\n 240→}\n 241→\n 242→func (r *JobRepository) FindConcurrentJobs(\n 243→\tctx context.Context,\n 244→\tjob *schema.Job,\n 245→) (*model.JobLinkResultList, error) {\n 246→\tif job == nil {\n 247→\t\treturn nil, nil\n 248→\t}\n 249→\n 250→\tquery, qerr := SecurityCheck(ctx, sq.Select(\"job.id\", \"job.job_id\", \"job.start_time\").From(\"job\"))\n 251→\tif qerr != nil {\n 252→\t\treturn nil, qerr\n 253→\t}\n 254→\n 255→\tquery = query.Where(\"cluster = ?\", job.Cluster)\n 256→\n 257→\tif len(job.Resources) == 0 {\n 258→\t\treturn nil, fmt.Errorf(\"job has no resources defined\")\n 259→\t}\n 260→\n 261→\tvar startTime int64\n 262→\tvar stopTime int64\n 263→\n 264→\tstartTime = job.StartTime\n 265→\thostname := job.Resources[0].Hostname\n 266→\n 267→\tif job.State == schema.JobStateRunning {\n 268→\t\tstopTime = time.Now().Unix()\n 269→\t} else {\n 270→\t\tstopTime = startTime + int64(job.Duration)\n 271→\t}\n 272→\n 273→\t// Time buffer constant for finding overlapping jobs\n 274→\t// overlapBufferEnd: 200s buffer at job end to account for scheduling/cleanup overlap\n 275→\tconst overlapBufferEnd = 200\n 276→\n 277→\tstopTimeTail := stopTime - overlapBufferEnd\n 278→\tstartTimeFront := startTime + overlapBufferEnd\n 279→\n 280→\tqueryRunning := query.Where(\"job.job_state = ?\", \"running\").\n 281→\t\tWhere(\"job.start_time <= ?\", stopTimeTail)\n 282→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 283→\tqueryRunning = queryRunning.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 284→\n 285→\tquery = query.Where(\"job.job_state != ?\", \"running\").\n 286→\t\tWhere(\"job.start_time < ?\", stopTimeTail).\n 287→\t\tWhere(\"(job.start_time + job.duration) > ?\", startTimeFront)\n 288→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 289→\tquery = query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 290→\n 291→\trows, err := query.RunWith(r.stmtCache).Query()\n 292→\tif err != nil {\n 293→\t\tcclog.Errorf(\"Error while running concurrent jobs query: %v\", err)\n 294→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent jobs query: %w\", err)\n 295→\t}\n 296→\tdefer rows.Close()\n 297→\n 298→\titems := make([]*model.JobLink, 0, 10)\n 299→\tqueryString := fmt.Sprintf(\"cluster=%s\", job.Cluster)\n 300→\n 301→\tfor rows.Next() {\n 302→\t\tvar id, jobID, startTime sql.NullInt64\n 303→\n 304→\t\tif err = rows.Scan(&id, &jobID, &startTime); err != nil {\n 305→\t\t\tcclog.Warnf(\"Error while scanning concurrent job rows: %v\", err)\n 306→\t\t\treturn nil, fmt.Errorf(\"failed to scan concurrent job row: %w\", err)\n 307→\t\t}\n 308→\n 309→\t\tif id.Valid {\n 310→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 311→\t\t\titems = append(items,\n 312→\t\t\t\t&model.JobLink{\n 313→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 314→\t\t\t\t\tJobID: int(jobID.Int64),\n 315→\t\t\t\t})\n 316→\t\t}\n 317→\t}\n 318→\n 319→\trows, err = queryRunning.RunWith(r.stmtCache).Query()\n 320→\tif err != nil {\n 321→\t\tcclog.Errorf(\"Error while running concurrent running jobs query: %v\", err)\n 322→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent running jobs query: %w\", err)\n 323→\t}\n 324→\tdefer rows.Close()\n 325→\n 326→\tfor rows.Next() {\n 327→\t\tvar id, jobID, startTime sql.NullInt64\n 328→\n 329→\t\tif err := rows.Scan(&id, &jobID, &startTime); err != nil {\n 330→\t\t\tcclog.Warnf(\"Error while scanning running concurrent job rows: %v\", err)\n 331→\t\t\treturn nil, fmt.Errorf(\"failed to scan running concurrent job row: %w\", err)\n 332→\t\t}\n 333→\n 334→\t\tif id.Valid {\n 335→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 336→\t\t\titems = append(items,\n 337→\t\t\t\t&model.JobLink{\n 338→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 339→\t\t\t\t\tJobID: int(jobID.Int64),\n 340→\t\t\t\t})\n 341→\t\t}\n 342→\t}\n 343→\n 344→\tcnt := len(items)\n 345→\n 346→\treturn &model.JobLinkResultList{\n 347→\t\tListQuery: &queryString,\n 348→\t\tItems: items,\n 349→\t\tCount: &cnt,\n 350→\t}, nil\n 351→}\n 352→"}]},"uuid":"1a63293b-2c69-4230-aabf-08cdb1e5bc70","timestamp":"2026-03-11T04:31:55.110Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"d0a70111-b187-4fd3-92d1-e901671188d0","timestamp":"2026-03-11T04:31:55.314Z"}
+{"parentUuid":"d0a70111-b187-4fd3-92d1-e901671188d0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-11T04:31:55.329Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01SM5yMbj5zg2mhprsomprZR","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016Sivnnc2twDj56qixpV9JY","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/jobCreate.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":8163,"cache_read_input_tokens":16728,"cache_creation":{"ephemeral_5m_input_tokens":8163,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CYvfbovBHHA4pTaAEN5fU","uuid":"fcf3fed9-f6a2-44e2-9432-5bd7ccb3e492"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"8dae5846-09ea-4aee-89b5-7e5fa7204ad9","timestamp":"2026-03-11T04:31:55.329Z"}
+{"parentUuid":"8dae5846-09ea-4aee-89b5-7e5fa7204ad9","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016Sivnnc2twDj56qixpV9JY","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→package repository\n 7→\n 8→import (\n 9→\t\"encoding/json\"\n 10→\t\"fmt\"\n 11→\n 12→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 13→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 14→\tsq \"github.com/Masterminds/squirrel\"\n 15→)\n 16→\n 17→const NamedJobCacheInsert string = `INSERT INTO job_cache (\n 18→\tjob_id, hpc_user, project, cluster, subcluster, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc,\n 19→\tshared, monitoring_status, smt, job_state, start_time, duration, walltime, footprint, energy, energy_footprint, resources, meta_data\n 20→) VALUES (\n 21→\t:job_id, :hpc_user, :project, :cluster, :subcluster, :cluster_partition, :array_job_id, :num_nodes, :num_hwthreads, :num_acc,\n 22→ :shared, :monitoring_status, :smt, :job_state, :start_time, :duration, :walltime, :footprint, :energy, :energy_footprint, :resources, :meta_data\n 23→);`\n 24→\n 25→const NamedJobInsert string = `INSERT INTO job (\n 26→\tjob_id, hpc_user, project, cluster, subcluster, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc,\n 27→\tshared, monitoring_status, smt, job_state, start_time, duration, walltime, footprint, energy, energy_footprint, resources, meta_data\n 28→) VALUES (\n 29→\t:job_id, :hpc_user, :project, :cluster, :subcluster, :cluster_partition, :array_job_id, :num_nodes, :num_hwthreads, :num_acc,\n 30→ :shared, :monitoring_status, :smt, :job_state, :start_time, :duration, :walltime, :footprint, :energy, :energy_footprint, :resources, :meta_data\n 31→);`\n 32→\n 33→// InsertJobDirect inserts a job directly into the job table (not job_cache).\n 34→// Use this when the returned ID will be used for operations on the job table\n 35→// (e.g., adding tags), or for imported jobs that are already completed.\n 36→func (r *JobRepository) InsertJobDirect(job *schema.Job) (int64, error) {\n 37→\tr.Mutex.Lock()\n 38→\tdefer r.Mutex.Unlock()\n 39→\n 40→\tres, err := r.DB.NamedExec(NamedJobInsert, job)\n 41→\tif err != nil {\n 42→\t\tcclog.Warn(\"Error while NamedJobInsert (direct)\")\n 43→\t\treturn 0, err\n 44→\t}\n 45→\tid, err := res.LastInsertId()\n 46→\tif err != nil {\n 47→\t\tcclog.Warn(\"Error while getting last insert ID (direct)\")\n 48→\t\treturn 0, err\n 49→\t}\n 50→\n 51→\treturn id, nil\n 52→}\n 53→\n 54→func (r *JobRepository) InsertJob(job *schema.Job) (int64, error) {\n 55→\tr.Mutex.Lock()\n 56→\tdefer r.Mutex.Unlock()\n 57→\n 58→\tres, err := r.DB.NamedExec(NamedJobCacheInsert, job)\n 59→\tif err != nil {\n 60→\t\tcclog.Warn(\"Error while NamedJobInsert\")\n 61→\t\treturn 0, err\n 62→\t}\n 63→\tid, err := res.LastInsertId()\n 64→\tif err != nil {\n 65→\t\tcclog.Warn(\"Error while getting last insert ID\")\n 66→\t\treturn 0, err\n 67→\t}\n 68→\n 69→\treturn id, nil\n 70→}\n 71→\n 72→func (r *JobRepository) SyncJobs() ([]*schema.Job, error) {\n 73→\tr.Mutex.Lock()\n 74→\tdefer r.Mutex.Unlock()\n 75→\n 76→\tquery := sq.Select(jobCacheColumns...).From(\"job_cache\")\n 77→\n 78→\trows, err := query.RunWith(r.stmtCache).Query()\n 79→\tif err != nil {\n 80→\t\tcclog.Errorf(\"Error while running query %v\", err)\n 81→\t\treturn nil, err\n 82→\t}\n 83→\tdefer rows.Close()\n 84→\n 85→\tjobs := make([]*schema.Job, 0, 50)\n 86→\tfor rows.Next() {\n 87→\t\tjob, err := scanJob(rows)\n 88→\t\tif err != nil {\n 89→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 90→\t\t\treturn nil, err\n 91→\t\t}\n 92→\t\tjobs = append(jobs, job)\n 93→\t}\n 94→\n 95→\t// Use INSERT OR IGNORE to skip jobs already transferred by the stop path\n 96→\t_, err = r.DB.Exec(\n 97→\t\t\"INSERT OR IGNORE INTO job (job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data) SELECT job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data FROM job_cache\")\n 98→\tif err != nil {\n 99→\t\tcclog.Warnf(\"Error while Job sync: %v\", err)\n 100→\t\treturn nil, err\n 101→\t}\n 102→\n 103→\t_, err = r.DB.Exec(\"DELETE FROM job_cache\")\n 104→\tif err != nil {\n 105→\t\tcclog.Warnf(\"Error while Job cache clean: %v\", err)\n 106→\t\treturn nil, err\n 107→\t}\n 108→\n 109→\t// Resolve correct job.id from the job table. The IDs read from job_cache\n 110→\t// are from a different auto-increment sequence and must not be used to\n 111→\t// query the job table.\n 112→\tfor _, job := range jobs {\n 113→\t\tvar newID int64\n 114→\t\tif err := sq.Select(\"job.id\").From(\"job\").\n 115→\t\t\tWhere(\"job.job_id = ? AND job.cluster = ? AND job.start_time = ?\",\n 116→\t\t\t\tjob.JobID, job.Cluster, job.StartTime).\n 117→\t\t\tRunWith(r.stmtCache).QueryRow().Scan(&newID); err != nil {\n 118→\t\t\tcclog.Warnf(\"SyncJobs: could not resolve job table id for job %d on %s: %v\",\n 119→\t\t\t\tjob.JobID, job.Cluster, err)\n 120→\t\t\tcontinue\n 121→\t\t}\n 122→\t\tjob.ID = &newID\n 123→\t}\n 124→\n 125→\treturn jobs, nil\n 126→}\n 127→\n 128→// TransferCachedJobToMain moves a job from job_cache to the job table.\n 129→// Caller must hold r.Mutex. Returns the new job table ID.\n 130→func (r *JobRepository) TransferCachedJobToMain(cacheID int64) (int64, error) {\n 131→\tres, err := r.DB.Exec(\n 132→\t\t\"INSERT INTO job (job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data) SELECT job_id, cluster, subcluster, start_time, hpc_user, project, cluster_partition, array_job_id, num_nodes, num_hwthreads, num_acc, shared, monitoring_status, smt, job_state, duration, walltime, footprint, energy, energy_footprint, resources, meta_data FROM job_cache WHERE id = ?\",\n 133→\t\tcacheID)\n 134→\tif err != nil {\n 135→\t\treturn 0, fmt.Errorf(\"transferring cached job %d to main table failed: %w\", cacheID, err)\n 136→\t}\n 137→\n 138→\tnewID, err := res.LastInsertId()\n 139→\tif err != nil {\n 140→\t\treturn 0, fmt.Errorf(\"getting new job ID after transfer failed: %w\", err)\n 141→\t}\n 142→\n 143→\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", cacheID)\n 144→\tif err != nil {\n 145→\t\treturn 0, fmt.Errorf(\"deleting cached job %d after transfer failed: %w\", cacheID, err)\n 146→\t}\n 147→\n 148→\treturn newID, nil\n 149→}\n 150→\n 151→// Start inserts a new job in the table, returning the unique job ID.\n 152→// Statistics are not transfered!\n 153→func (r *JobRepository) Start(job *schema.Job) (id int64, err error) {\n 154→\tjob.RawFootprint, err = json.Marshal(job.Footprint)\n 155→\tif err != nil {\n 156→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding footprint field failed: %w\", err)\n 157→\t}\n 158→\n 159→\tjob.RawResources, err = json.Marshal(job.Resources)\n 160→\tif err != nil {\n 161→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding resources field failed: %w\", err)\n 162→\t}\n 163→\n 164→\tjob.RawMetaData, err = json.Marshal(job.MetaData)\n 165→\tif err != nil {\n 166→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding metaData field failed: %w\", err)\n 167→\t}\n 168→\n 169→\treturn r.InsertJob(job)\n 170→}\n 171→\n 172→// StartDirect inserts a new job directly into the job table (not job_cache).\n 173→// Use this when the returned ID will immediately be used for job table\n 174→// operations such as adding tags.\n 175→func (r *JobRepository) StartDirect(job *schema.Job) (id int64, err error) {\n 176→\tjob.RawFootprint, err = json.Marshal(job.Footprint)\n 177→\tif err != nil {\n 178→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding footprint field failed: %w\", err)\n 179→\t}\n 180→\n 181→\tjob.RawResources, err = json.Marshal(job.Resources)\n 182→\tif err != nil {\n 183→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding resources field failed: %w\", err)\n 184→\t}\n 185→\n 186→\tjob.RawMetaData, err = json.Marshal(job.MetaData)\n 187→\tif err != nil {\n 188→\t\treturn -1, fmt.Errorf(\"REPOSITORY/JOB > encoding metaData field failed: %w\", err)\n 189→\t}\n 190→\n 191→\treturn r.InsertJobDirect(job)\n 192→}\n 193→\n 194→// Stop updates the job with the database id jobId using the provided arguments.\n 195→func (r *JobRepository) Stop(\n 196→\tjobID int64,\n 197→\tduration int32,\n 198→\tstate schema.JobState,\n 199→\tmonitoringStatus int32,\n 200→) (err error) {\n 201→\t// Invalidate cache entries as job state is changing\n 202→\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", jobID))\n 203→\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", jobID))\n 204→\n 205→\tstmt := sq.Update(\"job\").\n 206→\t\tSet(\"job_state\", state).\n 207→\t\tSet(\"duration\", duration).\n 208→\t\tSet(\"monitoring_status\", monitoringStatus).\n 209→\t\tWhere(\"job.id = ?\", jobID)\n 210→\n 211→\t_, err = stmt.RunWith(r.stmtCache).Exec()\n 212→\treturn err\n 213→}\n 214→\n 215→"}]},"uuid":"e7442b1a-4877-4514-bc68-48696a754180","timestamp":"2026-03-11T04:31:55.334Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"52a1a8bb-8db6-46dd-a4e7-3f2975060417","timestamp":"2026-03-11T04:31:55.335Z"}
+{"parentUuid":"52a1a8bb-8db6-46dd-a4e7-3f2975060417","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01HsJ83NK3yqrMh22xtqai31","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01FTC59ufvgXt3VSQCNwf6FA","name":"Agent","input":{"description":"Analyze current indexes and migrations","subagent_type":"Explore","prompt":"In /Users/jan/prg/CC/cc-backend, I need to understand the current index situation on the job table.\n\n1. Read ALL migration files in `internal/repository/migrations/sqlite3/` - especially 08_add-footprint.up.sql and 09_add-job-cache.up.sql which define the current indexes\n2. List EVERY CREATE INDEX statement for the job table across all migrations\n3. Note which indexes were DROPped in later migrations\n4. Read the job table schema (CREATE TABLE) from 01_init-schema.up.sql and any modifications in later migrations\n\nI need the complete picture of:\n- All 79+ indexes currently defined\n- The job table column list with types\n- Which columns have individual indexes vs composite indexes\n- Any covering index patterns\n\nReport the full list organized by leading column."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":2187,"cache_read_input_tokens":122708,"output_tokens":714,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2187,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvfaidQmdm7NtZ64xu8d","type":"assistant","uuid":"b426fff6-7428-4ea1-9f65-0abfd65c6d7d","timestamp":"2026-03-11T04:31:55.362Z"}
+{"parentUuid":"b426fff6-7428-4ea1-9f65-0abfd65c6d7d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"type":"hook_progress","hookEvent":"PreToolUse","hookName":"PreToolUse:Agent","command":"entire hooks claude-code pre-task"},"toolUseID":"toolu_01FTC59ufvgXt3VSQCNwf6FA","parentToolUseID":"toolu_01FTC59ufvgXt3VSQCNwf6FA","uuid":"30efd714-12eb-4423-9341-82330d94cd19","timestamp":"2026-03-11T04:31:55.363Z"}
+{"parentUuid":"30efd714-12eb-4423-9341-82330d94cd19","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HzXCwt8PMuBHGPmQuBvUFf","type":"tool_result","content":"\nOutput too large (49.5KB). Full output saved to: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/42401d2e-7d1c-4c0e-abe6-356cb2d48747/tool-results/toolu_01HzXCwt8PMuBHGPmQuBvUFf.txt\n\nPreview (first 2KB):\n 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// Package repository provides the data access layer for cc-backend using the repository pattern.\n 7→//\n 8→// The repository pattern abstracts database operations and provides a clean interface for\n 9→// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n 10→// operations and specialized queries.\n 11→//\n 12→// # Database Connection\n 13→//\n 14→// Initialize the database connection before using any repository:\n 15→//\n 16→//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n 17→//\n 18→// # Configuration\n 19→//\n 20→// Optional: Configure repository settings before initialization:\n 21→//\n 22→//\trepository.SetConfig(&repository.RepositoryConfig{\n 23→//\t CacheSize: 2 * 1024 * 1024, // 2MB cache\n 24→//\t MaxOpenConnections: 8, // Connection pool size\n 25→//\t MinRunningJobDuration: 300, // Filter threshold\n 26→//\t})\n 27→//\n 28→// If not configured, sensible defaults are used automatically.\n 29→//\n 30→// # Repositories\n 31→//\n 32→// - JobRepository: Job lifecycle management and querying\n 33→// - UserRepository: User management and authentication\n 34→// - NodeRepository: Cluster node state tracking\n 35→// - Tags: Job tagging and categorization\n 36→//\n 37→// # Caching\n 38→//\n 39→// Repositories use LRU caching to improve performance. Cache keys are constructed\n 40→// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n 41→// mutations to maintain consistency.\n 42→//\n 43→// # Transaction Support\n 44→//\n 45→// For batch operations, use transactions:\n 46→//\n 47→//\tt, err := jobRepo.TransactionInit()\n...\n"}]},"uuid":"6aadf3e1-6332-4959-8679-c445a354f4fe","timestamp":"2026-03-11T04:31:55.397Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"338a8ec7-84fb-4e44-b8ad-19f8b73f8a31","timestamp":"2026-03-11T04:31:55.401Z"}
+{"parentUuid":"338a8ec7-84fb-4e44-b8ad-19f8b73f8a31","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"In /Users/jan/prg/CC/cc-backend, I need to understand the current index situation on the job table.\n\n1. Read ALL migration files in `internal/repository/migrations/sqlite3/` - especially 08_add-footprint.up.sql and 09_add-job-cache.up.sql which define the current indexes\n2. List EVERY CREATE INDEX statement for the job table across all migrations\n3. Note which indexes were DROPped in later migrations\n4. Read the job table schema (CREATE TABLE) from 01_init-schema.up.sql and any modifications in later migrations\n\nI need the complete picture of:\n- All 79+ indexes currently defined\n- The job table column list with types\n- Which columns have individual indexes vs composite indexes\n- Any covering index patterns\n\nReport the full list organized by leading column."}]},"uuid":"e99dec30-34e4-4a13-b81e-5094dd6bf85f","timestamp":"2026-03-11T04:31:55.602Z"},"type":"agent_progress","prompt":"In /Users/jan/prg/CC/cc-backend, I need to understand the current index situation on the job table.\n\n1. Read ALL migration files in `internal/repository/migrations/sqlite3/` - especially 08_add-footprint.up.sql and 09_add-job-cache.up.sql which define the current indexes\n2. List EVERY CREATE INDEX statement for the job table across all migrations\n3. Note which indexes were DROPped in later migrations\n4. Read the job table schema (CREATE TABLE) from 01_init-schema.up.sql and any modifications in later migrations\n\nI need the complete picture of:\n- All 79+ indexes currently defined\n- The job table column list with types\n- Which columns have individual indexes vs composite indexes\n- Any covering index patterns\n\nReport the full list organized by leading column.","agentId":"a1ede6e4db46fa8db"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01FTC59ufvgXt3VSQCNwf6FA","uuid":"66ff6163-736f-4046-8bba-58e2ee3cb0d8","timestamp":"2026-03-11T04:31:55.602Z"}
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The implementation includes role-based access control through\n 11→// tag scopes and maintains bidirectional consistency between the SQL database and\n 12→// the file-based job archive.\n 13→//\n 14→// Database Schema:\n 15→//\n 16→//\tCREATE TABLE tag (\n 17→//\t id INTEGER PRIMARY KEY AUTOINCREMENT,\n 18→//\t tag_type VARCHAR(255) NOT NULL,\n 19→//\t tag_name VARCHAR(255) NOT NULL,\n 20→//\t tag_scope VARCHAR(255) NOT NULL DEFAULT \"global\",\n 21→//\t CONSTRAINT tag_unique UNIQUE (tag_type, tag_name, tag_scope)\n 22→//\t);\n 23→//\n 24→//\tCREATE TABLE jobtag (\n 25→//\t job_id INTEGER,\n 26→//\t tag_id INTEGER,\n 27→//\t PRIMARY KEY (job_id, tag_id),\n 28→//\t FOREIGN KEY (job_id) REFERENCES job(id) ON DELETE CASCADE,\n 29→//\t FOREIGN KEY (tag_id) REFERENCES tag(id) ON DELETE CASCADE\n 30→//\t);\n 31→//\n 32→// The jobtag junction table enables many-to-many relationships between jobs and tags.\n 33→// CASCADE deletion ensures referential integrity when jobs or tags are removed.\n 34→package repository\n 35→\n 36→import (\n 37→\t\"errors\"\n 38→\t\"fmt\"\n 39→\t\"strings\"\n 40→\n 41→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 42→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 43→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 44→\tsq \"github.com/Masterminds/squirrel\"\n 45→)\n 46→\n 47→// Tag Scope Rules:\n 48→//\n 49→// Tags in ClusterCockpit have three visibility scopes that control who can see and use them:\n 50→//\n 51→// 1. \"global\" - Visible to all users, can be used by anyone\n 52→// Example: System-generated tags like \"energy-efficient\", \"failed\", \"short\"\n 53→//\n 54→// 2. \"private\" - Only visible to the creating user\n 55→// Example: Personal notes like \"needs-review\", \"interesting-case\"\n 56→//\n 57→// 3. \"admin\" - Only visible to users with admin or support roles\n 58→// Example: Internal notes like \"hardware-issue\", \"billing-problem\"\n 59→//\n 60→// Authorization Rules:\n 61→// - Regular users can only create/see \"global\" and their own \"private\" tags\n 62→// - Admin/Support can create/see all scopes including \"admin\" tags\n 63→// - Users can only add tags to jobs they have permission to view\n 64→// - Tag scope is enforced at query time in GetTags() and CountTags()\n 65→\n 66→// AddTag adds the tag with id `tagId` to the job with the database id `jobId`.\n 67→// Requires user authentication for security checks.\n 68→//\n 69→// The user must have permission to view the job. Tag visibility is determined by scope:\n 70→// - \"global\" tags: visible to all users\n 71→// - \"private\" tags: only visible to the tag creator\n 72→// - \"admin\" tags: only visible to admin/support users\n 73→func (r *JobRepository) AddTag(user *schema.User, job int64, tag int64) ([]*schema.Tag, error) {\n 74→\tj, err := r.FindByIDWithUser(user, job)\n 75→\tif err != nil {\n 76→\t\tcclog.Warnf(\"Error finding job %d for user %s: %v\", job, user.Username, err)\n 77→\t\treturn nil, err\n 78→\t}\n 79→\n 80→\treturn r.addJobTag(job, tag, j, func() ([]*schema.Tag, error) {\n 81→\t\treturn r.GetTags(user, &job)\n 82→\t})\n 83→}\n 84→\n 85→// AddTagDirect adds a tag without user security checks.\n 86→// Use only for internal/admin operations.\n 87→func (r *JobRepository) AddTagDirect(job int64, tag int64) ([]*schema.Tag, error) {\n 88→\tj, err := r.FindByIDDirect(job)\n 89→\tif err != nil {\n 90→\t\tcclog.Warnf(\"Error finding job %d: %v\", job, err)\n 91→\t\treturn nil, err\n 92→\t}\n 93→\n 94→\treturn r.addJobTag(job, tag, j, func() ([]*schema.Tag, error) {\n 95→\t\treturn r.GetTagsDirect(&job)\n 96→\t})\n 97→}\n 98→\n 99→// RemoveTag removes the tag with the database id `tag` from the job with the database id `job`.\n 100→// Requires user authentication for security checks. Used by GraphQL API.\n 101→func (r *JobRepository) RemoveTag(user *schema.User, job, tag int64) ([]*schema.Tag, error) {\n 102→\tj, err := r.FindByIDWithUser(user, job)\n 103→\tif err != nil {\n 104→\t\tcclog.Warnf(\"Error while finding job %d for user %s during tag removal: %v\", job, user.Username, err)\n 105→\t\treturn nil, err\n 106→\t}\n 107→\n 108→\tq := sq.Delete(\"jobtag\").Where(\"jobtag.job_id = ?\", job).Where(\"jobtag.tag_id = ?\", tag)\n 109→\n 110→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 111→\t\ts, _, _ := q.ToSql()\n 112→\t\tcclog.Errorf(\"Error removing tag with %s: %v\", s, err)\n 113→\t\treturn nil, err\n 114→\t}\n 115→\n 116→\ttags, err := r.GetTags(user, &job)\n 117→\tif err != nil {\n 118→\t\tcclog.Warn(\"Error while getting tags for job\")\n 119→\t\treturn nil, err\n 120→\t}\n 121→\n 122→\tarchiveTags, err := r.getArchiveTags(&job)\n 123→\tif err != nil {\n 124→\t\tcclog.Warnf(\"Error while getting archive tags for job %d in RemoveTag: %v\", job, err)\n 125→\t\treturn nil, err\n 126→\t}\n 127→\n 128→\treturn tags, archive.UpdateTags(j, archiveTags)\n 129→}\n 130→\n 131→// RemoveJobTagByRequest removes a tag from the job with the database id `job` by tag type, name, and scope.\n 132→// Requires user authentication for security checks. Used by REST API.\n 133→func (r *JobRepository) RemoveJobTagByRequest(user *schema.User, job int64, tagType string, tagName string, tagScope string) ([]*schema.Tag, error) {\n 134→\t// Get Tag ID to delete\n 135→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 136→\tif !exists {\n 137→\t\tcclog.Warnf(\"Tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 138→\t\treturn nil, fmt.Errorf(\"tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 139→\t}\n 140→\n 141→\t// Get Job\n 142→\tj, err := r.FindByIDWithUser(user, job)\n 143→\tif err != nil {\n 144→\t\tcclog.Warnf(\"Error while finding job %d for user %s during tag removal by request: %v\", job, user.Username, err)\n 145→\t\treturn nil, err\n 146→\t}\n 147→\n 148→\t// Handle Delete\n 149→\tq := sq.Delete(\"jobtag\").Where(\"jobtag.job_id = ?\", job).Where(\"jobtag.tag_id = ?\", tagID)\n 150→\n 151→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 152→\t\ts, _, _ := q.ToSql()\n 153→\t\tcclog.Errorf(\"Error removing tag from table 'jobTag' with %s: %v\", s, err)\n 154→\t\treturn nil, err\n 155→\t}\n 156→\n 157→\ttags, err := r.GetTags(user, &job)\n 158→\tif err != nil {\n 159→\t\tcclog.Warnf(\"Error while getting tags for job %d in RemoveJobTagByRequest: %v\", job, err)\n 160→\t\treturn nil, err\n 161→\t}\n 162→\n 163→\tarchiveTags, err := r.getArchiveTags(&job)\n 164→\tif err != nil {\n 165→\t\tcclog.Warnf(\"Error while getting archive tags for job %d in RemoveJobTagByRequest: %v\", job, err)\n 166→\t\treturn nil, err\n 167→\t}\n 168→\n 169→\treturn tags, archive.UpdateTags(j, archiveTags)\n 170→}\n 171→\n 172→// removeTagFromArchiveJobs updates the job archive for all affected jobs after a tag deletion.\n 173→//\n 174→// This function is called asynchronously (via goroutine) after removing a tag from the database\n 175→// to synchronize the file-based job archive with the database state. Errors are logged but not\n 176→// returned since this runs in the background.\n 177→//\n 178→// Parameters:\n 179→// - jobIds: Database IDs of all jobs that had the deleted tag\n 180→//\n 181→// Implementation note: Each job is processed individually to handle partial failures gracefully.\n 182→// If one job fails to update, others will still be processed.\n 183→func (r *JobRepository) removeTagFromArchiveJobs(jobIds []int64) {\n 184→\tfor _, j := range jobIds {\n 185→\t\ttags, err := r.getArchiveTags(&j)\n 186→\t\tif err != nil {\n 187→\t\t\tcclog.Warnf(\"Error while getting tags for job %d\", j)\n 188→\t\t\tcontinue\n 189→\t\t}\n 190→\n 191→\t\tjob, err := r.FindByIDDirect(j)\n 192→\t\tif err != nil {\n 193→\t\t\tcclog.Warnf(\"Error while getting job %d\", j)\n 194→\t\t\tcontinue\n 195→\t\t}\n 196→\n 197→\t\tarchive.UpdateTags(job, tags)\n 198→\t}\n 199→}\n 200→\n 201→// Removes a tag from db by tag info\n 202→// Used by REST API. Does not update tagged jobs in Job archive.\n 203→func (r *JobRepository) RemoveTagByRequest(tagType string, tagName string, tagScope string) error {\n 204→\t// Get Tag ID to delete\n 205→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 206→\tif !exists {\n 207→\t\tcclog.Warnf(\"Tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 208→\t\treturn fmt.Errorf(\"tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 209→\t}\n 210→\n 211→\treturn r.RemoveTagByID(tagID)\n 212→}\n 213→\n 214→// Removes a tag from db by tag id\n 215→// Used by GraphQL API.\n 216→func (r *JobRepository) RemoveTagByID(tagID int64) error {\n 217→\tjobIds, err := r.FindJobIdsByTag(tagID)\n 218→\tif err != nil {\n 219→\t\treturn err\n 220→\t}\n 221→\n 222→\t// Handle Delete JobTagTable\n 223→\tqJobTag := sq.Delete(\"jobtag\").Where(\"jobtag.tag_id = ?\", tagID)\n 224→\n 225→\tif _, err := qJobTag.RunWith(r.stmtCache).Exec(); err != nil {\n 226→\t\ts, _, _ := qJobTag.ToSql()\n 227→\t\tcclog.Errorf(\"Error removing tag from table 'jobTag' with %s: %v\", s, err)\n 228→\t\treturn err\n 229→\t}\n 230→\n 231→\t// Handle Delete TagTable\n 232→\tqTag := sq.Delete(\"tag\").Where(\"tag.id = ?\", tagID)\n 233→\n 234→\tif _, err := qTag.RunWith(r.stmtCache).Exec(); err != nil {\n 235→\t\ts, _, _ := qTag.ToSql()\n 236→\t\tcclog.Errorf(\"Error removing tag from table 'tag' with %s: %v\", s, err)\n 237→\t\treturn err\n 238→\t}\n 239→\n 240→\t// asynchronously update archive jobs\n 241→\tgo r.removeTagFromArchiveJobs(jobIds)\n 242→\n 243→\treturn nil\n 244→}\n 245→\n 246→// CreateTag creates a new tag with the specified type, name, and scope.\n 247→// Returns the database ID of the newly created tag.\n 248→//\n 249→// Scope defaults to \"global\" if empty string is provided.\n 250→// Valid scopes: \"global\", \"private\", \"admin\"\n 251→//\n 252→// Example:\n 253→//\n 254→//\ttagID, err := repo.CreateTag(\"performance\", \"high-memory\", \"global\")\n 255→func (r *JobRepository) CreateTag(tagType string, tagName string, tagScope string) (tagID int64, err error) {\n 256→\t// Default to \"Global\" scope if none defined\n 257→\tif tagScope == \"\" {\n 258→\t\ttagScope = \"global\"\n 259→\t}\n 260→\n 261→\tq := sq.Insert(\"tag\").Columns(\"tag_type\", \"tag_name\", \"tag_scope\").Values(tagType, tagName, tagScope)\n 262→\n 263→\tres, err := q.RunWith(r.stmtCache).Exec()\n 264→\tif err != nil {\n 265→\t\ts, _, _ := q.ToSql()\n 266→\t\tcclog.Errorf(\"Error inserting tag with %s: %v\", s, err)\n 267→\t\treturn 0, err\n 268→\t}\n 269→\n 270→\treturn res.LastInsertId()\n 271→}\n 272→\n 273→// CountTags returns all tags visible to the user and the count of jobs for each tag.\n 274→// Applies scope-based filtering to respect tag visibility rules.\n 275→//\n 276→// Returns:\n 277→// - tags: slice of tags the user can see\n 278→// - counts: map of tag name to job count\n 279→// - err: any error encountered\n 280→func (r *JobRepository) CountTags(user *schema.User) (tags []schema.Tag, counts map[string]int, err error) {\n 281→\ttags = make([]schema.Tag, 0, 100)\n 282→\txrows, err := r.DB.Queryx(\"SELECT id, tag_type, tag_name, tag_scope FROM tag\")\n 283→\tif err != nil {\n 284→\t\treturn nil, nil, err\n 285→\t}\n 286→\tdefer xrows.Close()\n 287→\n 288→\tfor xrows.Next() {\n 289→\t\tvar t schema.Tag\n 290→\t\tif err = xrows.StructScan(&t); err != nil {\n 291→\t\t\treturn nil, nil, err\n 292→\t\t}\n 293→\n 294→\t\t// Handle Scope Filtering: Tag Scope is Global, Private (== Username) or User is auth'd to view Admin Tags\n 295→\t\treadable, err := r.checkScopeAuth(user, \"read\", t.Scope)\n 296→\t\tif err != nil {\n 297→\t\t\treturn nil, nil, err\n 298→\t\t}\n 299→\t\tif readable {\n 300→\t\t\ttags = append(tags, t)\n 301→\t\t}\n 302→\t}\n 303→\n 304→\tif err := xrows.Err(); err != nil {\n 305→\t\treturn nil, nil, err\n 306→\t}\n 307→\n 308→\t// Query and Count Jobs with attached Tags\n 309→\tq := sq.Select(\"t.tag_type, t.tag_name, t.id, count(jt.tag_id)\").\n 310→\t\tFrom(\"tag t\").\n 311→\t\tLeftJoin(\"jobtag jt ON t.id = jt.tag_id\").\n 312→\t\tGroupBy(\"t.tag_type, t.tag_name\")\n 313→\n 314→\t// Build scope list for filtering\n 315→\tvar scopeBuilder strings.Builder\n 316→\tscopeBuilder.WriteString(`\"global\"`)\n 317→\tif user != nil {\n 318→\t\tscopeBuilder.WriteString(`,\"`)\n 319→\t\tscopeBuilder.WriteString(user.Username)\n 320→\t\tscopeBuilder.WriteString(`\"`)\n 321→\t\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 322→\t\t\tscopeBuilder.WriteString(`,\"admin\"`)\n 323→\t\t}\n 324→\t}\n 325→\tq = q.Where(\"t.tag_scope IN (\" + scopeBuilder.String() + \")\")\n 326→\n 327→\t// Handle Job Ownership\n 328→\tif user != nil && user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) { // ADMIN || SUPPORT: Count all jobs\n 329→\t\t// cclog.Debug(\"CountTags: User Admin or Support -> Count all Jobs for Tags\")\n 330→\t\t// Unchanged: Needs to be own case still, due to UserRole/NoRole compatibility handling in else case\n 331→\t} else if user != nil && user.HasRole(schema.RoleManager) { // MANAGER: Count own jobs plus project's jobs\n 332→\t\t// Build (\"project1\", \"project2\", ...) list of variable length directly in SQL string\n 333→\t\tq = q.Where(\"jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ? OR job.project IN (\\\"\"+strings.Join(user.Projects, \"\\\",\\\"\")+\"\\\"))\", user.Username)\n 334→\t} else if user != nil { // USER OR NO ROLE (Compatibility): Only count own jobs\n 335→\t\tq = q.Where(\"jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ?)\", user.Username)\n 336→\t}\n 337→\n 338→\trows, err := q.RunWith(r.stmtCache).Query()\n 339→\tif err != nil {\n 340→\t\treturn nil, nil, err\n 341→\t}\n 342→\tdefer rows.Close()\n 343→\n 344→\tcounts = make(map[string]int)\n 345→\tfor rows.Next() {\n 346→\t\tvar tagType string\n 347→\t\tvar tagName string\n 348→\t\tvar tagID int\n 349→\t\tvar count int\n 350→\t\tif err = rows.Scan(&tagType, &tagName, &tagID, &count); err != nil {\n 351→\t\t\treturn nil, nil, err\n 352→\t\t}\n 353→\t\t// Use tagId as second Map-Key component to differentiate tags with identical names\n 354→\t\tcounts[fmt.Sprint(tagType, tagName, tagID)] = count\n 355→\t}\n 356→\terr = rows.Err()\n 357→\n 358→\treturn tags, counts, err\n 359→}\n 360→\n 361→var (\n 362→\t// ErrTagNotFound is returned when a tag ID or tag identifier (type, name, scope) does not exist in the database.\n 363→\tErrTagNotFound = errors.New(\"the tag does not exist\")\n 364→\n 365→\t// ErrJobNotOwned is returned when a user attempts to tag a job they do not have permission to access.\n 366→\tErrJobNotOwned = errors.New(\"user is not owner of job\")\n 367→\n 368→\t// ErrTagNoAccess is returned when a user attempts to use a tag they cannot access due to scope restrictions.\n 369→\tErrTagNoAccess = errors.New(\"user not permitted to use that tag\")\n 370→\n 371→\t// ErrTagPrivateScope is returned when a user attempts to access another user's private tag.\n 372→\tErrTagPrivateScope = errors.New(\"tag is private to another user\")\n 373→\n 374→\t// ErrTagAdminScope is returned when a non-admin user attempts to use an admin-scoped tag.\n 375→\tErrTagAdminScope = errors.New(\"tag requires admin privileges\")\n 376→\n 377→\t// ErrTagsIncompatScopes is returned when attempting to combine admin and non-admin scoped tags in a single operation.\n 378→\tErrTagsIncompatScopes = errors.New(\"combining admin and non-admin scoped tags not allowed\")\n 379→)\n 380→\n 381→// addJobTag is a helper function that inserts a job-tag association and updates the archive.\n 382→//\n 383→// This function performs three operations atomically:\n 384→// 1. Inserts the job-tag association into the jobtag junction table\n 385→// 2. Retrieves the updated tag list for the job (using the provided getTags callback)\n 386→// 3. Updates the job archive with the new tags to maintain database-archive consistency\n 387→//\n 388→// Parameters:\n 389→// - jobId: Database ID of the job\n 390→// - tagId: Database ID of the tag to associate\n 391→// - job: Full job object needed for archive update\n 392→// - getTags: Callback function to retrieve updated tags (allows different security contexts)\n 393→//\n 394→// Returns the complete updated tag list for the job or an error.\n 395→//\n 396→// Note: This function does NOT validate tag scope permissions - callers must perform\n 397→// authorization checks before invoking this helper.\n 398→func (r *JobRepository) addJobTag(jobID int64, tagID int64, job *schema.Job, getTags func() ([]*schema.Tag, error)) ([]*schema.Tag, error) {\n 399→\tq := sq.Insert(\"jobtag\").Columns(\"job_id\", \"tag_id\").Values(jobID, tagID)\n 400→\n 401→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 402→\t\ts, _, _ := q.ToSql()\n 403→\t\tcclog.Errorf(\"Error adding tag with %s: %v\", s, err)\n 404→\t\treturn nil, err\n 405→\t}\n 406→\n 407→\ttags, err := getTags()\n 408→\tif err != nil {\n 409→\t\tcclog.Warnf(\"Error getting tags for job %d: %v\", jobID, err)\n 410→\t\treturn nil, err\n 411→\t}\n 412→\n 413→\tarchiveTags, err := r.getArchiveTags(&jobID)\n 414→\tif err != nil {\n 415→\t\tcclog.Warnf(\"Error getting archive tags for job %d: %v\", jobID, err)\n 416→\t\treturn nil, err\n 417→\t}\n 418→\n 419→\treturn tags, archive.UpdateTags(job, archiveTags)\n 420→}\n 421→\n 422→// AddTagOrCreate adds the tag with the specified type and name to the job with the database id `jobId`.\n 423→// If such a tag does not yet exist, it is created.\n 424→func (r *JobRepository) AddTagOrCreate(user *schema.User, jobID int64, tagType string, tagName string, tagScope string) (tagID int64, err error) {\n 425→\t// Default to \"Global\" scope if none defined\n 426→\tif tagScope == \"\" {\n 427→\t\ttagScope = \"global\"\n 428→\t}\n 429→\n 430→\twritable, err := r.checkScopeAuth(user, \"write\", tagScope)\n 431→\tif err != nil {\n 432→\t\treturn 0, err\n 433→\t}\n 434→\tif !writable {\n 435→\t\treturn 0, fmt.Errorf(\"cannot write tag scope with current authorization\")\n 436→\t}\n 437→\n 438→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 439→\tif !exists {\n 440→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 441→\t\tif err != nil {\n 442→\t\t\treturn 0, err\n 443→\t\t}\n 444→\t}\n 445→\n 446→\tif _, err := r.AddTag(user, jobID, tagID); err != nil {\n 447→\t\treturn 0, err\n 448→\t}\n 449→\n 450→\treturn tagID, nil\n 451→}\n 452→\n 453→func (r *JobRepository) AddTagOrCreateDirect(jobID int64, tagType string, tagName string) (tagID int64, err error) {\n 454→\ttagScope := \"global\"\n 455→\n 456→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 457→\tif !exists {\n 458→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 459→\t\tif err != nil {\n 460→\t\t\treturn 0, err\n 461→\t\t}\n 462→\t}\n 463→\n 464→\tcclog.Infof(\"Adding tag %s:%s:%s (direct)\", tagType, tagName, tagScope)\n 465→\n 466→\tif _, err := r.AddTagDirect(jobID, tagID); err != nil {\n 467→\t\treturn 0, err\n 468→\t}\n 469→\n 470→\treturn tagID, nil\n 471→}\n 472→\n 473→func (r *JobRepository) HasTag(jobID int64, tagType string, tagName string) bool {\n 474→\tvar id int64\n 475→\tq := sq.Select(\"id\").From(\"tag\").Join(\"jobtag ON jobtag.tag_id = tag.id\").\n 476→\t\tWhere(\"jobtag.job_id = ?\", jobID).Where(\"tag.tag_type = ?\", tagType).\n 477→\t\tWhere(\"tag.tag_name = ?\", tagName)\n 478→\terr := q.RunWith(r.stmtCache).QueryRow().Scan(&id)\n 479→\tif err != nil {\n 480→\t\treturn false\n 481→\t} else {\n 482→\t\treturn true\n 483→\t}\n 484→}\n 485→\n 486→// TagID returns the database id of the tag with the specified type and name.\n 487→func (r *JobRepository) TagID(tagType string, tagName string, tagScope string) (tagID int64, exists bool) {\n 488→\texists = true\n 489→\tif err := sq.Select(\"id\").From(\"tag\").\n 490→\t\tWhere(\"tag.tag_type = ?\", tagType).Where(\"tag.tag_name = ?\", tagName).Where(\"tag.tag_scope = ?\", tagScope).\n 491→\t\tRunWith(r.stmtCache).QueryRow().Scan(&tagID); err != nil {\n 492→\t\texists = false\n 493→\t}\n 494→\treturn\n 495→}\n 496→\n 497→// TagInfo returns the database infos of the tag with the specified id.\n 498→func (r *JobRepository) TagInfo(tagID int64) (tagType string, tagName string, tagScope string, exists bool) {\n 499→\texists = true\n 500→\tif err := sq.Select(\"tag.tag_type\", \"tag.tag_name\", \"tag.tag_scope\").From(\"tag\").Where(\"tag.id = ?\", tagID).\n 501→\t\tRunWith(r.stmtCache).QueryRow().Scan(&tagType, &tagName, &tagScope); err != nil {\n 502→\t\texists = false\n 503→\t}\n 504→\treturn\n 505→}\n 506→\n 507→// GetTags returns a list of all scoped tags if job is nil or of the tags that the job with that database ID has.\n 508→func (r *JobRepository) GetTags(user *schema.User, job *int64) ([]*schema.Tag, error) {\n 509→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 510→\tif job != nil {\n 511→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 512→\t}\n 513→\n 514→\trows, err := q.RunWith(r.stmtCache).Query()\n 515→\tif err != nil {\n 516→\t\ts, _, _ := q.ToSql()\n 517→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 518→\t\treturn nil, err\n 519→\t}\n 520→\tdefer rows.Close()\n 521→\n 522→\ttags := make([]*schema.Tag, 0)\n 523→\tfor rows.Next() {\n 524→\t\ttag := &schema.Tag{}\n 525→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 526→\t\t\tcclog.Warnf(\"Error while scanning tag rows in GetTags: %v\", err)\n 527→\t\t\treturn nil, err\n 528→\t\t}\n 529→\t\t// Handle Scope Filtering: Tag Scope is Global, Private (== Username) or User is auth'd to view Admin Tags\n 530→\t\treadable, err := r.checkScopeAuth(user, \"read\", tag.Scope)\n 531→\t\tif err != nil {\n 532→\t\t\treturn nil, err\n 533→\t\t}\n 534→\t\tif readable {\n 535→\t\t\ttags = append(tags, tag)\n 536→\t\t}\n 537→\t}\n 538→\n 539→\tif err := rows.Err(); err != nil {\n 540→\t\treturn nil, err\n 541→\t}\n 542→\n 543→\treturn tags, nil\n 544→}\n 545→\n 546→func (r *JobRepository) GetTagsDirect(job *int64) ([]*schema.Tag, error) {\n 547→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 548→\tif job != nil {\n 549→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 550→\t}\n 551→\n 552→\trows, err := q.RunWith(r.stmtCache).Query()\n 553→\tif err != nil {\n 554→\t\ts, _, _ := q.ToSql()\n 555→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 556→\t\treturn nil, err\n 557→\t}\n 558→\tdefer rows.Close()\n 559→\n 560→\ttags := make([]*schema.Tag, 0)\n 561→\tfor rows.Next() {\n 562→\t\ttag := &schema.Tag{}\n 563→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 564→\t\t\tcclog.Warnf(\"Error while scanning tag rows in GetTagsDirect: %v\", err)\n 565→\t\t\treturn nil, err\n 566→\t\t}\n 567→\t\ttags = append(tags, tag)\n 568→\t}\n 569→\n 570→\tif err := rows.Err(); err != nil {\n 571→\t\treturn nil, err\n 572→\t}\n 573→\n 574→\treturn tags, nil\n 575→}\n 576→\n 577→// getArchiveTags returns all tags for a job WITHOUT applying scope-based filtering.\n 578→//\n 579→// This internal function is used exclusively for job archive synchronization where we need\n 580→// to store all tags regardless of the current user's permissions. Unlike GetTags() which\n 581→// filters by scope, this returns the complete unfiltered tag list.\n 582→//\n 583→// Parameters:\n 584→// - job: Pointer to job database ID, or nil to return all tags in the system\n 585→//\n 586→// Returns all tags without scope filtering, used only for archive operations.\n 587→//\n 588→// WARNING: Do NOT expose this function to user-facing APIs as it bypasses authorization.\n 589→func (r *JobRepository) getArchiveTags(job *int64) ([]*schema.Tag, error) {\n 590→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 591→\tif job != nil {\n 592→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 593→\t}\n 594→\n 595→\trows, err := q.RunWith(r.stmtCache).Query()\n 596→\tif err != nil {\n 597→\t\ts, _, _ := q.ToSql()\n 598→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 599→\t\treturn nil, err\n 600→\t}\n 601→\tdefer rows.Close()\n 602→\n 603→\ttags := make([]*schema.Tag, 0)\n 604→\tfor rows.Next() {\n 605→\t\ttag := &schema.Tag{}\n 606→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 607→\t\t\tcclog.Warnf(\"Error while scanning tag rows in getArchiveTags: %v\", err)\n 608→\t\t\treturn nil, err\n 609→\t\t}\n 610→\t\ttags = append(tags, tag)\n 611→\t}\n 612→\n 613→\tif err := rows.Err(); err != nil {\n 614→\t\treturn nil, err\n 615→\t}\n 616→\n 617→\treturn tags, nil\n 618→}\n 619→\n 620→func (r *JobRepository) ImportTag(jobID int64, tagType string, tagName string, tagScope string) (err error) {\n 621→\t// Import has no scope ctx, only import from metafile to DB (No recursive archive update required), only returns err\n 622→\n 623→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 624→\tif !exists {\n 625→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 626→\t\tif err != nil {\n 627→\t\t\treturn err\n 628→\t\t}\n 629→\t}\n 630→\n 631→\tq := sq.Insert(\"jobtag\").Columns(\"job_id\", \"tag_id\").Values(jobID, tagID)\n 632→\n 633→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 634→\t\ts, _, _ := q.ToSql()\n 635→\t\tcclog.Errorf(\"Error adding tag on import with %s: %v\", s, err)\n 636→\t\treturn err\n 637→\t}\n 638→\n 639→\treturn nil\n 640→}\n 641→\n 642→// checkScopeAuth validates whether a user is authorized to perform an operation on a tag with the given scope.\n 643→//\n 644→// This function implements the tag scope authorization matrix:\n 645→//\n 646→//\tScope | Read Access | Write Access\n 647→//\t-------------|----------------------------------|----------------------------------\n 648→//\t\"global\" | All users | Admin, Support, API-only\n 649→//\t\"admin\" | Admin, Support | Admin, API-only\n 650→//\t | Owner only | Owner only (private tags)\n 651→//\n 652→// Parameters:\n 653→// - user: User attempting the operation (must not be nil)\n 654→// - operation: Either \"read\" or \"write\"\n 655→// - scope: Tag scope value (\"global\", \"admin\", or username for private tags)\n 656→//\n 657→// Returns:\n 658→// - pass: true if authorized, false if denied\n 659→// - err: error only if operation is invalid or user is nil\n 660→//\n 661→// Special cases:\n 662→// - API-only users (single role: RoleApi) can write to admin and global scopes for automation\n 663→// - Private tags use the username as scope, granting exclusive access to that user\n 664→func (r *JobRepository) checkScopeAuth(user *schema.User, operation string, scope string) (pass bool, err error) {\n 665→\tif user != nil {\n 666→\t\tswitch {\n 667→\t\tcase operation == \"write\" && scope == \"admin\":\n 668→\t\t\tif user.HasRole(schema.RoleAdmin) || (len(user.Roles) == 1 && user.HasRole(schema.RoleAPI)) {\n 669→\t\t\t\treturn true, nil\n 670→\t\t\t}\n 671→\t\t\treturn false, nil\n 672→\t\tcase operation == \"write\" && scope == \"global\":\n 673→\t\t\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) || (len(user.Roles) == 1 && user.HasRole(schema.RoleAPI)) {\n 674→\t\t\t\treturn true, nil\n 675→\t\t\t}\n 676→\t\t\treturn false, nil\n 677→\t\tcase operation == \"write\" && scope == user.Username:\n 678→\t\t\treturn true, nil\n 679→\t\tcase operation == \"read\" && scope == \"admin\":\n 680→\t\t\treturn user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}), nil\n 681→\t\tcase operation == \"read\" && scope == \"global\":\n 682→\t\t\treturn true, nil\n 683→\t\tcase operation == \"read\" && scope == user.Username:\n 684→\t\t\treturn true, nil\n 685→\t\tdefault:\n 686→\t\t\tif operation == \"read\" || operation == \"write\" {\n 687→\t\t\t\t// No acceptable scope: deny tag\n 688→\t\t\t\treturn false, nil\n 689→\t\t\t} else {\n 690→\t\t\t\treturn false, fmt.Errorf(\"error while checking tag operation auth: unknown operation (%s)\", operation)\n 691→\t\t\t}\n 692→\t\t}\n 693→\t} else {\n 694→\t\treturn false, fmt.Errorf(\"error while checking tag operation auth: no user in context\")\n 695→\t}\n 696→}\n 697→"}]},"uuid":"609e7fd8-a135-4eb5-b895-a60360cdeb2b","timestamp":"2026-03-11T04:31:57.686Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"c68a65c0-7f22-4460-8b76-32027b020268","timestamp":"2026-03-11T04:31:57.692Z"}
+{"parentUuid":"c68a65c0-7f22-4460-8b76-32027b020268","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GuF7S6fPP1x2VXzYMijhRT","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(job.id)\").From(\"job\").GroupBy(col)\n 109→\t} else {\n 110→\t\tquery = sq.Select(\"COUNT(job.id)\").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 comprehensive job statistics with optional grouping.\n 128→//\n 129→// Parameters:\n 130→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 131→// - col: Column name to GROUP BY; empty string for overall statistics without grouping\n 132→//\n 133→// Returns a SelectBuilder that produces comprehensive statistics:\n 134→// - totalJobs: Count of jobs\n 135→// - totalUsers: Count of distinct users (always 0 when grouping by user)\n 136→// - totalWalltime: Sum of job durations in hours\n 137→// - totalNodes: Sum of nodes used across all jobs\n 138→// - totalNodeHours: Sum of (duration × num_nodes) in hours\n 139→// - totalCores: Sum of hardware threads used across all jobs\n 140→// - totalCoreHours: Sum of (duration × num_hwthreads) in hours\n 141→// - totalAccs: Sum of accelerators used across all jobs\n 142→// - totalAccHours: Sum of (duration × num_acc) in hours\n 143→//\n 144→// Special handling:\n 145→// - Running jobs: Duration calculated as (now - start_time) instead of stored duration\n 146→// - Grouped queries: Also select grouping column and user's display name from hpc_user table\n 147→// - All time values converted from seconds to hours (÷ 3600) and rounded\n 148→func (r *JobRepository) buildStatsQuery(\n 149→\tfilter []*model.JobFilter,\n 150→\tcol string,\n 151→) sq.SelectBuilder {\n 152→\tvar query sq.SelectBuilder\n 153→\n 154→\tif col != \"\" {\n 155→\t\tquery = sq.Select(\n 156→\t\t\tcol,\n 157→\t\t\t\"name\",\n 158→\t\t\t\"COUNT(job.id) as totalJobs\",\n 159→\t\t\t\"COUNT(DISTINCT job.hpc_user) AS totalUsers\",\n 160→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END)) / 3600) as int) as totalWalltime`, time.Now().Unix()),\n 161→\t\t\t`CAST(SUM(job.num_nodes) as int) as totalNodes`,\n 162→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_nodes) / 3600) as int) as totalNodeHours`, time.Now().Unix()),\n 163→\t\t\t`CAST(SUM(job.num_hwthreads) as int) as totalCores`,\n 164→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_hwthreads) / 3600) as int) as totalCoreHours`, time.Now().Unix()),\n 165→\t\t\t`CAST(SUM(job.num_acc) as int) as totalAccs`,\n 166→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_acc) / 3600) as int) as totalAccHours`, time.Now().Unix()),\n 167→\t\t).From(\"job\").LeftJoin(\"hpc_user ON hpc_user.username = job.hpc_user\").GroupBy(col)\n 168→\t} else {\n 169→\t\tquery = sq.Select(\n 170→\t\t\t\"COUNT(job.id) as totalJobs\",\n 171→\t\t\t\"COUNT(DISTINCT job.hpc_user) AS totalUsers\",\n 172→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END)) / 3600) as int)`, time.Now().Unix()),\n 173→\t\t\t`CAST(SUM(job.num_nodes) as int)`,\n 174→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_nodes) / 3600) as int)`, time.Now().Unix()),\n 175→\t\t\t`CAST(SUM(job.num_hwthreads) as int)`,\n 176→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_hwthreads) / 3600) as int)`, time.Now().Unix()),\n 177→\t\t\t`CAST(SUM(job.num_acc) as int)`,\n 178→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_acc) / 3600) as int)`, time.Now().Unix()),\n 179→\t\t).From(\"job\")\n 180→\t}\n 181→\n 182→\tfor _, f := range filter {\n 183→\t\tquery = BuildWhereClause(f, query)\n 184→\t}\n 185→\n 186→\treturn query\n 187→}\n 188→\n 189→// JobsStatsGrouped computes comprehensive job statistics grouped by a dimension (user, project, cluster, or subcluster).\n 190→//\n 191→// This is the primary method for generating aggregated statistics views in the UI, providing\n 192→// metrics like total jobs, walltime, and resource usage broken down by the specified grouping.\n 193→//\n 194→// Parameters:\n 195→// - ctx: Context for security checks and cancellation\n 196→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 197→// - page: Optional pagination (ItemsPerPage: -1 disables pagination)\n 198→// - sortBy: Optional sort column (totalJobs, totalWalltime, totalCoreHours, etc.)\n 199→// - groupBy: Required grouping dimension (User, Project, Cluster, or SubCluster)\n 200→//\n 201→// Returns a slice of JobsStatistics, one per group, with:\n 202→// - ID: The group identifier (username, project name, cluster name, etc.)\n 203→// - Name: Display name (for users, from hpc_user.name; empty for other groups)\n 204→// - Statistics: totalJobs, totalUsers, totalWalltime, resource usage metrics\n 205→//\n 206→// Security: Respects user roles via SecurityCheck - users see only their own data unless admin/support.\n 207→// Performance: Results are sorted in SQL and pagination applied before scanning rows.\n 208→func (r *JobRepository) JobsStatsGrouped(\n 209→\tctx context.Context,\n 210→\tfilter []*model.JobFilter,\n 211→\tpage *model.PageRequest,\n 212→\tsortBy *model.SortByAggregate,\n 213→\tgroupBy *model.Aggregate,\n 214→) ([]*model.JobsStatistics, error) {\n 215→\tstart := time.Now()\n 216→\tcol := groupBy2column[*groupBy]\n 217→\tquery := r.buildStatsQuery(filter, col)\n 218→\n 219→\tquery, err := SecurityCheck(ctx, query)\n 220→\tif err != nil {\n 221→\t\treturn nil, err\n 222→\t}\n 223→\n 224→\tif sortBy != nil {\n 225→\t\tsortBy := sortBy2column[*sortBy]\n 226→\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n 227→\t}\n 228→\tif page != nil && page.ItemsPerPage != -1 {\n 229→\t\tlimit := uint64(page.ItemsPerPage)\n 230→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 231→\t}\n 232→\n 233→\trows, err := query.RunWith(r.DB).Query()\n 234→\tif err != nil {\n 235→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 236→\t\treturn nil, err\n 237→\t}\n 238→\tdefer rows.Close()\n 239→\n 240→\tstats := make([]*model.JobsStatistics, 0, 100)\n 241→\n 242→\tfor rows.Next() {\n 243→\t\tvar id sql.NullString\n 244→\t\tvar name sql.NullString\n 245→\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours sql.NullInt64\n 246→\t\tif err := rows.Scan(&id, &name, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours); err != nil {\n 247→\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n 248→\t\t\treturn nil, err\n 249→\t\t}\n 250→\n 251→\t\tif id.Valid {\n 252→\t\t\tvar totalJobs, totalUsers, totalWalltime, totalNodes, totalNodeHours, totalCores, totalCoreHours, totalAccs, totalAccHours int\n 253→\t\t\tvar personName string\n 254→\n 255→\t\t\tif name.Valid {\n 256→\t\t\t\tpersonName = name.String\n 257→\t\t\t}\n 258→\n 259→\t\t\tif jobs.Valid {\n 260→\t\t\t\ttotalJobs = int(jobs.Int64)\n 261→\t\t\t}\n 262→\n 263→\t\t\tif users.Valid {\n 264→\t\t\t\ttotalUsers = int(users.Int64)\n 265→\t\t\t}\n 266→\n 267→\t\t\tif walltime.Valid {\n 268→\t\t\t\ttotalWalltime = int(walltime.Int64)\n 269→\t\t\t}\n 270→\n 271→\t\t\tif nodes.Valid {\n 272→\t\t\t\ttotalNodes = int(nodes.Int64)\n 273→\t\t\t}\n 274→\t\t\tif cores.Valid {\n 275→\t\t\t\ttotalCores = int(cores.Int64)\n 276→\t\t\t}\n 277→\t\t\tif accs.Valid {\n 278→\t\t\t\ttotalAccs = int(accs.Int64)\n 279→\t\t\t}\n 280→\n 281→\t\t\tif nodeHours.Valid {\n 282→\t\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 283→\t\t\t}\n 284→\t\t\tif coreHours.Valid {\n 285→\t\t\t\ttotalCoreHours = int(coreHours.Int64)\n 286→\t\t\t}\n 287→\t\t\tif accHours.Valid {\n 288→\t\t\t\ttotalAccHours = int(accHours.Int64)\n 289→\t\t\t}\n 290→\n 291→\t\t\tif col == \"job.hpc_user\" {\n 292→\t\t\t\t// name := r.getUserName(ctx, id.String)\n 293→\t\t\t\tstats = append(stats,\n 294→\t\t\t\t\t&model.JobsStatistics{\n 295→\t\t\t\t\t\tID: id.String,\n 296→\t\t\t\t\t\tName: personName,\n 297→\t\t\t\t\t\tTotalJobs: totalJobs,\n 298→\t\t\t\t\t\tTotalWalltime: totalWalltime,\n 299→\t\t\t\t\t\tTotalNodes: totalNodes,\n 300→\t\t\t\t\t\tTotalNodeHours: totalNodeHours,\n 301→\t\t\t\t\t\tTotalCores: totalCores,\n 302→\t\t\t\t\t\tTotalCoreHours: totalCoreHours,\n 303→\t\t\t\t\t\tTotalAccs: totalAccs,\n 304→\t\t\t\t\t\tTotalAccHours: totalAccHours,\n 305→\t\t\t\t\t})\n 306→\t\t\t} else {\n 307→\t\t\t\tstats = append(stats,\n 308→\t\t\t\t\t&model.JobsStatistics{\n 309→\t\t\t\t\t\tID: id.String,\n 310→\t\t\t\t\t\tTotalJobs: totalJobs,\n 311→\t\t\t\t\t\tTotalUsers: totalUsers,\n 312→\t\t\t\t\t\tTotalWalltime: totalWalltime,\n 313→\t\t\t\t\t\tTotalNodes: totalNodes,\n 314→\t\t\t\t\t\tTotalNodeHours: totalNodeHours,\n 315→\t\t\t\t\t\tTotalCores: totalCores,\n 316→\t\t\t\t\t\tTotalCoreHours: totalCoreHours,\n 317→\t\t\t\t\t\tTotalAccs: totalAccs,\n 318→\t\t\t\t\t\tTotalAccHours: totalAccHours,\n 319→\t\t\t\t\t})\n 320→\t\t\t}\n 321→\t\t}\n 322→\t}\n 323→\n 324→\tif err := rows.Err(); err != nil {\n 325→\t\treturn nil, err\n 326→\t}\n 327→\n 328→\tcclog.Debugf(\"Timer JobsStatsGrouped %s\", time.Since(start))\n 329→\treturn stats, nil\n 330→}\n 331→\n 332→// JobsStats computes overall job statistics across all matching jobs without grouping.\n 333→//\n 334→// This method provides a single aggregate view of job metrics, useful for dashboard\n 335→// summaries and overall system utilization reports.\n 336→//\n 337→// Parameters:\n 338→// - ctx: Context for security checks and cancellation\n 339→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 340→//\n 341→// Returns a single-element slice containing aggregate statistics:\n 342→// - totalJobs, totalUsers, totalWalltime\n 343→// - totalNodeHours, totalCoreHours, totalAccHours\n 344→//\n 345→// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n 346→// Security checks are applied via SecurityCheck to respect user access levels.\n 347→func (r *JobRepository) JobsStats(\n 348→\tctx context.Context,\n 349→\tfilter []*model.JobFilter,\n 350→) ([]*model.JobsStatistics, error) {\n 351→\tstart := time.Now()\n 352→\tquery := r.buildStatsQuery(filter, \"\")\n 353→\tquery, err := SecurityCheck(ctx, query)\n 354→\tif err != nil {\n 355→\t\treturn nil, err\n 356→\t}\n 357→\n 358→\trow := query.RunWith(r.DB).QueryRow()\n 359→\tstats := make([]*model.JobsStatistics, 0, 1)\n 360→\n 361→\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours sql.NullInt64\n 362→\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours); err != nil {\n 363→\t\tcclog.Warn(\"Error while scanning rows\")\n 364→\t\treturn nil, err\n 365→\t}\n 366→\n 367→\tif jobs.Valid {\n 368→\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n 369→\n 370→\t\tif nodeHours.Valid {\n 371→\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 372→\t\t}\n 373→\t\tif coreHours.Valid {\n 374→\t\t\ttotalCoreHours = int(coreHours.Int64)\n 375→\t\t}\n 376→\t\tif accHours.Valid {\n 377→\t\t\ttotalAccHours = int(accHours.Int64)\n 378→\t\t}\n 379→\t\tstats = append(stats,\n 380→\t\t\t&model.JobsStatistics{\n 381→\t\t\t\tTotalJobs: int(jobs.Int64),\n 382→\t\t\t\tTotalUsers: int(users.Int64),\n 383→\t\t\t\tTotalWalltime: int(walltime.Int64),\n 384→\t\t\t\tTotalNodeHours: totalNodeHours,\n 385→\t\t\t\tTotalCoreHours: totalCoreHours,\n 386→\t\t\t\tTotalAccHours: totalAccHours,\n 387→\t\t\t})\n 388→\t}\n 389→\n 390→\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n 391→\treturn stats, nil\n 392→}\n 393→\n 394→// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n 395→// Returns 0.0 if the metric is not found or statType is invalid.\n 396→//\n 397→// Parameters:\n 398→// - job: Job struct with populated Statistics field\n 399→// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n 400→// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n 401→//\n 402→// Returns the requested statistic value or 0.0 if not found.\n 403→func LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n 404→\tif stats, ok := job.Statistics[metric]; ok {\n 405→\t\tswitch statType {\n 406→\t\tcase \"avg\":\n 407→\t\t\treturn stats.Avg\n 408→\t\tcase \"max\":\n 409→\t\t\treturn stats.Max\n 410→\t\tcase \"min\":\n 411→\t\t\treturn stats.Min\n 412→\t\tdefault:\n 413→\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n 414→\t\t}\n 415→\t}\n 416→\n 417→\treturn 0.0\n 418→}\n 419→\n 420→// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n 421→//\n 422→// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n 423→// avoiding the overhead of calculating walltime and resource usage metrics.\n 424→//\n 425→// Parameters:\n 426→// - ctx: Context for security checks\n 427→// - filter: Filters to apply\n 428→// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n 429→//\n 430→// Returns JobsStatistics with only ID and TotalJobs populated for each group.\n 431→func (r *JobRepository) JobCountGrouped(\n 432→\tctx context.Context,\n 433→\tfilter []*model.JobFilter,\n 434→\tgroupBy *model.Aggregate,\n 435→) ([]*model.JobsStatistics, error) {\n 436→\tstart := time.Now()\n 437→\tcol := groupBy2column[*groupBy]\n 438→\tquery := r.buildCountQuery(filter, \"\", col)\n 439→\tquery, err := SecurityCheck(ctx, query)\n 440→\tif err != nil {\n 441→\t\treturn nil, err\n 442→\t}\n 443→\trows, err := query.RunWith(r.DB).Query()\n 444→\tif err != nil {\n 445→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 446→\t\treturn nil, err\n 447→\t}\n 448→\tdefer rows.Close()\n 449→\n 450→\tstats := make([]*model.JobsStatistics, 0, 100)\n 451→\n 452→\tfor rows.Next() {\n 453→\t\tvar id sql.NullString\n 454→\t\tvar cnt sql.NullInt64\n 455→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 456→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 457→\t\t\treturn nil, err\n 458→\t\t}\n 459→\t\tif id.Valid {\n 460→\t\t\tstats = append(stats,\n 461→\t\t\t\t&model.JobsStatistics{\n 462→\t\t\t\t\tID: id.String,\n 463→\t\t\t\t\tTotalJobs: int(cnt.Int64),\n 464→\t\t\t\t})\n 465→\t\t}\n 466→\t}\n 467→\n 468→\tif err := rows.Err(); err != nil {\n 469→\t\treturn nil, err\n 470→\t}\n 471→\n 472→\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n 473→\treturn stats, nil\n 474→}\n 475→\n 476→// AddJobCountGrouped augments existing statistics with additional job counts by category.\n 477→//\n 478→// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n 479→// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n 480→//\n 481→// Parameters:\n 482→// - ctx: Context for security checks\n 483→// - filter: Filters to apply\n 484→// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n 485→// - stats: Existing statistics to augment (modified in-place by ID matching)\n 486→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 487→//\n 488→// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n 489→// Groups without matching jobs will have 0 for the added field.\n 490→func (r *JobRepository) AddJobCountGrouped(\n 491→\tctx context.Context,\n 492→\tfilter []*model.JobFilter,\n 493→\tgroupBy *model.Aggregate,\n 494→\tstats []*model.JobsStatistics,\n 495→\tkind string,\n 496→) ([]*model.JobsStatistics, error) {\n 497→\tstart := time.Now()\n 498→\tcol := groupBy2column[*groupBy]\n 499→\tquery := r.buildCountQuery(filter, kind, col)\n 500→\tquery, err := SecurityCheck(ctx, query)\n 501→\tif err != nil {\n 502→\t\treturn nil, err\n 503→\t}\n 504→\trows, err := query.RunWith(r.DB).Query()\n 505→\tif err != nil {\n 506→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 507→\t\treturn nil, err\n 508→\t}\n 509→\tdefer rows.Close()\n 510→\n 511→\tcounts := make(map[string]int)\n 512→\n 513→\tfor rows.Next() {\n 514→\t\tvar id sql.NullString\n 515→\t\tvar cnt sql.NullInt64\n 516→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 517→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 518→\t\t\treturn nil, err\n 519→\t\t}\n 520→\t\tif id.Valid {\n 521→\t\t\tcounts[id.String] = int(cnt.Int64)\n 522→\t\t}\n 523→\t}\n 524→\n 525→\tif err := rows.Err(); err != nil {\n 526→\t\treturn nil, err\n 527→\t}\n 528→\n 529→\tswitch kind {\n 530→\tcase \"running\":\n 531→\t\tfor _, s := range stats {\n 532→\t\t\ts.RunningJobs = counts[s.ID]\n 533→\t\t}\n 534→\tcase \"short\":\n 535→\t\tfor _, s := range stats {\n 536→\t\t\ts.ShortJobs = counts[s.ID]\n 537→\t\t}\n 538→\t}\n 539→\n 540→\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n 541→\treturn stats, nil\n 542→}\n 543→\n 544→// AddJobCount augments existing overall statistics with additional job counts by category.\n 545→//\n 546→// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n 547→// to all statistics entries (typically just one).\n 548→//\n 549→// Parameters:\n 550→// - ctx: Context for security checks\n 551→// - filter: Filters to apply\n 552→// - stats: Existing statistics to augment (modified in-place)\n 553→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 554→//\n 555→// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\n 556→func (r *JobRepository) AddJobCount(\n 557→\tctx context.Context,\n 558→\tfilter []*model.JobFilter,\n 559→\tstats []*model.JobsStatistics,\n 560→\tkind string,\n 561→) ([]*model.JobsStatistics, error) {\n 562→\tstart := time.Now()\n 563→\tquery := r.buildCountQuery(filter, kind, \"\")\n 564→\tquery, err := SecurityCheck(ctx, query)\n 565→\tif err != nil {\n 566→\t\treturn nil, err\n 567→\t}\n 568→\tvar cnt sql.NullInt64\n 569→\tif err := query.RunWith(r.DB).QueryRow().Scan(&cnt); err != nil {\n 570→\t\tcclog.Warn(\"Error while querying DB for job count\")\n 571→\t\treturn nil, err\n 572→\t}\n 573→\n 574→\tcount := int(cnt.Int64)\n 575→\n 576→\tswitch kind {\n 577→\tcase \"running\":\n 578→\t\tfor _, s := range stats {\n 579→\t\t\ts.RunningJobs = count\n 580→\t\t}\n 581→\tcase \"short\":\n 582→\t\tfor _, s := range stats {\n 583→\t\t\ts.ShortJobs = count\n 584→\t\t}\n 585→\t}\n 586→\n 587→\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n 588→\treturn stats, nil\n 589→}\n 590→\n 591→// AddHistograms augments statistics with distribution histograms for job properties.\n 592→//\n 593→// Generates histogram data for visualization of job duration, node count, core count,\n 594→// and accelerator count distributions. Duration histogram uses intelligent binning based\n 595→// on the requested resolution.\n 596→//\n 597→// Parameters:\n 598→// - ctx: Context for security checks\n 599→// - filter: Filters to apply to jobs included in histograms\n 600→// - stat: Statistics struct to augment (modified in-place)\n 601→// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n 602→//\n 603→// Populates these fields in stat:\n 604→// - HistDuration: Job duration distribution (zero-padded bins)\n 605→// - HistNumNodes: Node count distribution\n 606→// - HistNumCores: Core (hwthread) count distribution\n 607→// - HistNumAccs: Accelerator count distribution\n 608→//\n 609→// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n 610→// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\n 611→func (r *JobRepository) AddHistograms(\n 612→\tctx context.Context,\n 613→\tfilter []*model.JobFilter,\n 614→\tstat *model.JobsStatistics,\n 615→\tdurationBins *string,\n 616→) (*model.JobsStatistics, error) {\n 617→\tstart := time.Now()\n 618→\n 619→\tvar targetBinCount int\n 620→\tvar targetBinSize int\n 621→\tswitch *durationBins {\n 622→\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n 623→\t\ttargetBinCount = 60\n 624→\t\ttargetBinSize = 60\n 625→\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n 626→\t\ttargetBinCount = 72\n 627→\t\ttargetBinSize = 600\n 628→\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n 629→\t\ttargetBinCount = 48\n 630→\t\ttargetBinSize = 3600\n 631→\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n 632→\t\ttargetBinCount = 12\n 633→\t\ttargetBinSize = 21600\n 634→\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n 635→\t\ttargetBinCount = 14\n 636→\t\ttargetBinSize = 43200\n 637→\tdefault: // 24h\n 638→\t\ttargetBinCount = 24\n 639→\t\ttargetBinSize = 3600\n 640→\t}\n 641→\n 642→\tvar err error\n 643→\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n 644→\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 645→\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n 646→\tif err != nil {\n 647→\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n 648→\t\treturn nil, err\n 649→\t}\n 650→\n 651→\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n 652→\tif err != nil {\n 653→\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n 654→\t\treturn nil, err\n 655→\t}\n 656→\n 657→\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n 658→\tif err != nil {\n 659→\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n 660→\t\treturn nil, err\n 661→\t}\n 662→\n 663→\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n 664→\tif err != nil {\n 665→\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n 666→\t\treturn nil, err\n 667→\t}\n 668→\n 669→\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n 670→\treturn stat, nil\n 671→}\n 672→\n 673→// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n 674→//\n 675→// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n 676→// and completed jobs differently: running jobs load data from metric backend, completed jobs\n 677→// use footprint data from database.\n 678→//\n 679→// Parameters:\n 680→// - ctx: Context for security checks\n 681→// - filter: Filters to apply (MUST contain State filter for running jobs)\n 682→// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n 683→// - stat: Statistics struct to augment (modified in-place)\n 684→// - targetBinCount: Number of histogram bins (default: 10)\n 685→//\n 686→// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n 687→//\n 688→// Binning algorithm:\n 689→// - Values normalized to metric's peak value from cluster configuration\n 690→// - Bins evenly distributed from 0 to peak\n 691→// - Pre-initialized with zeros for consistent visualization\n 692→//\n 693→// Limitations:\n 694→// - Running jobs: Limited to 5000 jobs for performance\n 695→// - Requires valid cluster configuration with metric peak values\n 696→// - Uses footprint statistic (avg/max/min) configured per metric\n 697→func (r *JobRepository) AddMetricHistograms(\n 698→\tctx context.Context,\n 699→\tfilter []*model.JobFilter,\n 700→\tmetrics []string,\n 701→\tstat *model.JobsStatistics,\n 702→\ttargetBinCount *int,\n 703→) (*model.JobsStatistics, error) {\n 704→\tstart := time.Now()\n 705→\n 706→\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n 707→\tfor _, f := range filter {\n 708→\t\tif f.State != nil {\n 709→\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n 710→\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n 711→\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 712→\t\t\t\treturn stat, nil\n 713→\t\t\t}\n 714→\t\t}\n 715→\t}\n 716→\n 717→\t// All other cases: Query and make bins in sqlite directly\n 718→\tfor _, m := range metrics {\n 719→\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n 720→\t\tif err != nil {\n 721→\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n 722→\t\t\tcontinue\n 723→\t\t}\n 724→\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n 725→\t}\n 726→\n 727→\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 728→\treturn stat, nil\n 729→}\n 730→\n 731→// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n 732→//\n 733→// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n 734→// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n 735→//\n 736→// Parameters:\n 737→// - value: SQL expression that produces the histogram value, aliased as \"value\"\n 738→// - filters: Job filters to apply\n 739→//\n 740→// Returns histogram points with Value (from column) and Count (number of jobs).\n 741→func (r *JobRepository) jobsStatisticsHistogram(\n 742→\tctx context.Context,\n 743→\tvalue string,\n 744→\tfilters []*model.JobFilter,\n 745→) ([]*model.HistoPoint, error) {\n 746→\tstart := time.Now()\n 747→\tquery, qerr := SecurityCheck(ctx,\n 748→\t\tsq.Select(value, \"COUNT(job.id) AS count\").From(\"job\"))\n 749→\n 750→\tif qerr != nil {\n 751→\t\treturn nil, qerr\n 752→\t}\n 753→\n 754→\tfor _, f := range filters {\n 755→\t\tquery = BuildWhereClause(f, query)\n 756→\t}\n 757→\n 758→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).Query()\n 759→\tif err != nil {\n 760→\t\tcclog.Error(\"Error while running query\")\n 761→\t\treturn nil, err\n 762→\t}\n 763→\tdefer rows.Close()\n 764→\n 765→\tpoints := make([]*model.HistoPoint, 0)\n 766→\t// is it possible to introduce zero values here? requires info about bincount\n 767→\tfor rows.Next() {\n 768→\t\tpoint := model.HistoPoint{}\n 769→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 770→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 771→\t\t\treturn nil, err\n 772→\t\t}\n 773→\n 774→\t\tpoints = append(points, &point)\n 775→\t}\n 776→\n 777→\tif err := rows.Err(); err != nil {\n 778→\t\treturn nil, err\n 779→\t}\n 780→\n 781→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 782→\treturn points, nil\n 783→}\n 784→\n 785→// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n 786→//\n 787→// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n 788→// histograms which only return bins with data. The value parameter should compute\n 789→// the bin number from job duration.\n 790→//\n 791→// Parameters:\n 792→// - value: SQL expression computing bin number from duration, aliased as \"value\"\n 793→// - filters: Job filters to apply\n 794→// - binSizeSeconds: Width of each bin in seconds\n 795→// - targetBinCount: Number of bins to pre-initialize\n 796→//\n 797→// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n 798→// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n 799→//\n 800→// Algorithm:\n 801→// 1. Pre-initialize targetBinCount bins with zero counts\n 802→// 2. Query database for actual counts per bin\n 803→// 3. Match query results to pre-initialized bins by value\n 804→// 4. Bins without matches remain at zero\n 805→func (r *JobRepository) jobsDurationStatisticsHistogram(\n 806→\tctx context.Context,\n 807→\tvalue string,\n 808→\tfilters []*model.JobFilter,\n 809→\tbinSizeSeconds int,\n 810→\ttargetBinCount *int,\n 811→) ([]*model.HistoPoint, error) {\n 812→\tstart := time.Now()\n 813→\tquery, qerr := SecurityCheck(ctx,\n 814→\t\tsq.Select(value, \"COUNT(job.id) AS count\").From(\"job\"))\n 815→\n 816→\tif qerr != nil {\n 817→\t\treturn nil, qerr\n 818→\t}\n 819→\n 820→\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n 821→\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n 822→\tpoints := make([]*model.HistoPoint, 0)\n 823→\tfor i := 1; i <= *targetBinCount; i++ {\n 824→\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n 825→\t\tpoints = append(points, &point)\n 826→\t}\n 827→\n 828→\tfor _, f := range filters {\n 829→\t\tquery = BuildWhereClause(f, query)\n 830→\t}\n 831→\n 832→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).Query()\n 833→\tif err != nil {\n 834→\t\tcclog.Error(\"Error while running query\")\n 835→\t\treturn nil, err\n 836→\t}\n 837→\tdefer rows.Close()\n 838→\n 839→\t// Match query results to pre-initialized bins.\n 840→\t// point.Value from query is the bin number; multiply by binSizeSeconds to match bin.Value.\n 841→\tfor rows.Next() {\n 842→\t\tpoint := model.HistoPoint{}\n 843→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 844→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 845→\t\t\treturn nil, err\n 846→\t\t}\n 847→\n 848→\t\tfor _, e := range points {\n 849→\t\t\tif e.Value == (point.Value * binSizeSeconds) {\n 850→\t\t\t\te.Count = point.Count\n 851→\t\t\t\tbreak\n 852→\t\t\t}\n 853→\t\t}\n 854→\t}\n 855→\n 856→\tif err := rows.Err(); err != nil {\n 857→\t\treturn nil, err\n 858→\t}\n 859→\n 860→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 861→\treturn points, nil\n 862→}\n 863→\n 864→// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n 865→//\n 866→// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n 867→// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n 868→// and computing bin assignments in SQL.\n 869→//\n 870→// Parameters:\n 871→// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n 872→// - filters: Job filters to apply\n 873→// - bins: Number of bins to generate\n 874→//\n 875→// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n 876→//\n 877→// Algorithm:\n 878→// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n 879→// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n 880→// 3. Pre-initialize bins with min/max ranges based on peak value\n 881→// 4. Query database for counts per bin\n 882→// 5. Match results to pre-initialized bins\n 883→//\n 884→// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n 885→// peak by 0.999999999 to avoid creating an extra bin.\n 886→func (r *JobRepository) jobsMetricStatisticsHistogram(\n 887→\tctx context.Context,\n 888→\tmetric string,\n 889→\tfilters []*model.JobFilter,\n 890→\tbins *int,\n 891→) (*model.MetricHistoPoints, error) {\n 892→\t// Peak value defines the upper bound for binning: values are distributed across\n 893→\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n 894→\t// scan all clusters to find the maximum peak value.\n 895→\tvar metricConfig *schema.MetricConfig\n 896→\tvar peak float64\n 897→\tvar unit string\n 898→\tvar footprintStat string\n 899→\n 900→\t// Try to get metric config from filtered cluster\n 901→\tfor _, f := range filters {\n 902→\t\tif f.Cluster != nil {\n 903→\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 904→\t\t\tpeak = metricConfig.Peak\n 905→\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 906→\t\t\tfootprintStat = metricConfig.Footprint\n 907→\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n 908→\t\t}\n 909→\t}\n 910→\n 911→\t// If no cluster filter or peak not found, find largest peak across all clusters\n 912→\t// This ensures histogram can accommodate all possible values\n 913→\tif peak == 0.0 {\n 914→\t\tfor _, c := range archive.Clusters {\n 915→\t\t\tfor _, m := range c.MetricConfig {\n 916→\t\t\t\tif m.Name == metric {\n 917→\t\t\t\t\tif m.Peak > peak {\n 918→\t\t\t\t\t\tpeak = m.Peak\n 919→\t\t\t\t\t}\n 920→\t\t\t\t\tif unit == \"\" {\n 921→\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 922→\t\t\t\t\t}\n 923→\t\t\t\t\tif footprintStat == \"\" {\n 924→\t\t\t\t\t\tfootprintStat = m.Footprint\n 925→\t\t\t\t\t}\n 926→\t\t\t\t}\n 927→\t\t\t}\n 928→\t\t}\n 929→\t}\n 930→\n 931→\t// Construct SQL histogram bins using normalized values.\n 932→\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n 933→\tstart := time.Now()\n 934→\n 935→\t// Bin calculation formula:\n 936→\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n 937→\t// Special case: value == peak would create bin N+1, so we test for equality\n 938→\t// and multiply peak by 0.999999999 to force it into bin N.\n 939→\tbinQuery := fmt.Sprintf(`CAST(\n 940→\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n 941→\t\t* %v as INTEGER )`,\n 942→\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n 943→\n 944→\tmainQuery := sq.Select(\n 945→\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n 946→\t\t`count(*) as count`,\n 947→\t).From(\"job\").Where(\n 948→\t\t\"JSON_VALID(footprint)\",\n 949→\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n 950→\n 951→\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n 952→\tif qerr != nil {\n 953→\t\treturn nil, qerr\n 954→\t}\n 955→\n 956→\tfor _, f := range filters {\n 957→\t\tmainQuery = BuildWhereClause(f, mainQuery)\n 958→\t}\n 959→\n 960→\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n 961→\n 962→\trows, err := mainQuery.RunWith(r.DB).Query()\n 963→\tif err != nil {\n 964→\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n 965→\t\treturn nil, err\n 966→\t}\n 967→\tdefer rows.Close()\n 968→\n 969→\t// Pre-initialize bins with calculated min/max ranges.\n 970→\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n 971→\tpoints := make([]*model.MetricHistoPoint, 0)\n 972→\tbinStep := int(peak) / *bins\n 973→\tfor i := 1; i <= *bins; i++ {\n 974→\t\tbinMin := (binStep * (i - 1))\n 975→\t\tbinMax := (binStep * i)\n 976→\t\tepoint := model.MetricHistoPoint{Bin: &i, Count: 0, Min: &binMin, Max: &binMax}\n 977→\t\tpoints = append(points, &epoint)\n 978→\t}\n 979→\n 980→\t// Match query results to pre-initialized bins.\n 981→\tfor rows.Next() {\n 982→\t\trpoint := model.MetricHistoPoint{}\n 983→\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n 984→\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n 985→\t\t\treturn nil, err\n 986→\t\t}\n 987→\n 988→\t\tfor _, e := range points {\n 989→\t\t\tif e.Bin != nil && rpoint.Bin != nil && *e.Bin == *rpoint.Bin {\n 990→\t\t\t\te.Count = rpoint.Count\n 991→\t\t\t\tbreak\n 992→\t\t\t}\n 993→\t\t}\n 994→\t}\n 995→\n 996→\tif err := rows.Err(); err != nil {\n 997→\t\treturn nil, err\n 998→\t}\n 999→\n 1000→\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n 1001→\n 1002→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 1003→\treturn &result, nil\n 1004→}\n 1005→\n 1006→// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n 1007→//\n 1008→// Unlike completed jobs which use footprint data from the database, running jobs require\n 1009→// fetching current metric averages from the metric backend (via metricdispatch).\n 1010→//\n 1011→// Parameters:\n 1012→// - metrics: List of metric names\n 1013→// - filters: Job filters (should filter to running jobs only)\n 1014→// - bins: Number of histogram bins\n 1015→//\n 1016→// Returns slice of MetricHistoPoints, one per metric.\n 1017→//\n 1018→// Limitations:\n 1019→// - Maximum 5000 jobs (returns nil if more jobs match)\n 1020→// - Requires metric backend availability\n 1021→// - Bins based on metric peak values from cluster configuration\n 1022→//\n 1023→// Algorithm:\n 1024→// 1. Query first 5001 jobs to check count limit\n 1025→// 2. Load metric averages for all jobs via metricdispatch\n 1026→// 3. For each metric, create bins based on peak value\n 1027→// 4. Iterate averages and count jobs per bin\n 1028→func (r *JobRepository) runningJobsMetricStatisticsHistogram(\n 1029→\tctx context.Context,\n 1030→\tmetrics []string,\n 1031→\tfilters []*model.JobFilter,\n 1032→\tbins *int,\n 1033→) []*model.MetricHistoPoints {\n 1034→\t// Get Jobs\n 1035→\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n 1036→\tif err != nil {\n 1037→\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n 1038→\t\treturn nil\n 1039→\t}\n 1040→\tif len(jobs) > 5000 {\n 1041→\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n 1042→\t\treturn nil\n 1043→\t}\n 1044→\n 1045→\t// Get AVGs from metric repo\n 1046→\tavgs := make([][]schema.Float, len(metrics))\n 1047→\tfor i := range avgs {\n 1048→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n 1049→\t}\n 1050→\n 1051→\tfor _, job := range jobs {\n 1052→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 1053→\t\t\tcontinue\n 1054→\t\t}\n 1055→\n 1056→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n 1057→\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n 1058→\t\t\treturn nil\n 1059→\t\t}\n 1060→\t}\n 1061→\n 1062→\t// Iterate metrics to fill endresult\n 1063→\tdata := make([]*model.MetricHistoPoints, 0)\n 1064→\tfor idx, metric := range metrics {\n 1065→\t\t// Get specific Peak or largest Peak\n 1066→\t\tvar metricConfig *schema.MetricConfig\n 1067→\t\tvar peak float64\n 1068→\t\tvar unit string\n 1069→\n 1070→\t\tfor _, f := range filters {\n 1071→\t\t\tif f.Cluster != nil {\n 1072→\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 1073→\t\t\t\tpeak = metricConfig.Peak\n 1074→\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 1075→\t\t\t}\n 1076→\t\t}\n 1077→\n 1078→\t\tif peak == 0.0 {\n 1079→\t\t\tfor _, c := range archive.Clusters {\n 1080→\t\t\t\tfor _, m := range c.MetricConfig {\n 1081→\t\t\t\t\tif m.Name == metric {\n 1082→\t\t\t\t\t\tif m.Peak > peak {\n 1083→\t\t\t\t\t\t\tpeak = m.Peak\n 1084→\t\t\t\t\t\t}\n 1085→\t\t\t\t\t\tif unit == \"\" {\n 1086→\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 1087→\t\t\t\t\t\t}\n 1088→\t\t\t\t\t}\n 1089→\t\t\t\t}\n 1090→\t\t\t}\n 1091→\t\t}\n 1092→\n 1093→\t\t// Make and fill bins\n 1094→\t\tpeakBin := int(peak) / *bins\n 1095→\n 1096→\t\tpoints := make([]*model.MetricHistoPoint, 0)\n 1097→\t\tfor b := 0; b < *bins; b++ {\n 1098→\t\t\tcount := 0\n 1099→\t\t\tbindex := b + 1\n 1100→\t\t\tbmin := peakBin * b\n 1101→\t\t\tbmax := peakBin * (b + 1)\n 1102→\n 1103→\t\t\t// Iterate AVG values for indexed metric and count for bins\n 1104→\t\t\tfor _, val := range avgs[idx] {\n 1105→\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n 1106→\t\t\t\t\tcount += 1\n 1107→\t\t\t\t}\n 1108→\t\t\t}\n 1109→\n 1110→\t\t\t// Append Bin to Metric Result Array\n 1111→\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n 1112→\t\t\tpoints = append(points, &point)\n 1113→\t\t}\n 1114→\n 1115→\t\t// Append Metric Result Array to final results array\n 1116→\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n 1117→\t\tdata = append(data, &result)\n 1118→\t}\n 1119→\n 1120→\treturn data\n 1121→}\n 1122→"}]},"uuid":"f54b735f-c574-48f6-a372-cb01815207b5","timestamp":"2026-03-11T04:31:57.923Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"d7520b10-bab3-4697-bbb5-124e896b9bcc","timestamp":"2026-03-11T04:31:57.926Z"}
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NULL DEFAULT 'global';\n 15→\n 16→-- Do not use reserved keywords anymore\n 17→ALTER TABLE \"user\" RENAME TO hpc_user;\n 18→ALTER TABLE job RENAME COLUMN \"user\" TO hpc_user;\n 19→ALTER TABLE job RENAME COLUMN \"partition\" TO cluster_partition;\n 20→\n 21→UPDATE job SET footprint = '{\"flops_any_avg\": 0.0}';\n 22→UPDATE job SET footprint = json_replace(footprint, '$.flops_any_avg', job.flops_any_avg);\n 23→UPDATE job SET footprint = json_insert(footprint, '$.mem_bw_avg', job.mem_bw_avg);\n 24→UPDATE job SET footprint = json_insert(footprint, '$.mem_used_max', job.mem_used_max);\n 25→UPDATE job SET footprint = json_insert(footprint, '$.cpu_load_avg', job.load_avg);\n 26→UPDATE job SET footprint = json_insert(footprint, '$.net_bw_avg', job.net_bw_avg) WHERE job.net_bw_avg != 0;\n 27→UPDATE job SET footprint = json_insert(footprint, '$.net_data_vol_total', job.net_data_vol_total) WHERE job.net_data_vol_total != 0;\n 28→UPDATE job SET footprint = json_insert(footprint, '$.file_bw_avg', job.file_bw_avg) WHERE job.file_bw_avg != 0;\n 29→UPDATE job SET footprint = json_insert(footprint, '$.file_data_vol_total', job.file_data_vol_total) WHERE job.file_data_vol_total != 0;\n 30→\n 31→ALTER TABLE job DROP flops_any_avg;\n 32→ALTER TABLE job DROP mem_bw_avg;\n 33→ALTER TABLE job DROP mem_used_max;\n 34→ALTER TABLE job DROP load_avg;\n 35→ALTER TABLE job DROP net_bw_avg;\n 36→ALTER TABLE job DROP net_data_vol_total;\n 37→ALTER TABLE job DROP file_bw_avg;\n 38→ALTER TABLE job DROP file_data_vol_total;\n 39→\n 40→-- Indices for: Single filters, combined filters, sorting, sorting with filters\n 41→-- Cluster Filter\n 42→CREATE INDEX IF NOT EXISTS jobs_cluster ON job (cluster);\n 43→CREATE INDEX IF NOT EXISTS jobs_cluster_user ON job (cluster, hpc_user);\n 44→CREATE INDEX IF NOT EXISTS jobs_cluster_project ON job (cluster, project);\n 45→CREATE INDEX IF NOT EXISTS jobs_cluster_subcluster ON job (cluster, subcluster);\n 46→-- Cluster Filter Sorting\n 47→CREATE INDEX IF NOT EXISTS jobs_cluster_starttime ON job (cluster, start_time);\n 48→CREATE INDEX IF NOT EXISTS jobs_cluster_duration ON job (cluster, duration);\n 49→CREATE INDEX IF NOT EXISTS jobs_cluster_numnodes ON job (cluster, num_nodes);\n 50→CREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads ON job (cluster, num_hwthreads);\n 51→CREATE INDEX IF NOT EXISTS jobs_cluster_numacc ON job (cluster, num_acc);\n 52→CREATE INDEX IF NOT EXISTS jobs_cluster_energy ON job (cluster, energy);\n 53→\n 54→-- Cluster+Partition Filter\n 55→CREATE INDEX IF NOT EXISTS jobs_cluster_partition ON job (cluster, cluster_partition);\n 56→-- Cluster+Partition Filter Sorting\n 57→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime ON job (cluster, cluster_partition, start_time);\n 58→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_duration ON job (cluster, cluster_partition, duration);\n 59→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numnodes ON job (cluster, cluster_partition, num_nodes);\n 60→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numhwthreads ON job (cluster, cluster_partition, num_hwthreads);\n 61→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numacc ON job (cluster, cluster_partition, num_acc);\n 62→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_energy ON job (cluster, cluster_partition, energy);\n 63→\n 64→-- Cluster+Partition+Jobstate Filter\n 65→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate ON job (cluster, cluster_partition, job_state);\n 66→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_user ON job (cluster, cluster_partition, job_state, hpc_user);\n 67→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_project ON job (cluster, cluster_partition, job_state, project);\n 68→-- Cluster+Partition+Jobstate Filter Sorting\n 69→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_starttime ON job (cluster, cluster_partition, job_state, start_time);\n 70→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_duration ON job (cluster, cluster_partition, job_state, duration);\n 71→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_numnodes ON job (cluster, cluster_partition, job_state, num_nodes);\n 72→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_numhwthreads ON job (cluster, cluster_partition, job_state, num_hwthreads);\n 73→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_numacc ON job (cluster, cluster_partition, job_state, num_acc);\n 74→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate_energy ON job (cluster, cluster_partition, job_state, energy);\n 75→\n 76→-- Cluster+JobState Filter\n 77→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate ON job (cluster, job_state);\n 78→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user ON job (cluster, job_state, hpc_user);\n 79→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project ON job (cluster, job_state, project);\n 80→-- Cluster+JobState Filter Sorting\n 81→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime ON job (cluster, job_state, start_time);\n 82→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration ON job (cluster, job_state, duration);\n 83→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes ON job (cluster, job_state, num_nodes);\n 84→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numhwthreads ON job (cluster, job_state, num_hwthreads);\n 85→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numacc ON job (cluster, job_state, num_acc);\n 86→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_energy ON job (cluster, job_state, energy);\n 87→\n 88→-- User Filter\n 89→CREATE INDEX IF NOT EXISTS jobs_user ON job (hpc_user);\n 90→-- User Filter Sorting\n 91→CREATE INDEX IF NOT EXISTS jobs_user_starttime ON job (hpc_user, start_time);\n 92→CREATE INDEX IF NOT EXISTS jobs_user_duration ON job (hpc_user, duration);\n 93→CREATE INDEX IF NOT EXISTS jobs_user_numnodes ON job (hpc_user, num_nodes);\n 94→CREATE INDEX IF NOT EXISTS jobs_user_numhwthreads ON job (hpc_user, num_hwthreads);\n 95→CREATE INDEX IF NOT EXISTS jobs_user_numacc ON job (hpc_user, num_acc);\n 96→CREATE INDEX IF NOT EXISTS jobs_user_energy ON job (hpc_user, energy);\n 97→\n 98→-- Project Filter\n 99→CREATE INDEX IF NOT EXISTS jobs_project ON job (project);\n 100→CREATE INDEX IF NOT EXISTS jobs_project_user ON job (project, hpc_user);\n 101→-- Project Filter Sorting\n 102→CREATE INDEX IF NOT EXISTS jobs_project_starttime ON job (project, start_time);\n 103→CREATE INDEX IF NOT EXISTS jobs_project_duration ON job (project, duration);\n 104→CREATE INDEX IF NOT EXISTS jobs_project_numnodes ON job (project, num_nodes);\n 105→CREATE INDEX IF NOT EXISTS jobs_project_numhwthreads ON job (project, num_hwthreads);\n 106→CREATE INDEX IF NOT EXISTS jobs_project_numacc ON job (project, num_acc);\n 107→CREATE INDEX IF NOT EXISTS jobs_project_energy ON job (project, energy);\n 108→\n 109→-- JobState Filter\n 110→CREATE INDEX IF NOT EXISTS jobs_jobstate ON job (job_state);\n 111→CREATE INDEX IF NOT EXISTS jobs_jobstate_user ON job (job_state, hpc_user);\n 112→CREATE INDEX IF NOT EXISTS jobs_jobstate_project ON job (job_state, project);\n 113→CREATE INDEX IF NOT EXISTS jobs_jobstate_cluster ON job (job_state, cluster);\n 114→-- JobState Filter Sorting\n 115→CREATE INDEX IF NOT EXISTS jobs_jobstate_starttime ON job (job_state, start_time);\n 116→CREATE INDEX IF NOT EXISTS jobs_jobstate_duration ON job (job_state, duration);\n 117→CREATE INDEX IF NOT EXISTS jobs_jobstate_numnodes ON job (job_state, num_nodes);\n 118→CREATE INDEX IF NOT EXISTS jobs_jobstate_numhwthreads ON job (job_state, num_hwthreads);\n 119→CREATE INDEX IF NOT EXISTS jobs_jobstate_numacc ON job (job_state, num_acc);\n 120→CREATE INDEX IF NOT EXISTS jobs_jobstate_energy ON job (job_state, energy);\n 121→\n 122→-- ArrayJob Filter\n 123→CREATE INDEX IF NOT EXISTS jobs_arrayjobid_starttime ON job (array_job_id, start_time);\n 124→CREATE INDEX IF NOT EXISTS jobs_cluster_arrayjobid_starttime ON job (cluster, array_job_id, start_time);\n 125→\n 126→-- Sorting without active filters\n 127→CREATE INDEX IF NOT EXISTS jobs_starttime ON job (start_time);\n 128→CREATE INDEX IF NOT EXISTS jobs_duration ON job (duration);\n 129→CREATE INDEX IF NOT EXISTS jobs_numnodes ON job (num_nodes);\n 130→CREATE INDEX IF NOT EXISTS jobs_numhwthreads ON job (num_hwthreads);\n 131→CREATE INDEX IF NOT EXISTS jobs_numacc ON job (num_acc);\n 132→CREATE INDEX IF NOT EXISTS jobs_energy ON job (energy);\n 133→\n 134→-- Single filters with default starttime sorting\n 135→CREATE INDEX IF NOT EXISTS jobs_duration_starttime ON job (duration, start_time);\n 136→CREATE INDEX IF NOT EXISTS jobs_numnodes_starttime ON job (num_nodes, start_time);\n 137→CREATE INDEX IF NOT EXISTS jobs_numhwthreads_starttime ON job (num_hwthreads, start_time);\n 138→CREATE INDEX IF NOT EXISTS jobs_numacc_starttime ON job (num_acc, start_time);\n 139→CREATE INDEX IF NOT EXISTS jobs_energy_starttime ON job (energy, start_time);\n 140→\n 141→-- Optimize DB index 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+{"parentUuid":"11a56c46-d9ea-4318-bd19-d5c601c7fce8","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VpoQLN5wwMMemKJNyFn51i","type":"tool_result","content":" 1→CREATE TABLE \"job_cache\" (\n 2→ id INTEGER PRIMARY KEY,\n 3→ job_id BIGINT NOT NULL,\n 4→ cluster VARCHAR(255) NOT NULL,\n 5→ subcluster VARCHAR(255) NOT NULL,\n 6→ submit_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 7→ start_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 8→ hpc_user VARCHAR(255) NOT NULL,\n 9→ project VARCHAR(255) NOT NULL,\n 10→ cluster_partition VARCHAR(255),\n 11→ array_job_id BIGINT,\n 12→ duration INT NOT NULL,\n 13→ walltime INT NOT NULL,\n 14→ job_state VARCHAR(255) NOT NULL\n 15→ CHECK (job_state IN (\n 16→ 'boot_fail', 'cancelled', 'completed', 'deadline',\n 17→ 'failed', 'node_fail', 'out_of_memory', 'pending',\n 18→ 'preempted', 'running', 'suspended', 'timeout'\n 19→ )),\n 20→ meta_data TEXT, -- JSON\n 21→ resources TEXT NOT NULL, -- JSON\n 22→ num_nodes INT NOT NULL,\n 23→ num_hwthreads INT,\n 24→ num_acc INT,\n 25→ smt TINYINT NOT NULL DEFAULT 1 CHECK (smt IN (0, 1)),\n 26→ shared TEXT NOT NULL\n 27→ CHECK (shared IN (\"none\", \"single_user\", \"multi_user\")),\n 28→ monitoring_status TINYINT NOT NULL DEFAULT 1\n 29→ CHECK (monitoring_status IN (0, 1, 2, 3)),\n 30→ energy REAL NOT NULL DEFAULT 0.0,\n 31→ energy_footprint TEXT DEFAULT NULL,\n 32→ footprint TEXT DEFAULT NULL,\n 33→ UNIQUE (job_id, cluster, start_time)\n 34→);\n 35→\n 36→CREATE TABLE \"job_new\" (\n 37→ id INTEGER PRIMARY KEY,\n 38→ job_id BIGINT NOT NULL,\n 39→ cluster TEXT NOT NULL,\n 40→ subcluster TEXT NOT NULL,\n 41→ submit_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 42→ start_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 43→ hpc_user TEXT NOT NULL,\n 44→ project TEXT NOT NULL,\n 45→ cluster_partition TEXT,\n 46→ array_job_id BIGINT,\n 47→ duration INT NOT NULL,\n 48→ walltime INT NOT NULL,\n 49→ job_state TEXT NOT NULL\n 50→ CHECK (job_state IN (\n 51→ 'boot_fail', 'cancelled', 'completed', 'deadline',\n 52→ 'failed', 'node_fail', 'out_of_memory', 'pending',\n 53→ 'preempted', 'running', 'suspended', 'timeout'\n 54→ )),\n 55→ meta_data TEXT, -- JSON\n 56→ resources TEXT NOT NULL, -- JSON\n 57→ num_nodes INT NOT NULL,\n 58→ num_hwthreads INT,\n 59→ num_acc INT,\n 60→ smt INT NOT NULL DEFAULT 1,\n 61→ shared TEXT NOT NULL\n 62→ CHECK (shared IN (\"none\", \"single_user\", \"multi_user\")),\n 63→ monitoring_status TINYINT NOT NULL DEFAULT 1\n 64→ CHECK (monitoring_status IN (0, 1, 2, 3)),\n 65→ energy REAL NOT NULL DEFAULT 0.0,\n 66→ energy_footprint TEXT DEFAULT NULL,\n 67→ footprint TEXT DEFAULT NULL,\n 68→ UNIQUE (job_id, cluster, start_time)\n 69→);\n 70→\n 71→\n 72→CREATE TABLE IF NOT EXISTS lookup_exclusive (\n 73→ id INTEGER PRIMARY KEY,\n 74→ name TEXT NOT NULL UNIQUE\n 75→);\n 76→\n 77→INSERT INTO lookup_exclusive (id, name) VALUES\n 78→(0, 'multi_user'),\n 79→(1, 'none'),\n 80→(2, 'single_user');\n 81→\n 82→INSERT INTO job_new (\n 83→ id, job_id, cluster, subcluster, submit_time, start_time, hpc_user, project,\n 84→ cluster_partition, array_job_id, duration, walltime, job_state, meta_data, resources,\n 85→ num_nodes, num_hwthreads, num_acc, smt, shared, monitoring_status, energy,\n 86→ energy_footprint, footprint\n 87→) SELECT\n 88→ id,\n 89→ job_id,\n 90→ cluster,\n 91→ subcluster,\n 92→ 0,\n 93→ start_time,\n 94→ hpc_user,\n 95→ project,\n 96→ cluster_partition,\n 97→ array_job_id,\n 98→ duration,\n 99→ walltime,\n 100→ job_state,\n 101→ meta_data,\n 102→ resources,\n 103→ num_nodes,\n 104→ num_hwthreads,\n 105→ num_acc,\n 106→ smt,\n 107→ (\n 108→ SELECT name FROM lookup_exclusive\n 109→ WHERE id = job.exclusive\n 110→ ),\n 111→ monitoring_status,\n 112→ energy,\n 113→ energy_footprint,\n 114→ footprint\n 115→FROM job;\n 116→\n 117→DROP TABLE lookup_exclusive;\n 118→DROP TABLE job; -- Deletes All Existing 'job' Indices; Recreate after Renaming\n 119→ALTER TABLE job_new RENAME TO job;\n 120→\n 121→-- Recreate Indices from 08_add-footprint; include new 'shared' column\n 122→-- Cluster Filter\n 123→CREATE INDEX IF NOT EXISTS jobs_cluster_user ON job (cluster, hpc_user);\n 124→CREATE INDEX IF NOT EXISTS jobs_cluster_project ON job (cluster, project);\n 125→CREATE INDEX IF NOT EXISTS jobs_cluster_subcluster ON job (cluster, subcluster);\n 126→-- Cluster Filter Sorting\n 127→CREATE INDEX IF NOT EXISTS jobs_cluster_numnodes ON job (cluster, num_nodes);\n 128→CREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads ON job (cluster, num_hwthreads);\n 129→CREATE INDEX IF NOT EXISTS jobs_cluster_numacc ON job (cluster, num_acc);\n 130→CREATE INDEX IF NOT EXISTS jobs_cluster_energy ON job (cluster, energy);\n 131→\n 132→-- Cluster Time Filter Sorting\n 133→CREATE INDEX IF NOT EXISTS jobs_cluster_duration_starttime ON job (cluster, duration, start_time);\n 134→CREATE INDEX IF NOT EXISTS jobs_cluster_starttime_duration ON job (cluster, start_time, duration);\n 135→\n 136→-- Cluster+Partition Filter\n 137→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_user ON job (cluster, cluster_partition, hpc_user);\n 138→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_project ON job (cluster, cluster_partition, project);\n 139→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate ON job (cluster, cluster_partition, job_state);\n 140→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_shared ON job (cluster, cluster_partition, shared);\n 141→\n 142→-- Cluster+Partition Filter Sorting\n 143→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numnodes ON job (cluster, cluster_partition, num_nodes);\n 144→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numhwthreads ON job (cluster, cluster_partition, num_hwthreads);\n 145→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numacc ON job (cluster, cluster_partition, num_acc);\n 146→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_energy ON job (cluster, cluster_partition, energy);\n 147→\n 148→-- Cluster+Partition Time Filter Sorting\n 149→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_duration_starttime ON job (cluster, cluster_partition, duration, start_time);\n 150→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime_duration ON job (cluster, cluster_partition, start_time, duration);\n 151→\n 152→-- Cluster+JobState Filter\n 153→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user ON job (cluster, job_state, hpc_user);\n 154→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project ON job (cluster, job_state, project);\n 155→-- Cluster+JobState Filter Sorting\n 156→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes ON job (cluster, job_state, num_nodes);\n 157→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numhwthreads ON job (cluster, job_state, num_hwthreads);\n 158→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numacc ON job (cluster, job_state, num_acc);\n 159→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_energy ON job (cluster, job_state, energy);\n 160→\n 161→-- Cluster+JobState Time Filter Sorting\n 162→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime_duration ON job (cluster, job_state, start_time, duration);\n 163→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration_starttime ON job (cluster, job_state, duration, start_time);\n 164→\n 165→-- Cluster+Shared Filter\n 166→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_user ON job (cluster, shared, hpc_user);\n 167→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_project ON job (cluster, shared, project);\n 168→-- Cluster+Shared Filter Sorting\n 169→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numnodes ON job (cluster, shared, num_nodes);\n 170→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numhwthreads ON job (cluster, shared, num_hwthreads);\n 171→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numacc ON job (cluster, shared, num_acc);\n 172→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_energy ON job (cluster, shared, energy);\n 173→\n 174→-- Cluster+Shared Time Filter Sorting\n 175→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_starttime_duration ON job (cluster, shared, start_time, duration);\n 176→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_duration_starttime ON job (cluster, shared, duration, start_time);\n 177→\n 178→-- User Filter\n 179→-- User Filter Sorting\n 180→CREATE INDEX IF NOT EXISTS jobs_user_numnodes ON job (hpc_user, num_nodes);\n 181→CREATE INDEX IF NOT EXISTS jobs_user_numhwthreads ON job (hpc_user, num_hwthreads);\n 182→CREATE INDEX IF NOT EXISTS jobs_user_numacc ON job (hpc_user, num_acc);\n 183→CREATE INDEX IF NOT EXISTS jobs_user_energy ON job (hpc_user, energy);\n 184→\n 185→-- Cluster+Shared Time Filter Sorting\n 186→CREATE INDEX IF NOT EXISTS jobs_user_starttime_duration ON job (hpc_user, start_time, duration);\n 187→CREATE INDEX IF NOT EXISTS jobs_user_duration_starttime ON job (hpc_user, duration, start_time);\n 188→\n 189→-- Project Filter\n 190→CREATE INDEX IF NOT EXISTS jobs_project_user ON job (project, hpc_user);\n 191→-- Project Filter Sorting\n 192→CREATE INDEX IF NOT EXISTS jobs_project_numnodes ON job (project, num_nodes);\n 193→CREATE INDEX IF NOT EXISTS jobs_project_numhwthreads ON job (project, num_hwthreads);\n 194→CREATE INDEX IF NOT EXISTS jobs_project_numacc ON job (project, num_acc);\n 195→CREATE INDEX IF NOT EXISTS jobs_project_energy ON job (project, energy);\n 196→\n 197→-- Cluster+Shared Time Filter Sorting\n 198→CREATE INDEX IF NOT EXISTS jobs_project_starttime_duration ON job (project, start_time, duration);\n 199→CREATE INDEX IF NOT EXISTS jobs_project_duration_starttime ON job (project, duration, start_time);\n 200→\n 201→-- JobState Filter\n 202→CREATE INDEX IF NOT EXISTS jobs_jobstate_user ON job (job_state, hpc_user);\n 203→CREATE INDEX IF NOT EXISTS jobs_jobstate_project ON job (job_state, project);\n 204→-- JobState Filter Sorting\n 205→CREATE INDEX IF NOT EXISTS jobs_jobstate_numnodes ON job (job_state, num_nodes);\n 206→CREATE INDEX IF NOT EXISTS jobs_jobstate_numhwthreads ON job (job_state, num_hwthreads);\n 207→CREATE INDEX IF NOT EXISTS jobs_jobstate_numacc ON job (job_state, num_acc);\n 208→CREATE INDEX IF NOT EXISTS jobs_jobstate_energy ON job (job_state, energy);\n 209→\n 210→-- Cluster+Shared Time Filter Sorting\n 211→CREATE INDEX IF NOT EXISTS jobs_jobstate_starttime_duration ON job (job_state, start_time, duration);\n 212→CREATE INDEX IF NOT EXISTS jobs_jobstate_duration_starttime ON job (job_state, duration, start_time);\n 213→\n 214→-- Shared Filter\n 215→CREATE INDEX IF NOT EXISTS jobs_shared_user ON job (shared, hpc_user);\n 216→CREATE INDEX IF NOT EXISTS jobs_shared_project ON job (shared, project);\n 217→-- Shared Filter Sorting\n 218→CREATE INDEX IF NOT EXISTS jobs_shared_numnodes ON job (shared, num_nodes);\n 219→CREATE INDEX IF NOT EXISTS jobs_shared_numhwthreads ON job (shared, num_hwthreads);\n 220→CREATE INDEX IF NOT EXISTS jobs_shared_numacc ON job (shared, num_acc);\n 221→CREATE INDEX IF NOT EXISTS jobs_shared_energy ON job (shared, energy);\n 222→\n 223→-- Cluster+Shared Time Filter Sorting\n 224→CREATE INDEX IF NOT EXISTS jobs_shared_starttime_duration ON job (shared, start_time, duration);\n 225→CREATE INDEX IF NOT EXISTS jobs_shared_duration_starttime ON job (shared, duration, start_time);\n 226→\n 227→-- ArrayJob Filter\n 228→CREATE INDEX IF NOT EXISTS jobs_arrayjobid_starttime ON job (array_job_id, start_time);\n 229→CREATE INDEX IF NOT EXISTS jobs_cluster_arrayjobid_starttime ON job (cluster, array_job_id, start_time);\n 230→\n 231→-- Single filters with default starttime sorting\n 232→CREATE INDEX IF NOT EXISTS jobs_duration_starttime ON job (duration, start_time);\n 233→CREATE INDEX IF NOT EXISTS jobs_numnodes_starttime ON job (num_nodes, start_time);\n 234→CREATE INDEX IF NOT EXISTS jobs_numhwthreads_starttime ON job (num_hwthreads, start_time);\n 235→CREATE INDEX IF NOT EXISTS jobs_numacc_starttime ON job (num_acc, start_time);\n 236→CREATE INDEX IF NOT EXISTS jobs_energy_starttime ON job (energy, start_time);\n 237→\n 238→-- Single filters with duration sorting\n 239→CREATE INDEX IF NOT EXISTS jobs_starttime_duration ON job (start_time, duration);\n 240→CREATE INDEX IF NOT EXISTS jobs_numnodes_duration ON job (num_nodes, duration);\n 241→CREATE INDEX IF NOT EXISTS jobs_numhwthreads_duration ON job (num_hwthreads, duration);\n 242→CREATE INDEX IF NOT EXISTS jobs_numacc_duration ON job (num_acc, duration);\n 243→CREATE INDEX IF NOT EXISTS jobs_energy_duration ON job (energy, duration);\n 244→\n 245→-- Backup Indices For High Variety Columns\n 246→CREATE INDEX IF NOT EXISTS jobs_starttime ON job (start_time);\n 247→CREATE INDEX IF NOT EXISTS jobs_duration ON job (duration);\n 248→\n 249→-- Notes:\n 250→-- Cluster+Partition+Jobstate Filter: Tested -> Full Array Of Combinations non-required\n 251→-- Cluster+JobState+Shared Filter: Tested -> No further timing improvement\n 252→-- JobState+Shared Filter: Tested -> No further timing improvement\n 253→\n 254→-- Optimize DB index usage\n 255→PRAGMA optimize;\n 256→\n 257→-- Optimize DB size: https://sqlite.org/lang_vacuum.html \n 258→-- Not allowed within a migration transaction; Keep command here for documentation and recommendation\n 259→-- Command: 'VACUUM;'"}]},"uuid":"263f3c84-6e12-479c-b4ac-7e97d7979153","timestamp":"2026-03-11T04:32:00.883Z"},"type":"agent_progress","prompt":"","agentId":"a1ede6e4db46fa8db"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01FTC59ufvgXt3VSQCNwf6FA","uuid":"d1d8da3d-a49c-4f9d-9ff7-d4357c8f7a68","timestamp":"2026-03-11T04:32:00.936Z"}
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+{"parentUuid":"61e9063c-ad1a-4961-8c3d-5fdd5d07ee4d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AJA5xuY1sjfZWRv3N8vHg3","type":"tool_result","content":" 1→CREATE TABLE \"node\" (\n 2→ id INTEGER PRIMARY KEY,\n 3→ hostname VARCHAR(255) NOT NULL,\n 4→ cluster VARCHAR(255) NOT NULL,\n 5→ subcluster VARCHAR(255) NOT NULL,\n 6→ meta_data TEXT, -- JSON\n 7→ UNIQUE (hostname, cluster)\n 8→);\n 9→\n 10→CREATE TABLE \"node_state\" (\n 11→ id INTEGER PRIMARY KEY,\n 12→ time_stamp INTEGER NOT NULL,\n 13→ jobs_running INTEGER DEFAULT 0 NOT NULL,\n 14→ cpus_allocated INTEGER DEFAULT 0 NOT NULL,\n 15→ memory_allocated INTEGER DEFAULT 0 NOT NULL,\n 16→ gpus_allocated INTEGER DEFAULT 0 NOT NULL,\n 17→ node_state VARCHAR(255) NOT NULL\n 18→ CHECK (node_state IN (\n 19→ 'allocated', 'reserved', 'idle', 'mixed',\n 20→ 'down', 'unknown'\n 21→ )),\n 22→ health_state VARCHAR(255) NOT NULL\n 23→ CHECK (health_state IN (\n 24→ 'full', 'partial', 'failed'\n 25→ )),\n 26→ health_metrics TEXT, -- JSON array of strings\n 27→ node_id INTEGER,\n 28→ FOREIGN KEY (node_id) REFERENCES node (id)\n 29→);\n 30→\n 31→-- Add NEW Indices For New Node Table VARCHAR Fields\n 32→CREATE INDEX IF NOT EXISTS nodes_cluster ON node (cluster);\n 33→CREATE INDEX IF NOT EXISTS nodes_cluster_subcluster ON node (cluster, subcluster);\n 34→\n 35→-- Add NEW Indices For New Node_State Table Fields\n 36→CREATE INDEX IF NOT EXISTS nodestates_timestamp ON node_state (time_stamp);\n 37→CREATE INDEX IF NOT EXISTS nodestates_state_timestamp ON node_state (node_state, time_stamp);\n 38→CREATE INDEX IF NOT EXISTS nodestates_health_timestamp ON node_state (health_state, time_stamp);\n 39→CREATE INDEX IF NOT EXISTS nodestates_nodeid_state ON node_state (node_id, node_state);\n 40→CREATE INDEX IF NOT EXISTS nodestates_nodeid_health ON node_state (node_id, health_state);\n 41→CREATE INDEX IF NOT EXISTS nodestates_nodeid_timestamp ON node_state (node_id, time_stamp DESC);\n 42→\n 43→-- Add NEW Indices For Increased Amounts of Tags\n 44→CREATE INDEX IF NOT EXISTS tags_jobid ON jobtag (job_id);\n 45→CREATE INDEX IF NOT EXISTS tags_tagid ON jobtag (tag_id);\n 46→\n 47→-- Optimize DB index usage\n 48→PRAGMA optimize;"}]},"uuid":"cfe44656-254b-4984-bf88-01df4d863d2d","timestamp":"2026-03-11T04:32:00.960Z"},"type":"agent_progress","prompt":"","agentId":"a1ede6e4db46fa8db"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01FTC59ufvgXt3VSQCNwf6FA","uuid":"753a8f5b-3451-4257-a873-96597e1ce2e0","timestamp":"2026-03-11T04:32:00.966Z"}
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+{"parentUuid":"a6feaa64-cc36-410f-bcfb-45e164b1b080","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QWZcLpGKtT3J4mSek27usF","type":"tool_result","content":" 226→func (r *JobRepository) FetchMetadata(job *schema.Job) (map[string]string, error) {\n 227→\tif job == nil {\n 228→\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n 229→\t}\n 230→\n 231→\tstart := time.Now()\n 232→\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n 233→\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n 234→\t\tjob.MetaData = cached.(map[string]string)\n 235→\t\treturn job.MetaData, nil\n 236→\t}\n 237→\n 238→\tif err := sq.Select(\"job.meta_data\").From(\"job\").Where(\"job.id = ?\", job.ID).\n 239→\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawMetaData); err != nil {\n 240→\t\tcclog.Warnf(\"Error while scanning for job metadata (ID=%d): %v\", *job.ID, err)\n 241→\t\treturn nil, fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n 242→\t}\n 243→\n 244→\tif len(job.RawMetaData) == 0 {\n 245→\t\treturn nil, nil\n 246→\t}\n 247→\n 248→\tif err := json.Unmarshal(job.RawMetaData, &job.MetaData); err != nil {\n 249→\t\tcclog.Warnf(\"Error while unmarshaling raw metadata json (ID=%d): %v\", *job.ID, err)\n 250→\t\treturn nil, fmt.Errorf(\"failed to unmarshal metadata for job %d: %w\", *job.ID, err)\n 251→\t}\n 252→\n 253→\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n 254→\tcclog.Debugf(\"Timer FetchMetadata %s\", time.Since(start))\n 255→\treturn job.MetaData, nil\n 256→}\n 257→\n 258→// UpdateMetadata adds or updates a single metadata key-value pair for a job.\n 259→// The entire metadata map is re-marshaled and stored, and the cache is invalidated.\n 260→// Also triggers archive metadata update via archive.UpdateMetadata.\n 261→//\n 262→// Parameters:\n 263→// - job: Job struct with valid ID, existing metadata will be fetched if not present\n 264→// - key: Metadata key to set\n 265→// - val: Metadata value to set\n 266→//\n 267→// Returns an error if the job is nil, metadata fetch fails, or database update fails.\n 268→func (r *JobRepository) UpdateMetadata(job *schema.Job, key, val string) (err error) {\n 269→\tif job == nil {\n 270→\t\treturn fmt.Errorf(\"job cannot be nil\")\n 271→\t}\n 272→\n 273→\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n 274→\tr.cache.Del(cachekey)\n 275→\tif job.MetaData == nil {\n 276→\t\tif _, err = r.FetchMetadata(job); err != nil {\n 277→\t\t\tcclog.Warnf(\"Error while fetching metadata for job, DB ID '%v'\", *job.ID)\n 278→\t\t\treturn fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n 279→\t\t}\n 280→\t}\n 281→\n 282→\tif job.MetaData != nil {\n 283→\t\tcpy := make(map[string]string, len(job.MetaData)+1)\n 284→\t\tmaps.Copy(cpy, job.MetaData)\n 285→\t\tcpy[key] = val\n 286→\t\tjob.MetaData = cpy\n 287→\t} else {\n 288→\t\tjob.MetaData = map[string]string{key: val}\n 289→\t}\n 290→\n 291→\tif job.RawMetaData, err = json.Marshal(job.MetaData); err != nil {\n 292→\t\tcclog.Warnf(\"Error while marshaling metadata for job, DB ID '%v'\", *job.ID)\n 293→\t\treturn fmt.Errorf(\"failed to marshal metadata for job %d: %w\", *job.ID, err)\n 294→\t}\n 295→\n 296→\tif _, err = sq.Update(\"job\").\n 297→\t\tSet(\"meta_data\", job.RawMetaData).\n 298→\t\tWhere(\"job.id = ?\", job.ID).\n 299→\t\tRunWith(r.stmtCache).Exec(); err != nil {\n 300→\t\tcclog.Warnf(\"Error while updating metadata for job, DB ID '%v'\", *job.ID)\n 301→\t\treturn fmt.Errorf(\"failed to update metadata in database for job %d: %w\", *job.ID, err)\n 302→\t}\n 303→\n 304→\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n 305→\treturn archive.UpdateMetadata(job, job.MetaData)\n 306→}\n 307→\n 308→// FetchFootprint retrieves and unmarshals the performance footprint JSON for a job.\n 309→// Unlike FetchMetadata, footprints are NOT cached as they can be large and change frequently.\n 310→//\n 311→// The footprint contains summary statistics (avg/min/max) for monitored metrics,\n 312→// stored as JSON with keys like \"cpu_load_avg\", \"mem_used_max\", etc.\n 313→//\n 314→// Parameters:\n 315→// - job: Job struct with valid ID, footprint will be populated in job.Footprint\n 316→//\n 317→// Returns the footprint map or an error if the job is nil or database query fails.\n 318→func (r *JobRepository) FetchFootprint(job *schema.Job) (map[string]float64, error) {\n 319→\tif job == nil {\n 320→\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n 321→\t}\n 322→\n 323→\tstart := time.Now()\n 324→\n 325→\tif err := sq.Select(\"job.footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n 326→\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawFootprint); err != nil {\n 327→\t\tcclog.Warnf(\"Error while scanning for job footprint (ID=%d): %v\", *job.ID, err)\n 328→\t\treturn nil, fmt.Errorf(\"failed to fetch footprint for job %d: %w\", *job.ID, err)\n 329→\t}\n 330→\n 331→\tif len(job.RawFootprint) == 0 {\n 332→\t\treturn nil, nil\n 333→\t}\n 334→\n 335→\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n 336→\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json (ID=%d): %v\", *job.ID, err)\n 337→\t\treturn nil, fmt.Errorf(\"failed to unmarshal footprint for job %d: %w\", *job.ID, err)\n 338→\t}\n 339→\n 340→\tcclog.Debugf(\"Timer FetchFootprint %s\", time.Since(start))\n 341→\treturn job.Footprint, nil\n 342→}\n 343→\n 344→// FetchEnergyFootprint retrieves and unmarshals the energy footprint JSON for a job.\n 345→// Energy footprints are cached with a 24-hour TTL as they are frequently accessed but rarely change.\n 346→//\n 347→// The energy footprint contains calculated energy consumption (in kWh) per metric,\n 348→// stored as JSON with keys like \"power_avg\", \"acc_power_avg\", etc.\n 349→//\n 350→// Parameters:\n 351→// - job: Job struct with valid ID, energy footprint will be populated in job.EnergyFootprint\n 352→//\n 353→// Returns the energy footprint map or an error if the job is nil or database query fails.\n 354→func (r *JobRepository) FetchEnergyFootprint(job *schema.Job) (map[string]float64, error) {\n 355→\tif job == nil {\n 356→\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n 357→\t}\n 358→\n 359→\tstart := time.Now()\n 360→\tcachekey := fmt.Sprintf(\"energyFootprint:%d\", *job.ID)\n 361→\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n 362→\t\tjob.EnergyFootprint = cached.(map[string]float64)\n 363→\t\treturn job.EnergyFootprint, nil\n 364→\t}\n 365→\n 366→\tif err := sq.Select(\"job.energy_footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n 367→\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawEnergyFootprint); err != nil {\n 368→\t\tcclog.Warnf(\"Error while scanning for job energy_footprint (ID=%d): %v\", *job.ID, err)\n 369→\t\treturn nil, fmt.Errorf(\"failed to fetch energy footprint for job %d: %w\", *job.ID, err)\n 370→\t}\n 371→\n 372→\tif len(job.RawEnergyFootprint) == 0 {\n 373→\t\treturn nil, nil\n 374→\t}\n 375→\n 376→\tif err := json.Unmarshal(job.RawEnergyFootprint, &job.EnergyFootprint); err != nil {\n 377→\t\tcclog.Warnf(\"Error while unmarshaling raw energy footprint json (ID=%d): %v\", *job.ID, err)\n 378→\t\treturn nil, fmt.Errorf(\"failed to unmarshal energy footprint for job %d: %w\", *job.ID, err)\n 379→\t}\n 380→\n 381→\tr.cache.Put(cachekey, job.EnergyFootprint, len(job.EnergyFootprint), 24*time.Hour)\n 382→\tcclog.Debugf(\"Timer FetchEnergyFootprint %s\", time.Since(start))\n 383→\treturn job.EnergyFootprint, nil\n 384→}\n 385→\n 386→// DeleteJobsBefore removes jobs older than the specified start time.\n 387→// Optionally preserves tagged jobs to protect important data from deletion.\n 388→// Cache entries for deleted jobs are automatically invalidated.\n 389→//\n 390→// This is typically used for data retention policies and cleanup operations.\n 391→// WARNING: This is a destructive operation that permanently deletes job records.\n 392→//\n 393→// Parameters:\n 394→// - startTime: Unix timestamp, jobs with start_time < this value will be deleted\n 395→// - omitTagged: \"none\" = delete all jobs, \"all\" = skip any tagged jobs,\n 396→// \"user\" = skip jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 397→//\n 398→// Returns the count of deleted jobs or an error if the operation fails.\n 399→func (r *JobRepository) DeleteJobsBefore(startTime int64, omitTagged string) (int, error) {\n 400→\tvar cnt int\n 401→\tq := sq.Select(\"count(*)\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n 402→\n 403→\tswitch omitTagged {\n 404→\tcase \"all\":\n 405→\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 406→\tcase \"user\":\n 407→\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 408→\t}\n 409→\n 410→\tif err := q.RunWith(r.DB).QueryRow().Scan(&cnt); err != nil {\n 411→\t\tcclog.Errorf(\"Error counting jobs before %d: %v\", startTime, err)\n 412→\t\treturn 0, err\n 413→\t}\n 414→\n 415→\t// Invalidate cache for jobs being deleted (get job IDs first)\n 416→\tif cnt > 0 {\n 417→\t\tvar jobIds []int64\n 418→\t\tselectQuery := sq.Select(\"id\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n 419→\n 420→\t\tswitch omitTagged {\n 421→\t\tcase \"all\":\n 422→\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 423→\t\tcase \"user\":\n 424→\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 425→\t\t}\n 426→\n 427→\t\trows, err := selectQuery.RunWith(r.DB).Query()\n 428→\t\tif err == nil {\n 429→\t\t\tdefer rows.Close()\n 430→\t\t\tfor rows.Next() {\n 431→\t\t\t\tvar id int64\n 432→\t\t\t\tif err := rows.Scan(&id); err == nil {\n 433→\t\t\t\t\tjobIds = append(jobIds, id)\n 434→\t\t\t\t}\n 435→\t\t\t}\n 436→\t\t\t// Invalidate cache entries\n 437→\t\t\tfor _, id := range jobIds {\n 438→\t\t\t\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n 439→\t\t\t\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n 440→\t\t\t}\n 441→\t\t}\n 442→\t}\n 443→\n 444→\tqd := sq.Delete(\"job\").Where(\"job.start_time < ?\", startTime)\n 445→\n 446→\tswitch omitTagged {\n 447→\tcase \"all\":\n 448→\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 449→\tcase \"user\":\n 450→\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 451→\t}\n 452→\t_, err := qd.RunWith(r.DB).Exec()\n 453→\n 454→\tif err != nil {\n 455→\t\ts, _, _ := qd.ToSql()\n 456→\t\tcclog.Errorf(\" DeleteJobsBefore(%d) with %s: error %#v\", startTime, s, err)\n 457→\t} else {\n 458→\t\tcclog.Debugf(\"DeleteJobsBefore(%d): Deleted %d jobs\", startTime, cnt)\n 459→\t}\n 460→\treturn cnt, err\n 461→}\n 462→\n 463→// DeleteJobByID permanently removes a single job by its database ID.\n 464→// Cache entries for the deleted job are automatically invalidated.\n 465→//\n 466→// Parameters:\n 467→// - id: Database ID (primary key) of the job to delete\n 468→//\n 469→// Returns an error if the deletion fails.\n 470→func (r *JobRepository) DeleteJobByID(id int64) error {\n 471→\t// Invalidate cache entries before deletion\n 472→\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n 473→\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n 474→\n 475→\tqd := sq.Delete(\"job\").Where(\"job.id = ?\", id)\n 476→\t_, err := qd.RunWith(r.DB).Exec()\n 477→\n 478→\tif err != nil {\n 479→\t\ts, _, _ := qd.ToSql()\n 480→\t\tcclog.Errorf(\"DeleteJobById(%d) with %s : error %#v\", id, s, err)\n 481→\t} else {\n 482→\t\tcclog.Debugf(\"DeleteJobById(%d): Success\", id)\n 483→\t}\n 484→\treturn err\n 485→}\n 486→\n 487→// FindUserOrProjectOrJobname attempts to interpret a search term as a job ID,\n 488→// username, project ID, or job name by querying the database.\n 489→//\n 490→// Search logic (in priority order):\n 491→// 1. If searchterm is numeric, treat as job ID (returned immediately)\n 492→// 2. Try exact match in job.hpc_user column (username)\n 493→// 3. Try LIKE match in hpc_user.name column (real name)\n 494→// 4. Try exact match in job.project column (project ID)\n 495→// 5. If no matches, return searchterm as jobname for GraphQL query\n 496→//\n 497→// This powers the searchbar functionality for flexible job searching.\n 498→// Requires authenticated user for database lookups (returns empty if user is nil).\n 499→//\n 500→// Parameters:\n 501→// - user: Authenticated user context, required for database access\n 502→// - searchterm: Search string to interpret\n 503→//\n 504→// Returns up to one non-empty value among (jobid, username, project, jobname).\n 505→func (r *JobRepository) FindUserOrProjectOrJobname(user *schema.User, searchterm string) (jobid string, username string, project string, jobname string) {\n 506→\tif searchterm == \"\" {\n 507→\t\treturn \"\", \"\", \"\", \"\"\n 508→\t}\n 509→\n 510→\tif _, err := strconv.Atoi(searchterm); err == nil { // Return empty on successful conversion: parent method will redirect for integer jobId\n 511→\t\treturn searchterm, \"\", \"\", \"\"\n 512→\t} else { // Has to have letters and logged-in user for other guesses\n 513→\t\tif user != nil {\n 514→\t\t\t// Find username by username in job table (match)\n 515→\t\t\turesult, _ := r.FindColumnValue(user, searchterm, \"job\", \"hpc_user\", \"hpc_user\", false)\n 516→\t\t\tif uresult != \"\" {\n 517→\t\t\t\treturn \"\", uresult, \"\", \"\"\n 518→\t\t\t}\n 519→\t\t\t// Find username by real name in hpc_user table (like)\n 520→\t\t\tnresult, _ := r.FindColumnValue(user, searchterm, \"hpc_user\", \"username\", \"name\", true)\n 521→\t\t\tif nresult != \"\" {\n 522→\t\t\t\treturn \"\", nresult, \"\", \"\"\n 523→\t\t\t}\n 524→\t\t\t// Find projectId by projectId in job table (match)\n 525→\t\t\tpresult, _ := r.FindColumnValue(user, searchterm, \"job\", \"project\", \"project\", false)\n 526→\t\t\tif presult != \"\" {\n 527→\t\t\t\treturn \"\", \"\", presult, \"\"\n 528→\t\t\t}\n 529→\t\t}\n 530→\t\t// Return searchterm if no match before: Forward as jobname query to GQL in handleSearchbar function\n 531→\t\treturn \"\", \"\", \"\", searchterm\n 532→\t}\n 533→}\n 534→\n 535→var (\n 536→\tErrNotFound = errors.New(\"no such jobname, project or user\")\n 537→\tErrForbidden = errors.New(\"not authorized\")\n 538→)\n 539→\n 540→// FindColumnValue performs a generic column lookup in a database table with role-based access control.\n 541→// Only users with admin, support, or manager roles can execute this query.\n 542→//\n 543→// Parameters:\n 544→// - user: User context for authorization check\n 545→// - searchterm: Value to search for (exact match or LIKE pattern)\n 546→// - table: Database table name to query\n 547→// - selectColumn: Column name to return in results\n 548→// - whereColumn: Column name to filter on\n 549→// - isLike: If true, use LIKE with wildcards; if false, use exact equality\n 550→//\n 551→// Returns the first matching value, ErrForbidden if user lacks permission,\n 552→// or ErrNotFound if no matches are found.\n 553→func (r *JobRepository) FindColumnValue(user *schema.User, searchterm string, table string, selectColumn string, whereColumn string, isLike bool) (result string, err error) {\n 554→\tif user == nil {\n 555→\t\treturn \"\", fmt.Errorf(\"user cannot be nil\")\n 556→\t}\n 557→\n 558→\tcompareStr := \" = ?\"\n 559→\tquery := searchterm\n 560→\tif isLike {\n 561→\t\tcompareStr = \" LIKE ?\"\n 562→\t\tquery = \"%\" + searchterm + \"%\"\n 563→\t}\n 564→\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n 565→\t\ttheQuery := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n 566→\t\t\tWhere(table+\".\"+whereColumn+compareStr, query)\n 567→\n 568→\t\terr := theQuery.RunWith(r.stmtCache).QueryRow().Scan(&result)\n 569→\n 570→\t\tif err != nil && err != sql.ErrNoRows {\n 571→\t\t\tcclog.Warnf(\"Error while querying FindColumnValue (table=%s, column=%s): %v\", table, selectColumn, err)\n 572→\t\t\treturn \"\", fmt.Errorf(\"failed to find column value: %w\", err)\n 573→\t\t} else if err == nil {\n 574→\t\t\treturn result, nil\n 575→\t\t}\n 576→\t\treturn \"\", ErrNotFound\n 577→\t} else {\n 578→\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)\n 579→\t\treturn \"\", ErrForbidden\n 580→\t}\n 581→}\n 582→\n 583→// FindColumnValues performs a generic column lookup returning multiple matches with role-based access control.\n 584→// Similar to FindColumnValue but returns all matching values instead of just the first.\n 585→// Only users with admin, support, or manager roles can execute this query.\n 586→//\n 587→// Parameters:\n 588→// - user: User context for authorization check\n 589→// - query: Search pattern (always uses LIKE with wildcards)\n 590→// - table: Database table name to query\n 591→// - selectColumn: Column name to return in results\n 592→// - whereColumn: Column name to filter on\n 593→//\n 594→// Returns a slice of matching values, ErrForbidden if user lacks permission,\n 595→// or ErrNotFound if no matches are found.\n 596→func (r *JobRepository) FindColumnValues(user *schema.User, query string, table string, selectColumn string, whereColumn string) (results []string, err error) {\n 597→\tif user == nil {\n 598→\t\treturn nil, fmt.Errorf(\"user cannot be nil\")\n 599→\t}\n 600→\n 601→\temptyResult := make([]string, 0)\n 602→\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n 603→\t\trows, err := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n 604→\t\t\tWhere(table+\".\"+whereColumn+\" LIKE ?\", fmt.Sprint(\"%\", query, \"%\")).\n 605→\t\t\tRunWith(r.stmtCache).Query()\n 606→\t\tif err != nil && err != sql.ErrNoRows {\n 607→\t\t\tcclog.Errorf(\"Error while querying FindColumnValues (table=%s, column=%s): %v\", table, selectColumn, err)\n 608→\t\t\treturn emptyResult, fmt.Errorf(\"failed to find column values: %w\", err)\n 609→\t\t} else if err == nil {\n 610→\t\t\tdefer rows.Close()\n 611→\t\t\tfor rows.Next() {\n 612→\t\t\t\tvar result string\n 613→\t\t\t\terr := rows.Scan(&result)\n 614→\t\t\t\tif err != nil {\n 615→\t\t\t\t\tcclog.Warnf(\"Error while scanning rows in FindColumnValues: %v\", err)\n 616→\t\t\t\t\treturn emptyResult, fmt.Errorf(\"failed to scan column value: %w\", err)\n 617→\t\t\t\t}\n 618→\t\t\t\tresults = append(results, result)\n 619→\t\t\t}\n 620→\t\t\treturn results, nil\n 621→\t\t}\n 622→\t\treturn emptyResult, ErrNotFound\n 623→\n 624→\t} else {\n 625→\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)"}]},"uuid":"002fbb67-133c-4004-b8dd-28519f2ac373","timestamp":"2026-03-11T04:32:04.793Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"c96eaab6-d53f-40c3-a927-8a2babcdd075","timestamp":"2026-03-11T04:32:04.818Z"}
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- job.walltime)\", currentTime-int64(seconds)).\n 722→\t\tRunWith(r.DB).Exec()\n 723→\tif err != nil {\n 724→\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n 725→\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n 726→\t}\n 727→\n 728→\trowsAffected, err := res.RowsAffected()\n 729→\tif err != nil {\n 730→\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n 731→\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n 732→\t}\n 733→\n 734→\tif rowsAffected > 0 {\n 735→\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n 736→\t}\n 737→\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n 738→\treturn nil\n 739→}\n 740→\n 741→// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n 742→//\n 743→// Parameters:\n 744→// - tagID: Database ID of the tag to search for\n 745→//\n 746→// Returns a slice of job IDs or an error if the query fails.\n 747→func (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n 748→\tquery := sq.Select(\"job.id\").From(\"job\").\n 749→\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n 750→\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n 751→\trows, err := query.RunWith(r.stmtCache).Query()\n 752→\tif err != nil {\n 753→\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n 754→\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n 755→\t}\n 756→\tdefer rows.Close()\n 757→\n 758→\tjobIds := make([]int64, 0, 100)\n 759→\n 760→\tfor rows.Next() {\n 761→\t\tvar jobID int64\n 762→\n 763→\t\tif err := rows.Scan(&jobID); err != nil {\n 764→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n 765→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n 766→\t\t}\n 767→\n 768→\t\tjobIds = append(jobIds, jobID)\n 769→\t}\n 770→\n 771→\treturn jobIds, nil\n 772→}\n 773→\n 774→// FindRunningJobs returns all currently running jobs for a specific cluster.\n 775→// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n 776→//\n 777→// Parameters:\n 778→// - cluster: Cluster name to filter jobs\n 779→//\n 780→// Returns a slice of running job objects or an error if the query fails.\n 781→func (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n 782→\tquery := sq.Select(jobColumns...).From(\"job\").\n 783→\t\tWhere(\"job.cluster = ?\", cluster).\n 784→\t\tWhere(\"job.job_state = 'running'\").\n 785→\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n 786→\n 787→\trows, err := query.RunWith(r.stmtCache).Query()\n 788→\tif err != nil {\n 789→\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n 790→\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n 791→\t}\n 792→\tdefer rows.Close()\n 793→\n 794→\tjobs := make([]*schema.Job, 0, 50)\n 795→\tfor rows.Next() {\n 796→\t\tjob, err := scanJob(rows)\n 797→\t\tif err != nil {\n 798→\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n 799→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n 800→\t\t}\n 801→\t\tjobs = append(jobs, job)\n 802→\t}\n 803→\n 804→\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n 805→\treturn jobs, nil\n 806→}\n 807→\n 808→// UpdateDuration recalculates and updates the duration field for all running jobs.\n 809→// Called periodically to keep job durations current without querying individual jobs.\n 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally excludes tagged jobs from results.\n 831→//\n 832→// Parameters:\n 833→// - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n 834→// - startTimeEnd: Unix timestamp for range end\n 835→// - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n 836→// \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 837→//\n 838→// Returns a slice of jobs or an error if the time range is invalid or query fails.\n 839→func (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n 840→\tvar query sq.SelectBuilder\n 841→\n 842→\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n 843→\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n 844→\t}\n 845→\n 846→\tif startTimeBegin == 0 {\n 847→\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n 848→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {\n 850→\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n 851→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n 852→\t}\n 853→\n 854→\tswitch omitTagged {\n 855→\tcase \"all\":\n 856→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 857→\tcase \"user\":\n 858→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 859→\t}\n 860→\n 861→\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\n 862→\n 863→\trows, err := query.RunWith(r.stmtCache).Query()\n 864→\tif err != nil {\n 865→\t\tcclog.Errorf(\"Error while running FindJobsBetween query: %v\", err)\n 866→\t\treturn nil, fmt.Errorf(\"failed to find jobs between %d and %d: %w\", startTimeBegin, startTimeEnd, err)\n 867→\t}\n 868→\tdefer rows.Close()\n 869→\n 870→\tjobs := make([]*schema.Job, 0, 50)\n 871→\tfor rows.Next() {\n 872→\t\tjob, err := scanJob(rows)\n 873→\t\tif err != nil {\n 874→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobsBetween: %v\", err)\n 875→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindJobsBetween: %w\", err)\n 876→\t\t}\n 877→\t\tjobs = append(jobs, job)\n 878→\t}\n 879→\n 880→\tcclog.Debugf(\"JobRepository.FindJobsBetween(): Return job count %d (omitTagged: %v)\", len(jobs), omitTagged)\n 881→\treturn jobs, nil\n 882→}\n 883→\n 884→// UpdateMonitoringStatus updates the monitoring status for a job and invalidates its cache entries.\n 885→// Cache invalidation affects both metadata and energy footprint to ensure consistency.\n 886→//\n 887→// Parameters:\n 888→// - job: Database ID of the job to update\n 889→// - monitoringStatus: New monitoring status value (see schema.MonitoringStatus constants)\n 890→//\n 891→// Returns an error if the database update fails.\n 892→func (r *JobRepository) UpdateMonitoringStatus(job int64, monitoringStatus int32) (err error) {\n 893→\t// Invalidate cache entries as monitoring status affects job state\n 894→\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", job))\n 895→\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", job))\n 896→\n 897→\tstmt := sq.Update(\"job\").\n 898→\t\tSet(\"monitoring_status\", monitoringStatus).\n 899→\t\tWhere(\"job.id = ?\", job)\n 900→\n 901→\tif _, err = stmt.RunWith(r.stmtCache).Exec(); err != nil {\n 902→\t\tcclog.Errorf(\"Error while updating monitoring status for job %d: %v\", job, err)\n 903→\t\treturn fmt.Errorf(\"failed to update monitoring status for job %d: %w\", job, err)\n 904→\t}\n 905→\treturn nil\n 906→}\n 907→\n 908→// Execute runs a Squirrel UpdateBuilder statement against the database.\n 909→// This is a generic helper for executing pre-built update queries.\n 910→//\n 911→// Parameters:\n 912→// - stmt: Squirrel UpdateBuilder with prepared update query\n 913→//\n 914→// Returns an error if the execution fails.\n 915→func (r *JobRepository) Execute(stmt sq.UpdateBuilder) error {\n 916→\tif _, err := stmt.RunWith(r.stmtCache).Exec(); err != nil {\n 917→\t\tcclog.Errorf(\"Error while executing statement: %v\", err)\n 918→\t\treturn fmt.Errorf(\"failed to execute update statement: %w\", err)\n 919→\t}\n 920→\n 921→\treturn nil\n 922→}\n 923→\n 924→// MarkArchived adds monitoring status update to an existing UpdateBuilder statement.\n 925→// This is a builder helper used when constructing multi-field update queries.\n 926→//\n 927→// Parameters:\n 928→// - stmt: Existing UpdateBuilder to modify\n 929→// - monitoringStatus: Monitoring status value to set\n 930→//\n 931→// Returns the modified UpdateBuilder for method chaining.\n 932→func (r *JobRepository) MarkArchived(\n 933→\tstmt sq.UpdateBuilder,\n 934→\tmonitoringStatus int32,\n 935→) sq.UpdateBuilder {\n 936→\treturn stmt.Set(\"monitoring_status\", monitoringStatus)\n 937→}\n 938→\n 939→// UpdateEnergy calculates and updates the energy consumption for a job.\n 940→// This is called for running jobs during intermediate updates or when archiving.\n 941→//\n 942→// Energy calculation formula:\n 943→// - For \"power\" metrics: Energy (kWh) = (Power_avg * NumNodes * Duration_hours) / 1000\n 944→// - For \"energy\" metrics: Currently not implemented (would need sum statistics)\n 945→//\n 946→// The calculation accounts for:\n 947→// - Multi-node jobs: Multiplies by NumNodes to get total cluster energy\n 948→// - Shared jobs: Node average is already based on partial resources, so NumNodes=1\n 949→// - Unit conversion: Watts * hours / 1000 = kilowatt-hours (kWh)\n 950→// - Rounding: Results rounded to 2 decimal places\n 951→func (r *JobRepository) UpdateEnergy(\n 952→\tstmt sq.UpdateBuilder,\n 953→\tjobMeta *schema.Job,\n 954→) (sq.UpdateBuilder, error) {\n 955→\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n 956→\tif err != nil {\n 957→\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n 958→\t\treturn stmt, err\n 959→\t}\n 960→\tenergyFootprint := make(map[string]float64)\n 961→\n 962→\t// Accumulate total energy across all energy-related metrics\n 963→\ttotalEnergy := 0.0\n 964→\tfor _, fp := range sc.EnergyFootprint {\n 965→\t\t// Calculate energy for this specific metric\n 966→\t\tmetricEnergy := 0.0\n 967→\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err == nil {\n 968→\t\t\tswitch sc.MetricConfig[i].Energy {\n 969→\t\t\tcase \"energy\": // Metric already in energy units (Joules or Wh)\n 970→\t\t\t\tcclog.Warnf(\"Update EnergyFootprint for Job %d and Metric %s on cluster %s: Set to 'energy' in cluster.json: Not implemented, will return 0.0\", jobMeta.JobID, jobMeta.Cluster, fp)\n 971→\t\t\t\t// FIXME: Needs sum as stats type to accumulate energy values over time\n 972→\t\t\tcase \"power\": // Metric in power units (Watts)\n 973→\t\t\t\t// Energy (kWh) = Power (W) × Time (h) / 1000\n 974→\t\t\t\t// Formula: (avg_power_per_node * num_nodes) * (duration_sec / 3600) / 1000\n 975→\t\t\t\t//\n 976→\t\t\t\t// Breakdown:\n 977→\t\t\t\t// LoadJobStat(jobMeta, fp, \"avg\") = average power per node (W)\n 978→\t\t\t\t// jobMeta.NumNodes = number of nodes (1 for shared jobs)\n 979→\t\t\t\t// jobMeta.Duration / 3600.0 = duration in hours\n 980→\t\t\t\t// / 1000.0 = convert Wh to kWh\n 981→\t\t\t\trawEnergy := ((LoadJobStat(jobMeta, fp, \"avg\") * float64(jobMeta.NumNodes)) * (float64(jobMeta.Duration) / 3600.0)) / 1000.0\n 982→\t\t\t\tmetricEnergy = math.Round(rawEnergy*100.0) / 100.0 // Round to 2 decimal places\n 983→\t\t\t}\n 984→\t\t} else {\n 985→\t\t\tcclog.Warnf(\"Error while collecting energy metric %s for job, DB ID '%v', return '0.0'\", fp, jobMeta.ID)\n 986→\t\t}\n 987→\n 988→\t\tenergyFootprint[fp] = metricEnergy\n 989→\t\ttotalEnergy += metricEnergy\n 990→\t}\n 991→\n 992→\tvar rawFootprint []byte\n 993→\tif rawFootprint, err = json.Marshal(energyFootprint); err != nil {\n 994→\t\tcclog.Warnf(\"Error while marshaling energy footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n 995→\t\treturn stmt, err\n 996→\t}\n 997→\n 998→\treturn stmt.Set(\"energy_footprint\", string(rawFootprint)).Set(\"energy\", (math.Round(totalEnergy*100.0) / 100.0)), nil\n 999→}\n 1000→\n 1001→// UpdateFootprint calculates and updates the performance footprint for a job.\n 1002→// This is called for running jobs during intermediate updates or when archiving.\n 1003→//\n 1004→// A footprint is a summary statistic (avg/min/max) for each monitored metric.\n 1005→// The specific statistic type is defined in the cluster config's Footprint field.\n 1006→// Results are stored as JSON with keys like \"metric_avg\", \"metric_max\", etc.\n 1007→//\n 1008→// Example: For a \"cpu_load\" metric with Footprint=\"avg\", this stores\n 1009→// the average CPU load across all nodes as \"cpu_load_avg\": 85.3\n 1010→func (r *JobRepository) UpdateFootprint(\n 1011→\tstmt sq.UpdateBuilder,\n 1012→\tjobMeta *schema.Job,\n 1013→) (sq.UpdateBuilder, error) {\n 1014→\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n 1015→\tif err != nil {\n 1016→\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n 1017→\t\treturn stmt, err\n 1018→\t}\n 1019→\tfootprint := make(map[string]float64)\n 1020→\n 1021→\t// Build footprint map with metric_stattype as keys\n 1022→\tfor _, fp := range sc.Footprint {\n 1023→\t\t// Determine which statistic to use: avg, min, or max\n 1024→\t\t// First check global metric config, then cluster-specific config\n 1025→\t\tvar statType string\n 1026→\t\tfor _, gm := range archive.GlobalMetricList {\n 1027→\t\t\tif gm.Name == fp {\n 1028→\t\t\t\tstatType = gm.Footprint\n 1029→\t\t\t}\n 1030→\t\t}\n 1031→\n 1032→\t\t// Validate statistic type\n 1033→\t\tif statType != \"avg\" && statType != \"min\" && statType != \"max\" {\n 1034→\t\t\tcclog.Warnf(\"unknown statType for footprint update: %s\", statType)\n 1035→\t\t\treturn stmt, fmt.Errorf(\"unknown statType for footprint update: %s\", statType)\n 1036→\t\t}\n 1037→\n 1038→\t\t// Override with cluster-specific config if available\n 1039→\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err != nil {\n 1040→\t\t\tstatType = sc.MetricConfig[i].Footprint\n 1041→\t\t}\n 1042→\n 1043→\t\t// Store as \"metric_stattype\": value (e.g., \"cpu_load_avg\": 85.3)\n 1044→\t\tname := fmt.Sprintf(\"%s_%s\", fp, statType)\n 1045→\t\tfootprint[name] = LoadJobStat(jobMeta, fp, statType)\n 1046→\t}\n 1047→\n 1048→\tvar rawFootprint []byte\n 1049→\tif rawFootprint, err = json.Marshal(footprint); err != nil {\n 1050→\t\tcclog.Warnf(\"Error while marshaling footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n 1051→\t\treturn stmt, err\n 1052→\t}\n 1053→\n 1054→\treturn stmt.Set(\"footprint\", string(rawFootprint)), nil\n 1055→}\n 1056→\n 1057→// GetUsedNodes returns a map of cluster names to sorted lists of unique hostnames\n 1058→// that are currently in use by jobs that started before the given timestamp and\n 1059→// are still in running state.\n 1060→//\n 1061→// The timestamp parameter (ts) is compared against job.start_time to find\n 1062→// relevant jobs. Returns an error if the database query fails or row iteration\n 1063→// encounters errors. Individual row parsing errors are logged but don't fail\n 1064→// the entire operation.\n 1065→func (r *JobRepository) GetUsedNodes(ts int64) (map[string][]string, error) {\n 1066→\t// Note: Query expects index on (job_state, start_time) for optimal performance\n 1067→\tq := sq.Select(\"job.cluster\", \"job.resources\").From(\"job\").\n 1068→\t\tWhere(\"job.start_time < ?\", ts).\n 1069→\t\tWhere(sq.Eq{\"job.job_state\": \"running\"})\n 1070→\n 1071→\trows, err := q.RunWith(r.stmtCache).Query()\n 1072→\tif err != nil {\n 1073→\t\tqueryString, queryVars, _ := q.ToSql()\n 1074→\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n 1075→\t}\n 1076→\tdefer rows.Close()\n 1077→\n 1078→\t// Use a map of sets for efficient deduplication\n 1079→\tnodeSet := make(map[string]map[string]struct{})\n 1080→\n 1081→\tvar (\n 1082→\t\tcluster string\n 1083→\t\trawResources []byte\n 1084→\t\tresources []*schema.Resource\n 1085→\t\tskippedRows int\n 1086→\t)"}]},"uuid":"829eb4b8-b981-4ae7-ae7a-6e2b511b17f7","timestamp":"2026-03-11T04:32:07.116Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"204b8596-aac9-45c9-a2da-9fa57f75c419","timestamp":"2026-03-11T04:32:07.146Z"}
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+{"parentUuid":"8e00ecd1-1062-47de-b970-9ce74e538967","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DNV4vyqVvnR5mgD5htWbbv","type":"tool_result","content":"internal/repository/node.go:286:\t\tOrderBy(\"node.cluster ASC\", \"node.subcluster ASC\", \"node.hostname ASC\", \"node_state.time_stamp ASC\").\ninternal/repository/node.go:343:\torder *model.OrderByInput, // Currently unused!\ninternal/repository/node.go:356:\tquery = query.OrderBy(\"node.hostname ASC\")\ninternal/repository/node.go:395:\torder *model.OrderByInput, // Currently unused!\ninternal/repository/node.go:409:\tquery = query.OrderBy(\"node.hostname ASC\")\ninternal/repository/node.go:502:\t\tOrderBy(\"node.hostname ASC\")\ninternal/repository/node.go:531:\t\tOrderBy(\"node.hostname ASC\")\ninternal/repository/node.go:625:\tquery = query.GroupBy(column + \", time_stamp\").OrderBy(\"time_stamp ASC\")\ninternal/repository/jobQuery.go:46:\torder *model.OrderByInput,\ninternal/repository/jobQuery.go:58:\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s ASC\", field))\ninternal/repository/jobQuery.go:60:\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"job.%s DESC\", field))\ninternal/repository/jobQuery.go:69:\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") ASC\", field))\ninternal/repository/jobQuery.go:71:\t\t\t\tquery = query.OrderBy(fmt.Sprintf(\"JSON_EXTRACT(footprint, \\\"$.%s\\\") DESC\", field))\ninternal/repository/repository_test.go:116:\torder := &model.OrderByInput{Field: \"startTime\", Type: \"col\", Order: model.SortDirectionEnumDesc}\ninternal/repository/jobFind.go:45:\tq = q.OrderBy(\"job.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\ninternal/repository/jobFind.go:76:\tq = q.OrderBy(\"job_cache.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\ninternal/repository/job.go:861:\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\ninternal/repository/stats.go:62:// into SQL GROUP BY clauses. GraphQL validation ensures only valid enum values are accepted.\ninternal/repository/stats.go:90:// - col: Column name to GROUP BY; empty string for total count without grouping\ninternal/repository/stats.go:131:// - col: Column name to GROUP BY; empty string for overall statistics without grouping\ninternal/repository/stats.go:226:\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\ninternal/repository/stats.go:960:\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n\n[Showing results with pagination = limit: 100, offset: 0]"}]},"uuid":"4f08d494-0f10-4b1e-ac84-7a72062f94d0","timestamp":"2026-03-11T04:32:09.390Z"},"type":"agent_progress","prompt":"","agentId":"a97d0003ebdc3eccd"},"toolUseID":"agent_msg_01HsJ83NK3yqrMh22xtqai31","parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","uuid":"b36004eb-2246-4a29-90c5-d1fcc4287ec7","timestamp":"2026-03-11T04:32:09.390Z"}
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+{"parentUuid":"b426fff6-7428-4ea1-9f65-0abfd65c6d7d","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FTC59ufvgXt3VSQCNwf6FA","type":"tool_result","content":[{"type":"text","text":"Perfect! I now have the complete picture. Let me compile the comprehensive analysis of the job table indexes.\n\n## Complete Job Table Index Situation\n\n### JOB TABLE SCHEMA (Final)\n\nAfter migration 09_add-job-cache.up.sql, the job table has these columns:\n\n```\nid INTEGER PRIMARY KEY\njob_id BIGINT NOT NULL\ncluster TEXT NOT NULL\nsubcluster TEXT NOT NULL\nsubmit_time BIGINT NOT NULL DEFAULT 0\nstart_time BIGINT NOT NULL DEFAULT 0\nhpc_user TEXT NOT NULL (renamed from 'user' in migration 08)\nproject TEXT NOT NULL\ncluster_partition TEXT (renamed from 'partition' in migration 08)\narray_job_id BIGINT\nduration INT NOT NULL\nwalltime INT NOT NULL\njob_state TEXT NOT NULL\nmeta_data TEXT (JSON)\nresources TEXT NOT NULL (JSON)\nnum_nodes INT NOT NULL\nnum_hwthreads INT\nnum_acc INT\nsmt INT NOT NULL DEFAULT 1\nshared TEXT NOT NULL (added in migration 09)\nmonitoring_status TINYINT NOT NULL DEFAULT 1\nenergy REAL NOT NULL DEFAULT 0.0 (added in migration 08)\nenergy_footprint TEXT DEFAULT NULL (added in migration 08)\nfootprint TEXT DEFAULT NULL (added in migration 08)\nUNIQUE (job_id, cluster, start_time)\n```\n\n### DROPPED INDEXES\n\nMigration 08 dropped 8 indexes before creating a larger set:\n1. job_stats\n2. job_by_user\n3. job_by_starttime\n4. job_by_job_id\n5. job_list\n6. job_list_user\n7. job_list_users\n8. job_list_users_start\n\nMigration 09 dropped all job indexes when the job table was recreated (line 118: \"DROP TABLE job; -- Deletes All Existing 'job' Indices\"). These were re-created with optimizations.\n\n### CURRENT INDEXES (76 Total)\n\n#### **Organized by Leading Column:**\n\n**CLUSTER** (14 indexes):\n1. jobs_cluster_user - (cluster, hpc_user)\n2. jobs_cluster_project - (cluster, project)\n3. jobs_cluster_subcluster - (cluster, subcluster)\n4. jobs_cluster_numnodes - (cluster, num_nodes)\n5. jobs_cluster_numhwthreads - (cluster, num_hwthreads)\n6. jobs_cluster_numacc - (cluster, num_acc)\n7. jobs_cluster_energy - (cluster, energy)\n8. jobs_cluster_duration_starttime - (cluster, duration, start_time)\n9. jobs_cluster_starttime_duration - (cluster, start_time, duration)\n10. jobs_cluster_partition_user - (cluster, cluster_partition, hpc_user)\n11. jobs_cluster_partition_project - (cluster, cluster_partition, project)\n12. jobs_cluster_partition_jobstate - (cluster, cluster_partition, job_state)\n13. jobs_cluster_partition_shared - (cluster, cluster_partition, shared)\n14. jobs_cluster_partition_numnodes - (cluster, cluster_partition, num_nodes)\n\n**CLUSTER+PARTITION** (10 indexes):\n15. jobs_cluster_partition_numhwthreads - (cluster, cluster_partition, num_hwthreads)\n16. jobs_cluster_partition_numacc - (cluster, cluster_partition, num_acc)\n17. jobs_cluster_partition_energy - (cluster, cluster_partition, energy)\n18. jobs_cluster_partition_duration_starttime - (cluster, cluster_partition, duration, start_time)\n19. jobs_cluster_partition_starttime_duration - (cluster, cluster_partition, start_time, duration)\n20. jobs_cluster_jobstate_user - (cluster, job_state, hpc_user)\n21. jobs_cluster_jobstate_project - (cluster, job_state, project)\n22. jobs_cluster_jobstate_numnodes - (cluster, job_state, num_nodes)\n23. jobs_cluster_jobstate_numhwthreads - (cluster, job_state, num_hwthreads)\n24. jobs_cluster_jobstate_numacc - (cluster, job_state, num_acc)\n\n**CLUSTER+JOBSTATE** (8 indexes):\n25. jobs_cluster_jobstate_energy - (cluster, job_state, energy)\n26. jobs_cluster_jobstate_starttime_duration - (cluster, job_state, start_time, duration)\n27. jobs_cluster_jobstate_duration_starttime - (cluster, job_state, duration, start_time)\n28. jobs_cluster_shared_user - (cluster, shared, hpc_user)\n29. jobs_cluster_shared_project - (cluster, shared, project)\n30. jobs_cluster_shared_numnodes - (cluster, shared, num_nodes)\n31. jobs_cluster_shared_numhwthreads - (cluster, shared, num_hwthreads)\n32. jobs_cluster_shared_numacc - (cluster, shared, num_acc)\n\n**CLUSTER+SHARED** (8 indexes):\n33. jobs_cluster_shared_energy - (cluster, shared, energy)\n34. jobs_cluster_shared_starttime_duration - (cluster, shared, start_time, duration)\n35. jobs_cluster_shared_duration_starttime - (cluster, shared, duration, start_time)\n36. jobs_user_numnodes - (hpc_user, num_nodes)\n37. jobs_user_numhwthreads - (hpc_user, num_hwthreads)\n38. jobs_user_numacc - (hpc_user, num_acc)\n39. jobs_user_energy - (hpc_user, energy)\n40. jobs_user_starttime_duration - (hpc_user, start_time, duration)\n\n**HPC_USER** (8 indexes):\n41. jobs_user_duration_starttime - (hpc_user, duration, start_time)\n42. jobs_project_user - (project, hpc_user)\n43. jobs_project_numnodes - (project, num_nodes)\n44. jobs_project_numhwthreads - (project, num_hwthreads)\n45. jobs_project_numacc - (project, num_acc)\n46. jobs_project_energy - (project, energy)\n47. jobs_project_starttime_duration - (project, start_time, duration)\n48. jobs_project_duration_starttime - (project, duration, start_time)\n\n**PROJECT** (8 indexes):\n49. jobs_jobstate_user - (job_state, hpc_user)\n50. jobs_jobstate_project - (job_state, project)\n51. jobs_jobstate_numnodes - (job_state, num_nodes)\n52. jobs_jobstate_numhwthreads - (job_state, num_hwthreads)\n53. jobs_jobstate_numacc - (job_state, num_acc)\n54. jobs_jobstate_energy - (job_state, energy)\n55. jobs_jobstate_starttime_duration - (job_state, start_time, duration)\n56. jobs_jobstate_duration_starttime - (job_state, duration, start_time)\n\n**JOB_STATE** (8 indexes):\n57. jobs_shared_user - (shared, hpc_user)\n58. jobs_shared_project - (shared, project)\n59. jobs_shared_numnodes - (shared, num_nodes)\n60. jobs_shared_numhwthreads - (shared, num_hwthreads)\n61. jobs_shared_numacc - (shared, num_acc)\n62. jobs_shared_energy - (shared, energy)\n63. jobs_shared_starttime_duration - (shared, start_time, duration)\n64. jobs_shared_duration_starttime - (shared, duration, start_time)\n\n**SHARED** (8 indexes):\n65. jobs_arrayjobid_starttime - (array_job_id, start_time)\n66. jobs_cluster_arrayjobid_starttime - (cluster, array_job_id, start_time)\n67. jobs_duration_starttime - (duration, start_time)\n68. jobs_numnodes_starttime - (num_nodes, start_time)\n69. jobs_numhwthreads_starttime - (num_hwthreads, start_time)\n70. jobs_numacc_starttime - (num_acc, start_time)\n71. jobs_energy_starttime - (energy, start_time)\n72. jobs_starttime_duration - (start_time, duration)\n\n**ARRAY_JOB_ID / SINGLE COLUMN SORTS** (8 indexes):\n73. jobs_numnodes_duration - (num_nodes, duration)\n74. jobs_numhwthreads_duration - (num_hwthreads, duration)\n75. jobs_numacc_duration - (num_acc, duration)\n76. jobs_energy_duration - (energy, duration)\n77. jobs_starttime - (start_time) — backup index\n78. jobs_duration - (duration) — backup index\n\n### KEY OBSERVATIONS\n\n1. **76 CREATE INDEX statements** across migrations 02, 04, 08, and 09\n2. **Composite indexes dominate** - most are 2-4 column indexes to support filtering + sorting combinations\n3. **Covering pattern**: Many indexes include sorting columns (start_time, duration) as covered columns\n4. **Leading columns**: cluster (heavily used), hpc_user, project, job_state, shared, array_job_id, duration, num_nodes, num_hwthreads, num_acc, energy\n5. **Sorting columns**: start_time and duration appear in 30+ indexes as included columns\n6. **Migration 08** introduced the comprehensive index strategy with 98 CREATE INDEX statements\n7. **Migration 09** refined the indexes when renaming columns and adding the `shared` column, optimizing away some redundant indexes and restructuring the index set to 76 final indexes\n\nThe current schema follows a **query-driven indexing strategy** where each common filter combination with its default sort gets its own index to optimize query plans."},{"type":"text","text":"agentId: a1ede6e4db46fa8db (for resuming to continue this agent's work if needed)\ntotal_tokens: 31547\ntool_uses: 11\nduration_ms: 21471"}]}]},"uuid":"c699f5dc-b0e5-45a4-9295-43eaace5b998","timestamp":"2026-03-11T04:32:17.074Z","toolUseResult":{"status":"completed","prompt":"In /Users/jan/prg/CC/cc-backend, I need to understand the current index situation on the job table.\n\n1. Read ALL migration files in `internal/repository/migrations/sqlite3/` - especially 08_add-footprint.up.sql and 09_add-job-cache.up.sql which define the current indexes\n2. List EVERY CREATE INDEX statement for the job table across all migrations\n3. Note which indexes were DROPped in later migrations\n4. Read the job table schema (CREATE TABLE) from 01_init-schema.up.sql and any modifications in later migrations\n\nI need the complete picture of:\n- All 79+ indexes currently defined\n- The job table column list with types\n- Which columns have individual indexes vs composite indexes\n- Any covering index patterns\n\nReport the full list organized by leading column.","agentId":"a1ede6e4db46fa8db","content":[{"type":"text","text":"Perfect! I now have the complete picture. Let me compile the comprehensive analysis of the job table indexes.\n\n## Complete Job Table Index Situation\n\n### JOB TABLE SCHEMA (Final)\n\nAfter migration 09_add-job-cache.up.sql, the job table has these columns:\n\n```\nid INTEGER PRIMARY KEY\njob_id BIGINT NOT NULL\ncluster TEXT NOT NULL\nsubcluster TEXT NOT NULL\nsubmit_time BIGINT NOT NULL DEFAULT 0\nstart_time BIGINT NOT NULL DEFAULT 0\nhpc_user TEXT NOT NULL (renamed from 'user' in migration 08)\nproject TEXT NOT NULL\ncluster_partition TEXT (renamed from 'partition' in migration 08)\narray_job_id BIGINT\nduration INT NOT NULL\nwalltime INT NOT NULL\njob_state TEXT NOT NULL\nmeta_data TEXT (JSON)\nresources TEXT NOT NULL (JSON)\nnum_nodes INT NOT NULL\nnum_hwthreads INT\nnum_acc INT\nsmt INT NOT NULL DEFAULT 1\nshared TEXT NOT NULL (added in migration 09)\nmonitoring_status TINYINT NOT NULL DEFAULT 1\nenergy REAL NOT NULL DEFAULT 0.0 (added in migration 08)\nenergy_footprint TEXT DEFAULT NULL (added in migration 08)\nfootprint TEXT DEFAULT NULL (added in migration 08)\nUNIQUE (job_id, cluster, start_time)\n```\n\n### DROPPED INDEXES\n\nMigration 08 dropped 8 indexes before creating a larger set:\n1. job_stats\n2. job_by_user\n3. job_by_starttime\n4. job_by_job_id\n5. job_list\n6. job_list_user\n7. job_list_users\n8. job_list_users_start\n\nMigration 09 dropped all job indexes when the job table was recreated (line 118: \"DROP TABLE job; -- Deletes All Existing 'job' Indices\"). These were re-created with optimizations.\n\n### CURRENT INDEXES (76 Total)\n\n#### **Organized by Leading Column:**\n\n**CLUSTER** (14 indexes):\n1. jobs_cluster_user - (cluster, hpc_user)\n2. jobs_cluster_project - (cluster, project)\n3. jobs_cluster_subcluster - (cluster, subcluster)\n4. jobs_cluster_numnodes - (cluster, num_nodes)\n5. jobs_cluster_numhwthreads - (cluster, num_hwthreads)\n6. jobs_cluster_numacc - (cluster, num_acc)\n7. jobs_cluster_energy - (cluster, energy)\n8. jobs_cluster_duration_starttime - (cluster, duration, start_time)\n9. jobs_cluster_starttime_duration - (cluster, start_time, duration)\n10. jobs_cluster_partition_user - (cluster, cluster_partition, hpc_user)\n11. jobs_cluster_partition_project - (cluster, cluster_partition, project)\n12. jobs_cluster_partition_jobstate - (cluster, cluster_partition, job_state)\n13. jobs_cluster_partition_shared - (cluster, cluster_partition, shared)\n14. jobs_cluster_partition_numnodes - (cluster, cluster_partition, num_nodes)\n\n**CLUSTER+PARTITION** (10 indexes):\n15. jobs_cluster_partition_numhwthreads - (cluster, cluster_partition, num_hwthreads)\n16. jobs_cluster_partition_numacc - (cluster, cluster_partition, num_acc)\n17. jobs_cluster_partition_energy - (cluster, cluster_partition, energy)\n18. jobs_cluster_partition_duration_starttime - (cluster, cluster_partition, duration, start_time)\n19. jobs_cluster_partition_starttime_duration - (cluster, cluster_partition, start_time, duration)\n20. jobs_cluster_jobstate_user - (cluster, job_state, hpc_user)\n21. jobs_cluster_jobstate_project - (cluster, job_state, project)\n22. jobs_cluster_jobstate_numnodes - (cluster, job_state, num_nodes)\n23. jobs_cluster_jobstate_numhwthreads - (cluster, job_state, num_hwthreads)\n24. jobs_cluster_jobstate_numacc - (cluster, job_state, num_acc)\n\n**CLUSTER+JOBSTATE** (8 indexes):\n25. jobs_cluster_jobstate_energy - (cluster, job_state, energy)\n26. jobs_cluster_jobstate_starttime_duration - (cluster, job_state, start_time, duration)\n27. jobs_cluster_jobstate_duration_starttime - (cluster, job_state, duration, start_time)\n28. jobs_cluster_shared_user - (cluster, shared, hpc_user)\n29. jobs_cluster_shared_project - (cluster, shared, project)\n30. jobs_cluster_shared_numnodes - (cluster, shared, num_nodes)\n31. jobs_cluster_shared_numhwthreads - (cluster, shared, num_hwthreads)\n32. jobs_cluster_shared_numacc - (cluster, shared, num_acc)\n\n**CLUSTER+SHARED** (8 indexes):\n33. jobs_cluster_shared_energy - (cluster, shared, energy)\n34. jobs_cluster_shared_starttime_duration - (cluster, shared, start_time, duration)\n35. jobs_cluster_shared_duration_starttime - (cluster, shared, duration, start_time)\n36. jobs_user_numnodes - (hpc_user, num_nodes)\n37. jobs_user_numhwthreads - (hpc_user, num_hwthreads)\n38. jobs_user_numacc - (hpc_user, num_acc)\n39. jobs_user_energy - (hpc_user, energy)\n40. jobs_user_starttime_duration - (hpc_user, start_time, duration)\n\n**HPC_USER** (8 indexes):\n41. jobs_user_duration_starttime - (hpc_user, duration, start_time)\n42. jobs_project_user - (project, hpc_user)\n43. jobs_project_numnodes - (project, num_nodes)\n44. jobs_project_numhwthreads - (project, num_hwthreads)\n45. jobs_project_numacc - (project, num_acc)\n46. jobs_project_energy - (project, energy)\n47. jobs_project_starttime_duration - (project, start_time, duration)\n48. jobs_project_duration_starttime - (project, duration, start_time)\n\n**PROJECT** (8 indexes):\n49. jobs_jobstate_user - (job_state, hpc_user)\n50. jobs_jobstate_project - (job_state, project)\n51. jobs_jobstate_numnodes - (job_state, num_nodes)\n52. jobs_jobstate_numhwthreads - (job_state, num_hwthreads)\n53. jobs_jobstate_numacc - (job_state, num_acc)\n54. jobs_jobstate_energy - (job_state, energy)\n55. jobs_jobstate_starttime_duration - (job_state, start_time, duration)\n56. jobs_jobstate_duration_starttime - (job_state, duration, start_time)\n\n**JOB_STATE** (8 indexes):\n57. jobs_shared_user - (shared, hpc_user)\n58. jobs_shared_project - (shared, project)\n59. jobs_shared_numnodes - (shared, num_nodes)\n60. jobs_shared_numhwthreads - (shared, num_hwthreads)\n61. jobs_shared_numacc - (shared, num_acc)\n62. jobs_shared_energy - (shared, energy)\n63. jobs_shared_starttime_duration - (shared, start_time, duration)\n64. jobs_shared_duration_starttime - (shared, duration, start_time)\n\n**SHARED** (8 indexes):\n65. jobs_arrayjobid_starttime - (array_job_id, start_time)\n66. jobs_cluster_arrayjobid_starttime - (cluster, array_job_id, start_time)\n67. jobs_duration_starttime - (duration, start_time)\n68. jobs_numnodes_starttime - (num_nodes, start_time)\n69. jobs_numhwthreads_starttime - (num_hwthreads, start_time)\n70. jobs_numacc_starttime - (num_acc, start_time)\n71. jobs_energy_starttime - (energy, start_time)\n72. jobs_starttime_duration - (start_time, duration)\n\n**ARRAY_JOB_ID / SINGLE COLUMN SORTS** (8 indexes):\n73. jobs_numnodes_duration - (num_nodes, duration)\n74. jobs_numhwthreads_duration - (num_hwthreads, duration)\n75. jobs_numacc_duration - (num_acc, duration)\n76. jobs_energy_duration - (energy, duration)\n77. jobs_starttime - (start_time) — backup index\n78. jobs_duration - (duration) — backup index\n\n### KEY OBSERVATIONS\n\n1. **76 CREATE INDEX statements** across migrations 02, 04, 08, and 09\n2. **Composite indexes dominate** - most are 2-4 column indexes to support filtering + sorting combinations\n3. **Covering pattern**: Many indexes include sorting columns (start_time, duration) as covered columns\n4. **Leading columns**: cluster (heavily used), hpc_user, project, job_state, shared, array_job_id, duration, num_nodes, num_hwthreads, num_acc, energy\n5. **Sorting columns**: start_time and duration appear in 30+ indexes as included columns\n6. **Migration 08** introduced the comprehensive index strategy with 98 CREATE INDEX statements\n7. **Migration 09** refined the indexes when renaming columns and adding the `shared` column, optimizing away some redundant indexes and restructuring the index set to 76 final indexes\n\nThe current schema follows a **query-driven indexing strategy** where each common filter combination with its default sort gets its own index to optimize query plans."}],"totalDurationMs":21471,"totalTokens":31547,"totalToolUseCount":11,"usage":{"input_tokens":6,"cache_creation_input_tokens":11660,"cache_read_input_tokens":17378,"output_tokens":2503,"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":11660},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"b426fff6-7428-4ea1-9f65-0abfd65c6d7d"}
+{"parentUuid":"c699f5dc-b0e5-45a4-9295-43eaace5b998","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","toolUseID":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","timestamp":"2026-03-11T04:32:51.740Z","uuid":"fe91fbcf-28d1-40a3-9162-82933438d168"}
+{"parentUuid":"9a8aebfd-9e7b-4bb4-97d0-6790df9b12d6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MJqptZJ5SuaZVBxAKZ1svX","type":"tool_result","content":[{"type":"text","text":"Perfect! Now I have a comprehensive understanding of all query patterns. Let me compile the complete analysis:\n\n## COMPREHENSIVE JOB TABLE QUERY ANALYSIS FOR INDEX OPTIMIZATION\n\n### Overview\nThe `job` table in this 20M row database is queried through multiple access patterns across 9 repository files. I've identified **28 distinct query sites** with varying WHERE, ORDER BY, GROUP BY, JOIN, and LIMIT patterns.\n\n---\n\n## 1. MAIN QUERYING FUNCTIONS (jobQuery.go)\n\n### QueryJobs - Security-controlled list with filtering, pagination, sorting\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` (line 42)\n- **Query Type:** SELECT with filters, pagination, sorting\n- **FROM:** `FROM job`\n- **WHERE Columns:** (from BuildWhereClause - see section below)\n- **ORDER BY:** Dynamic columns via `order.Field` (user, project, duration, etc.) OR JSON_EXTRACT on footprint\n- **LIMIT/PAGINATION:** Yes - `LIMIT` and `OFFSET`\n- **JOINs:** `JOIN jobtag ON jobtag.job_id = job.id` (conditional, when tag filtering)\n- **GROUP BY:** `DISTINCT` when joined with jobtag\n- **Critical:** Security checks apply, respects user roles\n\n### CountJobs - Count matching jobs (for pagination)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` (line 115)\n- **Query Type:** COUNT(DISTINCT job.id)\n- **FROM:** `FROM job`\n- **WHERE Columns:** Same as QueryJobs (applies BuildWhereClause)\n- **JOINs:** `JOIN jobtag` (conditional, for tag filtering)\n- **GROUP BY:** DISTINCT (when tags involved)\n- **Purpose:** Pagination total count\n\n---\n\n## 2. BUILD WHERE CLAUSE - ALL POSSIBLE FILTER COLUMNS (jobQuery.go line 182)\n\nThis function builds WHERE conditions from filters. Here are ALL filter columns accessed:\n\n| Column Name | Filter Type | Index? | Usage |\n|------------|-------------|--------|-------|\n| `job.id` | Primary Key lookup | **YES (PK)** | filter.DbID |\n| `job.cluster` | String equality/LIKE | **CONSIDER** | Direct filter, JOIN target |\n| `job.subcluster` | String equality/LIKE | **CONSIDER** | Geographic partitioning |\n| `job.cluster_partition` | String equality/LIKE | **OPTIONAL** | Partition filtering |\n| `job.job_state` | IN list | **CRITICAL** | Running/completed distinction |\n| `job.shared` | Boolean | **OPTIONAL** | Shared job filtering |\n| `job.project` | String equality/LIKE | **CONSIDER** | Project-scoped access |\n| `job.hpc_user` | String equality/LIKE | **CRITICAL** | Security: user-scoped access |\n| `job.num_nodes` | Range (BETWEEN/>=/<) | **OPTIONAL** | Resource filtering |\n| `job.num_hwthreads` | Range (BETWEEN/>=/<) | **OPTIONAL** | Core count filtering |\n| `job.num_acc` | Range (BETWEEN/>=/<) | **OPTIONAL** | Accelerator filtering |\n| `job.array_job_id` | Direct equality | **OPTIONAL** | Array job grouping |\n| `job.start_time` | Range/relative time | **CRITICAL** | Time filtering (last6h, last30d, etc.) |\n| `job.duration` | Range (BETWEEN/>=/<) | **OPTIONAL** | Duration filtering |\n| `job.energy` | Range (BETWEEN/>=/<) | **OPTIONAL** | Energy filtering |\n| **JSON columns:** | | | |\n| `job.footprint` | JSON_EXTRACT | **OPTIONAL** | Metric statistics in JSON |\n| `job.meta_data` | JSON_EXTRACT | **OPTIONAL** | Job name, interactive flag |\n| `job.resources` | json_each() EXISTS | **OPTIONAL** | Hostname lookup via JSON array |\n\n**Additional Complex Filters:**\n- `job.job_state` + `job.start_time` (MinRunningFor - recent job filtering)\n- Tag-based filtering via JOIN jobtag table\n\n---\n\n## 3. FIND/LOOKUP QUERIES (jobFind.go)\n\n### Find - Single job by job_id + cluster + start_time\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 25)\n- **WHERE:** `job.job_id`, `job.cluster`, `job.start_time` (optional)\n- **ORDER BY:** `job.id DESC`\n- **LIMIT:** 1\n- **Purpose:** Exact job lookup by SLURM credentials\n\n### FindCached - Same but from job_cache table\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 57)\n- **Same pattern as Find but on job_cache table**\n\n### FindAll - All jobs matching job_id + cluster + start_time\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 86)\n- **WHERE:** Same as Find\n- **No LIMIT, returns all matches**\n\n### GetJobList - IDs of non-running jobs (for archiving)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 130)\n- **WHERE:** `job.job_state != 'running'`\n- **LIMIT/OFFSET:** Yes (pagination for batch processing)\n- **Returns:** Job IDs only\n\n### FindByID - Single job by database ID\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 165)\n- **WHERE:** `job.id = ?` (PK)\n- **Security:** Applies SecurityCheck\n\n### FindByIDDirect - Same without security checks\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 198)\n- **WHERE:** `job.id = ?`\n- **No security checks**\n\n### FindByJobID - Job by job_id + cluster + start_time with security\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 208)\n- **WHERE:** All three: `job.job_id`, `job.cluster`, `job.start_time`\n- **Security:** Applies SecurityCheck\n\n### IsJobOwner - Check user ownership\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 227)\n- **WHERE:** `job.job_id`, `job.hpc_user`, `job.cluster`, `job.start_time`\n- **Returns:** Boolean\n\n### FindConcurrentJobs - Complex overlapping job query\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 242)\n- **WHERE Columns:** `job.cluster`, `job.job_state`, `job.start_time`, `job.duration`, plus JSON resource matching\n- **WHERE Logic:** \n - For running jobs: `job.job_state = 'running'` AND `job.start_time <= stopTimeTail`\n - For completed: `job.job_state != 'running'` AND time overlap check + `(job.start_time + job.duration) > startTimeFront`\n - Plus: `EXISTS (json_each(job.resources)...)` for hostname matching\n- **Security:** Applies SecurityCheck\n- **Purpose:** Find jobs running on same node during overlapping time\n\n---\n\n## 4. STATISTICS & AGGREGATION QUERIES (stats.go)\n\n### JobsStatsGrouped - Aggregated stats grouped by dimension\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 208)\n- **GROUP BY:** `job.hpc_user` OR `job.project` OR `job.cluster` OR `job.subcluster`\n- **SELECT:** COUNT, SUM, aggregations with complex CASE for running jobs\n- **WHERE:** All filter columns via BuildWhereClause\n- **ORDER BY:** Dynamic by sort dimension (totalJobs, totalWalltime, totalCoreHours, etc.)\n- **LIMIT/OFFSET:** Yes (pagination)\n- **JOINs:** `LEFT JOIN hpc_user ON hpc_user.username = job.hpc_user`\n- **Purpose:** Dashboard statistics, user/project/cluster reports\n\n### JobsStats - Overall aggregation (no grouping)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 347)\n- **SELECT:** COUNT, SUM across all jobs\n- **WHERE:** All filter columns\n- **No GROUP BY, no LIMIT**\n- **Purpose:** Total system statistics\n\n### JobCountGrouped - Count only (lightweight)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 431)\n- **GROUP BY:** Same as JobsStatsGrouped\n- **WHERE:** Filter columns\n- **Purpose:** Count breakdown by group\n\n### AddJobCountGrouped - Augment stats with running/short job counts\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 490)\n- **WHERE:** GROUP BY column + special `kind`: \"running\" or \"short\"\n- **Additional Filter:** `job.job_state = 'running'` OR `job.duration < config.ShortRunningJobsDuration`\n\n### AddJobCount - Augment overall stats with counts\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 556)\n- **Same as AddJobCountGrouped but ungrouped**\n\n### jobsStatisticsHistogram - Histogram generation\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 741)\n- **GROUP BY:** value (computed column, e.g., `job.num_nodes`, `job.num_hwthreads`, `job.num_acc`)\n- **WHERE:** Via BuildWhereClause + Security\n- **Purpose:** Distribution visualization\n\n### jobsDurationStatisticsHistogram - Duration histogram\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 805)\n- **GROUP BY:** Computed bin from duration division\n- **WHERE:** Via BuildWhereClause + Security\n- **Purpose:** Duration distribution with zero-padded bins\n\n### jobsMetricStatisticsHistogram - Metric footprint histogram\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 886)\n- **WHERE:** \n - `job.footprint` JSON_VALID check\n - JSON_EXTRACT condition on `job.footprint`\n - Via BuildWhereClause + Security\n- **GROUP BY:** Computed bin from JSON value\n- **ORDER BY:** bin ASC\n- **Purpose:** Metric distribution for completed jobs\n\n---\n\n## 5. SINGLE JOB METADATA QUERIES (job.go)\n\n### FetchMetadata - Get meta_data JSON for one job\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 238)\n- **SELECT:** `job.meta_data`\n- **WHERE:** `job.id = ?` (PK)\n- **Cached:** 24 hours\n\n### UpdateMetadata - Update one metadata field\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 296)\n- **WHERE:** `job.id = ?`\n\n### FetchFootprint - Get footprint JSON\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 325)\n- **WHERE:** `job.id = ?`\n- **Not cached**\n\n### FetchEnergyFootprint - Get energy_footprint JSON\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 366)\n- **WHERE:** `job.id = ?`\n- **Cached:** 24 hours\n\n---\n\n## 6. DELETION & ARCHIVE QUERIES (job.go)\n\n### DeleteJobsBefore - Delete jobs older than timestamp\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 399)\n- **WHERE:** \n - `job.start_time < ?` (CRITICAL for deletion)\n - Optional: `NOT EXISTS (SELECT 1 FROM jobtag...)` depending on `omitTagged` mode\n- **Two queries:** COUNT first, then SELECT for cache invalidation, then DELETE\n\n### DeleteJobByID - Delete single job\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 470)\n- **WHERE:** `job.id = ?`\n\n---\n\n## 7. SEARCH & LOOKUP QUERIES (job.go)\n\n### FindUserOrProjectOrJobname - Flexible search\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 505)\n- **Calls FindColumnValue on job/hpc_user tables**\n\n### FindColumnValue - Generic column lookup\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 553)\n- **WHERE:** `table.whereColumn = ? OR table.whereColumn LIKE ?`\n- **SELECT:** `table.selectColumn`\n- **DISTINCT:** Yes\n- **Authorization:** Admin/Support/Manager only\n\n### FindColumnValues - Multi-result column lookup\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 596)\n- **WHERE:** `table.whereColumn LIKE ?`\n- **Returns:** All matches\n\n### Partitions - Get cluster partitions\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 637)\n- **WHERE:** `job.cluster = ?`\n- **SELECT DISTINCT:** `job.cluster_partition`\n- **Cached:** 1 hour\n\n### AllocatedNodes - Node usage query\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 657)\n- **WHERE:** `job.job_state = 'running'` AND `job.cluster = ?`\n- **SELECT:** `job.resources`, `job.subcluster`\n- **Purpose:** Count jobs per node\n\n---\n\n## 8. RUNNING JOB QUERIES (job.go)\n\n### FindRunningJobs - Get running jobs for a cluster\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 781)\n- **WHERE:** `job.cluster = ?` AND `job.job_state = 'running'` AND `job.duration > repoConfig.MinRunningJobDuration`\n\n### StopJobsExceedingWalltimeBy - Mark stuck jobs as failed\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 712)\n- **UPDATE query with WHERE:** `job.job_state = 'running'` AND `job.walltime > 0` AND `job.start_time < (? - job.walltime)`\n\n### UpdateDuration - Update duration for running jobs\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 814)\n- **UPDATE with WHERE:** `job_state = 'running'`\n\n---\n\n## 9. TIME RANGE & BATCH QUERIES (job.go)\n\n### FindJobsBetween - Get jobs in time range\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 839)\n- **WHERE:** `job.start_time < endTime` OR `job.start_time BETWEEN beginTime AND endTime`\n- **Optional:** NOT EXISTS for jobtag filtering\n- **ORDER BY:** `job.cluster ASC, job.subcluster ASC, job.project ASC, job.start_time ASC`\n- **Purpose:** Archiving, data export\n\n### GetUsedNodes - Get running nodes before timestamp\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 1065)\n- **WHERE:** `job.start_time < ?` AND `job.job_state = 'running'`\n- **SELECT:** `job.cluster, job.resources`\n\n---\n\n## 10. TAG-RELATED QUERIES (tags.go, job.go)\n\n### FindJobIdsByTag - Get all jobs with a tag\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 747)\n- **WHERE:** Via `JOIN jobtag ON jobtag.job_id = job.id`\n- **WHERE:** `jobtag.tag_id = ?`\n- **SELECT DISTINCT:** `job.id`\n- **Purpose:** Tag deletion cascade\n\n### CountTags - Count jobs per tag\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/tags.go` (line 280)\n- **FROM:** `tag t LEFT JOIN jobtag jt ON t.id = jt.tag_id`\n- **WHERE:** `jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ? OR job.project IN (...))`\n- **GROUP BY:** tag columns\n- **Purpose:** Dashboard tag usage\n\n---\n\n## RECOMMENDED INDEX STRATEGY FOR 20M ROWS\n\nBased on this comprehensive analysis, here's the recommended indexing strategy:\n\n### CRITICAL INDEXES (Create First)\n```sql\n-- 1. job_state is queried in nearly every stats query\nCREATE INDEX idx_job_job_state ON job(job_state);\n\n-- 2. hpc_user is critical for security/filtering AND heavily used\nCREATE INDEX idx_job_hpc_user ON job(hpc_user);\n\n-- 3. start_time is used for ALL time-based filtering and range queries\nCREATE INDEX idx_job_start_time ON job(start_time);\n\n-- 4. cluster is frequently filtered and used for geographic partitioning\nCREATE INDEX idx_job_cluster ON job(cluster);\n```\n\n### HIGH PRIORITY INDEXES\n```sql\n-- 5. Composite for FindConcurrentJobs overlap detection (very complex query)\nCREATE INDEX idx_job_cluster_state_starttime ON job(cluster, job_state, start_time);\n\n-- 6. Project filtering for access control\nCREATE INDEX idx_job_project ON job(project);\n\n-- 7. Partitions query (DISTINCT on cluster_partition by cluster)\nCREATE INDEX idx_job_cluster_partition ON job(cluster, cluster_partition);\n\n-- 8. Subcluster for AllocatedNodes query\nCREATE INDEX idx_job_subcluster ON job(subcluster);\n\n-- 9. Composite for GetUsedNodes query (start_time < ? AND job_state = 'running')\nCREATE INDEX idx_job_running_nodes ON job(job_state, start_time);\n```\n\n### MEDIUM PRIORITY INDEXES\n```sql\n-- 10. Duration filtering (exists in multiple queries)\nCREATE INDEX idx_job_duration ON job(duration);\n\n-- 11. Array job grouping\nCREATE INDEX idx_job_array_job_id ON job(array_job_id);\n\n-- 12. Walltime for StopJobsExceedingWalltimeBy\nCREATE INDEX idx_job_walltime ON job(walltime);\n\n-- 13. Job ID lookup (for Find operations)\nCREATE INDEX idx_job_job_id ON job(job_id);\n\n-- 14. Energy for energy-based filtering\nCREATE INDEX idx_job_energy ON job(energy);\n\n-- 15. Composite for DeleteJobsBefore (very frequently called)\nCREATE INDEX idx_job_start_time_state ON job(start_time, job_state);\n```\n\n### JSON INDEXES (Optional, for large deployments)\n```sql\n-- For meta_data JSON queries (jobName, interactive filtering)\nCREATE INDEX idx_job_meta_data_jobname ON job(\n json_extract(meta_data, '$.jobName')\n);\n\n-- For footprint JSON histogram queries\nCREATE INDEX idx_job_footprint_valid ON job(\n json_extract(footprint, '$.cpu_load_avg')\n) WHERE json_valid(footprint);\n\n-- For resources JSON array queries (hostname lookup)\nCREATE INDEX idx_job_resources_hostname ON job(\n json_extract(resources, '$[0].hostname')\n) WHERE json_valid(resources);\n```\n\n### COMPOSITE INDEXES FOR COMMON QUERY PATTERNS\n```sql\n-- SecurityCheck + common filter combo\nCREATE INDEX idx_job_hpc_user_cluster_state ON job(hpc_user, cluster, job_state);\n\n-- Stats queries: GROUP BY column + filter columns\nCREATE INDEX idx_job_cluster_state_starttime_project ON job(\n cluster, job_state, start_time, project\n);\n\nCREATE INDEX idx_job_project_state_starttime ON job(\n project, job_state, start_time\n);\n\n-- Pagination: ORDER BY + LIMIT pattern\nCREATE INDEX idx_job_start_time_desc ON job(start_time DESC);\n```\n\n---\n\n## QUERY HOTSPOTS SUMMARY\n\n**Hottest Query Patterns (prioritize these):**\n1. **QueryJobs + CountJobs** - Core UI query, high concurrency, multiple WHERE conditions\n2. **JobsStatsGrouped** - Dashboard, aggregation on millions of rows\n3. **FindConcurrentJobs** - Complex overlap detection, multiple WHERE conditions + JSON\n4. **DeleteJobsBefore** - Batch operation, scans large time ranges\n5. **FindRunningJobs** - Periodic monitoring, filters on state + duration\n6. **AllocatedNodes** - Node inventory, JSON parsing\n\n**Security-critical columns (always indexed):**\n- `job.hpc_user` (access control)\n- `job.project` (access control)\n\n**Time-critical columns (always indexed):**\n- `job.start_time` (all historical queries)\n- `job.job_state` (running vs. archived distinction)\n\n**Resource-critical columns (indexed as secondary):**\n- `job.cluster`, `job.subcluster`\n- `job.num_nodes`, `job.num_acc`, `job.num_hwthreads`\n\n---\n\nThis analysis covers 28 distinct query sites across 9 files with complete WHERE, ORDER BY, GROUP BY, JOIN, and pagination patterns for your 20M row job table."},{"type":"text","text":"agentId: a97d0003ebdc3eccd (for resuming to continue this agent's work if needed)\ntotal_tokens: 84745\ntool_uses: 14\nduration_ms: 61574"}]}]},"uuid":"02d04de4-4d3a-4aa6-a488-8d40e2cf99f6","timestamp":"2026-03-11T04:32:51.740Z","toolUseResult":{"status":"completed","prompt":"In /Users/jan/prg/CC/cc-backend, I need to understand ALL query patterns that hit the `job` table. This is for index optimization on a 20M row table.\n\nSearch thoroughly for:\n\n1. **All SQL queries on the job table** - search for `.From(\"job\")`, `FROM job`, `from(\"job\")` in all .go files\n2. **All WHERE clause builders** - read `internal/repository/jobQuery.go` fully, especially `BuildWhereClause` to understand all possible filter columns\n3. **All ORDER BY patterns** - search for `OrderBy`, `ORDER BY` related to jobs\n4. **All GROUP BY patterns** - search for `GroupBy`, `GROUP BY` related to jobs\n5. **All JOIN patterns** - search for joins on the job table (jobtag, etc.)\n\nFor each query site, report:\n- File and function name\n- WHERE columns used\n- ORDER BY columns used \n- Whether it has LIMIT/pagination\n- Whether it uses GROUP BY\n\nBe very thorough - check jobQuery.go, job.go, jobFind.go, jobCreate.go, stats.go, tags.go, and any other files that query the job table.","agentId":"a97d0003ebdc3eccd","content":[{"type":"text","text":"Perfect! Now I have a comprehensive understanding of all query patterns. Let me compile the complete analysis:\n\n## COMPREHENSIVE JOB TABLE QUERY ANALYSIS FOR INDEX OPTIMIZATION\n\n### Overview\nThe `job` table in this 20M row database is queried through multiple access patterns across 9 repository files. I've identified **28 distinct query sites** with varying WHERE, ORDER BY, GROUP BY, JOIN, and LIMIT patterns.\n\n---\n\n## 1. MAIN QUERYING FUNCTIONS (jobQuery.go)\n\n### QueryJobs - Security-controlled list with filtering, pagination, sorting\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` (line 42)\n- **Query Type:** SELECT with filters, pagination, sorting\n- **FROM:** `FROM job`\n- **WHERE Columns:** (from BuildWhereClause - see section below)\n- **ORDER BY:** Dynamic columns via `order.Field` (user, project, duration, etc.) OR JSON_EXTRACT on footprint\n- **LIMIT/PAGINATION:** Yes - `LIMIT` and `OFFSET`\n- **JOINs:** `JOIN jobtag ON jobtag.job_id = job.id` (conditional, when tag filtering)\n- **GROUP BY:** `DISTINCT` when joined with jobtag\n- **Critical:** Security checks apply, respects user roles\n\n### CountJobs - Count matching jobs (for pagination)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` (line 115)\n- **Query Type:** COUNT(DISTINCT job.id)\n- **FROM:** `FROM job`\n- **WHERE Columns:** Same as QueryJobs (applies BuildWhereClause)\n- **JOINs:** `JOIN jobtag` (conditional, for tag filtering)\n- **GROUP BY:** DISTINCT (when tags involved)\n- **Purpose:** Pagination total count\n\n---\n\n## 2. BUILD WHERE CLAUSE - ALL POSSIBLE FILTER COLUMNS (jobQuery.go line 182)\n\nThis function builds WHERE conditions from filters. Here are ALL filter columns accessed:\n\n| Column Name | Filter Type | Index? | Usage |\n|------------|-------------|--------|-------|\n| `job.id` | Primary Key lookup | **YES (PK)** | filter.DbID |\n| `job.cluster` | String equality/LIKE | **CONSIDER** | Direct filter, JOIN target |\n| `job.subcluster` | String equality/LIKE | **CONSIDER** | Geographic partitioning |\n| `job.cluster_partition` | String equality/LIKE | **OPTIONAL** | Partition filtering |\n| `job.job_state` | IN list | **CRITICAL** | Running/completed distinction |\n| `job.shared` | Boolean | **OPTIONAL** | Shared job filtering |\n| `job.project` | String equality/LIKE | **CONSIDER** | Project-scoped access |\n| `job.hpc_user` | String equality/LIKE | **CRITICAL** | Security: user-scoped access |\n| `job.num_nodes` | Range (BETWEEN/>=/<) | **OPTIONAL** | Resource filtering |\n| `job.num_hwthreads` | Range (BETWEEN/>=/<) | **OPTIONAL** | Core count filtering |\n| `job.num_acc` | Range (BETWEEN/>=/<) | **OPTIONAL** | Accelerator filtering |\n| `job.array_job_id` | Direct equality | **OPTIONAL** | Array job grouping |\n| `job.start_time` | Range/relative time | **CRITICAL** | Time filtering (last6h, last30d, etc.) |\n| `job.duration` | Range (BETWEEN/>=/<) | **OPTIONAL** | Duration filtering |\n| `job.energy` | Range (BETWEEN/>=/<) | **OPTIONAL** | Energy filtering |\n| **JSON columns:** | | | |\n| `job.footprint` | JSON_EXTRACT | **OPTIONAL** | Metric statistics in JSON |\n| `job.meta_data` | JSON_EXTRACT | **OPTIONAL** | Job name, interactive flag |\n| `job.resources` | json_each() EXISTS | **OPTIONAL** | Hostname lookup via JSON array |\n\n**Additional Complex Filters:**\n- `job.job_state` + `job.start_time` (MinRunningFor - recent job filtering)\n- Tag-based filtering via JOIN jobtag table\n\n---\n\n## 3. FIND/LOOKUP QUERIES (jobFind.go)\n\n### Find - Single job by job_id + cluster + start_time\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 25)\n- **WHERE:** `job.job_id`, `job.cluster`, `job.start_time` (optional)\n- **ORDER BY:** `job.id DESC`\n- **LIMIT:** 1\n- **Purpose:** Exact job lookup by SLURM credentials\n\n### FindCached - Same but from job_cache table\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 57)\n- **Same pattern as Find but on job_cache table**\n\n### FindAll - All jobs matching job_id + cluster + start_time\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 86)\n- **WHERE:** Same as Find\n- **No LIMIT, returns all matches**\n\n### GetJobList - IDs of non-running jobs (for archiving)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 130)\n- **WHERE:** `job.job_state != 'running'`\n- **LIMIT/OFFSET:** Yes (pagination for batch processing)\n- **Returns:** Job IDs only\n\n### FindByID - Single job by database ID\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 165)\n- **WHERE:** `job.id = ?` (PK)\n- **Security:** Applies SecurityCheck\n\n### FindByIDDirect - Same without security checks\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 198)\n- **WHERE:** `job.id = ?`\n- **No security checks**\n\n### FindByJobID - Job by job_id + cluster + start_time with security\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 208)\n- **WHERE:** All three: `job.job_id`, `job.cluster`, `job.start_time`\n- **Security:** Applies SecurityCheck\n\n### IsJobOwner - Check user ownership\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 227)\n- **WHERE:** `job.job_id`, `job.hpc_user`, `job.cluster`, `job.start_time`\n- **Returns:** Boolean\n\n### FindConcurrentJobs - Complex overlapping job query\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/jobFind.go` (line 242)\n- **WHERE Columns:** `job.cluster`, `job.job_state`, `job.start_time`, `job.duration`, plus JSON resource matching\n- **WHERE Logic:** \n - For running jobs: `job.job_state = 'running'` AND `job.start_time <= stopTimeTail`\n - For completed: `job.job_state != 'running'` AND time overlap check + `(job.start_time + job.duration) > startTimeFront`\n - Plus: `EXISTS (json_each(job.resources)...)` for hostname matching\n- **Security:** Applies SecurityCheck\n- **Purpose:** Find jobs running on same node during overlapping time\n\n---\n\n## 4. STATISTICS & AGGREGATION QUERIES (stats.go)\n\n### JobsStatsGrouped - Aggregated stats grouped by dimension\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 208)\n- **GROUP BY:** `job.hpc_user` OR `job.project` OR `job.cluster` OR `job.subcluster`\n- **SELECT:** COUNT, SUM, aggregations with complex CASE for running jobs\n- **WHERE:** All filter columns via BuildWhereClause\n- **ORDER BY:** Dynamic by sort dimension (totalJobs, totalWalltime, totalCoreHours, etc.)\n- **LIMIT/OFFSET:** Yes (pagination)\n- **JOINs:** `LEFT JOIN hpc_user ON hpc_user.username = job.hpc_user`\n- **Purpose:** Dashboard statistics, user/project/cluster reports\n\n### JobsStats - Overall aggregation (no grouping)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 347)\n- **SELECT:** COUNT, SUM across all jobs\n- **WHERE:** All filter columns\n- **No GROUP BY, no LIMIT**\n- **Purpose:** Total system statistics\n\n### JobCountGrouped - Count only (lightweight)\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 431)\n- **GROUP BY:** Same as JobsStatsGrouped\n- **WHERE:** Filter columns\n- **Purpose:** Count breakdown by group\n\n### AddJobCountGrouped - Augment stats with running/short job counts\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 490)\n- **WHERE:** GROUP BY column + special `kind`: \"running\" or \"short\"\n- **Additional Filter:** `job.job_state = 'running'` OR `job.duration < config.ShortRunningJobsDuration`\n\n### AddJobCount - Augment overall stats with counts\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 556)\n- **Same as AddJobCountGrouped but ungrouped**\n\n### jobsStatisticsHistogram - Histogram generation\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 741)\n- **GROUP BY:** value (computed column, e.g., `job.num_nodes`, `job.num_hwthreads`, `job.num_acc`)\n- **WHERE:** Via BuildWhereClause + Security\n- **Purpose:** Distribution visualization\n\n### jobsDurationStatisticsHistogram - Duration histogram\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 805)\n- **GROUP BY:** Computed bin from duration division\n- **WHERE:** Via BuildWhereClause + Security\n- **Purpose:** Duration distribution with zero-padded bins\n\n### jobsMetricStatisticsHistogram - Metric footprint histogram\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` (line 886)\n- **WHERE:** \n - `job.footprint` JSON_VALID check\n - JSON_EXTRACT condition on `job.footprint`\n - Via BuildWhereClause + Security\n- **GROUP BY:** Computed bin from JSON value\n- **ORDER BY:** bin ASC\n- **Purpose:** Metric distribution for completed jobs\n\n---\n\n## 5. SINGLE JOB METADATA QUERIES (job.go)\n\n### FetchMetadata - Get meta_data JSON for one job\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 238)\n- **SELECT:** `job.meta_data`\n- **WHERE:** `job.id = ?` (PK)\n- **Cached:** 24 hours\n\n### UpdateMetadata - Update one metadata field\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 296)\n- **WHERE:** `job.id = ?`\n\n### FetchFootprint - Get footprint JSON\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 325)\n- **WHERE:** `job.id = ?`\n- **Not cached**\n\n### FetchEnergyFootprint - Get energy_footprint JSON\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 366)\n- **WHERE:** `job.id = ?`\n- **Cached:** 24 hours\n\n---\n\n## 6. DELETION & ARCHIVE QUERIES (job.go)\n\n### DeleteJobsBefore - Delete jobs older than timestamp\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 399)\n- **WHERE:** \n - `job.start_time < ?` (CRITICAL for deletion)\n - Optional: `NOT EXISTS (SELECT 1 FROM jobtag...)` depending on `omitTagged` mode\n- **Two queries:** COUNT first, then SELECT for cache invalidation, then DELETE\n\n### DeleteJobByID - Delete single job\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 470)\n- **WHERE:** `job.id = ?`\n\n---\n\n## 7. SEARCH & LOOKUP QUERIES (job.go)\n\n### FindUserOrProjectOrJobname - Flexible search\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 505)\n- **Calls FindColumnValue on job/hpc_user tables**\n\n### FindColumnValue - Generic column lookup\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 553)\n- **WHERE:** `table.whereColumn = ? OR table.whereColumn LIKE ?`\n- **SELECT:** `table.selectColumn`\n- **DISTINCT:** Yes\n- **Authorization:** Admin/Support/Manager only\n\n### FindColumnValues - Multi-result column lookup\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 596)\n- **WHERE:** `table.whereColumn LIKE ?`\n- **Returns:** All matches\n\n### Partitions - Get cluster partitions\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 637)\n- **WHERE:** `job.cluster = ?`\n- **SELECT DISTINCT:** `job.cluster_partition`\n- **Cached:** 1 hour\n\n### AllocatedNodes - Node usage query\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 657)\n- **WHERE:** `job.job_state = 'running'` AND `job.cluster = ?`\n- **SELECT:** `job.resources`, `job.subcluster`\n- **Purpose:** Count jobs per node\n\n---\n\n## 8. RUNNING JOB QUERIES (job.go)\n\n### FindRunningJobs - Get running jobs for a cluster\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 781)\n- **WHERE:** `job.cluster = ?` AND `job.job_state = 'running'` AND `job.duration > repoConfig.MinRunningJobDuration`\n\n### StopJobsExceedingWalltimeBy - Mark stuck jobs as failed\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 712)\n- **UPDATE query with WHERE:** `job.job_state = 'running'` AND `job.walltime > 0` AND `job.start_time < (? - job.walltime)`\n\n### UpdateDuration - Update duration for running jobs\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 814)\n- **UPDATE with WHERE:** `job_state = 'running'`\n\n---\n\n## 9. TIME RANGE & BATCH QUERIES (job.go)\n\n### FindJobsBetween - Get jobs in time range\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 839)\n- **WHERE:** `job.start_time < endTime` OR `job.start_time BETWEEN beginTime AND endTime`\n- **Optional:** NOT EXISTS for jobtag filtering\n- **ORDER BY:** `job.cluster ASC, job.subcluster ASC, job.project ASC, job.start_time ASC`\n- **Purpose:** Archiving, data export\n\n### GetUsedNodes - Get running nodes before timestamp\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 1065)\n- **WHERE:** `job.start_time < ?` AND `job.job_state = 'running'`\n- **SELECT:** `job.cluster, job.resources`\n\n---\n\n## 10. TAG-RELATED QUERIES (tags.go, job.go)\n\n### FindJobIdsByTag - Get all jobs with a tag\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` (line 747)\n- **WHERE:** Via `JOIN jobtag ON jobtag.job_id = job.id`\n- **WHERE:** `jobtag.tag_id = ?`\n- **SELECT DISTINCT:** `job.id`\n- **Purpose:** Tag deletion cascade\n\n### CountTags - Count jobs per tag\n**File:** `/Users/jan/prg/CC/cc-backend/internal/repository/tags.go` (line 280)\n- **FROM:** `tag t LEFT JOIN jobtag jt ON t.id = jt.tag_id`\n- **WHERE:** `jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ? OR job.project IN (...))`\n- **GROUP BY:** tag columns\n- **Purpose:** Dashboard tag usage\n\n---\n\n## RECOMMENDED INDEX STRATEGY FOR 20M ROWS\n\nBased on this comprehensive analysis, here's the recommended indexing strategy:\n\n### CRITICAL INDEXES (Create First)\n```sql\n-- 1. job_state is queried in nearly every stats query\nCREATE INDEX idx_job_job_state ON job(job_state);\n\n-- 2. hpc_user is critical for security/filtering AND heavily used\nCREATE INDEX idx_job_hpc_user ON job(hpc_user);\n\n-- 3. start_time is used for ALL time-based filtering and range queries\nCREATE INDEX idx_job_start_time ON job(start_time);\n\n-- 4. cluster is frequently filtered and used for geographic partitioning\nCREATE INDEX idx_job_cluster ON job(cluster);\n```\n\n### HIGH PRIORITY INDEXES\n```sql\n-- 5. Composite for FindConcurrentJobs overlap detection (very complex query)\nCREATE INDEX idx_job_cluster_state_starttime ON job(cluster, job_state, start_time);\n\n-- 6. Project filtering for access control\nCREATE INDEX idx_job_project ON job(project);\n\n-- 7. Partitions query (DISTINCT on cluster_partition by cluster)\nCREATE INDEX idx_job_cluster_partition ON job(cluster, cluster_partition);\n\n-- 8. Subcluster for AllocatedNodes query\nCREATE INDEX idx_job_subcluster ON job(subcluster);\n\n-- 9. Composite for GetUsedNodes query (start_time < ? AND job_state = 'running')\nCREATE INDEX idx_job_running_nodes ON job(job_state, start_time);\n```\n\n### MEDIUM PRIORITY INDEXES\n```sql\n-- 10. Duration filtering (exists in multiple queries)\nCREATE INDEX idx_job_duration ON job(duration);\n\n-- 11. Array job grouping\nCREATE INDEX idx_job_array_job_id ON job(array_job_id);\n\n-- 12. Walltime for StopJobsExceedingWalltimeBy\nCREATE INDEX idx_job_walltime ON job(walltime);\n\n-- 13. Job ID lookup (for Find operations)\nCREATE INDEX idx_job_job_id ON job(job_id);\n\n-- 14. Energy for energy-based filtering\nCREATE INDEX idx_job_energy ON job(energy);\n\n-- 15. Composite for DeleteJobsBefore (very frequently called)\nCREATE INDEX idx_job_start_time_state ON job(start_time, job_state);\n```\n\n### JSON INDEXES (Optional, for large deployments)\n```sql\n-- For meta_data JSON queries (jobName, interactive filtering)\nCREATE INDEX idx_job_meta_data_jobname ON job(\n json_extract(meta_data, '$.jobName')\n);\n\n-- For footprint JSON histogram queries\nCREATE INDEX idx_job_footprint_valid ON job(\n json_extract(footprint, '$.cpu_load_avg')\n) WHERE json_valid(footprint);\n\n-- For resources JSON array queries (hostname lookup)\nCREATE INDEX idx_job_resources_hostname ON job(\n json_extract(resources, '$[0].hostname')\n) WHERE json_valid(resources);\n```\n\n### COMPOSITE INDEXES FOR COMMON QUERY PATTERNS\n```sql\n-- SecurityCheck + common filter combo\nCREATE INDEX idx_job_hpc_user_cluster_state ON job(hpc_user, cluster, job_state);\n\n-- Stats queries: GROUP BY column + filter columns\nCREATE INDEX idx_job_cluster_state_starttime_project ON job(\n cluster, job_state, start_time, project\n);\n\nCREATE INDEX idx_job_project_state_starttime ON job(\n project, job_state, start_time\n);\n\n-- Pagination: ORDER BY + LIMIT pattern\nCREATE INDEX idx_job_start_time_desc ON job(start_time DESC);\n```\n\n---\n\n## QUERY HOTSPOTS SUMMARY\n\n**Hottest Query Patterns (prioritize these):**\n1. **QueryJobs + CountJobs** - Core UI query, high concurrency, multiple WHERE conditions\n2. **JobsStatsGrouped** - Dashboard, aggregation on millions of rows\n3. **FindConcurrentJobs** - Complex overlap detection, multiple WHERE conditions + JSON\n4. **DeleteJobsBefore** - Batch operation, scans large time ranges\n5. **FindRunningJobs** - Periodic monitoring, filters on state + duration\n6. **AllocatedNodes** - Node inventory, JSON parsing\n\n**Security-critical columns (always indexed):**\n- `job.hpc_user` (access control)\n- `job.project` (access control)\n\n**Time-critical columns (always indexed):**\n- `job.start_time` (all historical queries)\n- `job.job_state` (running vs. archived distinction)\n\n**Resource-critical columns (indexed as secondary):**\n- `job.cluster`, `job.subcluster`\n- `job.num_nodes`, `job.num_acc`, `job.num_hwthreads`\n\n---\n\nThis analysis covers 28 distinct query sites across 9 files with complete WHERE, ORDER BY, GROUP BY, JOIN, and pagination patterns for your 20M row job table."}],"totalDurationMs":61574,"totalTokens":84745,"totalToolUseCount":14,"usage":{"input_tokens":2,"cache_creation_input_tokens":1320,"cache_read_input_tokens":77839,"output_tokens":5584,"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":1320},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"9a8aebfd-9e7b-4bb4-97d0-6790df9b12d6"}
+{"parentUuid":"02d04de4-4d3a-4aa6-a488-8d40e2cf99f6","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01Uo3RmUCWcDzniBufSrMyQp","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nExcellent data. Now let me verify the actual query plans for the most critical patterns and check a few details."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":9075,"cache_read_input_tokens":124895,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":9075},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYvfgCUN1SkEueWHi9i2w","type":"assistant","uuid":"08bc0ab2-c327-4d83-90db-d2898b7f9c96","timestamp":"2026-03-11T04:32:55.764Z"}
+{"parentUuid":"08bc0ab2-c327-4d83-90db-d2898b7f9c96","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01Uo3RmUCWcDzniBufSrMyQp","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01WkdUXJNWHTNwCB5amTSd8n","name":"Bash","input":{"command":"sqlite3 ./var/job.db \"\n-- Pattern 1: Default job list (multi-state + ORDER BY start_time DESC)\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_state IN ('completed', 'running', 'failed') ORDER BY job.start_time DESC LIMIT 50 OFFSET 0;\n\" && echo '===P2===' && sqlite3 ./var/job.db \"\n-- Pattern 2: Cluster + state + ORDER BY start_time\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state IN ('completed','running') ORDER BY job.start_time DESC LIMIT 50;\n\" && echo '===P3===' && sqlite3 ./var/job.db \"\n-- Pattern 3: User filter + ORDER BY start_time\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.hpc_user = 'alice' ORDER BY job.start_time DESC LIMIT 50;\n\" && echo '===P4===' && sqlite3 ./var/job.db \"\n-- Pattern 4: Stats aggregation with cluster + state\nEXPLAIN QUERY PLAN SELECT COUNT(job.id), SUM(job.duration) FROM job WHERE job.cluster = 'fritz' AND job.job_state = 'completed';\n\" && echo '===P5===' && sqlite3 ./var/job.db \"\n-- Pattern 5: Find by job_id + cluster + start_time (unique lookup)\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_id = 123 AND job.cluster = 'fritz' AND job.start_time = 1000 ORDER BY job.id DESC LIMIT 1;\n\" && echo '===P6===' && sqlite3 ./var/job.db \"\n-- Pattern 6: Running jobs for cluster\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state = 'running' AND job.duration > 300;\n\" && echo '===P7===' && sqlite3 ./var/job.db \"\n-- Pattern 7: Time range query\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.start_time BETWEEN 1700000000 AND 1710000000 ORDER BY job.cluster, job.subcluster, job.project, job.start_time;\n\" && echo '===P8===' && sqlite3 ./var/job.db \"\n-- Pattern 8: GroupBy user with cluster filter\nEXPLAIN QUERY PLAN SELECT job.hpc_user, COUNT(job.id) FROM job WHERE job.cluster = 'fritz' GROUP BY job.hpc_user;\n\" && echo '===P9===' && sqlite3 ./var/job.db \"\n-- Pattern 9: Concurrent jobs (overlap detection)\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state != 'running' AND job.start_time <= 1710000000 AND (job.start_time + job.duration) > 1700000000;\n\"","description":"Check query plans for 9 critical query patterns"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":9075,"cache_read_input_tokens":124895,"output_tokens":831,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":9075,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvfgCUN1SkEueWHi9i2w","type":"assistant","uuid":"0f736c01-7248-4d49-97bf-ab091dbb5488","timestamp":"2026-03-11T04:33:05.616Z"}
+{"parentUuid":"0f736c01-7248-4d49-97bf-ab091dbb5488","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WkdUXJNWHTNwCB5amTSd8n","type":"tool_result","content":"QUERY PLAN\n`--SCAN job USING INDEX jobs_starttime\n===P2===\nQUERY PLAN\n`--SEARCH job USING INDEX jobs_cluster_starttime_duration (cluster=?)\n===P3===\nQUERY PLAN\n`--SEARCH job USING INDEX jobs_user_starttime_duration (hpc_user=?)\n===P4===\nQUERY PLAN\n`--SEARCH job USING COVERING INDEX jobs_cluster_jobstate_duration_starttime (cluster=? AND job_state=?)\n===P5===\nQUERY PLAN\n`--SEARCH job USING INDEX sqlite_autoindex_job_1 (job_id=? AND cluster=? AND start_time=?)\n===P6===\nQUERY PLAN\n`--SEARCH job USING INDEX jobs_cluster_jobstate_duration_starttime (cluster=? AND job_state=? AND duration>?)\n===P7===\nQUERY PLAN\n|--SEARCH job USING INDEX jobs_starttime (start_time>? AND start_time?)\n===P7===\nQUERY PLAN\n|--SEARCH job USING INDEX jobs_starttime (start_time>? AND start_time?)` ✓\n7. **Time range**: → `SEARCH jobs_starttime (start_time BETWEEN)` ✓ (temp b-tree for multi-col ORDER BY is acceptable)\n8. **Group by user with cluster**: → `SEARCH COVERING jobs_cluster_user (cluster=?)` ✓\n9. **Concurrent jobs**: → `SEARCH jobs_cluster_starttime_duration (cluster=? AND start_time?)` ✓\n7. **Time range**: → `SEARCH jobs_starttime (start_time BETWEEN)` ✓ (temp b-tree for multi-col ORDER BY is acceptable)\n8. **Group by user with cluster**: → `SEARCH COVERING jobs_cluster_user (cluster=?)` ✓\n9. **Concurrent jobs**: → `SEARCH jobs_cluster_starttime_duration (cluster=? AND start_time?)` ✓\n7. **Time range**: → `SEARCH jobs_starttime (start_time BETWEEN)` ✓ (temp b-tree for multi-col ORDER BY is acceptable)\n8. **Group by user with cluster**: → `SEARCH COVERING jobs_cluster_user (cluster=?)` ✓\n9. **Concurrent jobs**: → `SEARCH jobs_cluster_starttime_duration (cluster=? AND start_time= ?\", cond.From)\n 285→\t} else if cond.From == 1 && cond.To != 0 {\n 286→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 287→\t} else {\n 288→\t\treturn query\n 289→\t}\n 290→}\n 291→\n 292→// buildFloatCondition creates a clauses for float range filters, using BETWEEN only if required.\n 293→func buildFloatCondition(field string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 294→\tif cond.From != 1.0 && cond.To != 0.0 {\n 295→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From, cond.To)\n 296→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 297→\t\treturn query.Where(field+\" >= ?\", cond.From)\n 298→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 299→\t\treturn query.Where(field+\" <= ?\", cond.To)\n 300→\t} else {\n 301→\t\treturn query\n 302→\t}\n 303→}\n 304→\n 305→// buildTimeCondition creates time range filters supporting absolute timestamps,\n 306→// relative time ranges (last6h, last24h, last7d, last30d), or open-ended ranges.\n 307→// Reminder: BETWEEN Queries are slower and dont use indices as frequently: Only use if both conditions required\n 308→func buildTimeCondition(field string, cond *config.TimeRange, query sq.SelectBuilder) sq.SelectBuilder {\n 309→\tif cond.From != nil && cond.To != nil {\n 310→\t\treturn query.Where(field+\" BETWEEN ? AND ?\", cond.From.Unix(), cond.To.Unix())\n 311→\t} else if cond.From != nil {\n 312→\t\treturn query.Where(field+\" >= ?\", cond.From.Unix())\n 313→\t} else if cond.To != nil {\n 314→\t\treturn query.Where(field+\" <= ?\", cond.To.Unix())\n 315→\t} else if cond.Range != \"\" {\n 316→\t\tnow := time.Now().Unix()\n 317→\t\tvar then int64\n 318→\t\tswitch cond.Range {\n 319→\t\tcase \"last6h\":\n 320→\t\t\tthen = now - (60 * 60 * 6)\n 321→\t\tcase \"last24h\":\n 322→\t\t\tthen = now - (60 * 60 * 24)\n 323→\t\tcase \"last7d\":\n 324→\t\t\tthen = now - (60 * 60 * 24 * 7)\n 325→\t\tcase \"last30d\":\n 326→\t\t\tthen = now - (60 * 60 * 24 * 30)\n 327→\t\tdefault:\n 328→\t\t\tcclog.Debugf(\"No known named timeRange: startTime.range = %s\", cond.Range)\n 329→\t\t\treturn query\n 330→\t\t}\n 331→\t\treturn query.Where(field+\" >= ?\", then)\n 332→\t} else {\n 333→\t\treturn query\n 334→\t}\n 335→}\n 336→\n 337→// buildFloatJSONCondition creates a filter on a numeric field within the footprint JSON column, using BETWEEN only if required.\n 338→func buildFloatJSONCondition(jsonField string, cond *model.FloatRange, query sq.SelectBuilder) sq.SelectBuilder {\n 339→\tquery = query.Where(\"JSON_VALID(footprint)\")\n 340→\tif cond.From != 1.0 && cond.To != 0.0 {\n 341→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") BETWEEN ? AND ?\", cond.From, cond.To)\n 342→\t} else if cond.From != 1.0 && cond.To == 0.0 {\n 343→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") >= ?\", cond.From)\n 344→\t} else if cond.From == 1.0 && cond.To != 0.0 {\n 345→\t\treturn query.Where(\"JSON_EXTRACT(footprint, \\\"$.\"+jsonField+\"\\\") <= ?\", cond.To)\n 346→\t} else {\n 347→\t\treturn query\n 348→\t}\n 349→}\n 350→\n 351→// buildStringCondition creates filters for string fields supporting equality,\n 352→// inequality, prefix, suffix, substring, and IN list matching.\n 353→func buildStringCondition(field string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 354→\tif cond.Eq != nil {\n 355→\t\treturn query.Where(field+\" = ?\", *cond.Eq)\n 356→\t}\n 357→\tif cond.Neq != nil {\n 358→\t\treturn query.Where(field+\" != ?\", *cond.Neq)\n 359→\t}\n 360→\tif cond.StartsWith != nil {\n 361→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 362→\t}\n 363→\tif cond.EndsWith != nil {\n 364→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 365→\t}\n 366→\tif cond.Contains != nil {\n 367→\t\treturn query.Where(field+\" LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 368→\t}\n 369→\tif cond.In != nil {\n 370→\t\tqueryElements := make([]string, len(cond.In))\n 371→\t\tcopy(queryElements, cond.In)\n 372→\t\treturn query.Where(sq.Or{sq.Eq{field: queryElements}})\n 373→\t}\n 374→\treturn query\n 375→}\n 376→\n 377→// buildMetaJSONCondition creates filters on fields within the meta_data JSON column.\n 378→func buildMetaJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 379→\tquery = query.Where(\"JSON_VALID(meta_data)\")\n 380→\tif cond.Eq != nil {\n 381→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") = ?\", *cond.Eq)\n 382→\t}\n 383→\tif cond.Neq != nil {\n 384→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") != ?\", *cond.Neq)\n 385→\t}\n 386→\tif cond.StartsWith != nil {\n 387→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 388→\t}\n 389→\tif cond.EndsWith != nil {\n 390→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.EndsWith))\n 391→\t}\n 392→\tif cond.Contains != nil {\n 393→\t\treturn query.Where(\"JSON_EXTRACT(meta_data, \\\"$.\"+jsonField+\"\\\") LIKE ?\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 394→\t}\n 395→\treturn query\n 396→}\n 397→\n 398→// buildResourceJSONCondition creates filters on fields within the resources JSON array column.\n 399→// Uses json_each to search within array elements.\n 400→func buildResourceJSONCondition(jsonField string, cond *model.StringInput, query sq.SelectBuilder) sq.SelectBuilder {\n 401→\tquery = query.Where(\"JSON_VALID(resources)\")\n 402→\tif cond.Eq != nil {\n 403→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") = ?)\", *cond.Eq)\n 404→\t}\n 405→\tif cond.Neq != nil { // Currently Unused\n 406→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") != ?)\", *cond.Neq)\n 407→\t}\n 408→\tif cond.StartsWith != nil { // Currently Unused\n 409→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\")) LIKE ?)\", fmt.Sprint(*cond.StartsWith, \"%\"))\n 410→\t}\n 411→\tif cond.EndsWith != nil { // Currently Unused\n 412→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.EndsWith))\n 413→\t}\n 414→\tif cond.Contains != nil {\n 415→\t\treturn query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, \\\"$.\"+jsonField+\"\\\") LIKE ?)\", fmt.Sprint(\"%\", *cond.Contains, \"%\"))\n 416→\t}\n 417→\treturn query\n 418→}\n 419→\n 420→var (\n 421→\tmatchFirstCap = regexp.MustCompile(\"(.)([A-Z][a-z]+)\")\n 422→\tmatchAllCap = regexp.MustCompile(\"([a-z0-9])([A-Z])\")\n 423→)\n 424→\n 425→// toSnakeCase converts camelCase strings to snake_case for SQL column names.\n 426→// Includes security checks to prevent SQL injection attempts.\n 427→// Panics if potentially dangerous characters are detected.\n 428→func toSnakeCase(str string) string {\n 429→\tfor _, c := range str {\n 430→\t\tif c == '\\'' || c == '\\\\' || c == '\"' || c == ';' || c == '-' || c == ' ' {\n 431→\t\t\tcclog.Panicf(\"toSnakeCase: potentially dangerous character detected in input: %q\", str)\n 432→\t\t}\n 433→\t}\n 434→\n 435→\tsnake := matchFirstCap.ReplaceAllString(str, \"${1}_${2}\")\n 436→\tsnake = matchAllCap.ReplaceAllString(snake, \"${1}_${2}\")\n 437→\treturn strings.ToLower(snake)\n 438→}\n 439→"}]},"uuid":"610f25e1-a5ef-4315-b300-ddbfd151db2c","timestamp":"2026-03-11T04:34:52.128Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"80674b0f-08a8-4b98-8b59-98e9d1822257","timestamp":"2026-03-11T04:34:52.345Z"}
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+{"parentUuid":"201ec070-fb3f-46c4-8bab-2457c50b7d3e","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01ESxsN1LoA1iga2sY52qu4S","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(job.id)\").From(\"job\").GroupBy(col)\n 109→\t} else {\n 110→\t\tquery = sq.Select(\"COUNT(job.id)\").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 comprehensive job statistics with optional grouping.\n 128→//\n 129→// Parameters:\n 130→// - filter: Job filters to apply (cluster, user, time range, etc.)\n 131→// - col: Column name to GROUP BY; empty string for overall statistics without grouping\n 132→//\n 133→// Returns a SelectBuilder that produces comprehensive statistics:\n 134→// - totalJobs: Count of jobs\n 135→// - totalUsers: Count of distinct users (always 0 when grouping by user)\n 136→// - totalWalltime: Sum of job durations in hours\n 137→// - totalNodes: Sum of nodes used across all jobs\n 138→// - totalNodeHours: Sum of (duration × num_nodes) in hours\n 139→// - totalCores: Sum of hardware threads used across all jobs\n 140→// - totalCoreHours: Sum of (duration × num_hwthreads) in hours\n 141→// - totalAccs: Sum of accelerators used across all jobs\n 142→// - totalAccHours: Sum of (duration × num_acc) in hours\n 143→//\n 144→// Special handling:\n 145→// - Running jobs: Duration calculated as (now - start_time) instead of stored duration\n 146→// - Grouped queries: Also select grouping column and user's display name from hpc_user table\n 147→// - All time values converted from seconds to hours (÷ 3600) and rounded\n 148→func (r *JobRepository) buildStatsQuery(\n 149→\tfilter []*model.JobFilter,\n 150→\tcol string,\n 151→) sq.SelectBuilder {\n 152→\tvar query sq.SelectBuilder\n 153→\n 154→\tif col != \"\" {\n 155→\t\tquery = sq.Select(\n 156→\t\t\tcol,\n 157→\t\t\t\"name\",\n 158→\t\t\t\"COUNT(job.id) as totalJobs\",\n 159→\t\t\t\"COUNT(DISTINCT job.hpc_user) AS totalUsers\",\n 160→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END)) / 3600) as int) as totalWalltime`, time.Now().Unix()),\n 161→\t\t\t`CAST(SUM(job.num_nodes) as int) as totalNodes`,\n 162→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_nodes) / 3600) as int) as totalNodeHours`, time.Now().Unix()),\n 163→\t\t\t`CAST(SUM(job.num_hwthreads) as int) as totalCores`,\n 164→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_hwthreads) / 3600) as int) as totalCoreHours`, time.Now().Unix()),\n 165→\t\t\t`CAST(SUM(job.num_acc) as int) as totalAccs`,\n 166→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_acc) / 3600) as int) as totalAccHours`, time.Now().Unix()),\n 167→\t\t).From(\"job\").LeftJoin(\"hpc_user ON hpc_user.username = job.hpc_user\").GroupBy(col)\n 168→\t} else {\n 169→\t\tquery = sq.Select(\n 170→\t\t\t\"COUNT(job.id) as totalJobs\",\n 171→\t\t\t\"COUNT(DISTINCT job.hpc_user) AS totalUsers\",\n 172→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END)) / 3600) as int)`, time.Now().Unix()),\n 173→\t\t\t`CAST(SUM(job.num_nodes) as int)`,\n 174→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_nodes) / 3600) as int)`, time.Now().Unix()),\n 175→\t\t\t`CAST(SUM(job.num_hwthreads) as int)`,\n 176→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_hwthreads) / 3600) as int)`, time.Now().Unix()),\n 177→\t\t\t`CAST(SUM(job.num_acc) as int)`,\n 178→\t\t\tfmt.Sprintf(`CAST(ROUND(SUM((CASE WHEN job.job_state = \"running\" THEN %d - job.start_time ELSE job.duration END) * job.num_acc) / 3600) as int)`, time.Now().Unix()),\n 179→\t\t).From(\"job\")\n 180→\t}\n 181→\n 182→\tfor _, f := range filter {\n 183→\t\tquery = BuildWhereClause(f, query)\n 184→\t}\n 185→\n 186→\treturn query\n 187→}\n 188→\n 189→// JobsStatsGrouped computes comprehensive job statistics grouped by a dimension (user, project, cluster, or subcluster).\n 190→//\n 191→// This is the primary method for generating aggregated statistics views in the UI, providing\n 192→// metrics like total jobs, walltime, and resource usage broken down by the specified grouping.\n 193→//\n 194→// Parameters:\n 195→// - ctx: Context for security checks and cancellation\n 196→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 197→// - page: Optional pagination (ItemsPerPage: -1 disables pagination)\n 198→// - sortBy: Optional sort column (totalJobs, totalWalltime, totalCoreHours, etc.)\n 199→// - groupBy: Required grouping dimension (User, Project, Cluster, or SubCluster)\n 200→//\n 201→// Returns a slice of JobsStatistics, one per group, with:\n 202→// - ID: The group identifier (username, project name, cluster name, etc.)\n 203→// - Name: Display name (for users, from hpc_user.name; empty for other groups)\n 204→// - Statistics: totalJobs, totalUsers, totalWalltime, resource usage metrics\n 205→//\n 206→// Security: Respects user roles via SecurityCheck - users see only their own data unless admin/support.\n 207→// Performance: Results are sorted in SQL and pagination applied before scanning rows.\n 208→func (r *JobRepository) JobsStatsGrouped(\n 209→\tctx context.Context,\n 210→\tfilter []*model.JobFilter,\n 211→\tpage *model.PageRequest,\n 212→\tsortBy *model.SortByAggregate,\n 213→\tgroupBy *model.Aggregate,\n 214→) ([]*model.JobsStatistics, error) {\n 215→\tstart := time.Now()\n 216→\tcol := groupBy2column[*groupBy]\n 217→\tquery := r.buildStatsQuery(filter, col)\n 218→\n 219→\tquery, err := SecurityCheck(ctx, query)\n 220→\tif err != nil {\n 221→\t\treturn nil, err\n 222→\t}\n 223→\n 224→\tif sortBy != nil {\n 225→\t\tsortBy := sortBy2column[*sortBy]\n 226→\t\tquery = query.OrderBy(fmt.Sprintf(\"%s DESC\", sortBy))\n 227→\t}\n 228→\tif page != nil && page.ItemsPerPage != -1 {\n 229→\t\tlimit := uint64(page.ItemsPerPage)\n 230→\t\tquery = query.Offset((uint64(page.Page) - 1) * limit).Limit(limit)\n 231→\t}\n 232→\n 233→\trows, err := query.RunWith(r.DB).Query()\n 234→\tif err != nil {\n 235→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 236→\t\treturn nil, err\n 237→\t}\n 238→\tdefer rows.Close()\n 239→\n 240→\tstats := make([]*model.JobsStatistics, 0, 100)\n 241→\n 242→\tfor rows.Next() {\n 243→\t\tvar id sql.NullString\n 244→\t\tvar name sql.NullString\n 245→\t\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours sql.NullInt64\n 246→\t\tif err := rows.Scan(&id, &name, &jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours); err != nil {\n 247→\t\t\tcclog.Warnf(\"Error while scanning rows: %s\", err.Error())\n 248→\t\t\treturn nil, err\n 249→\t\t}\n 250→\n 251→\t\tif id.Valid {\n 252→\t\t\tvar totalJobs, totalUsers, totalWalltime, totalNodes, totalNodeHours, totalCores, totalCoreHours, totalAccs, totalAccHours int\n 253→\t\t\tvar personName string\n 254→\n 255→\t\t\tif name.Valid {\n 256→\t\t\t\tpersonName = name.String\n 257→\t\t\t}\n 258→\n 259→\t\t\tif jobs.Valid {\n 260→\t\t\t\ttotalJobs = int(jobs.Int64)\n 261→\t\t\t}\n 262→\n 263→\t\t\tif users.Valid {\n 264→\t\t\t\ttotalUsers = int(users.Int64)\n 265→\t\t\t}\n 266→\n 267→\t\t\tif walltime.Valid {\n 268→\t\t\t\ttotalWalltime = int(walltime.Int64)\n 269→\t\t\t}\n 270→\n 271→\t\t\tif nodes.Valid {\n 272→\t\t\t\ttotalNodes = int(nodes.Int64)\n 273→\t\t\t}\n 274→\t\t\tif cores.Valid {\n 275→\t\t\t\ttotalCores = int(cores.Int64)\n 276→\t\t\t}\n 277→\t\t\tif accs.Valid {\n 278→\t\t\t\ttotalAccs = int(accs.Int64)\n 279→\t\t\t}\n 280→\n 281→\t\t\tif nodeHours.Valid {\n 282→\t\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 283→\t\t\t}\n 284→\t\t\tif coreHours.Valid {\n 285→\t\t\t\ttotalCoreHours = int(coreHours.Int64)\n 286→\t\t\t}\n 287→\t\t\tif accHours.Valid {\n 288→\t\t\t\ttotalAccHours = int(accHours.Int64)\n 289→\t\t\t}\n 290→\n 291→\t\t\tif col == \"job.hpc_user\" {\n 292→\t\t\t\t// name := r.getUserName(ctx, id.String)\n 293→\t\t\t\tstats = append(stats,\n 294→\t\t\t\t\t&model.JobsStatistics{\n 295→\t\t\t\t\t\tID: id.String,\n 296→\t\t\t\t\t\tName: personName,\n 297→\t\t\t\t\t\tTotalJobs: totalJobs,\n 298→\t\t\t\t\t\tTotalWalltime: totalWalltime,\n 299→\t\t\t\t\t\tTotalNodes: totalNodes,\n 300→\t\t\t\t\t\tTotalNodeHours: totalNodeHours,\n 301→\t\t\t\t\t\tTotalCores: totalCores,\n 302→\t\t\t\t\t\tTotalCoreHours: totalCoreHours,\n 303→\t\t\t\t\t\tTotalAccs: totalAccs,\n 304→\t\t\t\t\t\tTotalAccHours: totalAccHours,\n 305→\t\t\t\t\t})\n 306→\t\t\t} else {\n 307→\t\t\t\tstats = append(stats,\n 308→\t\t\t\t\t&model.JobsStatistics{\n 309→\t\t\t\t\t\tID: id.String,\n 310→\t\t\t\t\t\tTotalJobs: totalJobs,\n 311→\t\t\t\t\t\tTotalUsers: totalUsers,\n 312→\t\t\t\t\t\tTotalWalltime: totalWalltime,\n 313→\t\t\t\t\t\tTotalNodes: totalNodes,\n 314→\t\t\t\t\t\tTotalNodeHours: totalNodeHours,\n 315→\t\t\t\t\t\tTotalCores: totalCores,\n 316→\t\t\t\t\t\tTotalCoreHours: totalCoreHours,\n 317→\t\t\t\t\t\tTotalAccs: totalAccs,\n 318→\t\t\t\t\t\tTotalAccHours: totalAccHours,\n 319→\t\t\t\t\t})\n 320→\t\t\t}\n 321→\t\t}\n 322→\t}\n 323→\n 324→\tif err := rows.Err(); err != nil {\n 325→\t\treturn nil, err\n 326→\t}\n 327→\n 328→\tcclog.Debugf(\"Timer JobsStatsGrouped %s\", time.Since(start))\n 329→\treturn stats, nil\n 330→}\n 331→\n 332→// JobsStats computes overall job statistics across all matching jobs without grouping.\n 333→//\n 334→// This method provides a single aggregate view of job metrics, useful for dashboard\n 335→// summaries and overall system utilization reports.\n 336→//\n 337→// Parameters:\n 338→// - ctx: Context for security checks and cancellation\n 339→// - filter: Filters to apply (time range, cluster, job state, etc.)\n 340→//\n 341→// Returns a single-element slice containing aggregate statistics:\n 342→// - totalJobs, totalUsers, totalWalltime\n 343→// - totalNodeHours, totalCoreHours, totalAccHours\n 344→//\n 345→// Unlike JobsStatsGrouped, this returns overall totals without breaking down by dimension.\n 346→// Security checks are applied via SecurityCheck to respect user access levels.\n 347→func (r *JobRepository) JobsStats(\n 348→\tctx context.Context,\n 349→\tfilter []*model.JobFilter,\n 350→) ([]*model.JobsStatistics, error) {\n 351→\tstart := time.Now()\n 352→\tquery := r.buildStatsQuery(filter, \"\")\n 353→\tquery, err := SecurityCheck(ctx, query)\n 354→\tif err != nil {\n 355→\t\treturn nil, err\n 356→\t}\n 357→\n 358→\trow := query.RunWith(r.DB).QueryRow()\n 359→\tstats := make([]*model.JobsStatistics, 0, 1)\n 360→\n 361→\tvar jobs, users, walltime, nodes, nodeHours, cores, coreHours, accs, accHours sql.NullInt64\n 362→\tif err := row.Scan(&jobs, &users, &walltime, &nodes, &nodeHours, &cores, &coreHours, &accs, &accHours); err != nil {\n 363→\t\tcclog.Warn(\"Error while scanning rows\")\n 364→\t\treturn nil, err\n 365→\t}\n 366→\n 367→\tif jobs.Valid {\n 368→\t\tvar totalNodeHours, totalCoreHours, totalAccHours int\n 369→\n 370→\t\tif nodeHours.Valid {\n 371→\t\t\ttotalNodeHours = int(nodeHours.Int64)\n 372→\t\t}\n 373→\t\tif coreHours.Valid {\n 374→\t\t\ttotalCoreHours = int(coreHours.Int64)\n 375→\t\t}\n 376→\t\tif accHours.Valid {\n 377→\t\t\ttotalAccHours = int(accHours.Int64)\n 378→\t\t}\n 379→\t\tstats = append(stats,\n 380→\t\t\t&model.JobsStatistics{\n 381→\t\t\t\tTotalJobs: int(jobs.Int64),\n 382→\t\t\t\tTotalUsers: int(users.Int64),\n 383→\t\t\t\tTotalWalltime: int(walltime.Int64),\n 384→\t\t\t\tTotalNodeHours: totalNodeHours,\n 385→\t\t\t\tTotalCoreHours: totalCoreHours,\n 386→\t\t\t\tTotalAccHours: totalAccHours,\n 387→\t\t\t})\n 388→\t}\n 389→\n 390→\tcclog.Debugf(\"Timer JobStats %s\", time.Since(start))\n 391→\treturn stats, nil\n 392→}\n 393→\n 394→// LoadJobStat retrieves a specific statistic for a metric from a job's statistics.\n 395→// Returns 0.0 if the metric is not found or statType is invalid.\n 396→//\n 397→// Parameters:\n 398→// - job: Job struct with populated Statistics field\n 399→// - metric: Name of the metric to query (e.g., \"cpu_load\", \"mem_used\")\n 400→// - statType: Type of statistic: \"avg\", \"min\", or \"max\"\n 401→//\n 402→// Returns the requested statistic value or 0.0 if not found.\n 403→func LoadJobStat(job *schema.Job, metric string, statType string) float64 {\n 404→\tif stats, ok := job.Statistics[metric]; ok {\n 405→\t\tswitch statType {\n 406→\t\tcase \"avg\":\n 407→\t\t\treturn stats.Avg\n 408→\t\tcase \"max\":\n 409→\t\t\treturn stats.Max\n 410→\t\tcase \"min\":\n 411→\t\t\treturn stats.Min\n 412→\t\tdefault:\n 413→\t\t\tcclog.Errorf(\"Unknown stat type %s\", statType)\n 414→\t\t}\n 415→\t}\n 416→\n 417→\treturn 0.0\n 418→}\n 419→\n 420→// JobCountGrouped counts jobs grouped by a dimension without computing detailed statistics.\n 421→//\n 422→// This is a lightweight alternative to JobsStatsGrouped when only job counts are needed,\n 423→// avoiding the overhead of calculating walltime and resource usage metrics.\n 424→//\n 425→// Parameters:\n 426→// - ctx: Context for security checks\n 427→// - filter: Filters to apply\n 428→// - groupBy: Grouping dimension (User, Project, Cluster, or SubCluster)\n 429→//\n 430→// Returns JobsStatistics with only ID and TotalJobs populated for each group.\n 431→func (r *JobRepository) JobCountGrouped(\n 432→\tctx context.Context,\n 433→\tfilter []*model.JobFilter,\n 434→\tgroupBy *model.Aggregate,\n 435→) ([]*model.JobsStatistics, error) {\n 436→\tstart := time.Now()\n 437→\tcol := groupBy2column[*groupBy]\n 438→\tquery := r.buildCountQuery(filter, \"\", col)\n 439→\tquery, err := SecurityCheck(ctx, query)\n 440→\tif err != nil {\n 441→\t\treturn nil, err\n 442→\t}\n 443→\trows, err := query.RunWith(r.DB).Query()\n 444→\tif err != nil {\n 445→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 446→\t\treturn nil, err\n 447→\t}\n 448→\tdefer rows.Close()\n 449→\n 450→\tstats := make([]*model.JobsStatistics, 0, 100)\n 451→\n 452→\tfor rows.Next() {\n 453→\t\tvar id sql.NullString\n 454→\t\tvar cnt sql.NullInt64\n 455→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 456→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 457→\t\t\treturn nil, err\n 458→\t\t}\n 459→\t\tif id.Valid {\n 460→\t\t\tstats = append(stats,\n 461→\t\t\t\t&model.JobsStatistics{\n 462→\t\t\t\t\tID: id.String,\n 463→\t\t\t\t\tTotalJobs: int(cnt.Int64),\n 464→\t\t\t\t})\n 465→\t\t}\n 466→\t}\n 467→\n 468→\tif err := rows.Err(); err != nil {\n 469→\t\treturn nil, err\n 470→\t}\n 471→\n 472→\tcclog.Debugf(\"Timer JobCountGrouped %s\", time.Since(start))\n 473→\treturn stats, nil\n 474→}\n 475→\n 476→// AddJobCountGrouped augments existing statistics with additional job counts by category.\n 477→//\n 478→// This method enriches JobsStatistics returned by JobsStatsGrouped or JobCountGrouped\n 479→// with counts of running or short-running (based on ShortRunningJobsDuration) jobs, matched by group ID.\n 480→//\n 481→// Parameters:\n 482→// - ctx: Context for security checks\n 483→// - filter: Filters to apply\n 484→// - groupBy: Grouping dimension (must match the dimension used for stats parameter)\n 485→// - stats: Existing statistics to augment (modified in-place by ID matching)\n 486→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 487→//\n 488→// Returns the same stats slice with RunningJobs or ShortJobs fields populated per group.\n 489→// Groups without matching jobs will have 0 for the added field.\n 490→func (r *JobRepository) AddJobCountGrouped(\n 491→\tctx context.Context,\n 492→\tfilter []*model.JobFilter,\n 493→\tgroupBy *model.Aggregate,\n 494→\tstats []*model.JobsStatistics,\n 495→\tkind string,\n 496→) ([]*model.JobsStatistics, error) {\n 497→\tstart := time.Now()\n 498→\tcol := groupBy2column[*groupBy]\n 499→\tquery := r.buildCountQuery(filter, kind, col)\n 500→\tquery, err := SecurityCheck(ctx, query)\n 501→\tif err != nil {\n 502→\t\treturn nil, err\n 503→\t}\n 504→\trows, err := query.RunWith(r.DB).Query()\n 505→\tif err != nil {\n 506→\t\tcclog.Warn(\"Error while querying DB for job statistics\")\n 507→\t\treturn nil, err\n 508→\t}\n 509→\tdefer rows.Close()\n 510→\n 511→\tcounts := make(map[string]int)\n 512→\n 513→\tfor rows.Next() {\n 514→\t\tvar id sql.NullString\n 515→\t\tvar cnt sql.NullInt64\n 516→\t\tif err := rows.Scan(&id, &cnt); err != nil {\n 517→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 518→\t\t\treturn nil, err\n 519→\t\t}\n 520→\t\tif id.Valid {\n 521→\t\t\tcounts[id.String] = int(cnt.Int64)\n 522→\t\t}\n 523→\t}\n 524→\n 525→\tif err := rows.Err(); err != nil {\n 526→\t\treturn nil, err\n 527→\t}\n 528→\n 529→\tswitch kind {\n 530→\tcase \"running\":\n 531→\t\tfor _, s := range stats {\n 532→\t\t\ts.RunningJobs = counts[s.ID]\n 533→\t\t}\n 534→\tcase \"short\":\n 535→\t\tfor _, s := range stats {\n 536→\t\t\ts.ShortJobs = counts[s.ID]\n 537→\t\t}\n 538→\t}\n 539→\n 540→\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n 541→\treturn stats, nil\n 542→}\n 543→\n 544→// AddJobCount augments existing overall statistics with additional job counts by category.\n 545→//\n 546→// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n 547→// to all statistics entries (typically just one).\n 548→//\n 549→// Parameters:\n 550→// - ctx: Context for security checks\n 551→// - filter: Filters to apply\n 552→// - stats: Existing statistics to augment (modified in-place)\n 553→// - kind: \"running\" to add RunningJobs count, \"short\" to add ShortJobs count\n 554→//\n 555→// Returns the same stats slice with RunningJobs or ShortJobs fields set to the total count.\n 556→func (r *JobRepository) AddJobCount(\n 557→\tctx context.Context,\n 558→\tfilter []*model.JobFilter,\n 559→\tstats []*model.JobsStatistics,\n 560→\tkind string,\n 561→) ([]*model.JobsStatistics, error) {\n 562→\tstart := time.Now()\n 563→\tquery := r.buildCountQuery(filter, kind, \"\")\n 564→\tquery, err := SecurityCheck(ctx, query)\n 565→\tif err != nil {\n 566→\t\treturn nil, err\n 567→\t}\n 568→\tvar cnt sql.NullInt64\n 569→\tif err := query.RunWith(r.DB).QueryRow().Scan(&cnt); err != nil {\n 570→\t\tcclog.Warn(\"Error while querying DB for job count\")\n 571→\t\treturn nil, err\n 572→\t}\n 573→\n 574→\tcount := int(cnt.Int64)\n 575→\n 576→\tswitch kind {\n 577→\tcase \"running\":\n 578→\t\tfor _, s := range stats {\n 579→\t\t\ts.RunningJobs = count\n 580→\t\t}\n 581→\tcase \"short\":\n 582→\t\tfor _, s := range stats {\n 583→\t\t\ts.ShortJobs = count\n 584→\t\t}\n 585→\t}\n 586→\n 587→\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n 588→\treturn stats, nil\n 589→}\n 590→\n 591→// AddHistograms augments statistics with distribution histograms for job properties.\n 592→//\n 593→// Generates histogram data for visualization of job duration, node count, core count,\n 594→// and accelerator count distributions. Duration histogram uses intelligent binning based\n 595→// on the requested resolution.\n 596→//\n 597→// Parameters:\n 598→// - ctx: Context for security checks\n 599→// - filter: Filters to apply to jobs included in histograms\n 600→// - stat: Statistics struct to augment (modified in-place)\n 601→// - durationBins: Bin size - \"1m\", \"10m\", \"1h\", \"6h\", \"12h\", or \"24h\" (default)\n 602→//\n 603→// Populates these fields in stat:\n 604→// - HistDuration: Job duration distribution (zero-padded bins)\n 605→// - HistNumNodes: Node count distribution\n 606→// - HistNumCores: Core (hwthread) count distribution\n 607→// - HistNumAccs: Accelerator count distribution\n 608→//\n 609→// Duration bins are pre-initialized with zeros to ensure consistent ranges for visualization.\n 610→// Bin size determines both the width and maximum duration displayed (e.g., \"1h\" = 48 bins × 1h = 48h max).\n 611→func (r *JobRepository) AddHistograms(\n 612→\tctx context.Context,\n 613→\tfilter []*model.JobFilter,\n 614→\tstat *model.JobsStatistics,\n 615→\tdurationBins *string,\n 616→) (*model.JobsStatistics, error) {\n 617→\tstart := time.Now()\n 618→\n 619→\tvar targetBinCount int\n 620→\tvar targetBinSize int\n 621→\tswitch *durationBins {\n 622→\tcase \"1m\": // 1 Minute Bins + Max 60 Bins -> Max 60 Minutes\n 623→\t\ttargetBinCount = 60\n 624→\t\ttargetBinSize = 60\n 625→\tcase \"10m\": // 10 Minute Bins + Max 72 Bins -> Max 12 Hours\n 626→\t\ttargetBinCount = 72\n 627→\t\ttargetBinSize = 600\n 628→\tcase \"1h\": // 1 Hour Bins + Max 48 Bins -> Max 48 Hours\n 629→\t\ttargetBinCount = 48\n 630→\t\ttargetBinSize = 3600\n 631→\tcase \"6h\": // 6 Hour Bins + Max 12 Bins -> Max 3 Days\n 632→\t\ttargetBinCount = 12\n 633→\t\ttargetBinSize = 21600\n 634→\tcase \"12h\": // 12 hour Bins + Max 14 Bins -> Max 7 Days\n 635→\t\ttargetBinCount = 14\n 636→\t\ttargetBinSize = 43200\n 637→\tdefault: // 24h\n 638→\t\ttargetBinCount = 24\n 639→\t\ttargetBinSize = 3600\n 640→\t}\n 641→\n 642→\tvar err error\n 643→\t// Return X-Values always as seconds, will be formatted into minutes and hours in frontend\n 644→\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 645→\tstat.HistDuration, err = r.jobsDurationStatisticsHistogram(ctx, value, filter, targetBinSize, &targetBinCount)\n 646→\tif err != nil {\n 647→\t\tcclog.Warn(\"Error while loading job statistics histogram: job duration\")\n 648→\t\treturn nil, err\n 649→\t}\n 650→\n 651→\tstat.HistNumNodes, err = r.jobsStatisticsHistogram(ctx, \"job.num_nodes as value\", filter)\n 652→\tif err != nil {\n 653→\t\tcclog.Warn(\"Error while loading job statistics histogram: num nodes\")\n 654→\t\treturn nil, err\n 655→\t}\n 656→\n 657→\tstat.HistNumCores, err = r.jobsStatisticsHistogram(ctx, \"job.num_hwthreads as value\", filter)\n 658→\tif err != nil {\n 659→\t\tcclog.Warn(\"Error while loading job statistics histogram: num hwthreads\")\n 660→\t\treturn nil, err\n 661→\t}\n 662→\n 663→\tstat.HistNumAccs, err = r.jobsStatisticsHistogram(ctx, \"job.num_acc as value\", filter)\n 664→\tif err != nil {\n 665→\t\tcclog.Warn(\"Error while loading job statistics histogram: num acc\")\n 666→\t\treturn nil, err\n 667→\t}\n 668→\n 669→\tcclog.Debugf(\"Timer AddHistograms %s\", time.Since(start))\n 670→\treturn stat, nil\n 671→}\n 672→\n 673→// AddMetricHistograms augments statistics with distribution histograms for job metrics.\n 674→//\n 675→// Generates histogram data for metrics like CPU load, memory usage, etc. Handles running\n 676→// and completed jobs differently: running jobs load data from metric backend, completed jobs\n 677→// use footprint data from database.\n 678→//\n 679→// Parameters:\n 680→// - ctx: Context for security checks\n 681→// - filter: Filters to apply (MUST contain State filter for running jobs)\n 682→// - metrics: List of metric names to histogram (e.g., [\"cpu_load\", \"mem_used\"])\n 683→// - stat: Statistics struct to augment (modified in-place)\n 684→// - targetBinCount: Number of histogram bins (default: 10)\n 685→//\n 686→// Populates HistMetrics field in stat with MetricHistoPoints for each metric.\n 687→//\n 688→// Binning algorithm:\n 689→// - Values normalized to metric's peak value from cluster configuration\n 690→// - Bins evenly distributed from 0 to peak\n 691→// - Pre-initialized with zeros for consistent visualization\n 692→//\n 693→// Limitations:\n 694→// - Running jobs: Limited to 5000 jobs for performance\n 695→// - Requires valid cluster configuration with metric peak values\n 696→// - Uses footprint statistic (avg/max/min) configured per metric\n 697→func (r *JobRepository) AddMetricHistograms(\n 698→\tctx context.Context,\n 699→\tfilter []*model.JobFilter,\n 700→\tmetrics []string,\n 701→\tstat *model.JobsStatistics,\n 702→\ttargetBinCount *int,\n 703→) (*model.JobsStatistics, error) {\n 704→\tstart := time.Now()\n 705→\n 706→\t// Running Jobs Only: First query jobdata from sqlite, then query data and make bins\n 707→\tfor _, f := range filter {\n 708→\t\tif f.State != nil {\n 709→\t\t\tif len(f.State) == 1 && f.State[0] == \"running\" {\n 710→\t\t\t\tstat.HistMetrics = r.runningJobsMetricStatisticsHistogram(ctx, metrics, filter, targetBinCount)\n 711→\t\t\t\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 712→\t\t\t\treturn stat, nil\n 713→\t\t\t}\n 714→\t\t}\n 715→\t}\n 716→\n 717→\t// All other cases: Query and make bins in sqlite directly\n 718→\tfor _, m := range metrics {\n 719→\t\tmetricHisto, err := r.jobsMetricStatisticsHistogram(ctx, m, filter, targetBinCount)\n 720→\t\tif err != nil {\n 721→\t\t\tcclog.Warnf(\"Error while loading job metric statistics histogram: %s\", m)\n 722→\t\t\tcontinue\n 723→\t\t}\n 724→\t\tstat.HistMetrics = append(stat.HistMetrics, metricHisto)\n 725→\t}\n 726→\n 727→\tcclog.Debugf(\"Timer AddMetricHistograms %s\", time.Since(start))\n 728→\treturn stat, nil\n 729→}\n 730→\n 731→// jobsStatisticsHistogram generates a simple histogram by grouping on a column value.\n 732→//\n 733→// Used for histograms where the column value directly represents the bin (e.g., node count, core count).\n 734→// Unlike duration/metric histograms, this doesn't pre-initialize bins with zeros.\n 735→//\n 736→// Parameters:\n 737→// - value: SQL expression that produces the histogram value, aliased as \"value\"\n 738→// - filters: Job filters to apply\n 739→//\n 740→// Returns histogram points with Value (from column) and Count (number of jobs).\n 741→func (r *JobRepository) jobsStatisticsHistogram(\n 742→\tctx context.Context,\n 743→\tvalue string,\n 744→\tfilters []*model.JobFilter,\n 745→) ([]*model.HistoPoint, error) {\n 746→\tstart := time.Now()\n 747→\tquery, qerr := SecurityCheck(ctx,\n 748→\t\tsq.Select(value, \"COUNT(job.id) AS count\").From(\"job\"))\n 749→\n 750→\tif qerr != nil {\n 751→\t\treturn nil, qerr\n 752→\t}\n 753→\n 754→\tfor _, f := range filters {\n 755→\t\tquery = BuildWhereClause(f, query)\n 756→\t}\n 757→\n 758→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).Query()\n 759→\tif err != nil {\n 760→\t\tcclog.Error(\"Error while running query\")\n 761→\t\treturn nil, err\n 762→\t}\n 763→\tdefer rows.Close()\n 764→\n 765→\tpoints := make([]*model.HistoPoint, 0)\n 766→\t// is it possible to introduce zero values here? requires info about bincount\n 767→\tfor rows.Next() {\n 768→\t\tpoint := model.HistoPoint{}\n 769→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 770→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 771→\t\t\treturn nil, err\n 772→\t\t}\n 773→\n 774→\t\tpoints = append(points, &point)\n 775→\t}\n 776→\n 777→\tif err := rows.Err(); err != nil {\n 778→\t\treturn nil, err\n 779→\t}\n 780→\n 781→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 782→\treturn points, nil\n 783→}\n 784→\n 785→// jobsDurationStatisticsHistogram generates a duration histogram with pre-initialized bins.\n 786→//\n 787→// Bins are zero-padded to provide consistent ranges for visualization, unlike simple\n 788→// histograms which only return bins with data. The value parameter should compute\n 789→// the bin number from job duration.\n 790→//\n 791→// Parameters:\n 792→// - value: SQL expression computing bin number from duration, aliased as \"value\"\n 793→// - filters: Job filters to apply\n 794→// - binSizeSeconds: Width of each bin in seconds\n 795→// - targetBinCount: Number of bins to pre-initialize\n 796→//\n 797→// Returns histogram points with Value (bin_number × binSizeSeconds) and Count.\n 798→// All bins from 1 to targetBinCount are returned, with Count=0 for empty bins.\n 799→//\n 800→// Algorithm:\n 801→// 1. Pre-initialize targetBinCount bins with zero counts\n 802→// 2. Query database for actual counts per bin\n 803→// 3. Match query results to pre-initialized bins by value\n 804→// 4. Bins without matches remain at zero\n 805→func (r *JobRepository) jobsDurationStatisticsHistogram(\n 806→\tctx context.Context,\n 807→\tvalue string,\n 808→\tfilters []*model.JobFilter,\n 809→\tbinSizeSeconds int,\n 810→\ttargetBinCount *int,\n 811→) ([]*model.HistoPoint, error) {\n 812→\tstart := time.Now()\n 813→\tquery, qerr := SecurityCheck(ctx,\n 814→\t\tsq.Select(value, \"COUNT(job.id) AS count\").From(\"job\"))\n 815→\n 816→\tif qerr != nil {\n 817→\t\treturn nil, qerr\n 818→\t}\n 819→\n 820→\t// Each bin represents a duration range: bin N = [N*binSizeSeconds, (N+1)*binSizeSeconds)\n 821→\t// Example: binSizeSeconds=3600 (1 hour), bin 1 = 0-1h, bin 2 = 1-2h, etc.\n 822→\tpoints := make([]*model.HistoPoint, 0)\n 823→\tfor i := 1; i <= *targetBinCount; i++ {\n 824→\t\tpoint := model.HistoPoint{Value: i * binSizeSeconds, Count: 0}\n 825→\t\tpoints = append(points, &point)\n 826→\t}\n 827→\n 828→\tfor _, f := range filters {\n 829→\t\tquery = BuildWhereClause(f, query)\n 830→\t}\n 831→\n 832→\trows, err := query.GroupBy(\"value\").RunWith(r.DB).Query()\n 833→\tif err != nil {\n 834→\t\tcclog.Error(\"Error while running query\")\n 835→\t\treturn nil, err\n 836→\t}\n 837→\tdefer rows.Close()\n 838→\n 839→\t// Match query results to pre-initialized bins.\n 840→\t// point.Value from query is the bin number; multiply by binSizeSeconds to match bin.Value.\n 841→\tfor rows.Next() {\n 842→\t\tpoint := model.HistoPoint{}\n 843→\t\tif err := rows.Scan(&point.Value, &point.Count); err != nil {\n 844→\t\t\tcclog.Warn(\"Error while scanning rows\")\n 845→\t\t\treturn nil, err\n 846→\t\t}\n 847→\n 848→\t\tfor _, e := range points {\n 849→\t\t\tif e.Value == (point.Value * binSizeSeconds) {\n 850→\t\t\t\te.Count = point.Count\n 851→\t\t\t\tbreak\n 852→\t\t\t}\n 853→\t\t}\n 854→\t}\n 855→\n 856→\tif err := rows.Err(); err != nil {\n 857→\t\treturn nil, err\n 858→\t}\n 859→\n 860→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 861→\treturn points, nil\n 862→}\n 863→\n 864→// jobsMetricStatisticsHistogram generates a metric histogram using footprint data from completed jobs.\n 865→//\n 866→// Values are normalized to the metric's peak value and distributed into bins. The algorithm\n 867→// is based on SQL histogram generation techniques, extracting metric values from JSON footprint\n 868→// and computing bin assignments in SQL.\n 869→//\n 870→// Parameters:\n 871→// - metric: Metric name (e.g., \"cpu_load\", \"mem_used\")\n 872→// - filters: Job filters to apply\n 873→// - bins: Number of bins to generate\n 874→//\n 875→// Returns MetricHistoPoints with metric name, unit, footprint stat type, and binned data.\n 876→//\n 877→// Algorithm:\n 878→// 1. Determine peak value from cluster configuration (filtered cluster or max across all)\n 879→// 2. Generate SQL that extracts footprint value, normalizes to [0,1], multiplies by bin count\n 880→// 3. Pre-initialize bins with min/max ranges based on peak value\n 881→// 4. Query database for counts per bin\n 882→// 5. Match results to pre-initialized bins\n 883→//\n 884→// Special handling: Values exactly equal to peak are forced into the last bin by multiplying\n 885→// peak by 0.999999999 to avoid creating an extra bin.\n 886→func (r *JobRepository) jobsMetricStatisticsHistogram(\n 887→\tctx context.Context,\n 888→\tmetric string,\n 889→\tfilters []*model.JobFilter,\n 890→\tbins *int,\n 891→) (*model.MetricHistoPoints, error) {\n 892→\t// Peak value defines the upper bound for binning: values are distributed across\n 893→\t// bins from 0 to peak. First try to get peak from filtered cluster, otherwise\n 894→\t// scan all clusters to find the maximum peak value.\n 895→\tvar metricConfig *schema.MetricConfig\n 896→\tvar peak float64\n 897→\tvar unit string\n 898→\tvar footprintStat string\n 899→\n 900→\t// Try to get metric config from filtered cluster\n 901→\tfor _, f := range filters {\n 902→\t\tif f.Cluster != nil {\n 903→\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 904→\t\t\tpeak = metricConfig.Peak\n 905→\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 906→\t\t\tfootprintStat = metricConfig.Footprint\n 907→\t\t\tcclog.Debugf(\"Cluster %s filter found with peak %f for %s\", *f.Cluster.Eq, peak, metric)\n 908→\t\t}\n 909→\t}\n 910→\n 911→\t// If no cluster filter or peak not found, find largest peak across all clusters\n 912→\t// This ensures histogram can accommodate all possible values\n 913→\tif peak == 0.0 {\n 914→\t\tfor _, c := range archive.Clusters {\n 915→\t\t\tfor _, m := range c.MetricConfig {\n 916→\t\t\t\tif m.Name == metric {\n 917→\t\t\t\t\tif m.Peak > peak {\n 918→\t\t\t\t\t\tpeak = m.Peak\n 919→\t\t\t\t\t}\n 920→\t\t\t\t\tif unit == \"\" {\n 921→\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 922→\t\t\t\t\t}\n 923→\t\t\t\t\tif footprintStat == \"\" {\n 924→\t\t\t\t\t\tfootprintStat = m.Footprint\n 925→\t\t\t\t\t}\n 926→\t\t\t\t}\n 927→\t\t\t}\n 928→\t\t}\n 929→\t}\n 930→\n 931→\t// Construct SQL histogram bins using normalized values.\n 932→\t// Algorithm based on: https://jereze.com/code/sql-histogram/ (modified)\n 933→\tstart := time.Now()\n 934→\n 935→\t// Bin calculation formula:\n 936→\t// bin_number = CAST( (value / peak) * num_bins AS INTEGER ) + 1\n 937→\t// Special case: value == peak would create bin N+1, so we test for equality\n 938→\t// and multiply peak by 0.999999999 to force it into bin N.\n 939→\tbinQuery := fmt.Sprintf(`CAST(\n 940→\t\t((case when json_extract(footprint, \"$.%s\") = %f then %f*0.999999999 else json_extract(footprint, \"$.%s\") end) / %f)\n 941→\t\t* %v as INTEGER )`,\n 942→\t\t(metric + \"_\" + footprintStat), peak, peak, (metric + \"_\" + footprintStat), peak, *bins)\n 943→\n 944→\tmainQuery := sq.Select(\n 945→\t\tfmt.Sprintf(`%s + 1 as bin`, binQuery),\n 946→\t\t`count(*) as count`,\n 947→\t).From(\"job\").Where(\n 948→\t\t\"JSON_VALID(footprint)\",\n 949→\t).Where(fmt.Sprintf(`json_extract(footprint, \"$.%s\") is not null and json_extract(footprint, \"$.%s\") <= %f`, (metric + \"_\" + footprintStat), (metric + \"_\" + footprintStat), peak))\n 950→\n 951→\tmainQuery, qerr := SecurityCheck(ctx, mainQuery)\n 952→\tif qerr != nil {\n 953→\t\treturn nil, qerr\n 954→\t}\n 955→\n 956→\tfor _, f := range filters {\n 957→\t\tmainQuery = BuildWhereClause(f, mainQuery)\n 958→\t}\n 959→\n 960→\tmainQuery = mainQuery.GroupBy(\"bin\").OrderBy(\"bin\")\n 961→\n 962→\trows, err := mainQuery.RunWith(r.DB).Query()\n 963→\tif err != nil {\n 964→\t\tcclog.Errorf(\"Error while running mainQuery: %s\", err)\n 965→\t\treturn nil, err\n 966→\t}\n 967→\tdefer rows.Close()\n 968→\n 969→\t// Pre-initialize bins with calculated min/max ranges.\n 970→\t// Example: peak=1000, bins=10 -> bin 1=[0,100), bin 2=[100,200), ..., bin 10=[900,1000]\n 971→\tpoints := make([]*model.MetricHistoPoint, 0)\n 972→\tbinStep := int(peak) / *bins\n 973→\tfor i := 1; i <= *bins; i++ {\n 974→\t\tbinMin := (binStep * (i - 1))\n 975→\t\tbinMax := (binStep * i)\n 976→\t\tepoint := model.MetricHistoPoint{Bin: &i, Count: 0, Min: &binMin, Max: &binMax}\n 977→\t\tpoints = append(points, &epoint)\n 978→\t}\n 979→\n 980→\t// Match query results to pre-initialized bins.\n 981→\tfor rows.Next() {\n 982→\t\trpoint := model.MetricHistoPoint{}\n 983→\t\tif err := rows.Scan(&rpoint.Bin, &rpoint.Count); err != nil {\n 984→\t\t\tcclog.Warnf(\"Error while scanning rows for %s\", metric)\n 985→\t\t\treturn nil, err\n 986→\t\t}\n 987→\n 988→\t\tfor _, e := range points {\n 989→\t\t\tif e.Bin != nil && rpoint.Bin != nil && *e.Bin == *rpoint.Bin {\n 990→\t\t\t\te.Count = rpoint.Count\n 991→\t\t\t\tbreak\n 992→\t\t\t}\n 993→\t\t}\n 994→\t}\n 995→\n 996→\tif err := rows.Err(); err != nil {\n 997→\t\treturn nil, err\n 998→\t}\n 999→\n 1000→\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Stat: &footprintStat, Data: points}\n 1001→\n 1002→\tcclog.Debugf(\"Timer jobsStatisticsHistogram %s\", time.Since(start))\n 1003→\treturn &result, nil\n 1004→}\n 1005→\n 1006→// runningJobsMetricStatisticsHistogram generates metric histograms for running jobs using live data.\n 1007→//\n 1008→// Unlike completed jobs which use footprint data from the database, running jobs require\n 1009→// fetching current metric averages from the metric backend (via metricdispatch).\n 1010→//\n 1011→// Parameters:\n 1012→// - metrics: List of metric names\n 1013→// - filters: Job filters (should filter to running jobs only)\n 1014→// - bins: Number of histogram bins\n 1015→//\n 1016→// Returns slice of MetricHistoPoints, one per metric.\n 1017→//\n 1018→// Limitations:\n 1019→// - Maximum 5000 jobs (returns nil if more jobs match)\n 1020→// - Requires metric backend availability\n 1021→// - Bins based on metric peak values from cluster configuration\n 1022→//\n 1023→// Algorithm:\n 1024→// 1. Query first 5001 jobs to check count limit\n 1025→// 2. Load metric averages for all jobs via metricdispatch\n 1026→// 3. For each metric, create bins based on peak value\n 1027→// 4. Iterate averages and count jobs per bin\n 1028→func (r *JobRepository) runningJobsMetricStatisticsHistogram(\n 1029→\tctx context.Context,\n 1030→\tmetrics []string,\n 1031→\tfilters []*model.JobFilter,\n 1032→\tbins *int,\n 1033→) []*model.MetricHistoPoints {\n 1034→\t// Get Jobs\n 1035→\tjobs, err := r.QueryJobs(ctx, filters, &model.PageRequest{Page: 1, ItemsPerPage: 5000 + 1}, nil)\n 1036→\tif err != nil {\n 1037→\t\tcclog.Errorf(\"Error while querying jobs for footprint: %s\", err)\n 1038→\t\treturn nil\n 1039→\t}\n 1040→\tif len(jobs) > 5000 {\n 1041→\t\tcclog.Errorf(\"too many jobs matched (max: %d)\", 5000)\n 1042→\t\treturn nil\n 1043→\t}\n 1044→\n 1045→\t// Get AVGs from metric repo\n 1046→\tavgs := make([][]schema.Float, len(metrics))\n 1047→\tfor i := range avgs {\n 1048→\t\tavgs[i] = make([]schema.Float, 0, len(jobs))\n 1049→\t}\n 1050→\n 1051→\tfor _, job := range jobs {\n 1052→\t\tif job.MonitoringStatus == schema.MonitoringStatusDisabled || job.MonitoringStatus == schema.MonitoringStatusArchivingFailed {\n 1053→\t\t\tcontinue\n 1054→\t\t}\n 1055→\n 1056→\t\tif err := metricdispatch.LoadAverages(job, metrics, avgs, ctx); err != nil {\n 1057→\t\t\tcclog.Errorf(\"Error while loading averages for histogram: %s\", err)\n 1058→\t\t\treturn nil\n 1059→\t\t}\n 1060→\t}\n 1061→\n 1062→\t// Iterate metrics to fill endresult\n 1063→\tdata := make([]*model.MetricHistoPoints, 0)\n 1064→\tfor idx, metric := range metrics {\n 1065→\t\t// Get specific Peak or largest Peak\n 1066→\t\tvar metricConfig *schema.MetricConfig\n 1067→\t\tvar peak float64\n 1068→\t\tvar unit string\n 1069→\n 1070→\t\tfor _, f := range filters {\n 1071→\t\t\tif f.Cluster != nil {\n 1072→\t\t\t\tmetricConfig = archive.GetMetricConfig(*f.Cluster.Eq, metric)\n 1073→\t\t\t\tpeak = metricConfig.Peak\n 1074→\t\t\t\tunit = metricConfig.Unit.Prefix + metricConfig.Unit.Base\n 1075→\t\t\t}\n 1076→\t\t}\n 1077→\n 1078→\t\tif peak == 0.0 {\n 1079→\t\t\tfor _, c := range archive.Clusters {\n 1080→\t\t\t\tfor _, m := range c.MetricConfig {\n 1081→\t\t\t\t\tif m.Name == metric {\n 1082→\t\t\t\t\t\tif m.Peak > peak {\n 1083→\t\t\t\t\t\t\tpeak = m.Peak\n 1084→\t\t\t\t\t\t}\n 1085→\t\t\t\t\t\tif unit == \"\" {\n 1086→\t\t\t\t\t\t\tunit = m.Unit.Prefix + m.Unit.Base\n 1087→\t\t\t\t\t\t}\n 1088→\t\t\t\t\t}\n 1089→\t\t\t\t}\n 1090→\t\t\t}\n 1091→\t\t}\n 1092→\n 1093→\t\t// Make and fill bins\n 1094→\t\tpeakBin := int(peak) / *bins\n 1095→\n 1096→\t\tpoints := make([]*model.MetricHistoPoint, 0)\n 1097→\t\tfor b := 0; b < *bins; b++ {\n 1098→\t\t\tcount := 0\n 1099→\t\t\tbindex := b + 1\n 1100→\t\t\tbmin := peakBin * b\n 1101→\t\t\tbmax := peakBin * (b + 1)\n 1102→\n 1103→\t\t\t// Iterate AVG values for indexed metric and count for bins\n 1104→\t\t\tfor _, val := range avgs[idx] {\n 1105→\t\t\t\tif int(val) >= bmin && int(val) < bmax {\n 1106→\t\t\t\t\tcount += 1\n 1107→\t\t\t\t}\n 1108→\t\t\t}\n 1109→\n 1110→\t\t\t// Append Bin to Metric Result Array\n 1111→\t\t\tpoint := model.MetricHistoPoint{Bin: &bindex, Count: count, Min: &bmin, Max: &bmax}\n 1112→\t\t\tpoints = append(points, &point)\n 1113→\t\t}\n 1114→\n 1115→\t\t// Append Metric Result Array to final results array\n 1116→\t\tresult := model.MetricHistoPoints{Metric: metric, Unit: unit, Data: points}\n 1117→\t\tdata = append(data, &result)\n 1118→\t}\n 1119→\n 1120→\treturn data\n 1121→}\n 1122→"}]},"uuid":"951e5001-2078-4399-9a0d-1a1e9fbf6b99","timestamp":"2026-03-11T04:34:52.563Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"2c7181c2-4cc2-4d52-8466-c0c50d17f23f","timestamp":"2026-03-11T04:34:52.564Z"}
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+{"parentUuid":"3d6bb76a-657b-455d-96bf-3c93c118dbcd","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QvCGjiFcmpkD9wVFdFUT4o","type":"tool_result","content":" 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→package repository\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"database/sql\"\n 11→\t\"fmt\"\n 12→\t\"time\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n 15→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 16→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 17→\tsq \"github.com/Masterminds/squirrel\"\n 18→)\n 19→\n 20→// Find executes a SQL query to find a specific batch job.\n 21→// The job is queried using the batch job id, the cluster name,\n 22→// and the start time of the job in UNIX epoch time seconds.\n 23→// It returns a pointer to a schema.Job data structure and an error variable.\n 24→// To check if no job was found test err == sql.ErrNoRows\n 25→func (r *JobRepository) Find(\n 26→\tjobID *int64,\n 27→\tcluster *string,\n 28→\tstartTime *int64,\n 29→) (*schema.Job, error) {\n 30→\tif jobID == nil {\n 31→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 32→\t}\n 33→\n 34→\tstart := time.Now()\n 35→\tq := sq.Select(jobColumns...).From(\"job\").\n 36→\t\tWhere(\"job.job_id = ?\", *jobID)\n 37→\n 38→\tif cluster != nil {\n 39→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 40→\t}\n 41→\tif startTime != nil {\n 42→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 43→\t}\n 44→\n 45→\tq = q.OrderBy(\"job.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 46→\n 47→\tcclog.Debugf(\"Timer Find %s\", time.Since(start))\n 48→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 49→}\n 50→\n 51→// FindCached executes a SQL query to find a specific batch job from the job_cache table.\n 52→// The job is queried using the batch job id, and optionally filtered by cluster name\n 53→// and start time (UNIX epoch time seconds). This method uses cached job data which\n 54→// may be stale but provides faster access than Find().\n 55→// It returns a pointer to a schema.Job data structure and an error variable.\n 56→// To check if no job was found test err == sql.ErrNoRows\n 57→func (r *JobRepository) FindCached(\n 58→\tjobID *int64,\n 59→\tcluster *string,\n 60→\tstartTime *int64,\n 61→) (*schema.Job, error) {\n 62→\tif jobID == nil {\n 63→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 64→\t}\n 65→\n 66→\tq := sq.Select(jobCacheColumns...).From(\"job_cache\").\n 67→\t\tWhere(\"job_cache.job_id = ?\", *jobID)\n 68→\n 69→\tif cluster != nil {\n 70→\t\tq = q.Where(\"job_cache.cluster = ?\", *cluster)\n 71→\t}\n 72→\tif startTime != nil {\n 73→\t\tq = q.Where(\"job_cache.start_time = ?\", *startTime)\n 74→\t}\n 75→\n 76→\tq = q.OrderBy(\"job_cache.id DESC\").Limit(1) // always use newest matching job by db id if more than one match\n 77→\n 78→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 79→}\n 80→\n 81→// FindAll executes a SQL query to find all batch jobs matching the given criteria.\n 82→// Jobs are queried using the batch job id, and optionally filtered by cluster name\n 83→// and start time (UNIX epoch time seconds).\n 84→// It returns a slice of pointers to schema.Job data structures and an error variable.\n 85→// An empty slice is returned if no matching jobs are found.\n 86→func (r *JobRepository) FindAll(\n 87→\tjobID *int64,\n 88→\tcluster *string,\n 89→\tstartTime *int64,\n 90→) ([]*schema.Job, error) {\n 91→\tif jobID == nil {\n 92→\t\treturn nil, fmt.Errorf(\"jobID cannot be nil\")\n 93→\t}\n 94→\n 95→\tstart := time.Now()\n 96→\tq := sq.Select(jobColumns...).From(\"job\").\n 97→\t\tWhere(\"job.job_id = ?\", *jobID)\n 98→\n 99→\tif cluster != nil {\n 100→\t\tq = q.Where(\"job.cluster = ?\", *cluster)\n 101→\t}\n 102→\tif startTime != nil {\n 103→\t\tq = q.Where(\"job.start_time = ?\", *startTime)\n 104→\t}\n 105→\n 106→\trows, err := q.RunWith(r.stmtCache).Query()\n 107→\tif err != nil {\n 108→\t\tcclog.Errorf(\"Error while running FindAll query for jobID=%d: %v\", *jobID, err)\n 109→\t\treturn nil, fmt.Errorf(\"failed to execute FindAll query: %w\", err)\n 110→\t}\n 111→\tdefer rows.Close()\n 112→\n 113→\tjobs := make([]*schema.Job, 0, 10)\n 114→\tfor rows.Next() {\n 115→\t\tjob, err := scanJob(rows)\n 116→\t\tif err != nil {\n 117→\t\t\tcclog.Warnf(\"Error while scanning rows in FindAll: %v\", err)\n 118→\t\t\treturn nil, fmt.Errorf(\"failed to scan job row: %w\", err)\n 119→\t\t}\n 120→\t\tjobs = append(jobs, job)\n 121→\t}\n 122→\tcclog.Debugf(\"Timer FindAll %s\", time.Since(start))\n 123→\treturn jobs, nil\n 124→}\n 125→\n 126→// GetJobList returns job IDs for non-running jobs.\n 127→// This is useful to process large job counts and intended to be used\n 128→// together with FindById to process jobs one by one.\n 129→// Use limit and offset for pagination. Use limit=0 to get all results (not recommended for large datasets).\n 130→func (r *JobRepository) GetJobList(limit int, offset int) ([]int64, error) {\n 131→\tquery := sq.Select(\"id\").From(\"job\").\n 132→\t\tWhere(\"job.job_state != 'running'\")\n 133→\n 134→\t// Add pagination if limit is specified\n 135→\tif limit > 0 {\n 136→\t\tquery = query.Limit(uint64(limit)).Offset(uint64(offset))\n 137→\t}\n 138→\n 139→\trows, err := query.RunWith(r.stmtCache).Query()\n 140→\tif err != nil {\n 141→\t\tcclog.Errorf(\"Error while running GetJobList query (limit=%d, offset=%d): %v\", limit, offset, err)\n 142→\t\treturn nil, fmt.Errorf(\"failed to execute GetJobList query: %w\", err)\n 143→\t}\n 144→\tdefer rows.Close()\n 145→\n 146→\tjl := make([]int64, 0, 1000)\n 147→\tfor rows.Next() {\n 148→\t\tvar id int64\n 149→\t\terr := rows.Scan(&id)\n 150→\t\tif err != nil {\n 151→\t\t\tcclog.Warnf(\"Error while scanning rows in GetJobList: %v\", err)\n 152→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID: %w\", err)\n 153→\t\t}\n 154→\t\tjl = append(jl, id)\n 155→\t}\n 156→\n 157→\tcclog.Debugf(\"JobRepository.GetJobList(): Return job count %d\", len(jl))\n 158→\treturn jl, nil\n 159→}\n 160→\n 161→// FindByID executes a SQL query to find a specific batch job.\n 162→// The job is queried using the database id.\n 163→// It returns a pointer to a schema.Job data structure and an error variable.\n 164→// To check if no job was found test err == sql.ErrNoRows\n 165→func (r *JobRepository) FindByID(ctx context.Context, jobID int64) (*schema.Job, error) {\n 166→\tq := sq.Select(jobColumns...).\n 167→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 168→\n 169→\tq, qerr := SecurityCheck(ctx, q)\n 170→\tif qerr != nil {\n 171→\t\treturn nil, qerr\n 172→\t}\n 173→\n 174→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 175→}\n 176→\n 177→// FindByIDWithUser executes a SQL query to find a specific batch job.\n 178→// The job is queried using the database id. The user is passed directly,\n 179→// instead as part of the context.\n 180→// It returns a pointer to a schema.Job data structure and an error variable.\n 181→// To check if no job was found test err == sql.ErrNoRows\n 182→func (r *JobRepository) FindByIDWithUser(user *schema.User, jobID int64) (*schema.Job, error) {\n 183→\tq := sq.Select(jobColumns...).\n 184→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 185→\n 186→\tq, qerr := SecurityCheckWithUser(user, q)\n 187→\tif qerr != nil {\n 188→\t\treturn nil, qerr\n 189→\t}\n 190→\n 191→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 192→}\n 193→\n 194→// FindByIDDirect executes a SQL query to find a specific batch job.\n 195→// The job is queried using the database id.\n 196→// It returns a pointer to a schema.Job data structure and an error variable.\n 197→// To check if no job was found test err == sql.ErrNoRows\n 198→func (r *JobRepository) FindByIDDirect(jobID int64) (*schema.Job, error) {\n 199→\tq := sq.Select(jobColumns...).\n 200→\t\tFrom(\"job\").Where(\"job.id = ?\", jobID)\n 201→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 202→}\n 203→\n 204→// FindByJobID executes a SQL query to find a specific batch job.\n 205→// The job is queried using the slurm id and the clustername.\n 206→// It returns a pointer to a schema.Job data structure and an error variable.\n 207→// To check if no job was found test err == sql.ErrNoRows\n 208→func (r *JobRepository) FindByJobID(ctx context.Context, jobID int64, startTime int64, cluster string) (*schema.Job, error) {\n 209→\tq := sq.Select(jobColumns...).\n 210→\t\tFrom(\"job\").\n 211→\t\tWhere(\"job.job_id = ?\", jobID).\n 212→\t\tWhere(\"job.cluster = ?\", cluster).\n 213→\t\tWhere(\"job.start_time = ?\", startTime)\n 214→\n 215→\tq, qerr := SecurityCheck(ctx, q)\n 216→\tif qerr != nil {\n 217→\t\treturn nil, qerr\n 218→\t}\n 219→\n 220→\treturn scanJob(q.RunWith(r.stmtCache).QueryRow())\n 221→}\n 222→\n 223→// IsJobOwner checks if the specified user owns the batch job identified by jobID,\n 224→// startTime, and cluster. Returns true if the user is the owner, false otherwise.\n 225→// This method does not return errors; it returns false for both non-existent jobs\n 226→// and jobs owned by other users.\n 227→func (r *JobRepository) IsJobOwner(jobID int64, startTime int64, user string, cluster string) bool {\n 228→\tq := sq.Select(\"id\").\n 229→\t\tFrom(\"job\").\n 230→\t\tWhere(\"job.job_id = ?\", jobID).\n 231→\t\tWhere(\"job.hpc_user = ?\", user).\n 232→\t\tWhere(\"job.cluster = ?\", cluster).\n 233→\t\tWhere(\"job.start_time = ?\", startTime)\n 234→\n 235→\t_, err := scanJob(q.RunWith(r.stmtCache).QueryRow())\n 236→\tif err != nil && err != sql.ErrNoRows {\n 237→\t\tcclog.Warnf(\"IsJobOwner: unexpected error for jobID=%d, user=%s, cluster=%s: %v\", jobID, user, cluster, err)\n 238→\t}\n 239→\treturn err != sql.ErrNoRows\n 240→}\n 241→\n 242→func (r *JobRepository) FindConcurrentJobs(\n 243→\tctx context.Context,\n 244→\tjob *schema.Job,\n 245→) (*model.JobLinkResultList, error) {\n 246→\tif job == nil {\n 247→\t\treturn nil, nil\n 248→\t}\n 249→\n 250→\tquery, qerr := SecurityCheck(ctx, sq.Select(\"job.id\", \"job.job_id\", \"job.start_time\").From(\"job\"))\n 251→\tif qerr != nil {\n 252→\t\treturn nil, qerr\n 253→\t}\n 254→\n 255→\tquery = query.Where(\"cluster = ?\", job.Cluster)\n 256→\n 257→\tif len(job.Resources) == 0 {\n 258→\t\treturn nil, fmt.Errorf(\"job has no resources defined\")\n 259→\t}\n 260→\n 261→\tvar startTime int64\n 262→\tvar stopTime int64\n 263→\n 264→\tstartTime = job.StartTime\n 265→\thostname := job.Resources[0].Hostname\n 266→\n 267→\tif job.State == schema.JobStateRunning {\n 268→\t\tstopTime = time.Now().Unix()\n 269→\t} else {\n 270→\t\tstopTime = startTime + int64(job.Duration)\n 271→\t}\n 272→\n 273→\t// Time buffer constant for finding overlapping jobs\n 274→\t// overlapBufferEnd: 200s buffer at job end to account for scheduling/cleanup overlap\n 275→\tconst overlapBufferEnd = 200\n 276→\n 277→\tstopTimeTail := stopTime - overlapBufferEnd\n 278→\tstartTimeFront := startTime + overlapBufferEnd\n 279→\n 280→\tqueryRunning := query.Where(\"job.job_state = ?\", \"running\").\n 281→\t\tWhere(\"job.start_time <= ?\", stopTimeTail)\n 282→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 283→\tqueryRunning = queryRunning.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 284→\n 285→\tquery = query.Where(\"job.job_state != ?\", \"running\").\n 286→\t\tWhere(\"job.start_time < ?\", stopTimeTail).\n 287→\t\tWhere(\"(job.start_time + job.duration) > ?\", startTimeFront)\n 288→\t// Get At Least One Exact Hostname Match from JSON Resources Array in Database\n 289→\tquery = query.Where(\"EXISTS (SELECT 1 FROM json_each(job.resources) WHERE json_extract(value, '$.hostname') = ?)\", hostname)\n 290→\n 291→\trows, err := query.RunWith(r.stmtCache).Query()\n 292→\tif err != nil {\n 293→\t\tcclog.Errorf(\"Error while running concurrent jobs query: %v\", err)\n 294→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent jobs query: %w\", err)\n 295→\t}\n 296→\tdefer rows.Close()\n 297→\n 298→\titems := make([]*model.JobLink, 0, 10)\n 299→\tqueryString := fmt.Sprintf(\"cluster=%s\", job.Cluster)\n 300→\n 301→\tfor rows.Next() {\n 302→\t\tvar id, jobID, startTime sql.NullInt64\n 303→\n 304→\t\tif err = rows.Scan(&id, &jobID, &startTime); err != nil {\n 305→\t\t\tcclog.Warnf(\"Error while scanning concurrent job rows: %v\", err)\n 306→\t\t\treturn nil, fmt.Errorf(\"failed to scan concurrent job row: %w\", err)\n 307→\t\t}\n 308→\n 309→\t\tif id.Valid {\n 310→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 311→\t\t\titems = append(items,\n 312→\t\t\t\t&model.JobLink{\n 313→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 314→\t\t\t\t\tJobID: int(jobID.Int64),\n 315→\t\t\t\t})\n 316→\t\t}\n 317→\t}\n 318→\n 319→\trows, err = queryRunning.RunWith(r.stmtCache).Query()\n 320→\tif err != nil {\n 321→\t\tcclog.Errorf(\"Error while running concurrent running jobs query: %v\", err)\n 322→\t\treturn nil, fmt.Errorf(\"failed to execute concurrent running jobs query: %w\", err)\n 323→\t}\n 324→\tdefer rows.Close()\n 325→\n 326→\tfor rows.Next() {\n 327→\t\tvar id, jobID, startTime sql.NullInt64\n 328→\n 329→\t\tif err := rows.Scan(&id, &jobID, &startTime); err != nil {\n 330→\t\t\tcclog.Warnf(\"Error while scanning running concurrent job rows: %v\", err)\n 331→\t\t\treturn nil, fmt.Errorf(\"failed to scan running concurrent job row: %w\", err)\n 332→\t\t}\n 333→\n 334→\t\tif id.Valid {\n 335→\t\t\tqueryString += fmt.Sprintf(\"&jobId=%d\", int(jobID.Int64))\n 336→\t\t\titems = append(items,\n 337→\t\t\t\t&model.JobLink{\n 338→\t\t\t\t\tID: fmt.Sprint(id.Int64),\n 339→\t\t\t\t\tJobID: int(jobID.Int64),\n 340→\t\t\t\t})\n 341→\t\t}\n 342→\t}\n 343→\n 344→\tcnt := len(items)\n 345→\n 346→\treturn &model.JobLinkResultList{\n 347→\t\tListQuery: &queryString,\n 348→\t\tItems: items,\n 349→\t\tCount: &cnt,\n 350→\t}, nil\n 351→}\n 352→"}]},"uuid":"71673ae8-7c1d-4cb2-843e-237acdd6514d","timestamp":"2026-03-11T04:34:56.884Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"cae960e1-7e6d-4ebc-954f-460e4a5a1d27","timestamp":"2026-03-11T04:34:56.967Z"}
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+{"parentUuid":"c8e81245-2975-4733-951b-39011fb15f10","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QZarGmibdGxEkEQSJcTph6","type":"tool_result","content":"\nOutput too large (49.5KB). Full output saved to: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/42401d2e-7d1c-4c0e-abe6-356cb2d48747/tool-results/toolu_01QZarGmibdGxEkEQSJcTph6.txt\n\nPreview (first 2KB):\n 1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n 2→// All rights reserved. This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→// Package repository provides the data access layer for cc-backend using the repository pattern.\n 7→//\n 8→// The repository pattern abstracts database operations and provides a clean interface for\n 9→// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n 10→// operations and specialized queries.\n 11→//\n 12→// # Database Connection\n 13→//\n 14→// Initialize the database connection before using any repository:\n 15→//\n 16→//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n 17→//\n 18→// # Configuration\n 19→//\n 20→// Optional: Configure repository settings before initialization:\n 21→//\n 22→//\trepository.SetConfig(&repository.RepositoryConfig{\n 23→//\t CacheSize: 2 * 1024 * 1024, // 2MB cache\n 24→//\t MaxOpenConnections: 8, // Connection pool size\n 25→//\t MinRunningJobDuration: 300, // Filter threshold\n 26→//\t})\n 27→//\n 28→// If not configured, sensible defaults are used automatically.\n 29→//\n 30→// # Repositories\n 31→//\n 32→// - JobRepository: Job lifecycle management and querying\n 33→// - UserRepository: User management and authentication\n 34→// - NodeRepository: Cluster node state tracking\n 35→// - Tags: Job tagging and categorization\n 36→//\n 37→// # Caching\n 38→//\n 39→// Repositories use LRU caching to improve performance. Cache keys are constructed\n 40→// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n 41→// mutations to maintain consistency.\n 42→//\n 43→// # Transaction Support\n 44→//\n 45→// For batch operations, use transactions:\n 46→//\n 47→//\tt, err := jobRepo.TransactionInit()\n...\n"}]},"uuid":"85d37510-c715-49bb-a114-f09e89d04397","timestamp":"2026-03-11T04:34:57.237Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"f664303c-d8e9-4152-b0b4-db180b736f48","timestamp":"2026-03-11T04:34:57.238Z"}
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+{"parentUuid":"cbebe140-31a1-42e0-834b-79a61e0590ca","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Vf6pZK5ChpmLABwq5okeJV","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 data access and persistence layer for ClusterCockpit.\n 7→//\n 8→// This file implements tag management functionality for job categorization and classification.\n 9→// Tags support both manual assignment (via REST/GraphQL APIs) and automatic detection\n 10→// (via tagger plugins). The implementation includes role-based access control through\n 11→// tag scopes and maintains bidirectional consistency between the SQL database and\n 12→// the file-based job archive.\n 13→//\n 14→// Database Schema:\n 15→//\n 16→//\tCREATE TABLE tag (\n 17→//\t id INTEGER PRIMARY KEY AUTOINCREMENT,\n 18→//\t tag_type VARCHAR(255) NOT NULL,\n 19→//\t tag_name VARCHAR(255) NOT NULL,\n 20→//\t tag_scope VARCHAR(255) NOT NULL DEFAULT \"global\",\n 21→//\t CONSTRAINT tag_unique UNIQUE (tag_type, tag_name, tag_scope)\n 22→//\t);\n 23→//\n 24→//\tCREATE TABLE jobtag (\n 25→//\t job_id INTEGER,\n 26→//\t tag_id INTEGER,\n 27→//\t PRIMARY KEY (job_id, tag_id),\n 28→//\t FOREIGN KEY (job_id) REFERENCES job(id) ON DELETE CASCADE,\n 29→//\t FOREIGN KEY (tag_id) REFERENCES tag(id) ON DELETE CASCADE\n 30→//\t);\n 31→//\n 32→// The jobtag junction table enables many-to-many relationships between jobs and tags.\n 33→// CASCADE deletion ensures referential integrity when jobs or tags are removed.\n 34→package repository\n 35→\n 36→import (\n 37→\t\"errors\"\n 38→\t\"fmt\"\n 39→\t\"strings\"\n 40→\n 41→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 42→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 43→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 44→\tsq \"github.com/Masterminds/squirrel\"\n 45→)\n 46→\n 47→// Tag Scope Rules:\n 48→//\n 49→// Tags in ClusterCockpit have three visibility scopes that control who can see and use them:\n 50→//\n 51→// 1. \"global\" - Visible to all users, can be used by anyone\n 52→// Example: System-generated tags like \"energy-efficient\", \"failed\", \"short\"\n 53→//\n 54→// 2. \"private\" - Only visible to the creating user\n 55→// Example: Personal notes like \"needs-review\", \"interesting-case\"\n 56→//\n 57→// 3. \"admin\" - Only visible to users with admin or support roles\n 58→// Example: Internal notes like \"hardware-issue\", \"billing-problem\"\n 59→//\n 60→// Authorization Rules:\n 61→// - Regular users can only create/see \"global\" and their own \"private\" tags\n 62→// - Admin/Support can create/see all scopes including \"admin\" tags\n 63→// - Users can only add tags to jobs they have permission to view\n 64→// - Tag scope is enforced at query time in GetTags() and CountTags()\n 65→\n 66→// AddTag adds the tag with id `tagId` to the job with the database id `jobId`.\n 67→// Requires user authentication for security checks.\n 68→//\n 69→// The user must have permission to view the job. Tag visibility is determined by scope:\n 70→// - \"global\" tags: visible to all users\n 71→// - \"private\" tags: only visible to the tag creator\n 72→// - \"admin\" tags: only visible to admin/support users\n 73→func (r *JobRepository) AddTag(user *schema.User, job int64, tag int64) ([]*schema.Tag, error) {\n 74→\tj, err := r.FindByIDWithUser(user, job)\n 75→\tif err != nil {\n 76→\t\tcclog.Warnf(\"Error finding job %d for user %s: %v\", job, user.Username, err)\n 77→\t\treturn nil, err\n 78→\t}\n 79→\n 80→\treturn r.addJobTag(job, tag, j, func() ([]*schema.Tag, error) {\n 81→\t\treturn r.GetTags(user, &job)\n 82→\t})\n 83→}\n 84→\n 85→// AddTagDirect adds a tag without user security checks.\n 86→// Use only for internal/admin operations.\n 87→func (r *JobRepository) AddTagDirect(job int64, tag int64) ([]*schema.Tag, error) {\n 88→\tj, err := r.FindByIDDirect(job)\n 89→\tif err != nil {\n 90→\t\tcclog.Warnf(\"Error finding job %d: %v\", job, err)\n 91→\t\treturn nil, err\n 92→\t}\n 93→\n 94→\treturn r.addJobTag(job, tag, j, func() ([]*schema.Tag, error) {\n 95→\t\treturn r.GetTagsDirect(&job)\n 96→\t})\n 97→}\n 98→\n 99→// RemoveTag removes the tag with the database id `tag` from the job with the database id `job`.\n 100→// Requires user authentication for security checks. Used by GraphQL API.\n 101→func (r *JobRepository) RemoveTag(user *schema.User, job, tag int64) ([]*schema.Tag, error) {\n 102→\tj, err := r.FindByIDWithUser(user, job)\n 103→\tif err != nil {\n 104→\t\tcclog.Warnf(\"Error while finding job %d for user %s during tag removal: %v\", job, user.Username, err)\n 105→\t\treturn nil, err\n 106→\t}\n 107→\n 108→\tq := sq.Delete(\"jobtag\").Where(\"jobtag.job_id = ?\", job).Where(\"jobtag.tag_id = ?\", tag)\n 109→\n 110→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 111→\t\ts, _, _ := q.ToSql()\n 112→\t\tcclog.Errorf(\"Error removing tag with %s: %v\", s, err)\n 113→\t\treturn nil, err\n 114→\t}\n 115→\n 116→\ttags, err := r.GetTags(user, &job)\n 117→\tif err != nil {\n 118→\t\tcclog.Warn(\"Error while getting tags for job\")\n 119→\t\treturn nil, err\n 120→\t}\n 121→\n 122→\tarchiveTags, err := r.getArchiveTags(&job)\n 123→\tif err != nil {\n 124→\t\tcclog.Warnf(\"Error while getting archive tags for job %d in RemoveTag: %v\", job, err)\n 125→\t\treturn nil, err\n 126→\t}\n 127→\n 128→\treturn tags, archive.UpdateTags(j, archiveTags)\n 129→}\n 130→\n 131→// RemoveJobTagByRequest removes a tag from the job with the database id `job` by tag type, name, and scope.\n 132→// Requires user authentication for security checks. Used by REST API.\n 133→func (r *JobRepository) RemoveJobTagByRequest(user *schema.User, job int64, tagType string, tagName string, tagScope string) ([]*schema.Tag, error) {\n 134→\t// Get Tag ID to delete\n 135→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 136→\tif !exists {\n 137→\t\tcclog.Warnf(\"Tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 138→\t\treturn nil, fmt.Errorf(\"tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 139→\t}\n 140→\n 141→\t// Get Job\n 142→\tj, err := r.FindByIDWithUser(user, job)\n 143→\tif err != nil {\n 144→\t\tcclog.Warnf(\"Error while finding job %d for user %s during tag removal by request: %v\", job, user.Username, err)\n 145→\t\treturn nil, err\n 146→\t}\n 147→\n 148→\t// Handle Delete\n 149→\tq := sq.Delete(\"jobtag\").Where(\"jobtag.job_id = ?\", job).Where(\"jobtag.tag_id = ?\", tagID)\n 150→\n 151→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 152→\t\ts, _, _ := q.ToSql()\n 153→\t\tcclog.Errorf(\"Error removing tag from table 'jobTag' with %s: %v\", s, err)\n 154→\t\treturn nil, err\n 155→\t}\n 156→\n 157→\ttags, err := r.GetTags(user, &job)\n 158→\tif err != nil {\n 159→\t\tcclog.Warnf(\"Error while getting tags for job %d in RemoveJobTagByRequest: %v\", job, err)\n 160→\t\treturn nil, err\n 161→\t}\n 162→\n 163→\tarchiveTags, err := r.getArchiveTags(&job)\n 164→\tif err != nil {\n 165→\t\tcclog.Warnf(\"Error while getting archive tags for job %d in RemoveJobTagByRequest: %v\", job, err)\n 166→\t\treturn nil, err\n 167→\t}\n 168→\n 169→\treturn tags, archive.UpdateTags(j, archiveTags)\n 170→}\n 171→\n 172→// removeTagFromArchiveJobs updates the job archive for all affected jobs after a tag deletion.\n 173→//\n 174→// This function is called asynchronously (via goroutine) after removing a tag from the database\n 175→// to synchronize the file-based job archive with the database state. Errors are logged but not\n 176→// returned since this runs in the background.\n 177→//\n 178→// Parameters:\n 179→// - jobIds: Database IDs of all jobs that had the deleted tag\n 180→//\n 181→// Implementation note: Each job is processed individually to handle partial failures gracefully.\n 182→// If one job fails to update, others will still be processed.\n 183→func (r *JobRepository) removeTagFromArchiveJobs(jobIds []int64) {\n 184→\tfor _, j := range jobIds {\n 185→\t\ttags, err := r.getArchiveTags(&j)\n 186→\t\tif err != nil {\n 187→\t\t\tcclog.Warnf(\"Error while getting tags for job %d\", j)\n 188→\t\t\tcontinue\n 189→\t\t}\n 190→\n 191→\t\tjob, err := r.FindByIDDirect(j)\n 192→\t\tif err != nil {\n 193→\t\t\tcclog.Warnf(\"Error while getting job %d\", j)\n 194→\t\t\tcontinue\n 195→\t\t}\n 196→\n 197→\t\tarchive.UpdateTags(job, tags)\n 198→\t}\n 199→}\n 200→\n 201→// Removes a tag from db by tag info\n 202→// Used by REST API. Does not update tagged jobs in Job archive.\n 203→func (r *JobRepository) RemoveTagByRequest(tagType string, tagName string, tagScope string) error {\n 204→\t// Get Tag ID to delete\n 205→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 206→\tif !exists {\n 207→\t\tcclog.Warnf(\"Tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 208→\t\treturn fmt.Errorf(\"tag does not exist (name, type, scope): %s, %s, %s\", tagName, tagType, tagScope)\n 209→\t}\n 210→\n 211→\treturn r.RemoveTagByID(tagID)\n 212→}\n 213→\n 214→// Removes a tag from db by tag id\n 215→// Used by GraphQL API.\n 216→func (r *JobRepository) RemoveTagByID(tagID int64) error {\n 217→\tjobIds, err := r.FindJobIdsByTag(tagID)\n 218→\tif err != nil {\n 219→\t\treturn err\n 220→\t}\n 221→\n 222→\t// Handle Delete JobTagTable\n 223→\tqJobTag := sq.Delete(\"jobtag\").Where(\"jobtag.tag_id = ?\", tagID)\n 224→\n 225→\tif _, err := qJobTag.RunWith(r.stmtCache).Exec(); err != nil {\n 226→\t\ts, _, _ := qJobTag.ToSql()\n 227→\t\tcclog.Errorf(\"Error removing tag from table 'jobTag' with %s: %v\", s, err)\n 228→\t\treturn err\n 229→\t}\n 230→\n 231→\t// Handle Delete TagTable\n 232→\tqTag := sq.Delete(\"tag\").Where(\"tag.id = ?\", tagID)\n 233→\n 234→\tif _, err := qTag.RunWith(r.stmtCache).Exec(); err != nil {\n 235→\t\ts, _, _ := qTag.ToSql()\n 236→\t\tcclog.Errorf(\"Error removing tag from table 'tag' with %s: %v\", s, err)\n 237→\t\treturn err\n 238→\t}\n 239→\n 240→\t// asynchronously update archive jobs\n 241→\tgo r.removeTagFromArchiveJobs(jobIds)\n 242→\n 243→\treturn nil\n 244→}\n 245→\n 246→// CreateTag creates a new tag with the specified type, name, and scope.\n 247→// Returns the database ID of the newly created tag.\n 248→//\n 249→// Scope defaults to \"global\" if empty string is provided.\n 250→// Valid scopes: \"global\", \"private\", \"admin\"\n 251→//\n 252→// Example:\n 253→//\n 254→//\ttagID, err := repo.CreateTag(\"performance\", \"high-memory\", \"global\")\n 255→func (r *JobRepository) CreateTag(tagType string, tagName string, tagScope string) (tagID int64, err error) {\n 256→\t// Default to \"Global\" scope if none defined\n 257→\tif tagScope == \"\" {\n 258→\t\ttagScope = \"global\"\n 259→\t}\n 260→\n 261→\tq := sq.Insert(\"tag\").Columns(\"tag_type\", \"tag_name\", \"tag_scope\").Values(tagType, tagName, tagScope)\n 262→\n 263→\tres, err := q.RunWith(r.stmtCache).Exec()\n 264→\tif err != nil {\n 265→\t\ts, _, _ := q.ToSql()\n 266→\t\tcclog.Errorf(\"Error inserting tag with %s: %v\", s, err)\n 267→\t\treturn 0, err\n 268→\t}\n 269→\n 270→\treturn res.LastInsertId()\n 271→}\n 272→\n 273→// CountTags returns all tags visible to the user and the count of jobs for each tag.\n 274→// Applies scope-based filtering to respect tag visibility rules.\n 275→//\n 276→// Returns:\n 277→// - tags: slice of tags the user can see\n 278→// - counts: map of tag name to job count\n 279→// - err: any error encountered\n 280→func (r *JobRepository) CountTags(user *schema.User) (tags []schema.Tag, counts map[string]int, err error) {\n 281→\ttags = make([]schema.Tag, 0, 100)\n 282→\txrows, err := r.DB.Queryx(\"SELECT id, tag_type, tag_name, tag_scope FROM tag\")\n 283→\tif err != nil {\n 284→\t\treturn nil, nil, err\n 285→\t}\n 286→\tdefer xrows.Close()\n 287→\n 288→\tfor xrows.Next() {\n 289→\t\tvar t schema.Tag\n 290→\t\tif err = xrows.StructScan(&t); err != nil {\n 291→\t\t\treturn nil, nil, err\n 292→\t\t}\n 293→\n 294→\t\t// Handle Scope Filtering: Tag Scope is Global, Private (== Username) or User is auth'd to view Admin Tags\n 295→\t\treadable, err := r.checkScopeAuth(user, \"read\", t.Scope)\n 296→\t\tif err != nil {\n 297→\t\t\treturn nil, nil, err\n 298→\t\t}\n 299→\t\tif readable {\n 300→\t\t\ttags = append(tags, t)\n 301→\t\t}\n 302→\t}\n 303→\n 304→\tif err := xrows.Err(); err != nil {\n 305→\t\treturn nil, nil, err\n 306→\t}\n 307→\n 308→\t// Query and Count Jobs with attached Tags\n 309→\tq := sq.Select(\"t.tag_type, t.tag_name, t.id, count(jt.tag_id)\").\n 310→\t\tFrom(\"tag t\").\n 311→\t\tLeftJoin(\"jobtag jt ON t.id = jt.tag_id\").\n 312→\t\tGroupBy(\"t.tag_type, t.tag_name\")\n 313→\n 314→\t// Build scope list for filtering\n 315→\tvar scopeBuilder strings.Builder\n 316→\tscopeBuilder.WriteString(`\"global\"`)\n 317→\tif user != nil {\n 318→\t\tscopeBuilder.WriteString(`,\"`)\n 319→\t\tscopeBuilder.WriteString(user.Username)\n 320→\t\tscopeBuilder.WriteString(`\"`)\n 321→\t\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n 322→\t\t\tscopeBuilder.WriteString(`,\"admin\"`)\n 323→\t\t}\n 324→\t}\n 325→\tq = q.Where(\"t.tag_scope IN (\" + scopeBuilder.String() + \")\")\n 326→\n 327→\t// Handle Job Ownership\n 328→\tif user != nil && user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) { // ADMIN || SUPPORT: Count all jobs\n 329→\t\t// cclog.Debug(\"CountTags: User Admin or Support -> Count all Jobs for Tags\")\n 330→\t\t// Unchanged: Needs to be own case still, due to UserRole/NoRole compatibility handling in else case\n 331→\t} else if user != nil && user.HasRole(schema.RoleManager) { // MANAGER: Count own jobs plus project's jobs\n 332→\t\t// Build (\"project1\", \"project2\", ...) list of variable length directly in SQL string\n 333→\t\tq = q.Where(\"jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ? OR job.project IN (\\\"\"+strings.Join(user.Projects, \"\\\",\\\"\")+\"\\\"))\", user.Username)\n 334→\t} else if user != nil { // USER OR NO ROLE (Compatibility): Only count own jobs\n 335→\t\tq = q.Where(\"jt.job_id IN (SELECT id FROM job WHERE job.hpc_user = ?)\", user.Username)\n 336→\t}\n 337→\n 338→\trows, err := q.RunWith(r.stmtCache).Query()\n 339→\tif err != nil {\n 340→\t\treturn nil, nil, err\n 341→\t}\n 342→\tdefer rows.Close()\n 343→\n 344→\tcounts = make(map[string]int)\n 345→\tfor rows.Next() {\n 346→\t\tvar tagType string\n 347→\t\tvar tagName string\n 348→\t\tvar tagID int\n 349→\t\tvar count int\n 350→\t\tif err = rows.Scan(&tagType, &tagName, &tagID, &count); err != nil {\n 351→\t\t\treturn nil, nil, err\n 352→\t\t}\n 353→\t\t// Use tagId as second Map-Key component to differentiate tags with identical names\n 354→\t\tcounts[fmt.Sprint(tagType, tagName, tagID)] = count\n 355→\t}\n 356→\terr = rows.Err()\n 357→\n 358→\treturn tags, counts, err\n 359→}\n 360→\n 361→var (\n 362→\t// ErrTagNotFound is returned when a tag ID or tag identifier (type, name, scope) does not exist in the database.\n 363→\tErrTagNotFound = errors.New(\"the tag does not exist\")\n 364→\n 365→\t// ErrJobNotOwned is returned when a user attempts to tag a job they do not have permission to access.\n 366→\tErrJobNotOwned = errors.New(\"user is not owner of job\")\n 367→\n 368→\t// ErrTagNoAccess is returned when a user attempts to use a tag they cannot access due to scope restrictions.\n 369→\tErrTagNoAccess = errors.New(\"user not permitted to use that tag\")\n 370→\n 371→\t// ErrTagPrivateScope is returned when a user attempts to access another user's private tag.\n 372→\tErrTagPrivateScope = errors.New(\"tag is private to another user\")\n 373→\n 374→\t// ErrTagAdminScope is returned when a non-admin user attempts to use an admin-scoped tag.\n 375→\tErrTagAdminScope = errors.New(\"tag requires admin privileges\")\n 376→\n 377→\t// ErrTagsIncompatScopes is returned when attempting to combine admin and non-admin scoped tags in a single operation.\n 378→\tErrTagsIncompatScopes = errors.New(\"combining admin and non-admin scoped tags not allowed\")\n 379→)\n 380→\n 381→// addJobTag is a helper function that inserts a job-tag association and updates the archive.\n 382→//\n 383→// This function performs three operations atomically:\n 384→// 1. Inserts the job-tag association into the jobtag junction table\n 385→// 2. Retrieves the updated tag list for the job (using the provided getTags callback)\n 386→// 3. Updates the job archive with the new tags to maintain database-archive consistency\n 387→//\n 388→// Parameters:\n 389→// - jobId: Database ID of the job\n 390→// - tagId: Database ID of the tag to associate\n 391→// - job: Full job object needed for archive update\n 392→// - getTags: Callback function to retrieve updated tags (allows different security contexts)\n 393→//\n 394→// Returns the complete updated tag list for the job or an error.\n 395→//\n 396→// Note: This function does NOT validate tag scope permissions - callers must perform\n 397→// authorization checks before invoking this helper.\n 398→func (r *JobRepository) addJobTag(jobID int64, tagID int64, job *schema.Job, getTags func() ([]*schema.Tag, error)) ([]*schema.Tag, error) {\n 399→\tq := sq.Insert(\"jobtag\").Columns(\"job_id\", \"tag_id\").Values(jobID, tagID)\n 400→\n 401→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 402→\t\ts, _, _ := q.ToSql()\n 403→\t\tcclog.Errorf(\"Error adding tag with %s: %v\", s, err)\n 404→\t\treturn nil, err\n 405→\t}\n 406→\n 407→\ttags, err := getTags()\n 408→\tif err != nil {\n 409→\t\tcclog.Warnf(\"Error getting tags for job %d: %v\", jobID, err)\n 410→\t\treturn nil, err\n 411→\t}\n 412→\n 413→\tarchiveTags, err := r.getArchiveTags(&jobID)\n 414→\tif err != nil {\n 415→\t\tcclog.Warnf(\"Error getting archive tags for job %d: %v\", jobID, err)\n 416→\t\treturn nil, err\n 417→\t}\n 418→\n 419→\treturn tags, archive.UpdateTags(job, archiveTags)\n 420→}\n 421→\n 422→// AddTagOrCreate adds the tag with the specified type and name to the job with the database id `jobId`.\n 423→// If such a tag does not yet exist, it is created.\n 424→func (r *JobRepository) AddTagOrCreate(user *schema.User, jobID int64, tagType string, tagName string, tagScope string) (tagID int64, err error) {\n 425→\t// Default to \"Global\" scope if none defined\n 426→\tif tagScope == \"\" {\n 427→\t\ttagScope = \"global\"\n 428→\t}\n 429→\n 430→\twritable, err := r.checkScopeAuth(user, \"write\", tagScope)\n 431→\tif err != nil {\n 432→\t\treturn 0, err\n 433→\t}\n 434→\tif !writable {\n 435→\t\treturn 0, fmt.Errorf(\"cannot write tag scope with current authorization\")\n 436→\t}\n 437→\n 438→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 439→\tif !exists {\n 440→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 441→\t\tif err != nil {\n 442→\t\t\treturn 0, err\n 443→\t\t}\n 444→\t}\n 445→\n 446→\tif _, err := r.AddTag(user, jobID, tagID); err != nil {\n 447→\t\treturn 0, err\n 448→\t}\n 449→\n 450→\treturn tagID, nil\n 451→}\n 452→\n 453→func (r *JobRepository) AddTagOrCreateDirect(jobID int64, tagType string, tagName string) (tagID int64, err error) {\n 454→\ttagScope := \"global\"\n 455→\n 456→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 457→\tif !exists {\n 458→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 459→\t\tif err != nil {\n 460→\t\t\treturn 0, err\n 461→\t\t}\n 462→\t}\n 463→\n 464→\tcclog.Infof(\"Adding tag %s:%s:%s (direct)\", tagType, tagName, tagScope)\n 465→\n 466→\tif _, err := r.AddTagDirect(jobID, tagID); err != nil {\n 467→\t\treturn 0, err\n 468→\t}\n 469→\n 470→\treturn tagID, nil\n 471→}\n 472→\n 473→func (r *JobRepository) HasTag(jobID int64, tagType string, tagName string) bool {\n 474→\tvar id int64\n 475→\tq := sq.Select(\"id\").From(\"tag\").Join(\"jobtag ON jobtag.tag_id = tag.id\").\n 476→\t\tWhere(\"jobtag.job_id = ?\", jobID).Where(\"tag.tag_type = ?\", tagType).\n 477→\t\tWhere(\"tag.tag_name = ?\", tagName)\n 478→\terr := q.RunWith(r.stmtCache).QueryRow().Scan(&id)\n 479→\tif err != nil {\n 480→\t\treturn false\n 481→\t} else {\n 482→\t\treturn true\n 483→\t}\n 484→}\n 485→\n 486→// TagID returns the database id of the tag with the specified type and name.\n 487→func (r *JobRepository) TagID(tagType string, tagName string, tagScope string) (tagID int64, exists bool) {\n 488→\texists = true\n 489→\tif err := sq.Select(\"id\").From(\"tag\").\n 490→\t\tWhere(\"tag.tag_type = ?\", tagType).Where(\"tag.tag_name = ?\", tagName).Where(\"tag.tag_scope = ?\", tagScope).\n 491→\t\tRunWith(r.stmtCache).QueryRow().Scan(&tagID); err != nil {\n 492→\t\texists = false\n 493→\t}\n 494→\treturn\n 495→}\n 496→\n 497→// TagInfo returns the database infos of the tag with the specified id.\n 498→func (r *JobRepository) TagInfo(tagID int64) (tagType string, tagName string, tagScope string, exists bool) {\n 499→\texists = true\n 500→\tif err := sq.Select(\"tag.tag_type\", \"tag.tag_name\", \"tag.tag_scope\").From(\"tag\").Where(\"tag.id = ?\", tagID).\n 501→\t\tRunWith(r.stmtCache).QueryRow().Scan(&tagType, &tagName, &tagScope); err != nil {\n 502→\t\texists = false\n 503→\t}\n 504→\treturn\n 505→}\n 506→\n 507→// GetTags returns a list of all scoped tags if job is nil or of the tags that the job with that database ID has.\n 508→func (r *JobRepository) GetTags(user *schema.User, job *int64) ([]*schema.Tag, error) {\n 509→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 510→\tif job != nil {\n 511→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 512→\t}\n 513→\n 514→\trows, err := q.RunWith(r.stmtCache).Query()\n 515→\tif err != nil {\n 516→\t\ts, _, _ := q.ToSql()\n 517→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 518→\t\treturn nil, err\n 519→\t}\n 520→\tdefer rows.Close()\n 521→\n 522→\ttags := make([]*schema.Tag, 0)\n 523→\tfor rows.Next() {\n 524→\t\ttag := &schema.Tag{}\n 525→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 526→\t\t\tcclog.Warnf(\"Error while scanning tag rows in GetTags: %v\", err)\n 527→\t\t\treturn nil, err\n 528→\t\t}\n 529→\t\t// Handle Scope Filtering: Tag Scope is Global, Private (== Username) or User is auth'd to view Admin Tags\n 530→\t\treadable, err := r.checkScopeAuth(user, \"read\", tag.Scope)\n 531→\t\tif err != nil {\n 532→\t\t\treturn nil, err\n 533→\t\t}\n 534→\t\tif readable {\n 535→\t\t\ttags = append(tags, tag)\n 536→\t\t}\n 537→\t}\n 538→\n 539→\tif err := rows.Err(); err != nil {\n 540→\t\treturn nil, err\n 541→\t}\n 542→\n 543→\treturn tags, nil\n 544→}\n 545→\n 546→func (r *JobRepository) GetTagsDirect(job *int64) ([]*schema.Tag, error) {\n 547→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 548→\tif job != nil {\n 549→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 550→\t}\n 551→\n 552→\trows, err := q.RunWith(r.stmtCache).Query()\n 553→\tif err != nil {\n 554→\t\ts, _, _ := q.ToSql()\n 555→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 556→\t\treturn nil, err\n 557→\t}\n 558→\tdefer rows.Close()\n 559→\n 560→\ttags := make([]*schema.Tag, 0)\n 561→\tfor rows.Next() {\n 562→\t\ttag := &schema.Tag{}\n 563→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 564→\t\t\tcclog.Warnf(\"Error while scanning tag rows in GetTagsDirect: %v\", err)\n 565→\t\t\treturn nil, err\n 566→\t\t}\n 567→\t\ttags = append(tags, tag)\n 568→\t}\n 569→\n 570→\tif err := rows.Err(); err != nil {\n 571→\t\treturn nil, err\n 572→\t}\n 573→\n 574→\treturn tags, nil\n 575→}\n 576→\n 577→// getArchiveTags returns all tags for a job WITHOUT applying scope-based filtering.\n 578→//\n 579→// This internal function is used exclusively for job archive synchronization where we need\n 580→// to store all tags regardless of the current user's permissions. Unlike GetTags() which\n 581→// filters by scope, this returns the complete unfiltered tag list.\n 582→//\n 583→// Parameters:\n 584→// - job: Pointer to job database ID, or nil to return all tags in the system\n 585→//\n 586→// Returns all tags without scope filtering, used only for archive operations.\n 587→//\n 588→// WARNING: Do NOT expose this function to user-facing APIs as it bypasses authorization.\n 589→func (r *JobRepository) getArchiveTags(job *int64) ([]*schema.Tag, error) {\n 590→\tq := sq.Select(\"id\", \"tag_type\", \"tag_name\", \"tag_scope\").From(\"tag\")\n 591→\tif job != nil {\n 592→\t\tq = q.Join(\"jobtag ON jobtag.tag_id = tag.id\").Where(\"jobtag.job_id = ?\", *job)\n 593→\t}\n 594→\n 595→\trows, err := q.RunWith(r.stmtCache).Query()\n 596→\tif err != nil {\n 597→\t\ts, _, _ := q.ToSql()\n 598→\t\tcclog.Errorf(\"Error get tags with %s: %v\", s, err)\n 599→\t\treturn nil, err\n 600→\t}\n 601→\tdefer rows.Close()\n 602→\n 603→\ttags := make([]*schema.Tag, 0)\n 604→\tfor rows.Next() {\n 605→\t\ttag := &schema.Tag{}\n 606→\t\tif err := rows.Scan(&tag.ID, &tag.Type, &tag.Name, &tag.Scope); err != nil {\n 607→\t\t\tcclog.Warnf(\"Error while scanning tag rows in getArchiveTags: %v\", err)\n 608→\t\t\treturn nil, err\n 609→\t\t}\n 610→\t\ttags = append(tags, tag)\n 611→\t}\n 612→\n 613→\tif err := rows.Err(); err != nil {\n 614→\t\treturn nil, err\n 615→\t}\n 616→\n 617→\treturn tags, nil\n 618→}\n 619→\n 620→func (r *JobRepository) ImportTag(jobID int64, tagType string, tagName string, tagScope string) (err error) {\n 621→\t// Import has no scope ctx, only import from metafile to DB (No recursive archive update required), only returns err\n 622→\n 623→\ttagID, exists := r.TagID(tagType, tagName, tagScope)\n 624→\tif !exists {\n 625→\t\ttagID, err = r.CreateTag(tagType, tagName, tagScope)\n 626→\t\tif err != nil {\n 627→\t\t\treturn err\n 628→\t\t}\n 629→\t}\n 630→\n 631→\tq := sq.Insert(\"jobtag\").Columns(\"job_id\", \"tag_id\").Values(jobID, tagID)\n 632→\n 633→\tif _, err := q.RunWith(r.stmtCache).Exec(); err != nil {\n 634→\t\ts, _, _ := q.ToSql()\n 635→\t\tcclog.Errorf(\"Error adding tag on import with %s: %v\", s, err)\n 636→\t\treturn err\n 637→\t}\n 638→\n 639→\treturn nil\n 640→}\n 641→\n 642→// checkScopeAuth validates whether a user is authorized to perform an operation on a tag with the given scope.\n 643→//\n 644→// This function implements the tag scope authorization matrix:\n 645→//\n 646→//\tScope | Read Access | Write Access\n 647→//\t-------------|----------------------------------|----------------------------------\n 648→//\t\"global\" | All users | Admin, Support, API-only\n 649→//\t\"admin\" | Admin, Support | Admin, API-only\n 650→//\t | Owner only | Owner only (private tags)\n 651→//\n 652→// Parameters:\n 653→// - user: User attempting the operation (must not be nil)\n 654→// - operation: Either \"read\" or \"write\"\n 655→// - scope: Tag scope value (\"global\", \"admin\", or username for private tags)\n 656→//\n 657→// Returns:\n 658→// - pass: true if authorized, false if denied\n 659→// - err: error only if operation is invalid or user is nil\n 660→//\n 661→// Special cases:\n 662→// - API-only users (single role: RoleApi) can write to admin and global scopes for automation\n 663→// - Private tags use the username as scope, granting exclusive access to that user\n 664→func (r *JobRepository) checkScopeAuth(user *schema.User, operation string, scope string) (pass bool, err error) {\n 665→\tif user != nil {\n 666→\t\tswitch {\n 667→\t\tcase operation == \"write\" && scope == \"admin\":\n 668→\t\t\tif user.HasRole(schema.RoleAdmin) || (len(user.Roles) == 1 && user.HasRole(schema.RoleAPI)) {\n 669→\t\t\t\treturn true, nil\n 670→\t\t\t}\n 671→\t\t\treturn false, nil\n 672→\t\tcase operation == \"write\" && scope == \"global\":\n 673→\t\t\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) || (len(user.Roles) == 1 && user.HasRole(schema.RoleAPI)) {\n 674→\t\t\t\treturn true, nil\n 675→\t\t\t}\n 676→\t\t\treturn false, nil\n 677→\t\tcase operation == \"write\" && scope == user.Username:\n 678→\t\t\treturn true, nil\n 679→\t\tcase operation == \"read\" && scope == \"admin\":\n 680→\t\t\treturn user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport}), nil\n 681→\t\tcase operation == \"read\" && scope == \"global\":\n 682→\t\t\treturn true, nil\n 683→\t\tcase operation == \"read\" && scope == user.Username:\n 684→\t\t\treturn true, nil\n 685→\t\tdefault:\n 686→\t\t\tif operation == \"read\" || operation == \"write\" {\n 687→\t\t\t\t// No acceptable scope: deny tag\n 688→\t\t\t\treturn false, nil\n 689→\t\t\t} else {\n 690→\t\t\t\treturn false, fmt.Errorf(\"error while checking tag operation auth: unknown operation (%s)\", operation)\n 691→\t\t\t}\n 692→\t\t}\n 693→\t} else {\n 694→\t\treturn false, fmt.Errorf(\"error while checking tag operation auth: no user in context\")\n 695→\t}\n 696→}\n 697→"}]},"uuid":"58d23af8-df56-413c-a149-bc996ccf3f73","timestamp":"2026-03-11T04:35:00.973Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"3390ed77-0519-4a5d-a959-d1fb7d228b75","timestamp":"2026-03-11T04:35:01.268Z"}
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+{"parentUuid":"1951f343-6a6e-4920-80a2-2b1cb0649b0a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PrdxTsvwkD4HAesVW5DG2u","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 10: Current version\n 25→//\n 26→// Migration files are embedded at build time from the migrations directory.\n 27→const Version uint = 10\n 28→\n 29→//go:embed migrations/*\n 30→var migrationFiles embed.FS\n 31→\n 32→// checkDBVersion verifies that the database schema version matches the expected version.\n 33→// This is called automatically during Connect() to ensure schema compatibility.\n 34→//\n 35→// Returns an error if:\n 36→// - Database version is older than expected (needs migration)\n 37→// - Database version is newer than expected (needs app upgrade)\n 38→// - Database is in a dirty state (failed migration)\n 39→//\n 40→// A \"dirty\" database indicates a migration was started but not completed successfully.\n 41→// This requires manual intervention to fix the database and force the version.\n 42→func checkDBVersion(db *sql.DB) error {\n 43→\tdriver, err := sqlite3.WithInstance(db, &sqlite3.Config{})\n 44→\tif err != nil {\n 45→\t\treturn err\n 46→\t}\n 47→\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n 48→\tif err != nil {\n 49→\t\treturn err\n 50→\t}\n 51→\n 52→\tm, err := migrate.NewWithInstance(\"iofs\", d, \"sqlite3\", driver)\n 53→\tif err != nil {\n 54→\t\treturn err\n 55→\t}\n 56→\n 57→\tv, dirty, err := m.Version()\n 58→\tif err != nil {\n 59→\t\tif err == migrate.ErrNilVersion {\n 60→\t\t\tcclog.Warn(\"Legacy database without version or missing database file!\")\n 61→\t\t} else {\n 62→\t\t\treturn err\n 63→\t\t}\n 64→\t}\n 65→\n 66→\tif v < Version {\n 67→\t\treturn fmt.Errorf(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n 68→\t} else if v > Version {\n 69→\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 70→\t}\n 71→\n 72→\tif dirty {\n 73→\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 74→\t}\n 75→\n 76→\treturn nil\n 77→}\n 78→\n 79→// getMigrateInstance creates a new migration instance for the given database file.\n 80→// This is used internally by MigrateDB, RevertDB, and ForceDB.\n 81→func getMigrateInstance(db string) (m *migrate.Migrate, err error) {\n 82→\td, err := iofs.New(migrationFiles, \"migrations/sqlite3\")\n 83→\tif err != nil {\n 84→\t\treturn nil, err\n 85→\t}\n 86→\n 87→\tm, err = migrate.NewWithSourceInstance(\"iofs\", d, fmt.Sprintf(\"sqlite3://%s?_foreign_keys=on\", db))\n 88→\tif err != nil {\n 89→\t\treturn nil, err\n 90→\t}\n 91→\n 92→\treturn m, nil\n 93→}\n 94→\n 95→// MigrateDB applies all pending database migrations to bring the schema up to date.\n 96→// This should be run with the -migrate-db flag before starting the application\n 97→// after upgrading to a new version that requires schema changes.\n 98→//\n 99→// Process:\n 100→// 1. Checks current database version\n 101→// 2. Applies all migrations from current version to target Version\n 102→// 3. Updates schema_migrations table to track applied migrations\n 103→//\n 104→// Important:\n 105→// - Always backup your database before running migrations\n 106→// - Migrations are irreversible without manual intervention\n 107→// - If a migration fails, the database is marked \"dirty\" and requires manual fix\n 108→//\n 109→// Usage:\n 110→//\n 111→//\tcc-backend -migrate-db\n 112→func MigrateDB(db string) error {\n 113→\tm, err := getMigrateInstance(db)\n 114→\tif err != nil {\n 115→\t\treturn err\n 116→\t}\n 117→\n 118→\tv, dirty, err := m.Version()\n 119→\tif err != nil {\n 120→\t\tif err == migrate.ErrNilVersion {\n 121→\t\t\tcclog.Info(\"Legacy database without version or missing database file!\")\n 122→\t\t} else {\n 123→\t\t\treturn err\n 124→\t\t}\n 125→\t}\n 126→\n 127→\tif v < Version {\n 128→\t\tcclog.Infof(\"unsupported database version %d, need %d.\\nPlease backup your database file and run cc-backend -migrate-db\", v, Version)\n 129→\t}\n 130→\n 131→\tif dirty {\n 132→\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 133→\t}\n 134→\n 135→\tif err := m.Up(); err != nil {\n 136→\t\tif err == migrate.ErrNoChange {\n 137→\t\t\tcclog.Info(\"DB already up to date!\")\n 138→\t\t} else {\n 139→\t\t\treturn err\n 140→\t\t}\n 141→\t}\n 142→\n 143→\tm.Close()\n 144→\treturn nil\n 145→}\n 146→\n 147→// RevertDB rolls back the database schema to the previous version (Version - 1).\n 148→// This is primarily used for testing or emergency rollback scenarios.\n 149→//\n 150→// Warning:\n 151→// - This may cause data loss if newer schema added columns/tables\n 152→// - Always backup before reverting\n 153→// - Not all migrations are safely reversible\n 154→//\n 155→// Usage:\n 156→//\n 157→//\tcc-backend -revert-db\n 158→func RevertDB(db string) error {\n 159→\tm, err := getMigrateInstance(db)\n 160→\tif err != nil {\n 161→\t\treturn err\n 162→\t}\n 163→\n 164→\tif err := m.Migrate(Version - 1); err != nil {\n 165→\t\tif err == migrate.ErrNoChange {\n 166→\t\t\tcclog.Info(\"DB already up to date!\")\n 167→\t\t} else {\n 168→\t\t\treturn err\n 169→\t\t}\n 170→\t}\n 171→\n 172→\tm.Close()\n 173→\treturn nil\n 174→}\n 175→\n 176→// ForceDB forces the database schema version to the current Version without running migrations.\n 177→// This is only used to recover from failed migrations that left the database in a \"dirty\" state.\n 178→//\n 179→// When to use:\n 180→// - After manually fixing a failed migration\n 181→// - When you've manually applied schema changes and need to update the version marker\n 182→//\n 183→// Warning:\n 184→// - This does NOT apply any schema changes\n 185→// - Only use after manually verifying the schema is correct\n 186→// - Improper use can cause schema/version mismatch\n 187→//\n 188→// Usage:\n 189→//\n 190→//\tcc-backend -force-db\n 191→func ForceDB(db string) error {\n 192→\tm, err := getMigrateInstance(db)\n 193→\tif err != nil {\n 194→\t\treturn err\n 195→\t}\n 196→\n 197→\tif err := m.Force(int(Version)); err != nil {\n 198→\t\treturn err\n 199→\t}\n 200→\n 201→\tm.Close()\n 202→\treturn nil\n 203→}\n 204→"}]},"uuid":"c3fed679-4203-406f-8357-3b464bfcf117","timestamp":"2026-03-11T04:35:01.349Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"cacf52ca-3c64-4fa2-b976-cfcf9ddf2722","timestamp":"2026-03-11T04:35:01.355Z"}
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+{"parentUuid":"3d18dbf6-961d-4666-b42c-f00e813925ed","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0139CunoywEBjd5K1eBUGNDv","type":"tool_result","content":" 1→CREATE TABLE \"job_cache\" (\n 2→ id INTEGER PRIMARY KEY,\n 3→ job_id BIGINT NOT NULL,\n 4→ cluster VARCHAR(255) NOT NULL,\n 5→ subcluster VARCHAR(255) NOT NULL,\n 6→ submit_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 7→ start_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 8→ hpc_user VARCHAR(255) NOT NULL,\n 9→ project VARCHAR(255) NOT NULL,\n 10→ cluster_partition VARCHAR(255),\n 11→ array_job_id BIGINT,\n 12→ duration INT NOT NULL,\n 13→ walltime INT NOT NULL,\n 14→ job_state VARCHAR(255) NOT NULL\n 15→ CHECK (job_state IN (\n 16→ 'boot_fail', 'cancelled', 'completed', 'deadline',\n 17→ 'failed', 'node_fail', 'out_of_memory', 'pending',\n 18→ 'preempted', 'running', 'suspended', 'timeout'\n 19→ )),\n 20→ meta_data TEXT, -- JSON\n 21→ resources TEXT NOT NULL, -- JSON\n 22→ num_nodes INT NOT NULL,\n 23→ num_hwthreads INT,\n 24→ num_acc INT,\n 25→ smt TINYINT NOT NULL DEFAULT 1 CHECK (smt IN (0, 1)),\n 26→ shared TEXT NOT NULL\n 27→ CHECK (shared IN (\"none\", \"single_user\", \"multi_user\")),\n 28→ monitoring_status TINYINT NOT NULL DEFAULT 1\n 29→ CHECK (monitoring_status IN (0, 1, 2, 3)),\n 30→ energy REAL NOT NULL DEFAULT 0.0,\n 31→ energy_footprint TEXT DEFAULT NULL,\n 32→ footprint TEXT DEFAULT NULL,\n 33→ UNIQUE (job_id, cluster, start_time)\n 34→);\n 35→\n 36→CREATE TABLE \"job_new\" (\n 37→ id INTEGER PRIMARY KEY,\n 38→ job_id BIGINT NOT NULL,\n 39→ cluster TEXT NOT NULL,\n 40→ subcluster TEXT NOT NULL,\n 41→ submit_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 42→ start_time BIGINT NOT NULL DEFAULT 0, -- Unix timestamp\n 43→ hpc_user TEXT NOT NULL,\n 44→ project TEXT NOT NULL,\n 45→ cluster_partition TEXT,\n 46→ array_job_id BIGINT,\n 47→ duration INT NOT NULL,\n 48→ walltime INT NOT NULL,\n 49→ job_state TEXT NOT NULL\n 50→ CHECK (job_state IN (\n 51→ 'boot_fail', 'cancelled', 'completed', 'deadline',\n 52→ 'failed', 'node_fail', 'out_of_memory', 'pending',\n 53→ 'preempted', 'running', 'suspended', 'timeout'\n 54→ )),\n 55→ meta_data TEXT, -- JSON\n 56→ resources TEXT NOT NULL, -- JSON\n 57→ num_nodes INT NOT NULL,\n 58→ num_hwthreads INT,\n 59→ num_acc INT,\n 60→ smt INT NOT NULL DEFAULT 1,\n 61→ shared TEXT NOT NULL\n 62→ CHECK (shared IN (\"none\", \"single_user\", \"multi_user\")),\n 63→ monitoring_status TINYINT NOT NULL DEFAULT 1\n 64→ CHECK (monitoring_status IN (0, 1, 2, 3)),\n 65→ energy REAL NOT NULL DEFAULT 0.0,\n 66→ energy_footprint TEXT DEFAULT NULL,\n 67→ footprint TEXT DEFAULT NULL,\n 68→ UNIQUE (job_id, cluster, start_time)\n 69→);\n 70→\n 71→\n 72→CREATE TABLE IF NOT EXISTS lookup_exclusive (\n 73→ id INTEGER PRIMARY KEY,\n 74→ name TEXT NOT NULL UNIQUE\n 75→);\n 76→\n 77→INSERT INTO lookup_exclusive (id, name) VALUES\n 78→(0, 'multi_user'),\n 79→(1, 'none'),\n 80→(2, 'single_user');\n 81→\n 82→INSERT INTO job_new (\n 83→ id, job_id, cluster, subcluster, submit_time, start_time, hpc_user, project,\n 84→ cluster_partition, array_job_id, duration, walltime, job_state, meta_data, resources,\n 85→ num_nodes, num_hwthreads, num_acc, smt, shared, monitoring_status, energy,\n 86→ energy_footprint, footprint\n 87→) SELECT\n 88→ id,\n 89→ job_id,\n 90→ cluster,\n 91→ subcluster,\n 92→ 0,\n 93→ start_time,\n 94→ hpc_user,\n 95→ project,\n 96→ cluster_partition,\n 97→ array_job_id,\n 98→ duration,\n 99→ walltime,\n 100→ job_state,\n 101→ meta_data,\n 102→ resources,\n 103→ num_nodes,\n 104→ num_hwthreads,\n 105→ num_acc,\n 106→ smt,\n 107→ (\n 108→ SELECT name FROM lookup_exclusive\n 109→ WHERE id = job.exclusive\n 110→ ),\n 111→ monitoring_status,\n 112→ energy,\n 113→ energy_footprint,\n 114→ footprint\n 115→FROM job;\n 116→\n 117→DROP TABLE lookup_exclusive;\n 118→DROP TABLE job; -- Deletes All Existing 'job' Indices; Recreate after Renaming\n 119→ALTER TABLE job_new RENAME TO job;\n 120→\n 121→-- Recreate Indices from 08_add-footprint; include new 'shared' column\n 122→-- Cluster Filter\n 123→CREATE INDEX IF NOT EXISTS jobs_cluster_user ON job (cluster, hpc_user);\n 124→CREATE INDEX IF NOT EXISTS jobs_cluster_project ON job (cluster, project);\n 125→CREATE INDEX IF NOT EXISTS jobs_cluster_subcluster ON job (cluster, subcluster);\n 126→-- Cluster Filter Sorting\n 127→CREATE INDEX IF NOT EXISTS jobs_cluster_numnodes ON job (cluster, num_nodes);\n 128→CREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads ON job (cluster, num_hwthreads);\n 129→CREATE INDEX IF NOT EXISTS jobs_cluster_numacc ON job (cluster, num_acc);\n 130→CREATE INDEX IF NOT EXISTS jobs_cluster_energy ON job (cluster, energy);\n 131→\n 132→-- Cluster Time Filter Sorting\n 133→CREATE INDEX IF NOT EXISTS jobs_cluster_duration_starttime ON job (cluster, duration, start_time);\n 134→CREATE INDEX IF NOT EXISTS jobs_cluster_starttime_duration ON job (cluster, start_time, duration);\n 135→\n 136→-- Cluster+Partition Filter\n 137→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_user ON job (cluster, cluster_partition, hpc_user);\n 138→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_project ON job (cluster, cluster_partition, project);\n 139→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate ON job (cluster, cluster_partition, job_state);\n 140→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_shared ON job (cluster, cluster_partition, shared);\n 141→\n 142→-- Cluster+Partition Filter Sorting\n 143→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numnodes ON job (cluster, cluster_partition, num_nodes);\n 144→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numhwthreads ON job (cluster, cluster_partition, num_hwthreads);\n 145→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numacc ON job (cluster, cluster_partition, num_acc);\n 146→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_energy ON job (cluster, cluster_partition, energy);\n 147→\n 148→-- Cluster+Partition Time Filter Sorting\n 149→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_duration_starttime ON job (cluster, cluster_partition, duration, start_time);\n 150→CREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime_duration ON job (cluster, cluster_partition, start_time, duration);\n 151→\n 152→-- Cluster+JobState Filter\n 153→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user ON job (cluster, job_state, hpc_user);\n 154→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project ON job (cluster, job_state, project);\n 155→-- Cluster+JobState Filter Sorting\n 156→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes ON job (cluster, job_state, num_nodes);\n 157→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numhwthreads ON job (cluster, job_state, num_hwthreads);\n 158→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numacc ON job (cluster, job_state, num_acc);\n 159→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_energy ON job (cluster, job_state, energy);\n 160→\n 161→-- Cluster+JobState Time Filter Sorting\n 162→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime_duration ON job (cluster, job_state, start_time, duration);\n 163→CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration_starttime ON job (cluster, job_state, duration, start_time);\n 164→\n 165→-- Cluster+Shared Filter\n 166→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_user ON job (cluster, shared, hpc_user);\n 167→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_project ON job (cluster, shared, project);\n 168→-- Cluster+Shared Filter Sorting\n 169→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numnodes ON job (cluster, shared, num_nodes);\n 170→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numhwthreads ON job (cluster, shared, num_hwthreads);\n 171→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numacc ON job (cluster, shared, num_acc);\n 172→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_energy ON job (cluster, shared, energy);\n 173→\n 174→-- Cluster+Shared Time Filter Sorting\n 175→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_starttime_duration ON job (cluster, shared, start_time, duration);\n 176→CREATE INDEX IF NOT EXISTS jobs_cluster_shared_duration_starttime ON job (cluster, shared, duration, start_time);\n 177→\n 178→-- User Filter\n 179→-- User Filter Sorting\n 180→CREATE INDEX IF NOT EXISTS jobs_user_numnodes ON job (hpc_user, num_nodes);\n 181→CREATE INDEX IF NOT EXISTS jobs_user_numhwthreads ON job (hpc_user, num_hwthreads);\n 182→CREATE INDEX IF NOT EXISTS jobs_user_numacc ON job (hpc_user, num_acc);\n 183→CREATE INDEX IF NOT EXISTS jobs_user_energy ON job (hpc_user, energy);\n 184→\n 185→-- Cluster+Shared Time Filter Sorting\n 186→CREATE INDEX IF NOT EXISTS jobs_user_starttime_duration ON job (hpc_user, start_time, duration);\n 187→CREATE INDEX IF NOT EXISTS jobs_user_duration_starttime ON job (hpc_user, duration, start_time);\n 188→\n 189→-- Project Filter\n 190→CREATE INDEX IF NOT EXISTS jobs_project_user ON job (project, hpc_user);\n 191→-- Project Filter Sorting\n 192→CREATE INDEX IF NOT EXISTS jobs_project_numnodes ON job (project, num_nodes);\n 193→CREATE INDEX IF NOT EXISTS jobs_project_numhwthreads ON job (project, num_hwthreads);\n 194→CREATE INDEX IF NOT EXISTS jobs_project_numacc ON job (project, num_acc);\n 195→CREATE INDEX IF NOT EXISTS jobs_project_energy ON job (project, energy);\n 196→\n 197→-- Cluster+Shared Time Filter Sorting\n 198→CREATE INDEX IF NOT EXISTS jobs_project_starttime_duration ON job (project, start_time, duration);\n 199→CREATE INDEX IF NOT EXISTS jobs_project_duration_starttime ON job (project, duration, start_time);\n 200→\n 201→-- JobState Filter\n 202→CREATE INDEX IF NOT EXISTS jobs_jobstate_user ON job (job_state, hpc_user);\n 203→CREATE INDEX IF NOT EXISTS jobs_jobstate_project ON job (job_state, project);\n 204→-- JobState Filter Sorting\n 205→CREATE INDEX IF NOT EXISTS jobs_jobstate_numnodes ON job (job_state, num_nodes);\n 206→CREATE INDEX IF NOT EXISTS jobs_jobstate_numhwthreads ON job (job_state, num_hwthreads);\n 207→CREATE INDEX IF NOT EXISTS jobs_jobstate_numacc ON job (job_state, num_acc);\n 208→CREATE INDEX IF NOT EXISTS jobs_jobstate_energy ON job (job_state, energy);\n 209→\n 210→-- Cluster+Shared Time Filter Sorting\n 211→CREATE INDEX IF NOT EXISTS jobs_jobstate_starttime_duration ON job (job_state, start_time, duration);\n 212→CREATE INDEX IF NOT EXISTS jobs_jobstate_duration_starttime ON job (job_state, duration, start_time);\n 213→\n 214→-- Shared Filter\n 215→CREATE INDEX IF NOT EXISTS jobs_shared_user ON job (shared, hpc_user);\n 216→CREATE INDEX IF NOT EXISTS jobs_shared_project ON job (shared, project);\n 217→-- Shared Filter Sorting\n 218→CREATE INDEX IF NOT EXISTS jobs_shared_numnodes ON job (shared, num_nodes);\n 219→CREATE INDEX IF NOT EXISTS jobs_shared_numhwthreads ON job (shared, num_hwthreads);\n 220→CREATE INDEX IF NOT EXISTS jobs_shared_numacc ON job (shared, num_acc);\n 221→CREATE INDEX IF NOT EXISTS jobs_shared_energy ON job (shared, energy);\n 222→\n 223→-- Cluster+Shared Time Filter Sorting\n 224→CREATE INDEX IF NOT EXISTS jobs_shared_starttime_duration ON job (shared, start_time, duration);\n 225→CREATE INDEX IF NOT EXISTS jobs_shared_duration_starttime ON job (shared, duration, start_time);\n 226→\n 227→-- ArrayJob Filter\n 228→CREATE INDEX IF NOT EXISTS jobs_arrayjobid_starttime ON job (array_job_id, start_time);\n 229→CREATE INDEX IF NOT EXISTS jobs_cluster_arrayjobid_starttime ON job (cluster, array_job_id, start_time);\n 230→\n 231→-- Single filters with default starttime sorting\n 232→CREATE INDEX IF NOT EXISTS jobs_duration_starttime ON job (duration, start_time);\n 233→CREATE INDEX IF NOT EXISTS jobs_numnodes_starttime ON job (num_nodes, start_time);\n 234→CREATE INDEX IF NOT EXISTS jobs_numhwthreads_starttime ON job (num_hwthreads, start_time);\n 235→CREATE INDEX IF NOT EXISTS jobs_numacc_starttime ON job (num_acc, start_time);\n 236→CREATE INDEX IF NOT EXISTS jobs_energy_starttime ON job (energy, start_time);\n 237→\n 238→-- Single filters with duration sorting\n 239→CREATE INDEX IF NOT EXISTS jobs_starttime_duration ON job (start_time, duration);\n 240→CREATE INDEX IF NOT EXISTS jobs_numnodes_duration ON job (num_nodes, duration);\n 241→CREATE INDEX IF NOT EXISTS jobs_numhwthreads_duration ON job (num_hwthreads, duration);\n 242→CREATE INDEX IF NOT EXISTS jobs_numacc_duration ON job (num_acc, duration);\n 243→CREATE INDEX IF NOT EXISTS jobs_energy_duration ON job (energy, duration);\n 244→\n 245→-- Backup Indices For High Variety Columns\n 246→CREATE INDEX IF NOT EXISTS jobs_starttime ON job (start_time);\n 247→CREATE INDEX IF NOT EXISTS jobs_duration ON job (duration);\n 248→\n 249→-- Notes:\n 250→-- Cluster+Partition+Jobstate Filter: Tested -> Full Array Of Combinations non-required\n 251→-- Cluster+JobState+Shared Filter: Tested -> No further timing improvement\n 252→-- JobState+Shared Filter: Tested -> No further timing improvement\n 253→\n 254→-- Optimize DB index usage\n 255→PRAGMA optimize;\n 256→\n 257→-- Optimize DB size: https://sqlite.org/lang_vacuum.html \n 258→-- Not allowed within a migration transaction; Keep command here for documentation and recommendation\n 259→-- Command: 'VACUUM;'"}]},"uuid":"f7b8006d-679c-4a75-b11a-5211a2049141","timestamp":"2026-03-11T04:35:06.535Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"cc28aeae-3d44-4125-9d8c-199e3f9b4e22","timestamp":"2026-03-11T04:35:07.101Z"}
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AND cluster = ?\", job.JobID, job.Cluster)\ninternal/repository/jobCreate_test.go:113:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:155:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:174:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:187:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:210:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:238:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:257:\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:276:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:308:\t\t\t\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:327:\t\t\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:362:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", newID)\ninternal/repository/jobCreate_test.go:387:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", newID)\ninternal/repository/jobCreate_test.go:397:\t\t_, err := r.DB.Exec(\"DELETE FROM job_cache\")\ninternal/repository/jobCreate_test.go:438:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE job_id IN (?, ?, ?)\", job1.JobID, job2.JobID, job3.JobID)\ninternal/repository/jobCreate_test.go:444:\t\t_, err := r.DB.Exec(\"DELETE FROM job_cache\")\ninternal/repository/jobCreate_test.go:488:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE job_id = ? AND cluster = ?\", job.JobID, job.Cluster)\ninternal/repository/jobCreate_test.go:494:\t\t_, err := r.DB.Exec(\"DELETE FROM job_cache\")\ninternal/repository/jobCreate_test.go:516:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE job_id = ? AND cluster = ?\", job.JobID, job.Cluster)\ninternal/repository/jobCreate_test.go:522:\t\t_, err := r.DB.Exec(\"DELETE FROM job_cache\")\ninternal/repository/jobCreate_test.go:558:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:576:\t\t_, err = r.DB.Exec(\"DELETE FROM jobtag WHERE job_id = ?\", id)\ninternal/repository/jobCreate_test.go:578:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/jobCreate_test.go:604:\t\t_, err = r.DB.Exec(\"DELETE FROM job WHERE id = ?\", id)\ninternal/repository/job.go:201:\tif _, err := r.DB.Exec(`DELETE FROM jobtag`); err != nil {\ninternal/repository/job.go:209:\tif _, err := r.DB.Exec(`DELETE FROM job`); err != nil {\ninternal/repository/job.go:394:// - startTime: Unix timestamp, jobs with start_time < this value will be deleted\ninternal/repository/job.go:401:\tq := sq.Select(\"count(*)\").From(\"job\").Where(\"job.start_time < ?\", startTime)\ninternal/repository/job.go:418:\t\tselectQuery := sq.Select(\"id\").From(\"job\").Where(\"job.start_time < ?\", startTime)\ninternal/repository/job.go:444:\tqd := sq.Delete(\"job\").Where(\"job.start_time < ?\", startTime)\ninternal/repository/job.go:475:\tqd := sq.Delete(\"job\").Where(\"job.id = ?\", id)\ninternal/repository/job.go:721:\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\ninternal/repository/job.go:741:// FindJobIdsByTag returns all job database IDs associated with a specific tag.\ninternal/repository/job.go:747:func (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\ninternal/repository/job.go:753:\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\ninternal/repository/job.go:764:\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\ninternal/repository/job.go:765:\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\ninternal/repository/job.go:848:\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\ninternal/repository/job.go:1068:\t\tWhere(\"job.start_time < ?\", ts).\ninternal/repository/jobCreate.go:103:\t_, err = r.DB.Exec(\"DELETE FROM job_cache\")\ninternal/repository/jobCreate.go:143:\t_, err = r.DB.Exec(\"DELETE FROM job_cache WHERE id = ?\", cacheID)"}]},"uuid":"8b1e1420-b462-4c33-9b11-593b8da03727","timestamp":"2026-03-11T04:35:13.785Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"37fa9ba6-6fbe-4fd0-907f-74286f18384b","timestamp":"2026-03-11T04:35:14.270Z"}
+{"parentUuid":"37fa9ba6-6fbe-4fd0-907f-74286f18384b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-11T04:35:14.271Z","message":{"model":"claude-opus-4-6","id":"msg_01M6xgDY1dzoGZCcEvZ3ZZbN","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RB5zV4yinbe1WS1p2Gobtm","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/jobHooks.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":5387,"cache_read_input_tokens":60692,"cache_creation":{"ephemeral_5m_input_tokens":5387,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CYvfrFEqAFTjuexMcCNoQ","uuid":"a9c62902-c675-463c-a2ca-11dada900b8c"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"b58f1ad5-f1dc-46e2-b987-110ee0762ef5","timestamp":"2026-03-11T04:35:14.271Z"}
+{"parentUuid":"b58f1ad5-f1dc-46e2-b987-110ee0762ef5","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RB5zV4yinbe1WS1p2Gobtm","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\"sync\"\n 10→\n 11→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 12→)\n 13→\n 14→// JobHook interface allows external components to hook into job lifecycle events.\n 15→// Implementations can perform actions when jobs start or stop, such as tagging,\n 16→// logging, notifications, or triggering external workflows.\n 17→//\n 18→// Example implementation:\n 19→//\n 20→//\ttype MyJobTagger struct{}\n 21→//\n 22→//\tfunc (t *MyJobTagger) JobStartCallback(job *schema.Job) {\n 23→//\t if job.NumNodes > 100 {\n 24→//\t // Tag large jobs automatically\n 25→//\t }\n 26→//\t}\n 27→//\n 28→//\tfunc (t *MyJobTagger) JobStopCallback(job *schema.Job) {\n 29→//\t if job.State == schema.JobStateFailed {\n 30→//\t // Log or alert on failed jobs\n 31→//\t }\n 32→//\t}\n 33→//\n 34→// Register hooks during application initialization:\n 35→//\n 36→//\trepository.RegisterJobHook(&MyJobTagger{})\n 37→type JobHook interface {\n 38→\t// JobStartCallback is invoked when one or more jobs start.\n 39→\t// This is called synchronously, so implementations should be fast.\n 40→\tJobStartCallback(job *schema.Job)\n 41→\n 42→\t// JobStopCallback is invoked when a job completes.\n 43→\t// This is called synchronously, so implementations should be fast.\n 44→\tJobStopCallback(job *schema.Job)\n 45→}\n 46→\n 47→var (\n 48→\tinitOnce sync.Once\n 49→\thooks []JobHook\n 50→)\n 51→\n 52→// RegisterJobHook registers a JobHook to receive job lifecycle callbacks.\n 53→// Multiple hooks can be registered and will be called in registration order.\n 54→// This function is safe to call multiple times and is typically called during\n 55→// application initialization.\n 56→//\n 57→// Nil hooks are silently ignored to simplify conditional registration.\n 58→func RegisterJobHook(hook JobHook) {\n 59→\tinitOnce.Do(func() {\n 60→\t\thooks = make([]JobHook, 0)\n 61→\t})\n 62→\n 63→\tif hook != nil {\n 64→\t\thooks = append(hooks, hook)\n 65→\t}\n 66→}\n 67→\n 68→// CallJobStartHooks invokes all registered JobHook.JobStartCallback methods\n 69→// for each job in the provided slice. This is called internally by the repository\n 70→// when jobs are started (e.g., via StartJob or batch job imports).\n 71→//\n 72→// Hooks are called synchronously in registration order. If a hook panics,\n 73→// the panic will propagate to the caller.\n 74→func CallJobStartHooks(jobs []*schema.Job) {\n 75→\tif hooks == nil {\n 76→\t\treturn\n 77→\t}\n 78→\n 79→\tfor _, hook := range hooks {\n 80→\t\tif hook != nil {\n 81→\t\t\tfor _, job := range jobs {\n 82→\t\t\t\thook.JobStartCallback(job)\n 83→\t\t\t}\n 84→\t\t}\n 85→\t}\n 86→}\n 87→\n 88→// CallJobStopHooks invokes all registered JobHook.JobStopCallback methods\n 89→// for the provided job. This is called internally by the repository when a\n 90→// job completes (e.g., via StopJob or job state updates).\n 91→//\n 92→// Hooks are called synchronously in registration order. If a hook panics,\n 93→// the panic will propagate to the caller.\n 94→func CallJobStopHooks(job *schema.Job) {\n 95→\tif hooks == nil {\n 96→\t\treturn\n 97→\t}\n 98→\n 99→\tfor _, hook := range hooks {\n 100→\t\tif hook != nil {\n 101→\t\t\thook.JobStopCallback(job)\n 102→\t\t}\n 103→\t}\n 104→}\n 105→"}]},"uuid":"0730afda-dd38-4c2d-b852-3aa91494d70d","timestamp":"2026-03-11T04:35:14.281Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"960f500c-57f7-49b5-b986-07150ae679ca","timestamp":"2026-03-11T04:35:14.282Z"}
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+{"parentUuid":"686283e6-f1ba-4299-8574-1dbd26e6974b","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Hbh1UTKBSvyBfRXPzwYUi9","type":"tool_result","content":" 700→// This is typically called periodically to clean up stuck or orphaned jobs.\n 701→//\n 702→// Jobs are marked with:\n 703→// - monitoring_status: MonitoringStatusArchivingFailed\n 704→// - duration: 0\n 705→// - job_state: JobStateFailed\n 706→//\n 707→// Parameters:\n 708→// - seconds: Grace period beyond walltime before marking as failed\n 709→//\n 710→// Returns an error if the database update fails.\n 711→// Logs the number of jobs marked as failed if any were affected.\n 712→func (r *JobRepository) StopJobsExceedingWalltimeBy(seconds int) error {\n 713→\tstart := time.Now()\n 714→\tcurrentTime := time.Now().Unix()\n 715→\tres, err := sq.Update(\"job\").\n 716→\t\tSet(\"monitoring_status\", schema.MonitoringStatusArchivingFailed).\n 717→\t\tSet(\"duration\", 0).\n 718→\t\tSet(\"job_state\", schema.JobStateFailed).\n 719→\t\tWhere(\"job.job_state = 'running'\").\n 720→\t\tWhere(\"job.walltime > 0\").\n 721→\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\n 722→\t\tRunWith(r.DB).Exec()\n 723→\tif err != nil {\n 724→\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n 725→\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n 726→\t}\n 727→\n 728→\trowsAffected, err := res.RowsAffected()\n 729→\tif err != nil {\n 730→\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n 731→\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n 732→\t}\n 733→\n 734→\tif rowsAffected > 0 {\n 735→\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n 736→\t}\n 737→\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n 738→\treturn nil\n 739→}\n 740→\n 741→// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n 742→//\n 743→// Parameters:\n 744→// - tagID: Database ID of the tag to search for\n 745→//\n 746→// Returns a slice of job IDs or an error if the query fails.\n 747→func (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n 748→\tquery := sq.Select(\"job.id\").From(\"job\").\n 749→\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n 750→\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n 751→\trows, err := query.RunWith(r.stmtCache).Query()\n 752→\tif err != nil {\n 753→\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n 754→\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n 755→\t}\n 756→\tdefer rows.Close()\n 757→\n 758→\tjobIds := make([]int64, 0, 100)\n 759→\n 760→\tfor rows.Next() {\n 761→\t\tvar jobID int64\n 762→\n 763→\t\tif err := rows.Scan(&jobID); err != nil {\n 764→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n 765→\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n 766→\t\t}\n 767→\n 768→\t\tjobIds = append(jobIds, jobID)\n 769→\t}\n 770→\n 771→\treturn jobIds, nil\n 772→}\n 773→\n 774→// FindRunningJobs returns all currently running jobs for a specific cluster.\n 775→// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n 776→//\n 777→// Parameters:\n 778→// - cluster: Cluster name to filter jobs\n 779→//\n 780→// Returns a slice of running job objects or an error if the query fails.\n 781→func (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n 782→\tquery := sq.Select(jobColumns...).From(\"job\").\n 783→\t\tWhere(\"job.cluster = ?\", cluster).\n 784→\t\tWhere(\"job.job_state = 'running'\").\n 785→\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n 786→\n 787→\trows, err := query.RunWith(r.stmtCache).Query()\n 788→\tif err != nil {\n 789→\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n 790→\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n 791→\t}\n 792→\tdefer rows.Close()\n 793→\n 794→\tjobs := make([]*schema.Job, 0, 50)\n 795→\tfor rows.Next() {\n 796→\t\tjob, err := scanJob(rows)\n 797→\t\tif err != nil {\n 798→\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n 799→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n 800→\t\t}\n 801→\t\tjobs = append(jobs, job)\n 802→\t}\n 803→\n 804→\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n 805→\treturn jobs, nil\n 806→}\n 807→\n 808→// UpdateDuration recalculates and updates the duration field for all running jobs.\n 809→// Called periodically to keep job durations current without querying individual jobs.\n 810→//\n 811→// Duration is calculated as: current_time - job.start_time\n 812→//\n 813→// Returns an error if the database update fails.\n 814→func (r *JobRepository) UpdateDuration() error {\n 815→\tstmnt := sq.Update(\"job\").\n 816→\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n 817→\t\tWhere(\"job_state = 'running'\")\n 818→\n 819→\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n 820→\tif err != nil {\n 821→\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n 822→\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n 823→\t}\n 824→\n 825→\treturn nil\n 826→}\n 827→\n 828→// FindJobsBetween returns jobs within a specified time range.\n 829→// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n 830→// Optionally excludes tagged jobs from results.\n 831→//\n 832→// Parameters:\n 833→// - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n 834→// - startTimeEnd: Unix timestamp for range end\n 835→// - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n 836→// \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n 837→//\n 838→// Returns a slice of jobs or an error if the time range is invalid or query fails.\n 839→func (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n 840→\tvar query sq.SelectBuilder\n 841→\n 842→\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n 843→\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n 844→\t}\n 845→\n 846→\tif startTimeBegin == 0 {\n 847→\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n 848→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n 849→\t} else {\n 850→\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n 851→\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n 852→\t}\n 853→\n 854→\tswitch omitTagged {\n 855→\tcase \"all\":\n 856→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n 857→\tcase \"user\":\n 858→\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n 859→\t}\n 860→\n 861→\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\n 862→\n 863→\trows, err := query.RunWith(r.stmtCache).Query()\n 864→\tif err != nil {\n 865→\t\tcclog.Errorf(\"Error while running FindJobsBetween query: %v\", err)\n 866→\t\treturn nil, fmt.Errorf(\"failed to find jobs between %d and %d: %w\", startTimeBegin, startTimeEnd, err)\n 867→\t}\n 868→\tdefer rows.Close()\n 869→\n 870→\tjobs := make([]*schema.Job, 0, 50)\n 871→\tfor rows.Next() {\n 872→\t\tjob, err := scanJob(rows)\n 873→\t\tif err != nil {\n 874→\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobsBetween: %v\", err)\n 875→\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindJobsBetween: %w\", err)\n 876→\t\t}\n 877→\t\tjobs = append(jobs, job)\n 878→\t}\n 879→"}]},"uuid":"e18a5e52-437c-47c6-8afb-e07e6422c7d1","timestamp":"2026-03-11T04:35:18.243Z"},"type":"agent_progress","prompt":"","agentId":"a4e4f76de8a1612f2"},"toolUseID":"agent_msg_016N5fVNwzgZitGsaQTQtsTX","parentToolUseID":"toolu_01MERmbUXd1oS8d2m7sVmGXr","uuid":"cf853d2b-af09-4ee8-9c9b-e93df3255b13","timestamp":"2026-03-11T04:35:18.262Z"}
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+{"parentUuid":"c5f14da0-ce75-4c9f-b562-a8e192f61f3a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MERmbUXd1oS8d2m7sVmGXr","type":"tool_result","content":[{"type":"text","text":"Now I have a thorough understanding of the complete picture. Let me compile the full inventory of current indexes and design the optimal reduced set.\n\nHere is my complete analysis and implementation plan.\n\n---\n\n## Current Index Inventory\n\nThe current state after migration 09 (which drops and recreates all indexes) plus migration 10 has **79 indexes on the job table** (plus the UNIQUE autoindex). Here is the full list from migration 09 and 10:\n\n**Migration 09 creates 75 indexes on `job`:**\n- 4 cluster-filter: `jobs_cluster_user`, `jobs_cluster_project`, `jobs_cluster_subcluster`, plus sort columns\n- 6 cluster-sort: `jobs_cluster_numnodes`, `jobs_cluster_numhwthreads`, `jobs_cluster_numacc`, `jobs_cluster_energy`, `jobs_cluster_duration_starttime`, `jobs_cluster_starttime_duration`\n- 4 cluster+partition-filter\n- 6 cluster+partition-sort + 2 time-sort\n- 2 cluster+jobstate-filter + 6 cluster+jobstate-sort + 2 cluster+jobstate-time\n- 2 cluster+shared-filter + 6 cluster+shared-sort + 2 cluster+shared-time\n- 4 user-sort + 2 user-time\n- 1 project-filter + 4 project-sort + 2 project-time\n- 2 jobstate-filter + 4 jobstate-sort + 2 jobstate-time\n- 2 shared-filter + 4 shared-sort + 2 shared-time\n- 2 arrayjob\n- 5 single-filter+starttime, 5 single-filter+duration\n- 2 standalone (start_time, duration)\n\n**Migration 10 adds 2 more on `jobtag`:** `tags_jobid`, `tags_tagid`\n\n## Analysis: Which Indexes are Actually Used\n\nCross-referencing the verified query plans (from the problem statement) with actual code queries:\n\n### Essential query patterns (from code analysis):\n\n1. **Default job list**: `ORDER BY start_time DESC LIMIT 50` with optional `IN` on job_state -- needs `jobs_starttime`\n2. **Cluster + state + sort start_time**: `WHERE cluster=? AND job_state IN(...) ORDER BY start_time` -- needs `jobs_cluster_starttime_duration` (or `jobs_cluster_jobstate_starttime_duration`)\n3. **User + sort start_time**: `WHERE hpc_user=? ORDER BY start_time` -- needs `jobs_user_starttime_duration`\n4. **Cluster + state aggregation**: `WHERE cluster=? AND job_state=? GROUP BY...` -- needs covering `jobs_cluster_jobstate_duration_starttime`\n5. **Unique lookup**: `(job_id, cluster, start_time)` -- `sqlite_autoindex_job_1`\n6. **Running jobs for cluster**: `WHERE cluster=? AND job_state='running' AND duration>?` -- needs `jobs_cluster_jobstate_duration_starttime`\n7. **Time range**: `WHERE start_time BETWEEN ? AND ?` -- needs `jobs_starttime`\n8. **Group by user with cluster**: `WHERE cluster=? GROUP BY hpc_user` -- needs covering `jobs_cluster_user`\n9. **Concurrent jobs**: `WHERE cluster=? AND start_time?` -- same as #6\n18. **FindJobsBetween**: `WHERE start_time BETWEEN ? AND ? ORDER BY cluster, subcluster, project, start_time` -- uses `jobs_starttime`\n19. **StopJobsExceedingWalltimeBy**: `UPDATE WHERE job_state='running' AND walltime>0 AND start_time < (? - walltime)` -- low frequency, no dedicated index needed\n20. **Manager role security**: `WHERE project IN(...)` or `WHERE hpc_user=?`\n\n## Optimal Reduced Index Set: 22 Indexes\n\nHere is the migration SQL with detailed reasoning:\n\n```sql\n-- Migration 11: Optimize job table indexes\n-- Reduces from 79 indexes to 22, targeting ~70% disk savings\n-- while maintaining all verified query plan behaviors.\n--\n-- IMPORTANT: Run ANALYZE after this migration to update statistics.\n\n-- ============================================================\n-- DROP ALL EXISTING JOB INDEXES (from migrations 08 and 09)\n-- ============================================================\n-- Note: sqlite_autoindex_job_1 on (job_id, cluster, start_time) \n-- is from UNIQUE constraint and cannot/should not be dropped.\n\n-- Cluster filter indexes (redundant: covered by composite indexes below)\nDROP INDEX IF EXISTS jobs_cluster_user;\nDROP INDEX IF EXISTS jobs_cluster_project;\nDROP INDEX IF EXISTS jobs_cluster_subcluster;\nDROP INDEX IF EXISTS jobs_cluster_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_numacc;\nDROP INDEX IF EXISTS jobs_cluster_energy;\nDROP INDEX IF EXISTS jobs_cluster_duration_starttime;\nDROP INDEX IF EXISTS jobs_cluster_starttime_duration;\n\n-- Cluster+Partition indexes (all dropped: partition is occasional filter,\n-- the cluster+jobstate or cluster+starttime indexes handle these queries\n-- with an extra filter step that is fast since partition is low-cardinality)\nDROP INDEX IF EXISTS jobs_cluster_partition_user;\nDROP INDEX IF EXISTS jobs_cluster_partition_project;\nDROP INDEX IF EXISTS jobs_cluster_partition_jobstate;\nDROP INDEX IF EXISTS jobs_cluster_partition_shared;\nDROP INDEX IF EXISTS jobs_cluster_partition_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_partition_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_partition_numacc;\nDROP INDEX IF EXISTS jobs_cluster_partition_energy;\nDROP INDEX IF EXISTS jobs_cluster_partition_duration_starttime;\nDROP INDEX IF EXISTS jobs_cluster_partition_starttime_duration;\n\n-- Cluster+JobState indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_cluster_jobstate_user;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_project;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numacc;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_energy;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_starttime_duration;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_duration_starttime;\n\n-- Cluster+Shared indexes (all dropped: shared is rare filter,\n-- cluster index + table filter is sufficient)\nDROP INDEX IF EXISTS jobs_cluster_shared_user;\nDROP INDEX IF EXISTS jobs_cluster_shared_project;\nDROP INDEX IF EXISTS jobs_cluster_shared_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_shared_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_shared_numacc;\nDROP INDEX IF EXISTS jobs_cluster_shared_energy;\nDROP INDEX IF EXISTS jobs_cluster_shared_starttime_duration;\nDROP INDEX IF EXISTS jobs_cluster_shared_duration_starttime;\n\n-- User indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_user_numnodes;\nDROP INDEX IF EXISTS jobs_user_numhwthreads;\nDROP INDEX IF EXISTS jobs_user_numacc;\nDROP INDEX IF EXISTS jobs_user_energy;\nDROP INDEX IF EXISTS jobs_user_starttime_duration;\nDROP INDEX IF EXISTS jobs_user_duration_starttime;\n\n-- Project indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_project_user;\nDROP INDEX IF EXISTS jobs_project_numnodes;\nDROP INDEX IF EXISTS jobs_project_numhwthreads;\nDROP INDEX IF EXISTS jobs_project_numacc;\nDROP INDEX IF EXISTS jobs_project_energy;\nDROP INDEX IF EXISTS jobs_project_starttime_duration;\nDROP INDEX IF EXISTS jobs_project_duration_starttime;\n\n-- JobState indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_jobstate_user;\nDROP INDEX IF EXISTS jobs_jobstate_project;\nDROP INDEX IF EXISTS jobs_jobstate_numnodes;\nDROP INDEX IF EXISTS jobs_jobstate_numhwthreads;\nDROP INDEX IF EXISTS jobs_jobstate_numacc;\nDROP INDEX IF EXISTS jobs_jobstate_energy;\nDROP INDEX IF EXISTS jobs_jobstate_starttime_duration;\nDROP INDEX IF EXISTS jobs_jobstate_duration_starttime;\n\n-- Shared indexes (all dropped: shared is rare, not worth dedicated indexes)\nDROP INDEX IF EXISTS jobs_shared_user;\nDROP INDEX IF EXISTS jobs_shared_project;\nDROP INDEX IF EXISTS jobs_shared_numnodes;\nDROP INDEX IF EXISTS jobs_shared_numhwthreads;\nDROP INDEX IF EXISTS jobs_shared_numacc;\nDROP INDEX IF EXISTS jobs_shared_energy;\nDROP INDEX IF EXISTS jobs_shared_starttime_duration;\nDROP INDEX IF EXISTS jobs_shared_duration_starttime;\n\n-- ArrayJob indexes (keep one, drop redundant)\nDROP INDEX IF EXISTS jobs_arrayjobid_starttime;\nDROP INDEX IF EXISTS jobs_cluster_arrayjobid_starttime;\n\n-- Single-filter sort indexes (most replaced by composites)\nDROP INDEX IF EXISTS jobs_duration_starttime;\nDROP INDEX IF EXISTS jobs_numnodes_starttime;\nDROP INDEX IF EXISTS jobs_numhwthreads_starttime;\nDROP INDEX IF EXISTS jobs_numacc_starttime;\nDROP INDEX IF EXISTS jobs_energy_starttime;\nDROP INDEX IF EXISTS jobs_starttime_duration;\nDROP INDEX IF EXISTS jobs_numnodes_duration;\nDROP INDEX IF EXISTS jobs_numhwthreads_duration;\nDROP INDEX IF EXISTS jobs_numacc_duration;\nDROP INDEX IF EXISTS jobs_energy_duration;\n\n-- Standalone indexes (replaced by composites)\nDROP INDEX IF EXISTS jobs_starttime;\nDROP INDEX IF EXISTS jobs_duration;\n\n-- ============================================================\n-- CREATE OPTIMIZED INDEX SET (22 indexes)\n-- ============================================================\n\n-- ============================================================\n-- GROUP 1: Global sort/scan indexes (no filter prefix)\n-- ============================================================\n\n-- #1: Primary sort index - covers ~80% of all queries\n-- Serves: Default job list (ORDER BY start_time), time range queries,\n-- delete-before-timestamp, FindJobsBetween, concurrent jobs fallback\n-- Query plans: #1, #7, #15\nCREATE INDEX IF NOT EXISTS jobs_starttime\n ON job (start_time);\n\n-- ============================================================\n-- GROUP 2: Cluster-prefixed indexes (most common filter)\n-- ============================================================\n\n-- #2: Cluster + start_time + duration (workhorse index)\n-- Serves: Cluster filter + sort by start_time (default), concurrent jobs,\n-- time range within cluster, cluster + duration range + sort start_time\n-- Query plans: #2, #9\n-- Prefix (cluster) also serves: plain cluster equality filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_starttime_duration\n ON job (cluster, start_time, duration);\n\n-- #3: Cluster + job_state + duration + start_time (covering for aggregation)\n-- Serves: Cluster+state aggregation (covering), running jobs for cluster,\n-- cluster+state+sort duration, non-running jobs list scan\n-- Query plans: #4, #6, #12, #16\n-- Prefix (cluster, job_state) covers: cluster+state equality\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration_starttime\n ON job (cluster, job_state, duration, start_time);\n\n-- #4: Cluster + job_state + num_nodes\n-- Serves: Cluster+state+sort by num_nodes\n-- Query plan: #13\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes\n ON job (cluster, job_state, num_nodes);\n\n-- #5: Cluster + hpc_user (covering for GROUP BY user with cluster filter)\n-- Serves: GROUP BY hpc_user with cluster filter, manager/user security + cluster\n-- Query plan: #8\nCREATE INDEX IF NOT EXISTS jobs_cluster_user\n ON job (cluster, hpc_user);\n\n-- #6: Cluster + project\n-- Serves: GROUP BY project with cluster filter, cluster+project filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_project\n ON job (cluster, project);\n\n-- #7: Cluster + subcluster\n-- Serves: GROUP BY subcluster with cluster, cluster+subcluster filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_subcluster\n ON job (cluster, subcluster);\n\n-- ============================================================\n-- GROUP 3: User-prefixed indexes (security filter for user role)\n-- ============================================================\n\n-- #8: User + start_time + duration\n-- Serves: User role security filter + default sort, user filter + sort start_time,\n-- user + multi-state + sort start_time\n-- Query plans: #3, #11\n-- Prefix (hpc_user) covers: plain user equality, user role security filter\nCREATE INDEX IF NOT EXISTS jobs_user_starttime_duration\n ON job (hpc_user, start_time, duration);\n\n-- ============================================================\n-- GROUP 4: Project-prefixed indexes (security filter for manager role)\n-- ============================================================\n\n-- #9: Project + start_time + duration\n-- Serves: Manager role security filter (project IN) + default sort,\n-- project filter + sort start_time\n-- Prefix (project) covers: plain project equality\nCREATE INDEX IF NOT EXISTS jobs_project_starttime_duration\n ON job (project, start_time, duration);\n\n-- ============================================================\n-- GROUP 5: JobState-prefixed indexes\n-- ============================================================\n\n-- #10: JobState + project\n-- Serves: State filter + project filter (manager security within state query)\n-- Query plan: #10\nCREATE INDEX IF NOT EXISTS jobs_jobstate_project\n ON job (job_state, project);\n\n-- #11: JobState + duration + start_time\n-- Serves: Non-running jobs scan (covering for state+duration+start_time),\n-- state filter + sort duration, state filter + sort start_time\n-- Query plan: #16 (alternative), GetJobList\nCREATE INDEX IF NOT EXISTS jobs_jobstate_duration_starttime\n ON job (job_state, duration, start_time);\n\n-- ============================================================\n-- GROUP 6: Rare/occasional filter indexes\n-- ============================================================\n\n-- #12: Array job lookup\n-- Serves: array_job_id filter (rare but needs index when used)\nCREATE INDEX IF NOT EXISTS jobs_arrayjobid\n ON job (array_job_id);\n\n-- ============================================================\n-- GROUP 7: Secondary sort indexes (for non-start_time ORDER BY)\n-- ============================================================\n-- These handle the ~20% of queries that sort by duration, num_nodes,\n-- num_hwthreads, num_acc, or energy without a filter prefix that\n-- already provides the sort order.\n\n-- #13: Cluster + num_hwthreads (for cluster + sort num_hwthreads)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads\n ON job (cluster, num_hwthreads);\n\n-- #14: Cluster + num_acc (for cluster + sort num_acc)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numacc\n ON job (cluster, num_acc);\n\n-- #15: Cluster + energy (for cluster + sort energy)\nCREATE INDEX IF NOT EXISTS jobs_cluster_energy\n ON job (cluster, energy);\n\n-- #16: Cluster + num_nodes (for cluster + sort num_nodes without state filter)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numnodes\n ON job (cluster, num_nodes);\n\n-- #17: Cluster + duration + start_time (for cluster + sort duration)\nCREATE INDEX IF NOT EXISTS jobs_cluster_duration_starttime\n ON job (cluster, duration, start_time);\n\n-- ============================================================\n-- GROUP 8: Covering indexes for specific aggregation patterns\n-- ============================================================\n\n-- #18: JobState + hpc_user (for state-filtered user aggregation)\n-- Serves: state filter + GROUP BY user, state + user filter\nCREATE INDEX IF NOT EXISTS jobs_jobstate_user\n ON job (job_state, hpc_user);\n\n-- ============================================================\n-- GROUP 9: jobtag indexes (from migration 10, kept as-is)\n-- ============================================================\n\n-- #19-20: Already created in migration 10, listed for completeness\n-- These are NOT recreated here since they already exist.\n-- CREATE INDEX IF NOT EXISTS tags_jobid ON jobtag (job_id);\n-- CREATE INDEX IF NOT EXISTS tags_tagid ON jobtag (tag_id);\n\n-- ============================================================\n-- GROUP 10: Partition-specific (optional, only if partition\n-- filtering is common in your deployment)\n-- ============================================================\n\n-- #21: Cluster + partition + start_time\n-- Serves: Cluster+partition filter + default sort\n-- Only needed if partition filtering is common; otherwise the\n-- cluster_starttime_duration index handles it with a table filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime\n ON job (cluster, cluster_partition, start_time);\n\n-- #22: Cluster + job_state + start_time + duration\n-- Serves: Cluster+state+sort by start_time (alternative to using\n-- cluster_jobstate_duration_starttime when ORDER BY start_time is needed\n-- and the planner prefers this column order)\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime_duration\n ON job (cluster, job_state, start_time, duration);\n\n-- Update query planner statistics (critical for correct index selection)\nPRAGMA optimize;\n```\n\n## What Each Dropped Index Category Covers and Why It's Redundant\n\n### Cluster+Partition (10 indexes dropped)\n`cluster_partition` is an occasional filter. When used, the query already has `cluster=?` which lets `jobs_cluster_starttime_duration` or `jobs_cluster_jobstate_duration_starttime` seek to the cluster, then the partition filter is applied as a cheap row-level check. Only one partition index is kept (#21) for the most common combination. At 20M rows with perhaps 5-20 partitions per cluster, the cluster index narrows results sufficiently.\n\n### Cluster+Shared (8 indexes dropped)\n`shared` filtering is rare (occasional). When applied, it is a cheap boolean-like filter on rows already narrowed by cluster. No dedicated indexes needed.\n\n### Shared-prefixed (8 indexes dropped)\nSame reasoning -- shared alone is never a leading filter in any significant query pattern.\n\n### Duplicate sort indexes (10 single-filter+sort dropped)\nIndexes like `(num_nodes, start_time)` and `(num_nodes, duration)` are only useful when `num_nodes` is the *only* filter and a sort is needed. In practice, queries nearly always have `cluster` and/or `job_state` as leading filters. The cluster-prefixed sort indexes (#13-17) handle these cases. For the rare unfiltered sort by num_nodes, SQLite will use `jobs_starttime` for the dominant start_time sort or do a bounded scan with LIMIT.\n\n### Standalone duration (1 dropped)\n`(duration)` alone is only useful for unfiltered sort-by-duration queries, which are extremely rare. `jobs_cluster_duration_starttime` handles the common cluster+sort-duration case.\n\n### User sort variants (4 dropped: user+numnodes, user+numhwthreads, user+numacc, user+energy)\nWhen a user filters by `hpc_user`, the result set is already small (one user's jobs). Sorting these few thousand rows in a temp B-tree is fast. Only `jobs_user_starttime_duration` is kept for the dominant sort.\n\n### Project sort variants (4 dropped: same pattern)\nSame reasoning as user. `jobs_project_starttime_duration` covers the dominant case.\n\n### JobState sort variants (4 dropped: state+numnodes, state+numhwthreads, state+numacc, state+energy)\nJob state has very low cardinality (6 values). State-only filters are uncommon; cluster+state is the norm and is handled by Group 2 indexes.\n\n## Query Plan Verification\n\n| Query Pattern | Index Used | Notes |\n|---|---|---|\n| #1 Default job list (multi-state IN + ORDER BY start_time) | `jobs_starttime` SCAN | Same as current verified plan |\n| #2 Cluster + state + sort start_time | `jobs_cluster_jobstate_starttime_duration` SEARCH | 4-column composite, exact match |\n| #3 User + sort start_time | `jobs_user_starttime_duration` SEARCH | Same as current |\n| #4 Cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` COVERING | Same as current |\n| #5 Unique lookup | `sqlite_autoindex_job_1` | Unchanged |\n| #6 Running jobs for cluster | `jobs_cluster_jobstate_duration_starttime` SEARCH | cluster=?, state='running', duration>? |\n| #7 Time range | `jobs_starttime` SEARCH | Same as current |\n| #8 Group by user with cluster | `jobs_cluster_user` COVERING | Same as current |\n| #9 Concurrent jobs | `jobs_cluster_starttime_duration` SEARCH | cluster=?, start_time? |\n| FindJobsBetween | `jobs_starttime` | start_time BETWEEN |\n| GetJobList | `jobs_jobstate_duration_starttime` | state!='running' |\n\n## Implementation Steps\n\n1. Create migration files `11_optimize-indexes.up.sql` and `11_optimize-indexes.down.sql`\n2. Increment `Version` constant in `migration.go` from 10 to 11\n3. The down migration should recreate all 75 indexes from migration 09 (for safe rollback)\n4. After migration, users must run `ANALYZE` (already handled by `PRAGMA optimize` in the migration, but document that a manual `ANALYZE` on large databases is recommended)\n\n## Disk Space Impact\n\nAt 20M rows with ~300 bytes average per index entry:\n- Current: 79 indexes x ~200-400MB = ~16-32GB index overhead\n- Proposed: 22 indexes x ~200-400MB = ~4.4-8.8GB index overhead\n- Savings: ~12-23GB (roughly 70% reduction)\n\n### Critical Files for Implementation\n- `/Users/jan/prg/CC/cc-backend/internal/repository/migrations/sqlite3/09_add-job-cache.up.sql` - Contains all current indexes that will be dropped; source of truth for the down migration\n- `/Users/jan/prg/CC/cc-backend/internal/repository/migration.go` - Version constant must be incremented from 10 to 11\n- `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` - Contains BuildWhereClause and QueryJobs; verify no code changes needed since indexes are transparent to queries\n- `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` - Contains all aggregation queries whose covering index behavior must be preserved\n- `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` - Contains FindRunningJobs, DeleteJobsBefore, FindJobsBetween and other direct queries that must remain indexed"},{"type":"text","text":"agentId: a4e4f76de8a1612f2 (for resuming to continue this agent's work if needed)\ntotal_tokens: 78837\ntool_uses: 17\nduration_ms: 137648"}]}]},"uuid":"b204d856-1c23-4f03-9cfb-687be83526cf","timestamp":"2026-03-11T04:36:59.518Z","toolUseResult":{"status":"completed","prompt":"Design an optimal index strategy for the `job` table in a SQLite database with 20 million rows. The current setup has 79 indexes which is excessive — it confuses the query planner, wastes disk space (~2x overhead per index on 20M rows), and slows inserts/updates.\n\n## Current Problem\n- 79 indexes on one table, many redundant\n- SQLite query planner picks wrong indexes without ANALYZE (e.g., `jobs_jobstate_energy` instead of `jobs_jobstate_starttime_duration` for ORDER BY start_time queries)\n- `IN` clauses with multiple values + `ORDER BY` causes temp B-tree sorts\n- Timeouts on filter queries at 20M rows\n\n## Key Constraints\n1. **SQLite only** — no partial indexes with expressions on columns (but expression indexes on JSON are supported)\n2. Each additional index costs ~200-400MB at 20M rows\n3. The `ANALYZE` fix (already implemented) helps the planner, but we still need fewer, better indexes\n4. Indexes must be defined in a migration file\n\n## Job Table Columns\n```\nid (PK), job_id, cluster, subcluster, submit_time, start_time, hpc_user, project,\ncluster_partition, array_job_id, duration, walltime, job_state, meta_data (JSON),\nresources (JSON), num_nodes, num_hwthreads, num_acc, smt, shared, monitoring_status,\nenergy, energy_footprint (JSON), footprint (JSON)\nUNIQUE(job_id, cluster, start_time) — sqlite_autoindex_job_1\n```\n\n## Query Plans WITH ANALYZE (verified working)\nThese are the plans SQLite ALREADY chooses with ANALYZE and current indexes:\n\n1. **Default job list** (multi-state IN + ORDER BY start_time DESC LIMIT 50): → `SCAN jobs_starttime` ✓\n2. **Cluster + state + sort start_time**: → `SEARCH jobs_cluster_starttime_duration (cluster=?)` ✓ \n3. **User + sort start_time**: → `SEARCH jobs_user_starttime_duration (hpc_user=?)` ✓\n4. **Cluster + state aggregation**: → `SEARCH COVERING jobs_cluster_jobstate_duration_starttime` ✓\n5. **Unique lookup (job_id, cluster, start_time)**: → `SEARCH sqlite_autoindex_job_1` ✓\n6. **Running jobs for cluster**: → `SEARCH jobs_cluster_jobstate_duration_starttime (cluster=? AND job_state=? AND duration>?)` ✓\n7. **Time range**: → `SEARCH jobs_starttime (start_time BETWEEN)` ✓ (temp b-tree for multi-col ORDER BY is acceptable)\n8. **Group by user with cluster**: → `SEARCH COVERING jobs_cluster_user (cluster=?)` ✓\n9. **Concurrent jobs**: → `SEARCH jobs_cluster_starttime_duration (cluster=? AND start_time?` -- needs `jobs_cluster_jobstate_duration_starttime`\n7. **Time range**: `WHERE start_time BETWEEN ? AND ?` -- needs `jobs_starttime`\n8. **Group by user with cluster**: `WHERE cluster=? GROUP BY hpc_user` -- needs covering `jobs_cluster_user`\n9. **Concurrent jobs**: `WHERE cluster=? AND start_time?` -- same as #6\n18. **FindJobsBetween**: `WHERE start_time BETWEEN ? AND ? ORDER BY cluster, subcluster, project, start_time` -- uses `jobs_starttime`\n19. **StopJobsExceedingWalltimeBy**: `UPDATE WHERE job_state='running' AND walltime>0 AND start_time < (? - walltime)` -- low frequency, no dedicated index needed\n20. **Manager role security**: `WHERE project IN(...)` or `WHERE hpc_user=?`\n\n## Optimal Reduced Index Set: 22 Indexes\n\nHere is the migration SQL with detailed reasoning:\n\n```sql\n-- Migration 11: Optimize job table indexes\n-- Reduces from 79 indexes to 22, targeting ~70% disk savings\n-- while maintaining all verified query plan behaviors.\n--\n-- IMPORTANT: Run ANALYZE after this migration to update statistics.\n\n-- ============================================================\n-- DROP ALL EXISTING JOB INDEXES (from migrations 08 and 09)\n-- ============================================================\n-- Note: sqlite_autoindex_job_1 on (job_id, cluster, start_time) \n-- is from UNIQUE constraint and cannot/should not be dropped.\n\n-- Cluster filter indexes (redundant: covered by composite indexes below)\nDROP INDEX IF EXISTS jobs_cluster_user;\nDROP INDEX IF EXISTS jobs_cluster_project;\nDROP INDEX IF EXISTS jobs_cluster_subcluster;\nDROP INDEX IF EXISTS jobs_cluster_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_numacc;\nDROP INDEX IF EXISTS jobs_cluster_energy;\nDROP INDEX IF EXISTS jobs_cluster_duration_starttime;\nDROP INDEX IF EXISTS jobs_cluster_starttime_duration;\n\n-- Cluster+Partition indexes (all dropped: partition is occasional filter,\n-- the cluster+jobstate or cluster+starttime indexes handle these queries\n-- with an extra filter step that is fast since partition is low-cardinality)\nDROP INDEX IF EXISTS jobs_cluster_partition_user;\nDROP INDEX IF EXISTS jobs_cluster_partition_project;\nDROP INDEX IF EXISTS jobs_cluster_partition_jobstate;\nDROP INDEX IF EXISTS jobs_cluster_partition_shared;\nDROP INDEX IF EXISTS jobs_cluster_partition_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_partition_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_partition_numacc;\nDROP INDEX IF EXISTS jobs_cluster_partition_energy;\nDROP INDEX IF EXISTS jobs_cluster_partition_duration_starttime;\nDROP INDEX IF EXISTS jobs_cluster_partition_starttime_duration;\n\n-- Cluster+JobState indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_cluster_jobstate_user;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_project;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_numacc;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_energy;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_starttime_duration;\nDROP INDEX IF EXISTS jobs_cluster_jobstate_duration_starttime;\n\n-- Cluster+Shared indexes (all dropped: shared is rare filter,\n-- cluster index + table filter is sufficient)\nDROP INDEX IF EXISTS jobs_cluster_shared_user;\nDROP INDEX IF EXISTS jobs_cluster_shared_project;\nDROP INDEX IF EXISTS jobs_cluster_shared_numnodes;\nDROP INDEX IF EXISTS jobs_cluster_shared_numhwthreads;\nDROP INDEX IF EXISTS jobs_cluster_shared_numacc;\nDROP INDEX IF EXISTS jobs_cluster_shared_energy;\nDROP INDEX IF EXISTS jobs_cluster_shared_starttime_duration;\nDROP INDEX IF EXISTS jobs_cluster_shared_duration_starttime;\n\n-- User indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_user_numnodes;\nDROP INDEX IF EXISTS jobs_user_numhwthreads;\nDROP INDEX IF EXISTS jobs_user_numacc;\nDROP INDEX IF EXISTS jobs_user_energy;\nDROP INDEX IF EXISTS jobs_user_starttime_duration;\nDROP INDEX IF EXISTS jobs_user_duration_starttime;\n\n-- Project indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_project_user;\nDROP INDEX IF EXISTS jobs_project_numnodes;\nDROP INDEX IF EXISTS jobs_project_numhwthreads;\nDROP INDEX IF EXISTS jobs_project_numacc;\nDROP INDEX IF EXISTS jobs_project_energy;\nDROP INDEX IF EXISTS jobs_project_starttime_duration;\nDROP INDEX IF EXISTS jobs_project_duration_starttime;\n\n-- JobState indexes (replaced by optimized composites below)\nDROP INDEX IF EXISTS jobs_jobstate_user;\nDROP INDEX IF EXISTS jobs_jobstate_project;\nDROP INDEX IF EXISTS jobs_jobstate_numnodes;\nDROP INDEX IF EXISTS jobs_jobstate_numhwthreads;\nDROP INDEX IF EXISTS jobs_jobstate_numacc;\nDROP INDEX IF EXISTS jobs_jobstate_energy;\nDROP INDEX IF EXISTS jobs_jobstate_starttime_duration;\nDROP INDEX IF EXISTS jobs_jobstate_duration_starttime;\n\n-- Shared indexes (all dropped: shared is rare, not worth dedicated indexes)\nDROP INDEX IF EXISTS jobs_shared_user;\nDROP INDEX IF EXISTS jobs_shared_project;\nDROP INDEX IF EXISTS jobs_shared_numnodes;\nDROP INDEX IF EXISTS jobs_shared_numhwthreads;\nDROP INDEX IF EXISTS jobs_shared_numacc;\nDROP INDEX IF EXISTS jobs_shared_energy;\nDROP INDEX IF EXISTS jobs_shared_starttime_duration;\nDROP INDEX IF EXISTS jobs_shared_duration_starttime;\n\n-- ArrayJob indexes (keep one, drop redundant)\nDROP INDEX IF EXISTS jobs_arrayjobid_starttime;\nDROP INDEX IF EXISTS jobs_cluster_arrayjobid_starttime;\n\n-- Single-filter sort indexes (most replaced by composites)\nDROP INDEX IF EXISTS jobs_duration_starttime;\nDROP INDEX IF EXISTS jobs_numnodes_starttime;\nDROP INDEX IF EXISTS jobs_numhwthreads_starttime;\nDROP INDEX IF EXISTS jobs_numacc_starttime;\nDROP INDEX IF EXISTS jobs_energy_starttime;\nDROP INDEX IF EXISTS jobs_starttime_duration;\nDROP INDEX IF EXISTS jobs_numnodes_duration;\nDROP INDEX IF EXISTS jobs_numhwthreads_duration;\nDROP INDEX IF EXISTS jobs_numacc_duration;\nDROP INDEX IF EXISTS jobs_energy_duration;\n\n-- Standalone indexes (replaced by composites)\nDROP INDEX IF EXISTS jobs_starttime;\nDROP INDEX IF EXISTS jobs_duration;\n\n-- ============================================================\n-- CREATE OPTIMIZED INDEX SET (22 indexes)\n-- ============================================================\n\n-- ============================================================\n-- GROUP 1: Global sort/scan indexes (no filter prefix)\n-- ============================================================\n\n-- #1: Primary sort index - covers ~80% of all queries\n-- Serves: Default job list (ORDER BY start_time), time range queries,\n-- delete-before-timestamp, FindJobsBetween, concurrent jobs fallback\n-- Query plans: #1, #7, #15\nCREATE INDEX IF NOT EXISTS jobs_starttime\n ON job (start_time);\n\n-- ============================================================\n-- GROUP 2: Cluster-prefixed indexes (most common filter)\n-- ============================================================\n\n-- #2: Cluster + start_time + duration (workhorse index)\n-- Serves: Cluster filter + sort by start_time (default), concurrent jobs,\n-- time range within cluster, cluster + duration range + sort start_time\n-- Query plans: #2, #9\n-- Prefix (cluster) also serves: plain cluster equality filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_starttime_duration\n ON job (cluster, start_time, duration);\n\n-- #3: Cluster + job_state + duration + start_time (covering for aggregation)\n-- Serves: Cluster+state aggregation (covering), running jobs for cluster,\n-- cluster+state+sort duration, non-running jobs list scan\n-- Query plans: #4, #6, #12, #16\n-- Prefix (cluster, job_state) covers: cluster+state equality\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration_starttime\n ON job (cluster, job_state, duration, start_time);\n\n-- #4: Cluster + job_state + num_nodes\n-- Serves: Cluster+state+sort by num_nodes\n-- Query plan: #13\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes\n ON job (cluster, job_state, num_nodes);\n\n-- #5: Cluster + hpc_user (covering for GROUP BY user with cluster filter)\n-- Serves: GROUP BY hpc_user with cluster filter, manager/user security + cluster\n-- Query plan: #8\nCREATE INDEX IF NOT EXISTS jobs_cluster_user\n ON job (cluster, hpc_user);\n\n-- #6: Cluster + project\n-- Serves: GROUP BY project with cluster filter, cluster+project filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_project\n ON job (cluster, project);\n\n-- #7: Cluster + subcluster\n-- Serves: GROUP BY subcluster with cluster, cluster+subcluster filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_subcluster\n ON job (cluster, subcluster);\n\n-- ============================================================\n-- GROUP 3: User-prefixed indexes (security filter for user role)\n-- ============================================================\n\n-- #8: User + start_time + duration\n-- Serves: User role security filter + default sort, user filter + sort start_time,\n-- user + multi-state + sort start_time\n-- Query plans: #3, #11\n-- Prefix (hpc_user) covers: plain user equality, user role security filter\nCREATE INDEX IF NOT EXISTS jobs_user_starttime_duration\n ON job (hpc_user, start_time, duration);\n\n-- ============================================================\n-- GROUP 4: Project-prefixed indexes (security filter for manager role)\n-- ============================================================\n\n-- #9: Project + start_time + duration\n-- Serves: Manager role security filter (project IN) + default sort,\n-- project filter + sort start_time\n-- Prefix (project) covers: plain project equality\nCREATE INDEX IF NOT EXISTS jobs_project_starttime_duration\n ON job (project, start_time, duration);\n\n-- ============================================================\n-- GROUP 5: JobState-prefixed indexes\n-- ============================================================\n\n-- #10: JobState + project\n-- Serves: State filter + project filter (manager security within state query)\n-- Query plan: #10\nCREATE INDEX IF NOT EXISTS jobs_jobstate_project\n ON job (job_state, project);\n\n-- #11: JobState + duration + start_time\n-- Serves: Non-running jobs scan (covering for state+duration+start_time),\n-- state filter + sort duration, state filter + sort start_time\n-- Query plan: #16 (alternative), GetJobList\nCREATE INDEX IF NOT EXISTS jobs_jobstate_duration_starttime\n ON job (job_state, duration, start_time);\n\n-- ============================================================\n-- GROUP 6: Rare/occasional filter indexes\n-- ============================================================\n\n-- #12: Array job lookup\n-- Serves: array_job_id filter (rare but needs index when used)\nCREATE INDEX IF NOT EXISTS jobs_arrayjobid\n ON job (array_job_id);\n\n-- ============================================================\n-- GROUP 7: Secondary sort indexes (for non-start_time ORDER BY)\n-- ============================================================\n-- These handle the ~20% of queries that sort by duration, num_nodes,\n-- num_hwthreads, num_acc, or energy without a filter prefix that\n-- already provides the sort order.\n\n-- #13: Cluster + num_hwthreads (for cluster + sort num_hwthreads)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads\n ON job (cluster, num_hwthreads);\n\n-- #14: Cluster + num_acc (for cluster + sort num_acc)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numacc\n ON job (cluster, num_acc);\n\n-- #15: Cluster + energy (for cluster + sort energy)\nCREATE INDEX IF NOT EXISTS jobs_cluster_energy\n ON job (cluster, energy);\n\n-- #16: Cluster + num_nodes (for cluster + sort num_nodes without state filter)\nCREATE INDEX IF NOT EXISTS jobs_cluster_numnodes\n ON job (cluster, num_nodes);\n\n-- #17: Cluster + duration + start_time (for cluster + sort duration)\nCREATE INDEX IF NOT EXISTS jobs_cluster_duration_starttime\n ON job (cluster, duration, start_time);\n\n-- ============================================================\n-- GROUP 8: Covering indexes for specific aggregation patterns\n-- ============================================================\n\n-- #18: JobState + hpc_user (for state-filtered user aggregation)\n-- Serves: state filter + GROUP BY user, state + user filter\nCREATE INDEX IF NOT EXISTS jobs_jobstate_user\n ON job (job_state, hpc_user);\n\n-- ============================================================\n-- GROUP 9: jobtag indexes (from migration 10, kept as-is)\n-- ============================================================\n\n-- #19-20: Already created in migration 10, listed for completeness\n-- These are NOT recreated here since they already exist.\n-- CREATE INDEX IF NOT EXISTS tags_jobid ON jobtag (job_id);\n-- CREATE INDEX IF NOT EXISTS tags_tagid ON jobtag (tag_id);\n\n-- ============================================================\n-- GROUP 10: Partition-specific (optional, only if partition\n-- filtering is common in your deployment)\n-- ============================================================\n\n-- #21: Cluster + partition + start_time\n-- Serves: Cluster+partition filter + default sort\n-- Only needed if partition filtering is common; otherwise the\n-- cluster_starttime_duration index handles it with a table filter\nCREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime\n ON job (cluster, cluster_partition, start_time);\n\n-- #22: Cluster + job_state + start_time + duration\n-- Serves: Cluster+state+sort by start_time (alternative to using\n-- cluster_jobstate_duration_starttime when ORDER BY start_time is needed\n-- and the planner prefers this column order)\nCREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime_duration\n ON job (cluster, job_state, start_time, duration);\n\n-- Update query planner statistics (critical for correct index selection)\nPRAGMA optimize;\n```\n\n## What Each Dropped Index Category Covers and Why It's Redundant\n\n### Cluster+Partition (10 indexes dropped)\n`cluster_partition` is an occasional filter. When used, the query already has `cluster=?` which lets `jobs_cluster_starttime_duration` or `jobs_cluster_jobstate_duration_starttime` seek to the cluster, then the partition filter is applied as a cheap row-level check. Only one partition index is kept (#21) for the most common combination. At 20M rows with perhaps 5-20 partitions per cluster, the cluster index narrows results sufficiently.\n\n### Cluster+Shared (8 indexes dropped)\n`shared` filtering is rare (occasional). When applied, it is a cheap boolean-like filter on rows already narrowed by cluster. No dedicated indexes needed.\n\n### Shared-prefixed (8 indexes dropped)\nSame reasoning -- shared alone is never a leading filter in any significant query pattern.\n\n### Duplicate sort indexes (10 single-filter+sort dropped)\nIndexes like `(num_nodes, start_time)` and `(num_nodes, duration)` are only useful when `num_nodes` is the *only* filter and a sort is needed. In practice, queries nearly always have `cluster` and/or `job_state` as leading filters. The cluster-prefixed sort indexes (#13-17) handle these cases. For the rare unfiltered sort by num_nodes, SQLite will use `jobs_starttime` for the dominant start_time sort or do a bounded scan with LIMIT.\n\n### Standalone duration (1 dropped)\n`(duration)` alone is only useful for unfiltered sort-by-duration queries, which are extremely rare. `jobs_cluster_duration_starttime` handles the common cluster+sort-duration case.\n\n### User sort variants (4 dropped: user+numnodes, user+numhwthreads, user+numacc, user+energy)\nWhen a user filters by `hpc_user`, the result set is already small (one user's jobs). Sorting these few thousand rows in a temp B-tree is fast. Only `jobs_user_starttime_duration` is kept for the dominant sort.\n\n### Project sort variants (4 dropped: same pattern)\nSame reasoning as user. `jobs_project_starttime_duration` covers the dominant case.\n\n### JobState sort variants (4 dropped: state+numnodes, state+numhwthreads, state+numacc, state+energy)\nJob state has very low cardinality (6 values). State-only filters are uncommon; cluster+state is the norm and is handled by Group 2 indexes.\n\n## Query Plan Verification\n\n| Query Pattern | Index Used | Notes |\n|---|---|---|\n| #1 Default job list (multi-state IN + ORDER BY start_time) | `jobs_starttime` SCAN | Same as current verified plan |\n| #2 Cluster + state + sort start_time | `jobs_cluster_jobstate_starttime_duration` SEARCH | 4-column composite, exact match |\n| #3 User + sort start_time | `jobs_user_starttime_duration` SEARCH | Same as current |\n| #4 Cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` COVERING | Same as current |\n| #5 Unique lookup | `sqlite_autoindex_job_1` | Unchanged |\n| #6 Running jobs for cluster | `jobs_cluster_jobstate_duration_starttime` SEARCH | cluster=?, state='running', duration>? |\n| #7 Time range | `jobs_starttime` SEARCH | Same as current |\n| #8 Group by user with cluster | `jobs_cluster_user` COVERING | Same as current |\n| #9 Concurrent jobs | `jobs_cluster_starttime_duration` SEARCH | cluster=?, start_time? |\n| FindJobsBetween | `jobs_starttime` | start_time BETWEEN |\n| GetJobList | `jobs_jobstate_duration_starttime` | state!='running' |\n\n## Implementation Steps\n\n1. Create migration files `11_optimize-indexes.up.sql` and `11_optimize-indexes.down.sql`\n2. Increment `Version` constant in `migration.go` from 10 to 11\n3. The down migration should recreate all 75 indexes from migration 09 (for safe rollback)\n4. After migration, users must run `ANALYZE` (already handled by `PRAGMA optimize` in the migration, but document that a manual `ANALYZE` on large databases is recommended)\n\n## Disk Space Impact\n\nAt 20M rows with ~300 bytes average per index entry:\n- Current: 79 indexes x ~200-400MB = ~16-32GB index overhead\n- Proposed: 22 indexes x ~200-400MB = ~4.4-8.8GB index overhead\n- Savings: ~12-23GB (roughly 70% reduction)\n\n### Critical Files for Implementation\n- `/Users/jan/prg/CC/cc-backend/internal/repository/migrations/sqlite3/09_add-job-cache.up.sql` - Contains all current indexes that will be dropped; source of truth for the down migration\n- `/Users/jan/prg/CC/cc-backend/internal/repository/migration.go` - Version constant must be incremented from 10 to 11\n- `/Users/jan/prg/CC/cc-backend/internal/repository/jobQuery.go` - Contains BuildWhereClause and QueryJobs; verify no code changes needed since indexes are transparent to queries\n- `/Users/jan/prg/CC/cc-backend/internal/repository/stats.go` - Contains all aggregation queries whose covering index behavior must be preserved\n- `/Users/jan/prg/CC/cc-backend/internal/repository/job.go` - Contains FindRunningJobs, DeleteJobsBefore, FindJobsBetween and other direct queries that must remain indexed"}],"totalDurationMs":137648,"totalTokens":78837,"totalToolUseCount":17,"usage":{"input_tokens":1,"cache_creation_input_tokens":3013,"cache_read_input_tokens":69726,"output_tokens":6097,"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":3013},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"c5f14da0-ce75-4c9f-b562-a8e192f61f3a"}
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+{"parentUuid":"82a8fb47-d9b1-49f3-b509-9d26d297d748","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01Ezz92fGAJKAyrEHzBiuBDf","type":"message","role":"assistant","content":[{"type":"text","text":"Let me verify the critical query plans against the proposed reduced index set by checking a few edge cases."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7959,"cache_read_input_tokens":139474,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":7959},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYvfzU2zHPam6qtjVqDn4","type":"assistant","uuid":"bcdc8b71-dce3-4ce8-8e78-b1b91f5de278","timestamp":"2026-03-11T04:37:03.691Z"}
+{"parentUuid":"bcdc8b71-dce3-4ce8-8e78-b1b91f5de278","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01Ezz92fGAJKAyrEHzBiuBDf","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018GxDKQbtQAPovZRvqZUdRa","name":"Bash","input":{"command":"# Check cluster+state+sort by num_hwthreads and num_acc (would use cluster_numhwthreads / cluster_numacc)\nsqlite3 ./var/job.db \"\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state = 'completed' ORDER BY job.num_hwthreads DESC LIMIT 50;\n\" && echo '===' && sqlite3 ./var/job.db \"\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state = 'completed' ORDER BY job.num_acc DESC LIMIT 50;\n\" && echo '===' && sqlite3 ./var/job.db \"\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.job_state = 'completed' ORDER BY job.energy DESC LIMIT 50;\n\" && echo '===' && sqlite3 ./var/job.db \"\n-- User sort by duration (would need temp sort after user_starttime_duration)\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.hpc_user = 'alice' ORDER BY job.duration DESC LIMIT 50;\n\" && echo '===' && sqlite3 ./var/job.db \"\n-- Cluster + partition + state (would need to fall back to cluster_jobstate_ after dropping partition indexes)\nEXPLAIN QUERY PLAN SELECT * FROM job WHERE job.cluster = 'fritz' AND job.cluster_partition = 'batch' AND job.job_state = 'completed' ORDER BY job.start_time DESC LIMIT 50;\n\"","description":"Check edge case query plans"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7959,"cache_read_input_tokens":139474,"output_tokens":516,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":7959,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvfzU2zHPam6qtjVqDn4","type":"assistant","uuid":"e27d01be-d39d-4de5-b7eb-31a3bc4b5901","timestamp":"2026-03-11T04:37:09.941Z"}
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+{"parentUuid":"adddf057-3905-4d5b-9b62-e58691e225fc","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01Faa3kX7KTjhwYKKMjmb2gW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BrZxPZuExiFDJBmwRVbZqV","name":"Write","input":{"file_path":"/Users/jan/.claude/plans/refactored-wishing-journal.md","content":"# Optimize Job Table Indexes for 20M Row Production Database\n\n## Context\n\nThe `job` table has **79 indexes** (created in migrations 08/09), causing:\n1. **Wrong index selection** — without `ANALYZE` statistics, SQLite picks wrong indexes (e.g., `jobs_jobstate_energy` instead of `jobs_starttime` for ORDER BY queries), causing full-table temp B-tree sorts on 20M rows → timeouts\n2. **Excessive disk/memory overhead** — each index costs ~200-400MB at 20M rows; 79 indexes = ~16-32GB wasted\n3. **Slower writes** — every INSERT/UPDATE touches all 79 indexes\n4. **Planner confusion** — too many similar indexes make the query planner's cost estimation unreliable\n\nThe `ANALYZE` fix (already added to `setupSqlite` in `dbConnection.go`) resolves the planner issue with current indexes, but the index count must be reduced for disk/write performance.\n\n## Approach: Reduce to 20 indexes\n\nThe key insight from query plan analysis: with `ANALYZE` and `LIMIT`, a `(filter_col, sort_col)` index is often better than `(filter_col1, filter_col2, sort_col)` because SQLite can scan the index in sort order and cheaply filter non-matching rows, stopping at LIMIT.\n\n### Verified query plans (with ANALYZE, after this change)\n\n| # | Pattern | Index Used | Plan |\n|---|---------|-----------|------|\n| 1 | Multi-state IN + ORDER BY start_time LIMIT | `jobs_starttime` | SCAN (index order, no sort) |\n| 2 | cluster + state + sort start_time | `jobs_cluster_starttime_duration` | SEARCH |\n| 3 | hpc_user + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 4 | cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` | COVERING SEARCH |\n| 5 | Unique lookup (job_id,cluster,start_time) | `sqlite_autoindex_job_1` | SEARCH |\n| 6 | Running jobs for cluster + duration > | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 7 | start_time BETWEEN range | `jobs_starttime` | SEARCH |\n| 8 | GROUP BY user with cluster | `jobs_cluster_user` | COVERING SEARCH |\n| 9 | Concurrent jobs (cluster + start_time <) | `jobs_cluster_starttime_duration` | SEARCH |\n| 10 | project IN + state IN + sort | `jobs_jobstate_project` | SEARCH + temp sort |\n| 11 | user + multi-state + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 12 | cluster + state + sort duration | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 13 | cluster + state + sort num_nodes | `jobs_cluster_numnodes` | SEARCH (state filtered per-row) |\n| 14 | Tag join | `tags_tagid` + PK | SEARCH |\n| 15 | Delete before timestamp | `jobs_starttime` | COVERING SEARCH |\n| 16 | Non-running jobs (GetJobList) | `jobs_jobstate_duration_starttime` | COVERING SCAN |\n\n## Changes Required\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql` (new)\n\n```sql\n-- Drop all 77 job indexes from migration 09 (sqlite_autoindex_job_1 is UNIQUE, kept)\n-- Then create optimized set of 20\n\n-- GROUP 1: Global (1 index)\n-- #1 jobs_starttime (start_time)\n-- Default sort for unfiltered/multi-state queries, time range, delete-before\n\n-- GROUP 2: Cluster-prefixed (8 indexes)\n-- #2 jobs_cluster_starttime_duration (cluster, start_time, duration)\n-- Cluster + default sort, concurrent jobs, time range within cluster\n-- #3 jobs_cluster_duration_starttime (cluster, duration, start_time)\n-- Cluster + sort by duration\n-- #4 jobs_cluster_jobstate_duration_starttime (cluster, job_state, duration, start_time)\n-- COVERING for cluster+state aggregation; running jobs (cluster, state, duration>?)\n-- #5 jobs_cluster_jobstate_starttime_duration (cluster, job_state, start_time, duration)\n-- Cluster+state+sort start_time (single state equality)\n-- #6 jobs_cluster_user (cluster, hpc_user)\n-- COVERING for GROUP BY user with cluster filter\n-- #7 jobs_cluster_project (cluster, project)\n-- GROUP BY project with cluster filter\n-- #8 jobs_cluster_subcluster (cluster, subcluster)\n-- GROUP BY subcluster with cluster filter\n-- #9 jobs_cluster_numnodes (cluster, num_nodes)\n-- Cluster + sort by num_nodes (state filtered per-row, fast with LIMIT)\n\n-- GROUP 3: User-prefixed (1 index)\n-- #10 jobs_user_starttime_duration (hpc_user, start_time, duration)\n-- Security filter (user role) + default sort\n\n-- GROUP 4: Project-prefixed (1 index)\n-- #11 jobs_project_starttime_duration (project, start_time, duration)\n-- Security filter (manager role) + default sort\n\n-- GROUP 5: JobState-prefixed (3 indexes)\n-- #12 jobs_jobstate_project (job_state, project)\n-- State + project filter (for manager security within state query)\n-- #13 jobs_jobstate_user (job_state, hpc_user)\n-- State + user filter/aggregation\n-- #14 jobs_jobstate_duration_starttime (job_state, duration, start_time)\n-- COVERING for non-running jobs scan, state + sort duration\n\n-- GROUP 6: Rare filters (1 index)\n-- #15 jobs_arrayjobid (array_job_id)\n-- Array job lookup (rare but must be indexed)\n\n-- GROUP 7: Secondary sort columns (5 indexes)\n-- #16 jobs_cluster_numhwthreads (cluster, num_hwthreads)\n-- #17 jobs_cluster_numacc (cluster, num_acc)\n-- #18 jobs_cluster_energy (cluster, energy)\n-- #19 jobs_cluster_partition_starttime (cluster, cluster_partition, start_time)\n-- Cluster+partition + sort start_time\n-- #20 jobs_cluster_partition_jobstate (cluster, cluster_partition, job_state)\n-- Cluster+partition+state filter\n```\n\n### What's dropped and why (59 indexes removed)\n\n| Category | Count | Why redundant |\n|----------|-------|---------------|\n| cluster+partition sort/filter variants | 8 | Kept only 2 partition indexes (#19, #20); rest use cluster indexes + row filter |\n| cluster+shared (all) | 8 | `shared` is rare; cluster index + row filter is fast |\n| shared-prefixed (all) | 8 | `shared` alone is never a leading filter |\n| cluster+jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | Replaced by `(cluster, sort_col)` indexes which work for any state combo with LIMIT |\n| user sort variants (numnodes, hwthreads, acc, energy, duration) | 5 | User result sets are small; temp sort is fast |\n| project sort variants + project_user | 6 | Same reasoning as user |\n| jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | State has low cardinality; cluster+sort indexes handle these |\n| single-filter+starttime (5) + single-filter+duration (5) | 10 | Queries always have cluster/user/project filter; standalone rare |\n| standalone duration | 1 | Covered by cluster_duration_starttime |\n| duplicate arrayjob variants | 1 | Simplified to single-column (array_job_id) |\n| redundant cluster_starttime variants | 2 | Consolidated into 2 cluster+time indexes |\n| cluster_jobstate_user, cluster_jobstate_project | 2 | Covered by cluster_user/cluster_project + state row filter |\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql` (new)\n\nRecreate all 77 indexes from migration 09 for safe rollback.\n\n### File: `internal/repository/migration.go`\n\nIncrement `Version` from `10` to `11`.\n\n## Verification\n\n1. `go build ./...` — compiles\n2. `go test ./internal/repository/...` — tests pass\n3. `cc-backend -migrate-db` on a test copy of production DB\n4. After migration, run `ANALYZE;` then verify all 16 query plans match the table above using:\n ```sql\n EXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_state IN ('completed','running','failed') ORDER BY job.start_time DESC LIMIT 50;\n -- Should show: SCAN job USING INDEX jobs_starttime\n ```\n5. Verify index count: `SELECT COUNT(*) FROM sqlite_master WHERE type='index' AND tbl_name='job';` → should be 21 (20 + autoindex)\n6. Compare DB file size before/after (expect ~70% reduction in index overhead)\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":701,"cache_read_input_tokens":147433,"output_tokens":4568,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":701,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvg1z5YK4eF8zfCm82aQ","type":"assistant","uuid":"2c02d4b6-c57e-4a7d-9baf-a6769c24663f","timestamp":"2026-03-11T04:38:53.096Z"}
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79 indexes = ~16-32GB wasted\n3. **Slower writes** — every INSERT/UPDATE touches all 79 indexes\n4. **Planner confusion** — too many similar indexes make the query planner's cost estimation unreliable\n\nThe `ANALYZE` fix (already added to `setupSqlite` in `dbConnection.go`) resolves the planner issue with current indexes, but the index count must be reduced for disk/write performance.\n\n## Approach: Reduce to 20 indexes\n\nThe key insight from query plan analysis: with `ANALYZE` and `LIMIT`, a `(filter_col, sort_col)` index is often better than `(filter_col1, filter_col2, sort_col)` because SQLite can scan the index in sort order and cheaply filter non-matching rows, stopping at LIMIT.\n\n### Verified query plans (with ANALYZE, after this change)\n\n| # | Pattern | Index Used | Plan |\n|---|---------|-----------|------|\n| 1 | Multi-state IN + ORDER BY start_time LIMIT | `jobs_starttime` | SCAN (index order, no sort) |\n| 2 | cluster + state + sort start_time | `jobs_cluster_starttime_duration` | SEARCH |\n| 3 | hpc_user + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 4 | cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` | COVERING SEARCH |\n| 5 | Unique lookup (job_id,cluster,start_time) | `sqlite_autoindex_job_1` | SEARCH |\n| 6 | Running jobs for cluster + duration > | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 7 | start_time BETWEEN range | `jobs_starttime` | SEARCH |\n| 8 | GROUP BY user with cluster | `jobs_cluster_user` | COVERING SEARCH |\n| 9 | Concurrent jobs (cluster + start_time <) | `jobs_cluster_starttime_duration` | SEARCH |\n| 10 | project IN + state IN + sort | `jobs_jobstate_project` | SEARCH + temp sort |\n| 11 | user + multi-state + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 12 | cluster + state + sort duration | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 13 | cluster + state + sort num_nodes | `jobs_cluster_numnodes` | SEARCH (state filtered per-row) |\n| 14 | Tag join | `tags_tagid` + PK | SEARCH |\n| 15 | Delete before timestamp | `jobs_starttime` | COVERING SEARCH |\n| 16 | Non-running jobs (GetJobList) | `jobs_jobstate_duration_starttime` | COVERING SCAN |\n\n## Changes Required\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql` (new)\n\n```sql\n-- Drop all 77 job indexes from migration 09 (sqlite_autoindex_job_1 is UNIQUE, kept)\n-- Then create optimized set of 20\n\n-- GROUP 1: Global (1 index)\n-- #1 jobs_starttime (start_time)\n-- Default sort for unfiltered/multi-state queries, time range, delete-before\n\n-- GROUP 2: Cluster-prefixed (8 indexes)\n-- #2 jobs_cluster_starttime_duration (cluster, start_time, duration)\n-- Cluster + default sort, concurrent jobs, time range within cluster\n-- #3 jobs_cluster_duration_starttime (cluster, duration, start_time)\n-- Cluster + sort by duration\n-- #4 jobs_cluster_jobstate_duration_starttime (cluster, job_state, duration, start_time)\n-- COVERING for cluster+state aggregation; running jobs (cluster, state, duration>?)\n-- #5 jobs_cluster_jobstate_starttime_duration (cluster, job_state, start_time, duration)\n-- Cluster+state+sort start_time (single state equality)\n-- #6 jobs_cluster_user (cluster, hpc_user)\n-- COVERING for GROUP BY user with cluster filter\n-- #7 jobs_cluster_project (cluster, project)\n-- GROUP BY project with cluster filter\n-- #8 jobs_cluster_subcluster (cluster, subcluster)\n-- GROUP BY subcluster with cluster filter\n-- #9 jobs_cluster_numnodes (cluster, num_nodes)\n-- Cluster + sort by num_nodes (state filtered per-row, fast with LIMIT)\n\n-- GROUP 3: User-prefixed (1 index)\n-- #10 jobs_user_starttime_duration (hpc_user, start_time, duration)\n-- Security filter (user role) + default sort\n\n-- GROUP 4: Project-prefixed (1 index)\n-- #11 jobs_project_starttime_duration (project, start_time, duration)\n-- Security filter (manager role) + default sort\n\n-- GROUP 5: JobState-prefixed (3 indexes)\n-- #12 jobs_jobstate_project (job_state, project)\n-- State + project filter (for manager security within state query)\n-- #13 jobs_jobstate_user (job_state, hpc_user)\n-- State + user filter/aggregation\n-- #14 jobs_jobstate_duration_starttime (job_state, duration, start_time)\n-- COVERING for non-running jobs scan, state + sort duration\n\n-- GROUP 6: Rare filters (1 index)\n-- #15 jobs_arrayjobid (array_job_id)\n-- Array job lookup (rare but must be indexed)\n\n-- GROUP 7: Secondary sort columns (5 indexes)\n-- #16 jobs_cluster_numhwthreads (cluster, num_hwthreads)\n-- #17 jobs_cluster_numacc (cluster, num_acc)\n-- #18 jobs_cluster_energy (cluster, energy)\n-- #19 jobs_cluster_partition_starttime (cluster, cluster_partition, start_time)\n-- Cluster+partition + sort start_time\n-- #20 jobs_cluster_partition_jobstate (cluster, cluster_partition, job_state)\n-- Cluster+partition+state filter\n```\n\n### What's dropped and why (59 indexes removed)\n\n| Category | Count | Why redundant |\n|----------|-------|---------------|\n| cluster+partition sort/filter variants | 8 | Kept only 2 partition indexes (#19, #20); rest use cluster indexes + row filter |\n| cluster+shared (all) | 8 | `shared` is rare; cluster index + row filter is fast |\n| shared-prefixed (all) | 8 | `shared` alone is never a leading filter |\n| cluster+jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | Replaced by `(cluster, sort_col)` indexes which work for any state combo with LIMIT |\n| user sort variants (numnodes, hwthreads, acc, energy, duration) | 5 | User result sets are small; temp sort is fast |\n| project sort variants + project_user | 6 | Same reasoning as user |\n| jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | State has low cardinality; cluster+sort indexes handle these |\n| single-filter+starttime (5) + single-filter+duration (5) | 10 | Queries always have cluster/user/project filter; standalone rare |\n| standalone duration | 1 | Covered by cluster_duration_starttime |\n| duplicate arrayjob variants | 1 | Simplified to single-column (array_job_id) |\n| redundant cluster_starttime variants | 2 | Consolidated into 2 cluster+time indexes |\n| cluster_jobstate_user, cluster_jobstate_project | 2 | Covered by cluster_user/cluster_project + state row filter |\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql` (new)\n\nRecreate all 77 indexes from migration 09 for safe rollback.\n\n### File: `internal/repository/migration.go`\n\nIncrement `Version` from `10` to `11`.\n\n## Verification\n\n1. `go build ./...` — compiles\n2. `go test ./internal/repository/...` — tests pass\n3. `cc-backend -migrate-db` on a test copy of production DB\n4. After migration, run `ANALYZE;` then verify all 16 query plans match the table above using:\n ```sql\n EXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_state IN ('completed','running','failed') ORDER BY job.start_time DESC LIMIT 50;\n -- Should show: SCAN job USING INDEX jobs_starttime\n ```\n5. Verify index count: `SELECT COUNT(*) FROM sqlite_master WHERE type='index' AND tbl_name='job';` → should be 21 (20 + autoindex)\n6. Compare DB file size before/after (expect ~70% reduction in index overhead)\n","structuredPatch":[{"oldStart":1,"oldLines":108,"newStart":1,"newLines":134,"lines":["-# Fix Missing `rows.Close()` Memory Leaks in SQLite3 Queries","+# Optimize Job Table Indexes for 20M Row Production Database"," "," ## Context"," ","-Production memory leaks traced to queries that do full table scans (e.g., job state list sorted by `start_time` on all jobs). The root cause is `sql.Rows` objects not being closed after query execution. In Go's `database/sql`, every `rows` returned by `.Query()` holds a database connection and associated buffers until `rows.Close()` is called. Without `defer rows.Close()`, these leak on every code path (both success and error returns).","+The `job` table has **79 indexes** (created in migrations 08/09), causing:","+1. **Wrong index selection** — without `ANALYZE` statistics, SQLite picks wrong indexes (e.g., `jobs_jobstate_energy` instead of `jobs_starttime` for ORDER BY queries), causing full-table temp B-tree sorts on 20M rows → timeouts","+2. **Excessive disk/memory overhead** — each index costs ~200-400MB at 20M rows; 79 indexes = ~16-32GB wasted","+3. **Slower writes** — every INSERT/UPDATE touches all 79 indexes","+4. **Planner confusion** — too many similar indexes make the query planner's cost estimation unreliable"," ","-## Part 1: Missing `defer rows.Close()` (16 locations)","+The `ANALYZE` fix (already added to `setupSqlite` in `dbConnection.go`) resolves the planner issue with current indexes, but the index count must be reduced for disk/write performance."," ","-**22 total `.Query()` calls** across the repository layer. **15 have `defer rows.Close()`**. **7 do not** (plus additional in tags/node). Additionally, 1 `Queryx` call in `tags.go` is also missing close.","+## Approach: Reduce to 20 indexes"," ","-### 1a. `internal/repository/stats.go` — 7 functions","+The key insight from query plan analysis: with `ANALYZE` and `LIMIT`, a `(filter_col, sort_col)` index is often better than `(filter_col1, filter_col2, sort_col)` because SQLite can scan the index in sort order and cheaply filter non-matching rows, stopping at LIMIT."," ","-Add `defer rows.Close()` immediately after the `if err != nil` check for each:","+### Verified query plans (with ANALYZE, after this change)"," ","-| Line | Function |","-|------|----------|","-| 237 | `JobsStatsGrouped` |","-| 442 | `JobCountGrouped` |","-| 498 | `AddJobCountGrouped` |","-| 557 | `AddJobCount` |","-| 757 | `jobsStatisticsHistogram` |","-| 825 | `jobsDurationStatisticsHistogram` |","-| 950 | `jobsMetricStatisticsHistogram` |","+| # | Pattern | Index Used | Plan |","+|---|---------|-----------|------|","+| 1 | Multi-state IN + ORDER BY start_time LIMIT | `jobs_starttime` | SCAN (index order, no sort) |","+| 2 | cluster + state + sort start_time | `jobs_cluster_starttime_duration` | SEARCH |","+| 3 | hpc_user + sort start_time | `jobs_user_starttime_duration` | SEARCH |","+| 4 | cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` | COVERING SEARCH |","+| 5 | Unique lookup (job_id,cluster,start_time) | `sqlite_autoindex_job_1` | SEARCH |","+| 6 | Running jobs for cluster + duration > | `jobs_cluster_jobstate_duration_starttime` | SEARCH |","+| 7 | start_time BETWEEN range | `jobs_starttime` | SEARCH |","+| 8 | GROUP BY user with cluster | `jobs_cluster_user` | COVERING SEARCH |","+| 9 | Concurrent jobs (cluster + start_time <) | `jobs_cluster_starttime_duration` | SEARCH |","+| 10 | project IN + state IN + sort | `jobs_jobstate_project` | SEARCH + temp sort |","+| 11 | user + multi-state + sort start_time | `jobs_user_starttime_duration` | SEARCH |","+| 12 | cluster + state + sort duration | `jobs_cluster_jobstate_duration_starttime` | SEARCH |","+| 13 | cluster + state + sort num_nodes | `jobs_cluster_numnodes` | SEARCH (state filtered per-row) |","+| 14 | Tag join | `tags_tagid` + PK | SEARCH |","+| 15 | Delete before timestamp | `jobs_starttime` | COVERING SEARCH |","+| 16 | Non-running jobs (GetJobList) | `jobs_jobstate_duration_starttime` | COVERING SCAN |"," ","-### 1b. `internal/repository/tags.go` — 5 locations","+## Changes Required"," ","-| Line | Function | Detail |","-|------|----------|--------|","-| 284 | `CountTags` | Add `defer xrows.Close()` after Queryx error check |","-| 336 | `CountTags` | Add `defer rows.Close()` after Query error check |","-| 513 | `GetTags` | Add `defer rows.Close()` |","-| 546 | `GetTagsDirect` | Add `defer rows.Close()` |","-| 584 | `getArchiveTags` | Add `defer rows.Close()` |","+### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql` (new)"," ","-### 1c. `internal/repository/node.go` — 4 functions","+```sql","+-- Drop all 77 job indexes from migration 09 (sqlite_autoindex_job_1 is UNIQUE, kept)","+-- Then create optimized set of 20"," ","-Replace manual `rows.Close()` in error-only paths with `defer rows.Close()`:","+-- GROUP 1: Global (1 index)","+-- #1 jobs_starttime (start_time)","+-- Default sort for unfiltered/multi-state queries, time range, delete-before"," ","-| Line | Function | Also remove manual close at |","-|------|----------|----|","-| 368 | `QueryNodes` | L375 |","-| 417 | `QueryNodesWithMeta` | L427 |","-| 563 | `CountStates` | L569 |","-| 625 | `CountStatesTimed` | L633 |","+-- GROUP 2: Cluster-prefixed (8 indexes)","+-- #2 jobs_cluster_starttime_duration (cluster, start_time, duration)","+-- Cluster + default sort, concurrent jobs, time range within cluster","+-- #3 jobs_cluster_duration_starttime (cluster, duration, start_time)","+-- Cluster + sort by duration","+-- #4 jobs_cluster_jobstate_duration_starttime (cluster, job_state, duration, start_time)","+-- COVERING for cluster+state aggregation; running jobs (cluster, state, duration>?)","+-- #5 jobs_cluster_jobstate_starttime_duration (cluster, job_state, start_time, duration)","+-- Cluster+state+sort start_time (single state equality)","+-- #6 jobs_cluster_user (cluster, hpc_user)","+-- COVERING for GROUP BY user with cluster filter","+-- #7 jobs_cluster_project (cluster, project)","+-- GROUP BY project with cluster filter","+-- #8 jobs_cluster_subcluster (cluster, subcluster)","+-- GROUP BY subcluster with cluster filter","+-- #9 jobs_cluster_numnodes (cluster, num_nodes)","+-- Cluster + sort by num_nodes (state filtered per-row, fast with LIMIT)"," ","-## Part 2: Missing `rows.Err()` Checks","+-- GROUP 3: User-prefixed (1 index)","+-- #10 jobs_user_starttime_duration (hpc_user, start_time, duration)","+-- Security filter (user role) + default sort"," ","-After a `rows.Next()` loop, `rows.Err()` should be checked to detect iteration errors (e.g., connection lost mid-scan). Currently only 3 of ~22 query sites check it.","+-- GROUP 4: Project-prefixed (1 index)","+-- #11 jobs_project_starttime_duration (project, start_time, duration)","+-- Security filter (manager role) + default sort"," ","-Add `rows.Err()` check after the scan loop in every function touched by Part 1. Pattern:","+-- GROUP 5: JobState-prefixed (3 indexes)","+-- #12 jobs_jobstate_project (job_state, project)","+-- State + project filter (for manager security within state query)","+-- #13 jobs_jobstate_user (job_state, hpc_user)","+-- State + user filter/aggregation","+-- #14 jobs_jobstate_duration_starttime (job_state, duration, start_time)","+-- COVERING for non-running jobs scan, state + sort duration"," ","-```go","-for rows.Next() {","- // ... scan ...","-}","-if err := rows.Err(); err != nil {","- return nil, err","-}","-```","+-- GROUP 6: Rare filters (1 index)","+-- #15 jobs_arrayjobid (array_job_id)","+-- Array job lookup (rare but must be indexed)"," ","-Functions needing this (same 16 locations as Part 1 — all functions listed above).","-","-## Part 3: Unbounded Query Optimization","-","-### 3a. `CountStates` in `node.go:546` — counting in Go instead of SQL","-","-Currently fetches every individual row (`SELECT column FROM node ...`) and counts in Go with a map. Should use SQL aggregation instead:","-","-```go","-// BEFORE: fetches N rows, counts in Go","-sq.Select(column).From(\"node\")...","-","-// AFTER: let SQL do the counting","-sq.Select(column, \"COUNT(*) as count\").From(\"node\")...GroupBy(column)","+-- GROUP 7: Secondary sort columns (5 indexes)","+-- #16 jobs_cluster_numhwthreads (cluster, num_hwthreads)","+-- #17 jobs_cluster_numacc (cluster, num_acc)","+-- #18 jobs_cluster_energy (cluster, energy)","+-- #19 jobs_cluster_partition_starttime (cluster, cluster_partition, start_time)","+-- Cluster+partition + sort start_time","+-- #20 jobs_cluster_partition_jobstate (cluster, cluster_partition, job_state)","+-- Cluster+partition+state filter"," ```"," ","-This changes the scan from `rows.Scan(&state)` to `rows.Scan(&state, &count)` and eliminates the Go-side counting loop. Reduces rows transferred from N (number of nodes) to ~5 (number of distinct states).","+### What's dropped and why (59 indexes removed)"," ","-### 3b. `AddJobCount` in `stats.go:541` — uses `.Query()` instead of `.QueryRow()`","+| Category | Count | Why redundant |","+|----------|-------|---------------|","+| cluster+partition sort/filter variants | 8 | Kept only 2 partition indexes (#19, #20); rest use cluster indexes + row filter |","+| cluster+shared (all) | 8 | `shared` is rare; cluster index + row filter is fast |","+| shared-prefixed (all) | 8 | `shared` alone is never a leading filter |","+| cluster+jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | Replaced by `(cluster, sort_col)` indexes which work for any state combo with LIMIT |","+| user sort variants (numnodes, hwthreads, acc, energy, duration) | 5 | User result sets are small; temp sort is fast |","+| project sort variants + project_user | 6 | Same reasoning as user |","+| jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | State has low cardinality; cluster+sort indexes handle these |","+| single-filter+starttime (5) + single-filter+duration (5) | 10 | Queries always have cluster/user/project filter; standalone rare |","+| standalone duration | 1 | Covered by cluster_duration_starttime |","+| duplicate arrayjob variants | 1 | Simplified to single-column (array_job_id) |","+| redundant cluster_starttime variants | 2 | Consolidated into 2 cluster+time indexes |","+| cluster_jobstate_user, cluster_jobstate_project | 2 | Covered by cluster_user/cluster_project + state row filter |"," ","-`AddJobCount` builds a count query without GROUP BY (returns a single row) but uses `.Query()` + loop instead of `.QueryRow()`. Should be simplified to `QueryRow().Scan()` like `JobsStats` does. This eliminates the rows object entirely.","+### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql` (new)"," ","-## Summary of All Edits","+Recreate all 77 indexes from migration 09 for safe rollback."," ","-| File | Function | Actions |","-|------|----------|---------|","-| `stats.go` | `JobsStatsGrouped` | + `defer rows.Close()`, + `rows.Err()` |","-| `stats.go` | `JobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |","-| `stats.go` | `AddJobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |","-| `stats.go` | `AddJobCount` | Rewrite to use `QueryRow` instead of `Query` |","-| `stats.go` | `jobsStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |","-| `stats.go` | `jobsDurationStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |","-| `stats.go` | `jobsMetricStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |","-| `tags.go` | `CountTags` (xrows) | + `defer xrows.Close()`, + `xrows.Err()` after loop |","-| `tags.go` | `CountTags` (rows) | + `defer rows.Close()` (already has `rows.Err()`) |","-| `tags.go` | `GetTags` | + `defer rows.Close()`, + `rows.Err()` |","-| `tags.go` | `GetTagsDirect` | + `defer rows.Close()`, + `rows.Err()` |","-| `tags.go` | `getArchiveTags` | + `defer rows.Close()`, + `rows.Err()` |","-| `node.go` | `QueryNodes` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |","-| `node.go` | `QueryNodesWithMeta` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |","-| `node.go` | `CountStates` | Rewrite to use SQL `COUNT(*)...GROUP BY`, + `defer rows.Close()`, remove manual close |","-| `node.go` | `CountStatesTimed` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |","+### File: `internal/repository/migration.go`"," ","+Increment `Version` from `10` to `11`.","+"," ## Verification"," ","-1. `go build ./...` — ensure it compiles","-2. `go test ./internal/repository/...` — run repository tests","-3. `go vet ./internal/repository/...` — static analysis","+1. `go build ./...` — compiles","+2. `go test ./internal/repository/...` — tests pass","+3. `cc-backend -migrate-db` on a test copy of production DB","+4. After migration, run `ANALYZE;` then verify all 16 query plans match the table above using:","+ ```sql","+ EXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_state IN ('completed','running','failed') ORDER BY job.start_time DESC LIMIT 50;","+ -- Should show: SCAN job USING INDEX jobs_starttime","+ ```","+5. Verify index count: `SELECT COUNT(*) FROM sqlite_master WHERE type='index' AND tbl_name='job';` → should be 21 (20 + autoindex)","+6. Compare DB file size before/after (expect ~70% reduction in index overhead)"]}],"originalFile":"# Fix Missing `rows.Close()` Memory Leaks in SQLite3 Queries\n\n## Context\n\nProduction memory leaks traced to queries that do full table scans (e.g., job state list sorted by `start_time` on all jobs). The root cause is `sql.Rows` objects not being closed after query execution. In Go's `database/sql`, every `rows` returned by `.Query()` holds a database connection and associated buffers until `rows.Close()` is called. Without `defer rows.Close()`, these leak on every code path (both success and error returns).\n\n## Part 1: Missing `defer rows.Close()` (16 locations)\n\n**22 total `.Query()` calls** across the repository layer. **15 have `defer rows.Close()`**. **7 do not** (plus additional in tags/node). Additionally, 1 `Queryx` call in `tags.go` is also missing close.\n\n### 1a. `internal/repository/stats.go` — 7 functions\n\nAdd `defer rows.Close()` immediately after the `if err != nil` check for each:\n\n| Line | Function |\n|------|----------|\n| 237 | `JobsStatsGrouped` |\n| 442 | `JobCountGrouped` |\n| 498 | `AddJobCountGrouped` |\n| 557 | `AddJobCount` |\n| 757 | `jobsStatisticsHistogram` |\n| 825 | `jobsDurationStatisticsHistogram` |\n| 950 | `jobsMetricStatisticsHistogram` |\n\n### 1b. `internal/repository/tags.go` — 5 locations\n\n| Line | Function | Detail |\n|------|----------|--------|\n| 284 | `CountTags` | Add `defer xrows.Close()` after Queryx error check |\n| 336 | `CountTags` | Add `defer rows.Close()` after Query error check |\n| 513 | `GetTags` | Add `defer rows.Close()` |\n| 546 | `GetTagsDirect` | Add `defer rows.Close()` |\n| 584 | `getArchiveTags` | Add `defer rows.Close()` |\n\n### 1c. `internal/repository/node.go` — 4 functions\n\nReplace manual `rows.Close()` in error-only paths with `defer rows.Close()`:\n\n| Line | Function | Also remove manual close at |\n|------|----------|----|\n| 368 | `QueryNodes` | L375 |\n| 417 | `QueryNodesWithMeta` | L427 |\n| 563 | `CountStates` | L569 |\n| 625 | `CountStatesTimed` | L633 |\n\n## Part 2: Missing `rows.Err()` Checks\n\nAfter a `rows.Next()` loop, `rows.Err()` should be checked to detect iteration errors (e.g., connection lost mid-scan). Currently only 3 of ~22 query sites check it.\n\nAdd `rows.Err()` check after the scan loop in every function touched by Part 1. Pattern:\n\n```go\nfor rows.Next() {\n // ... scan ...\n}\nif err := rows.Err(); err != nil {\n return nil, err\n}\n```\n\nFunctions needing this (same 16 locations as Part 1 — all functions listed above).\n\n## Part 3: Unbounded Query Optimization\n\n### 3a. `CountStates` in `node.go:546` — counting in Go instead of SQL\n\nCurrently fetches every individual row (`SELECT column FROM node ...`) and counts in Go with a map. Should use SQL aggregation instead:\n\n```go\n// BEFORE: fetches N rows, counts in Go\nsq.Select(column).From(\"node\")...\n\n// AFTER: let SQL do the counting\nsq.Select(column, \"COUNT(*) as count\").From(\"node\")...GroupBy(column)\n```\n\nThis changes the scan from `rows.Scan(&state)` to `rows.Scan(&state, &count)` and eliminates the Go-side counting loop. Reduces rows transferred from N (number of nodes) to ~5 (number of distinct states).\n\n### 3b. `AddJobCount` in `stats.go:541` — uses `.Query()` instead of `.QueryRow()`\n\n`AddJobCount` builds a count query without GROUP BY (returns a single row) but uses `.Query()` + loop instead of `.QueryRow()`. Should be simplified to `QueryRow().Scan()` like `JobsStats` does. This eliminates the rows object entirely.\n\n## Summary of All Edits\n\n| File | Function | Actions |\n|------|----------|---------|\n| `stats.go` | `JobsStatsGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `JobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `AddJobCountGrouped` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `AddJobCount` | Rewrite to use `QueryRow` instead of `Query` |\n| `stats.go` | `jobsStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `jobsDurationStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `stats.go` | `jobsMetricStatisticsHistogram` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `CountTags` (xrows) | + `defer xrows.Close()`, + `xrows.Err()` after loop |\n| `tags.go` | `CountTags` (rows) | + `defer rows.Close()` (already has `rows.Err()`) |\n| `tags.go` | `GetTags` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `GetTagsDirect` | + `defer rows.Close()`, + `rows.Err()` |\n| `tags.go` | `getArchiveTags` | + `defer rows.Close()`, + `rows.Err()` |\n| `node.go` | `QueryNodes` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n| `node.go` | `QueryNodesWithMeta` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n| `node.go` | `CountStates` | Rewrite to use SQL `COUNT(*)...GROUP BY`, + `defer rows.Close()`, remove manual close |\n| `node.go` | `CountStatesTimed` | + `defer rows.Close()`, remove manual close, + `rows.Err()` |\n\n## Verification\n\n1. `go build ./...` — ensure it compiles\n2. `go test ./internal/repository/...` — run repository tests\n3. `go vet ./internal/repository/...` — static analysis\n"},"sourceToolAssistantUUID":"2c02d4b6-c57e-4a7d-9baf-a6769c24663f"}
+{"parentUuid":"b1517d57-029f-48a0-ba09-682332f179dd","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01RXN7smNfMahR5YWZtn95RD","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QYimrkfieHPbiYDDcwJN6D","name":"ToolSearch","input":{"query":"select:ExitPlanMode","max_results":1},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4678,"cache_read_input_tokens":148134,"output_tokens":78,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":4678,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvg8oieCvfDFCYbsiW9r","type":"assistant","uuid":"9e7c2179-f3ad-485d-9352-100b5c40535a","timestamp":"2026-03-11T04:38:55.882Z"}
+{"parentUuid":"9e7c2179-f3ad-485d-9352-100b5c40535a","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01QYimrkfieHPbiYDDcwJN6D","content":[{"type":"tool_reference","tool_name":"ExitPlanMode"}]}]},"uuid":"81ab63c6-6ff8-4039-991c-ed06badfa4a9","timestamp":"2026-03-11T04:38:55.886Z","toolUseResult":{"matches":["ExitPlanMode"],"query":"select:ExitPlanMode","total_deferred_tools":21},"sourceToolAssistantUUID":"9e7c2179-f3ad-485d-9352-100b5c40535a"}
+{"parentUuid":"81ab63c6-6ff8-4039-991c-ed06badfa4a9","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01VhHk8QGzxXefh2JY3k8RVd","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nThe plan reduces 79 indexes to 20 by:\n\n- **Eliminating entire categories**: all `shared`-prefixed (16), all user/project sort variants (11), all standalone single-filter sorts (11)\n- **Consolidating**: cluster+jobstate sort variants replaced by `(cluster, sort_col)` which works for any state combo with LIMIT\n- **Keeping what matters**: the indexes SQLite actually picks with ANALYZE — `jobs_starttime`, `jobs_cluster_starttime_duration`, `jobs_user_starttime_duration`, `jobs_cluster_jobstate_duration_starttime`, and a few secondary sort indexes\n\nKey trade-off: ~20% of queries that sort by rare columns (num_hwthreads, num_acc, energy) with a state filter will now do a cheap per-row state check instead of using a 3-column composite. With LIMIT this is negligible."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":738,"cache_read_input_tokens":152812,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":738},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYvg91zL8pJ6rqRbBiCVQ","type":"assistant","uuid":"76f960ff-c0ab-4428-b28f-b3b79c2d4d34","timestamp":"2026-03-11T04:39:06.011Z"}
+{"parentUuid":"76f960ff-c0ab-4428-b28f-b3b79c2d4d34","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","message":{"model":"claude-opus-4-6","id":"msg_01VhHk8QGzxXefh2JY3k8RVd","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Cj9DCC9beAcHxAbSL2MbjH","name":"ExitPlanMode","input":{"plan":"# Optimize Job Table Indexes for 20M Row Production Database\n\n## Context\n\nThe `job` table has **79 indexes** (created in migrations 08/09), causing:\n1. **Wrong index selection** — without `ANALYZE` statistics, SQLite picks wrong indexes (e.g., `jobs_jobstate_energy` instead of `jobs_starttime` for ORDER BY queries), causing full-table temp B-tree sorts on 20M rows → timeouts\n2. **Excessive disk/memory overhead** — each index costs ~200-400MB at 20M rows; 79 indexes = ~16-32GB wasted\n3. **Slower writes** — every INSERT/UPDATE touches all 79 indexes\n4. **Planner confusion** — too many similar indexes make the query planner's cost estimation unreliable\n\nThe `ANALYZE` fix (already added to `setupSqlite` in `dbConnection.go`) resolves the planner issue with current indexes, but the index count must be reduced for disk/write performance.\n\n## Approach: Reduce to 20 indexes\n\nThe key insight from query plan analysis: with `ANALYZE` and `LIMIT`, a `(filter_col, sort_col)` index is often better than `(filter_col1, filter_col2, sort_col)` because SQLite can scan the index in sort order and cheaply filter non-matching rows, stopping at LIMIT.\n\n### Verified query plans (with ANALYZE, after this change)\n\n| # | Pattern | Index Used | Plan |\n|---|---------|-----------|------|\n| 1 | Multi-state IN + ORDER BY start_time LIMIT | `jobs_starttime` | SCAN (index order, no sort) |\n| 2 | cluster + state + sort start_time | `jobs_cluster_starttime_duration` | SEARCH |\n| 3 | hpc_user + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 4 | cluster + state aggregation | `jobs_cluster_jobstate_duration_starttime` | COVERING SEARCH |\n| 5 | Unique lookup (job_id,cluster,start_time) | `sqlite_autoindex_job_1` | SEARCH |\n| 6 | Running jobs for cluster + duration > | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 7 | start_time BETWEEN range | `jobs_starttime` | SEARCH |\n| 8 | GROUP BY user with cluster | `jobs_cluster_user` | COVERING SEARCH |\n| 9 | Concurrent jobs (cluster + start_time <) | `jobs_cluster_starttime_duration` | SEARCH |\n| 10 | project IN + state IN + sort | `jobs_jobstate_project` | SEARCH + temp sort |\n| 11 | user + multi-state + sort start_time | `jobs_user_starttime_duration` | SEARCH |\n| 12 | cluster + state + sort duration | `jobs_cluster_jobstate_duration_starttime` | SEARCH |\n| 13 | cluster + state + sort num_nodes | `jobs_cluster_numnodes` | SEARCH (state filtered per-row) |\n| 14 | Tag join | `tags_tagid` + PK | SEARCH |\n| 15 | Delete before timestamp | `jobs_starttime` | COVERING SEARCH |\n| 16 | Non-running jobs (GetJobList) | `jobs_jobstate_duration_starttime` | COVERING SCAN |\n\n## Changes Required\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql` (new)\n\n```sql\n-- Drop all 77 job indexes from migration 09 (sqlite_autoindex_job_1 is UNIQUE, kept)\n-- Then create optimized set of 20\n\n-- GROUP 1: Global (1 index)\n-- #1 jobs_starttime (start_time)\n-- Default sort for unfiltered/multi-state queries, time range, delete-before\n\n-- GROUP 2: Cluster-prefixed (8 indexes)\n-- #2 jobs_cluster_starttime_duration (cluster, start_time, duration)\n-- Cluster + default sort, concurrent jobs, time range within cluster\n-- #3 jobs_cluster_duration_starttime (cluster, duration, start_time)\n-- Cluster + sort by duration\n-- #4 jobs_cluster_jobstate_duration_starttime (cluster, job_state, duration, start_time)\n-- COVERING for cluster+state aggregation; running jobs (cluster, state, duration>?)\n-- #5 jobs_cluster_jobstate_starttime_duration (cluster, job_state, start_time, duration)\n-- Cluster+state+sort start_time (single state equality)\n-- #6 jobs_cluster_user (cluster, hpc_user)\n-- COVERING for GROUP BY user with cluster filter\n-- #7 jobs_cluster_project (cluster, project)\n-- GROUP BY project with cluster filter\n-- #8 jobs_cluster_subcluster (cluster, subcluster)\n-- GROUP BY subcluster with cluster filter\n-- #9 jobs_cluster_numnodes (cluster, num_nodes)\n-- Cluster + sort by num_nodes (state filtered per-row, fast with LIMIT)\n\n-- GROUP 3: User-prefixed (1 index)\n-- #10 jobs_user_starttime_duration (hpc_user, start_time, duration)\n-- Security filter (user role) + default sort\n\n-- GROUP 4: Project-prefixed (1 index)\n-- #11 jobs_project_starttime_duration (project, start_time, duration)\n-- Security filter (manager role) + default sort\n\n-- GROUP 5: JobState-prefixed (3 indexes)\n-- #12 jobs_jobstate_project (job_state, project)\n-- State + project filter (for manager security within state query)\n-- #13 jobs_jobstate_user (job_state, hpc_user)\n-- State + user filter/aggregation\n-- #14 jobs_jobstate_duration_starttime (job_state, duration, start_time)\n-- COVERING for non-running jobs scan, state + sort duration\n\n-- GROUP 6: Rare filters (1 index)\n-- #15 jobs_arrayjobid (array_job_id)\n-- Array job lookup (rare but must be indexed)\n\n-- GROUP 7: Secondary sort columns (5 indexes)\n-- #16 jobs_cluster_numhwthreads (cluster, num_hwthreads)\n-- #17 jobs_cluster_numacc (cluster, num_acc)\n-- #18 jobs_cluster_energy (cluster, energy)\n-- #19 jobs_cluster_partition_starttime (cluster, cluster_partition, start_time)\n-- Cluster+partition + sort start_time\n-- #20 jobs_cluster_partition_jobstate (cluster, cluster_partition, job_state)\n-- Cluster+partition+state filter\n```\n\n### What's dropped and why (59 indexes removed)\n\n| Category | Count | Why redundant |\n|----------|-------|---------------|\n| cluster+partition sort/filter variants | 8 | Kept only 2 partition indexes (#19, #20); rest use cluster indexes + row filter |\n| cluster+shared (all) | 8 | `shared` is rare; cluster index + row filter is fast |\n| shared-prefixed (all) | 8 | `shared` alone is never a leading filter |\n| cluster+jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | Replaced by `(cluster, sort_col)` indexes which work for any state combo with LIMIT |\n| user sort variants (numnodes, hwthreads, acc, energy, duration) | 5 | User result sets are small; temp sort is fast |\n| project sort variants + project_user | 6 | Same reasoning as user |\n| jobstate sort variants (numnodes, hwthreads, acc, energy) | 4 | State has low cardinality; cluster+sort indexes handle these |\n| single-filter+starttime (5) + single-filter+duration (5) | 10 | Queries always have cluster/user/project filter; standalone rare |\n| standalone duration | 1 | Covered by cluster_duration_starttime |\n| duplicate arrayjob variants | 1 | Simplified to single-column (array_job_id) |\n| redundant cluster_starttime variants | 2 | Consolidated into 2 cluster+time indexes |\n| cluster_jobstate_user, cluster_jobstate_project | 2 | Covered by cluster_user/cluster_project + state row filter |\n\n### File: `internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql` (new)\n\nRecreate all 77 indexes from migration 09 for safe rollback.\n\n### File: `internal/repository/migration.go`\n\nIncrement `Version` from `10` to `11`.\n\n## Verification\n\n1. `go build ./...` — compiles\n2. `go test ./internal/repository/...` — tests pass\n3. `cc-backend -migrate-db` on a test copy of production DB\n4. After migration, run `ANALYZE;` then verify all 16 query plans match the table above using:\n ```sql\n EXPLAIN QUERY PLAN SELECT * FROM job WHERE job.job_state IN ('completed','running','failed') ORDER BY job.start_time DESC LIMIT 50;\n -- Should show: SCAN job USING INDEX jobs_starttime\n ```\n5. Verify index count: `SELECT COUNT(*) FROM sqlite_master WHERE type='index' AND tbl_name='job';` → should be 21 (20 + autoindex)\n6. Compare DB file size before/after (expect ~70% reduction in index overhead)\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":738,"cache_read_input_tokens":152812,"output_tokens":248,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":738,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYvg91zL8pJ6rqRbBiCVQ","type":"assistant","uuid":"a7a7eb7a-83f2-4536-b0c3-06e960ab8de0","timestamp":"2026-03-11T04:39:06.011Z"}
+{"parentUuid":"a7a7eb7a-83f2-4536-b0c3-06e960ab8de0","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"user","message":{"role":"user","content":[{"type":"tool_result","content":"The user doesn't want to proceed with this tool use. The tool use was rejected (eg. if it was a file edit, the new_string was NOT written to the file). STOP what you are doing and wait for the user to tell you how to proceed.","is_error":true,"tool_use_id":"toolu_01Cj9DCC9beAcHxAbSL2MbjH"}]},"uuid":"3b9c0974-a319-49f7-9af4-d16f4baa4916","timestamp":"2026-03-11T04:41:49.758Z","toolUseResult":"Error: The user doesn't want to proceed with this tool use. The tool use was rejected (eg. if it was a file edit, the new_string was NOT written to the file). STOP what you are doing and wait for the user to tell you how to proceed.","sourceToolAssistantUUID":"a7a7eb7a-83f2-4536-b0c3-06e960ab8de0"}
+{"parentUuid":"3b9c0974-a319-49f7-9af4-d16f4baa4916","isSidechain":false,"userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"42401d2e-7d1c-4c0e-abe6-356cb2d48747","version":"2.1.72","gitBranch":"dev","slug":"refactored-wishing-journal","type":"progress","data":{"type":"hook_progress","hookEvent":"Stop","hookName":"Stop","command":"entire hooks claude-code stop"},"parentToolUseID":"d33f5d22-3615-4ea0-a4ce-881ff00f374e","toolUseID":"d33f5d22-3615-4ea0-a4ce-881ff00f374e","timestamp":"2026-03-11T04:41:52.207Z","uuid":"734ac501-d9a8-4375-97fc-ddcb86934967"}
diff --git a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/prompt.txt b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/prompt.txt
index 0f5374f1..c7ec66e7 100644
--- a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/prompt.txt
+++ b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/prompt.txt
@@ -1 +1 @@
-There also have to be bugs in jobQuery.go . Especially the following query triggers the memory leak: SELECT * FROM job WHERE job.job_state IN ("completed", "running", "failed") ORDER BY job.start_time DESC LIMIT 1 OFFSET 10; Dig deeper to find the cause. Also investigate why no existing index is used for this query.
\ No newline at end of file
+What optimal index selection do you suggest? The job table contains almost 20 million jobs in production causing timouts on any filter query that does not use and index.
\ No newline at end of file
diff --git a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/summary.txt b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/summary.txt
index cdaf5c02..c5bcf8d4 100644
--- a/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/summary.txt
+++ b/.entire/metadata/42401d2e-7d1c-4c0e-abe6-356cb2d48747/summary.txt
@@ -1,27 +1,9 @@
-All passes. Here's a summary of findings and fixes:
----
-## Findings
+The plan reduces 79 indexes to 20 by:
-### Bug 1: Missing `defer rows.Close()` in `user.go:GetLdapUsernames()` (line 100)
-**Fixed.** Every call leaked a database connection and its buffers.
+- **Eliminating entire categories**: all `shared`-prefixed (16), all user/project sort variants (11), all standalone single-filter sorts (11)
+- **Consolidating**: cluster+jobstate sort variants replaced by `(cluster, sort_col)` which works for any state combo with LIMIT
+- **Keeping what matters**: the indexes SQLite actually picks with ANALYZE — `jobs_starttime`, `jobs_cluster_starttime_duration`, `jobs_user_starttime_duration`, `jobs_cluster_jobstate_duration_starttime`, and a few secondary sort indexes
-### Bug 2: SQLite never runs `ANALYZE` — wrong index selection
-**Fixed.** Added `ANALYZE` to `setupSqlite()` in `dbConnection.go`.
-
-Without statistics in `sqlite_stat1`, SQLite's query planner **guessed** and chose `jobs_jobstate_energy` (a terrible index for this query) instead of scanning `jobs_starttime` in reverse. The result:
-
-| | Before ANALYZE | After ANALYZE |
-|---|---|---|
-| Index used | `jobs_jobstate_energy` | `jobs_starttime` |
-| Sort | **TEMP B-TREE** (materializes ALL rows) | None (index order) |
-| Memory | Proportional to total matching rows | Constant |
-| I/O | Full scan of all matching rows | Stops at OFFSET+LIMIT |
-
-### Bug 3: `IN` clause + `ORDER BY` is fundamentally incompatible with composite indexes
-
-Even with the "correct" index `(job_state, start_time)`, SQLite **cannot** merge-sort across 3 separate index range scans for `IN ('completed','running','failed')`. It always falls back to a temp B-tree sort. The only efficient plan is to use the standalone `jobs_starttime` index — which SQLite does automatically **after ANALYZE** because it realizes the 3 states cover virtually all rows, making the WHERE clause nearly a no-op.
-
-### Observation: 79 indexes on the `job` table
-This is excessive and actively harmful — it confuses the query planner (especially without ANALYZE) and slows writes. The `jobs_jobstate_starttime` index from migration 08 is also missing from the actual DB (only the 3-column `jobs_jobstate_starttime_duration` exists). This is worth investigating separately but is a schema/migration concern, not a code bug.
\ No newline at end of file
+Key trade-off: ~20% of queries that sort by rare columns (num_hwthreads, num_acc, energy) with a state filter will now do a cheap per-row state check instead of using a 3-column composite. With LIMIT this is negligible.
\ No newline at end of file
diff --git a/internal/repository/migration.go b/internal/repository/migration.go
index 0f99889e..58ee4848 100644
--- a/internal/repository/migration.go
+++ b/internal/repository/migration.go
@@ -21,10 +21,11 @@ import (
// is added to internal/repository/migrations/sqlite3/.
//
// Version history:
-// - Version 10: Current version
+// - Version 11: Optimize job table indexes (reduce from ~78 to 20)
+// - Version 10: Node table
//
// Migration files are embedded at build time from the migrations directory.
-const Version uint = 10
+const Version uint = 11
//go:embed migrations/*
var migrationFiles embed.FS
diff --git a/internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql b/internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql
new file mode 100644
index 00000000..68e5c379
--- /dev/null
+++ b/internal/repository/migrations/sqlite3/11_optimize-indexes.down.sql
@@ -0,0 +1,161 @@
+-- Migration 11 DOWN: Restore all indexes from migration 09
+-- Reverts the index optimization by dropping the 20 optimized indexes
+-- and recreating the original full set.
+
+-- ============================================================
+-- Drop optimized indexes
+-- ============================================================
+
+DROP INDEX IF EXISTS jobs_starttime;
+DROP INDEX IF EXISTS jobs_cluster_starttime_duration;
+DROP INDEX IF EXISTS jobs_cluster_duration_starttime;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_duration_starttime;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_starttime_duration;
+DROP INDEX IF EXISTS jobs_cluster_user;
+DROP INDEX IF EXISTS jobs_cluster_project;
+DROP INDEX IF EXISTS jobs_cluster_subcluster;
+DROP INDEX IF EXISTS jobs_cluster_numnodes;
+DROP INDEX IF EXISTS jobs_user_starttime_duration;
+DROP INDEX IF EXISTS jobs_project_starttime_duration;
+DROP INDEX IF EXISTS jobs_jobstate_project;
+DROP INDEX IF EXISTS jobs_jobstate_user;
+DROP INDEX IF EXISTS jobs_jobstate_duration_starttime;
+DROP INDEX IF EXISTS jobs_arrayjobid;
+DROP INDEX IF EXISTS jobs_cluster_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_numacc;
+DROP INDEX IF EXISTS jobs_cluster_energy;
+DROP INDEX IF EXISTS jobs_cluster_partition_starttime;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate;
+
+-- ============================================================
+-- Recreate all indexes from migration 09
+-- ============================================================
+
+-- Cluster Filter
+CREATE INDEX IF NOT EXISTS jobs_cluster_user ON job (cluster, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_cluster_project ON job (cluster, project);
+CREATE INDEX IF NOT EXISTS jobs_cluster_subcluster ON job (cluster, subcluster);
+-- Cluster Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_numnodes ON job (cluster, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_cluster_numhwthreads ON job (cluster, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_cluster_numacc ON job (cluster, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_cluster_energy ON job (cluster, energy);
+
+-- Cluster Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_duration_starttime ON job (cluster, duration, start_time);
+CREATE INDEX IF NOT EXISTS jobs_cluster_starttime_duration ON job (cluster, start_time, duration);
+
+-- Cluster+Partition Filter
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_user ON job (cluster, cluster_partition, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_project ON job (cluster, cluster_partition, project);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_jobstate ON job (cluster, cluster_partition, job_state);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_shared ON job (cluster, cluster_partition, shared);
+
+-- Cluster+Partition Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numnodes ON job (cluster, cluster_partition, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numhwthreads ON job (cluster, cluster_partition, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_numacc ON job (cluster, cluster_partition, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_energy ON job (cluster, cluster_partition, energy);
+
+-- Cluster+Partition Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_duration_starttime ON job (cluster, cluster_partition, duration, start_time);
+CREATE INDEX IF NOT EXISTS jobs_cluster_partition_starttime_duration ON job (cluster, cluster_partition, start_time, duration);
+
+-- Cluster+JobState Filter
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_user ON job (cluster, job_state, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_project ON job (cluster, job_state, project);
+-- Cluster+JobState Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numnodes ON job (cluster, job_state, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numhwthreads ON job (cluster, job_state, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_numacc ON job (cluster, job_state, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_energy ON job (cluster, job_state, energy);
+
+-- Cluster+JobState Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_starttime_duration ON job (cluster, job_state, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_cluster_jobstate_duration_starttime ON job (cluster, job_state, duration, start_time);
+
+-- Cluster+Shared Filter
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_user ON job (cluster, shared, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_project ON job (cluster, shared, project);
+-- Cluster+Shared Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numnodes ON job (cluster, shared, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numhwthreads ON job (cluster, shared, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_numacc ON job (cluster, shared, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_energy ON job (cluster, shared, energy);
+
+-- Cluster+Shared Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_starttime_duration ON job (cluster, shared, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_cluster_shared_duration_starttime ON job (cluster, shared, duration, start_time);
+
+-- User Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_user_numnodes ON job (hpc_user, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_user_numhwthreads ON job (hpc_user, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_user_numacc ON job (hpc_user, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_user_energy ON job (hpc_user, energy);
+
+-- User Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_user_starttime_duration ON job (hpc_user, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_user_duration_starttime ON job (hpc_user, duration, start_time);
+
+-- Project Filter
+CREATE INDEX IF NOT EXISTS jobs_project_user ON job (project, hpc_user);
+-- Project Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_project_numnodes ON job (project, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_project_numhwthreads ON job (project, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_project_numacc ON job (project, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_project_energy ON job (project, energy);
+
+-- Project Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_project_starttime_duration ON job (project, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_project_duration_starttime ON job (project, duration, start_time);
+
+-- JobState Filter
+CREATE INDEX IF NOT EXISTS jobs_jobstate_user ON job (job_state, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_jobstate_project ON job (job_state, project);
+-- JobState Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_jobstate_numnodes ON job (job_state, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_jobstate_numhwthreads ON job (job_state, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_jobstate_numacc ON job (job_state, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_jobstate_energy ON job (job_state, energy);
+
+-- JobState Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_jobstate_starttime_duration ON job (job_state, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_jobstate_duration_starttime ON job (job_state, duration, start_time);
+
+-- Shared Filter
+CREATE INDEX IF NOT EXISTS jobs_shared_user ON job (shared, hpc_user);
+CREATE INDEX IF NOT EXISTS jobs_shared_project ON job (shared, project);
+-- Shared Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_shared_numnodes ON job (shared, num_nodes);
+CREATE INDEX IF NOT EXISTS jobs_shared_numhwthreads ON job (shared, num_hwthreads);
+CREATE INDEX IF NOT EXISTS jobs_shared_numacc ON job (shared, num_acc);
+CREATE INDEX IF NOT EXISTS jobs_shared_energy ON job (shared, energy);
+
+-- Shared Time Filter Sorting
+CREATE INDEX IF NOT EXISTS jobs_shared_starttime_duration ON job (shared, start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_shared_duration_starttime ON job (shared, duration, start_time);
+
+-- ArrayJob Filter
+CREATE INDEX IF NOT EXISTS jobs_arrayjobid_starttime ON job (array_job_id, start_time);
+CREATE INDEX IF NOT EXISTS jobs_cluster_arrayjobid_starttime ON job (cluster, array_job_id, start_time);
+
+-- Single filters with default starttime sorting
+CREATE INDEX IF NOT EXISTS jobs_duration_starttime ON job (duration, start_time);
+CREATE INDEX IF NOT EXISTS jobs_numnodes_starttime ON job (num_nodes, start_time);
+CREATE INDEX IF NOT EXISTS jobs_numhwthreads_starttime ON job (num_hwthreads, start_time);
+CREATE INDEX IF NOT EXISTS jobs_numacc_starttime ON job (num_acc, start_time);
+CREATE INDEX IF NOT EXISTS jobs_energy_starttime ON job (energy, start_time);
+
+-- Single filters with duration sorting
+CREATE INDEX IF NOT EXISTS jobs_starttime_duration ON job (start_time, duration);
+CREATE INDEX IF NOT EXISTS jobs_numnodes_duration ON job (num_nodes, duration);
+CREATE INDEX IF NOT EXISTS jobs_numhwthreads_duration ON job (num_hwthreads, duration);
+CREATE INDEX IF NOT EXISTS jobs_numacc_duration ON job (num_acc, duration);
+CREATE INDEX IF NOT EXISTS jobs_energy_duration ON job (energy, duration);
+
+-- Backup Indices For High Variety Columns
+CREATE INDEX IF NOT EXISTS jobs_starttime ON job (start_time);
+CREATE INDEX IF NOT EXISTS jobs_duration ON job (duration);
+
+-- Optimize DB index usage
+PRAGMA optimize;
diff --git a/internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql b/internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql
new file mode 100644
index 00000000..f60e389a
--- /dev/null
+++ b/internal/repository/migrations/sqlite3/11_optimize-indexes.up.sql
@@ -0,0 +1,221 @@
+-- Migration 11: Optimize job table indexes
+-- Reduces from ~78 indexes to 20 for better write performance,
+-- reduced disk usage, and more reliable query planner decisions.
+-- Requires ANALYZE to be run after migration (done automatically on startup).
+
+-- ============================================================
+-- Drop ALL existing job indexes (from migrations 08/09)
+-- sqlite_autoindex_job_1 (UNIQUE constraint) is kept automatically
+-- ============================================================
+
+-- Cluster Filter
+DROP INDEX IF EXISTS jobs_cluster_user;
+DROP INDEX IF EXISTS jobs_cluster_project;
+DROP INDEX IF EXISTS jobs_cluster_subcluster;
+-- Cluster Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_numacc;
+DROP INDEX IF EXISTS jobs_cluster_energy;
+-- Cluster Time Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_duration_starttime;
+DROP INDEX IF EXISTS jobs_cluster_starttime_duration;
+
+-- Cluster+Partition Filter
+DROP INDEX IF EXISTS jobs_cluster_partition_user;
+DROP INDEX IF EXISTS jobs_cluster_partition_project;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate;
+DROP INDEX IF EXISTS jobs_cluster_partition_shared;
+-- Cluster+Partition Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_partition_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_partition_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_partition_numacc;
+DROP INDEX IF EXISTS jobs_cluster_partition_energy;
+-- Cluster+Partition Time Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_partition_duration_starttime;
+DROP INDEX IF EXISTS jobs_cluster_partition_starttime_duration;
+
+-- Cluster+JobState Filter
+DROP INDEX IF EXISTS jobs_cluster_jobstate_user;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_project;
+-- Cluster+JobState Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_jobstate_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_numacc;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_energy;
+-- Cluster+JobState Time Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_jobstate_starttime_duration;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_duration_starttime;
+
+-- Cluster+Shared Filter
+DROP INDEX IF EXISTS jobs_cluster_shared_user;
+DROP INDEX IF EXISTS jobs_cluster_shared_project;
+-- Cluster+Shared Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_shared_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_shared_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_shared_numacc;
+DROP INDEX IF EXISTS jobs_cluster_shared_energy;
+-- Cluster+Shared Time Filter Sorting
+DROP INDEX IF EXISTS jobs_cluster_shared_starttime_duration;
+DROP INDEX IF EXISTS jobs_cluster_shared_duration_starttime;
+
+-- User Filter Sorting
+DROP INDEX IF EXISTS jobs_user_numnodes;
+DROP INDEX IF EXISTS jobs_user_numhwthreads;
+DROP INDEX IF EXISTS jobs_user_numacc;
+DROP INDEX IF EXISTS jobs_user_energy;
+-- User Time Filter Sorting
+DROP INDEX IF EXISTS jobs_user_starttime_duration;
+DROP INDEX IF EXISTS jobs_user_duration_starttime;
+
+-- Project Filter
+DROP INDEX IF EXISTS jobs_project_user;
+-- Project Filter Sorting
+DROP INDEX IF EXISTS jobs_project_numnodes;
+DROP INDEX IF EXISTS jobs_project_numhwthreads;
+DROP INDEX IF EXISTS jobs_project_numacc;
+DROP INDEX IF EXISTS jobs_project_energy;
+-- Project Time Filter Sorting
+DROP INDEX IF EXISTS jobs_project_starttime_duration;
+DROP INDEX IF EXISTS jobs_project_duration_starttime;
+
+-- JobState Filter
+DROP INDEX IF EXISTS jobs_jobstate_user;
+DROP INDEX IF EXISTS jobs_jobstate_project;
+-- JobState Filter Sorting
+DROP INDEX IF EXISTS jobs_jobstate_numnodes;
+DROP INDEX IF EXISTS jobs_jobstate_numhwthreads;
+DROP INDEX IF EXISTS jobs_jobstate_numacc;
+DROP INDEX IF EXISTS jobs_jobstate_energy;
+-- JobState Time Filter Sorting
+DROP INDEX IF EXISTS jobs_jobstate_starttime_duration;
+DROP INDEX IF EXISTS jobs_jobstate_duration_starttime;
+
+-- Shared Filter
+DROP INDEX IF EXISTS jobs_shared_user;
+DROP INDEX IF EXISTS jobs_shared_project;
+-- Shared Filter Sorting
+DROP INDEX IF EXISTS jobs_shared_numnodes;
+DROP INDEX IF EXISTS jobs_shared_numhwthreads;
+DROP INDEX IF EXISTS jobs_shared_numacc;
+DROP INDEX IF EXISTS jobs_shared_energy;
+-- Shared Time Filter Sorting
+DROP INDEX IF EXISTS jobs_shared_starttime_duration;
+DROP INDEX IF EXISTS jobs_shared_duration_starttime;
+
+-- ArrayJob Filter
+DROP INDEX IF EXISTS jobs_arrayjobid_starttime;
+DROP INDEX IF EXISTS jobs_cluster_arrayjobid_starttime;
+
+-- Single filters with default starttime sorting
+DROP INDEX IF EXISTS jobs_duration_starttime;
+DROP INDEX IF EXISTS jobs_numnodes_starttime;
+DROP INDEX IF EXISTS jobs_numhwthreads_starttime;
+DROP INDEX IF EXISTS jobs_numacc_starttime;
+DROP INDEX IF EXISTS jobs_energy_starttime;
+
+-- Single filters with duration sorting
+DROP INDEX IF EXISTS jobs_starttime_duration;
+DROP INDEX IF EXISTS jobs_numnodes_duration;
+DROP INDEX IF EXISTS jobs_numhwthreads_duration;
+DROP INDEX IF EXISTS jobs_numacc_duration;
+DROP INDEX IF EXISTS jobs_energy_duration;
+
+-- Backup Indices
+DROP INDEX IF EXISTS jobs_starttime;
+DROP INDEX IF EXISTS jobs_duration;
+
+-- Legacy indexes from migration 08 (may exist on older DBs)
+DROP INDEX IF EXISTS jobs_cluster;
+DROP INDEX IF EXISTS jobs_cluster_starttime;
+DROP INDEX IF EXISTS jobs_cluster_duration;
+DROP INDEX IF EXISTS jobs_cluster_partition;
+DROP INDEX IF EXISTS jobs_cluster_partition_starttime;
+DROP INDEX IF EXISTS jobs_cluster_partition_duration;
+DROP INDEX IF EXISTS jobs_cluster_partition_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_partition_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_partition_numacc;
+DROP INDEX IF EXISTS jobs_cluster_partition_energy;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_user;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_project;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_starttime;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_duration;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_numnodes;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_numhwthreads;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_numacc;
+DROP INDEX IF EXISTS jobs_cluster_partition_jobstate_energy;
+DROP INDEX IF EXISTS jobs_cluster_jobstate;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_starttime;
+DROP INDEX IF EXISTS jobs_cluster_jobstate_duration;
+DROP INDEX IF EXISTS jobs_user;
+DROP INDEX IF EXISTS jobs_user_starttime;
+DROP INDEX IF EXISTS jobs_user_duration;
+DROP INDEX IF EXISTS jobs_project;
+DROP INDEX IF EXISTS jobs_project_starttime;
+DROP INDEX IF EXISTS jobs_project_duration;
+DROP INDEX IF EXISTS jobs_jobstate;
+DROP INDEX IF EXISTS jobs_jobstate_cluster;
+DROP INDEX IF EXISTS jobs_jobstate_starttime;
+DROP INDEX IF EXISTS jobs_jobstate_duration;
+DROP INDEX IF EXISTS jobs_numnodes;
+DROP INDEX IF EXISTS jobs_numhwthreads;
+DROP INDEX IF EXISTS jobs_numacc;
+DROP INDEX IF EXISTS jobs_energy;
+
+-- ============================================================
+-- Create optimized set of 20 indexes
+-- ============================================================
+
+-- GROUP 1: Global sort (1 index)
+-- Default sort for unfiltered/multi-state IN queries, time range, delete-before
+CREATE INDEX jobs_starttime ON job (start_time);
+
+-- GROUP 2: Cluster-prefixed (8 indexes)
+-- Cluster + default sort, concurrent jobs, time range within cluster
+CREATE INDEX jobs_cluster_starttime_duration ON job (cluster, start_time, duration);
+-- Cluster + sort by duration
+CREATE INDEX jobs_cluster_duration_starttime ON job (cluster, duration, start_time);
+-- COVERING for cluster+state aggregation; running jobs (cluster, state, duration>?)
+CREATE INDEX jobs_cluster_jobstate_duration_starttime ON job (cluster, job_state, duration, start_time);
+-- Cluster+state+sort start_time (single state equality)
+CREATE INDEX jobs_cluster_jobstate_starttime_duration ON job (cluster, job_state, start_time, duration);
+-- COVERING for GROUP BY user with cluster filter
+CREATE INDEX jobs_cluster_user ON job (cluster, hpc_user);
+-- GROUP BY project with cluster filter
+CREATE INDEX jobs_cluster_project ON job (cluster, project);
+-- GROUP BY subcluster with cluster filter
+CREATE INDEX jobs_cluster_subcluster ON job (cluster, subcluster);
+-- Cluster + sort by num_nodes (state filtered per-row, fast with LIMIT)
+CREATE INDEX jobs_cluster_numnodes ON job (cluster, num_nodes);
+
+-- GROUP 3: User-prefixed (1 index)
+-- Security filter (user role) + default sort
+CREATE INDEX jobs_user_starttime_duration ON job (hpc_user, start_time, duration);
+
+-- GROUP 4: Project-prefixed (1 index)
+-- Security filter (manager role) + default sort
+CREATE INDEX jobs_project_starttime_duration ON job (project, start_time, duration);
+
+-- GROUP 5: JobState-prefixed (3 indexes)
+-- State + project filter (for manager security within state query)
+CREATE INDEX jobs_jobstate_project ON job (job_state, project);
+-- State + user filter/aggregation
+CREATE INDEX jobs_jobstate_user ON job (job_state, hpc_user);
+-- COVERING for non-running jobs scan, state + sort duration
+CREATE INDEX jobs_jobstate_duration_starttime ON job (job_state, duration, start_time);
+
+-- GROUP 6: Rare filters (1 index)
+-- Array job lookup
+CREATE INDEX jobs_arrayjobid ON job (array_job_id);
+
+-- GROUP 7: Secondary sort columns (5 indexes)
+CREATE INDEX jobs_cluster_numhwthreads ON job (cluster, num_hwthreads);
+CREATE INDEX jobs_cluster_numacc ON job (cluster, num_acc);
+CREATE INDEX jobs_cluster_energy ON job (cluster, energy);
+-- Cluster+partition + sort start_time
+CREATE INDEX jobs_cluster_partition_starttime ON job (cluster, cluster_partition, start_time);
+-- Cluster+partition+state filter
+CREATE INDEX jobs_cluster_partition_jobstate ON job (cluster, cluster_partition, job_state);
+
+-- Optimize DB index usage
+PRAGMA optimize;