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1abea621e5920ccbcd53e68fe033fb866b59fe4d
cc-backend/16/60b8cf2571/1/full.jsonl
Jan Eitzinger 1abea621e5 Checkpoint: 1660b8cf2571 
Entire-Session: 94e2d90e-5772-4423-a4fb-75c7caa1e1c4
Entire-Strategy: manual-commit
Entire-Agent: Claude Code
Ephemeral-branch: entire/01ec70b-e3b0c4
2026-03-23 06:32:24 +01:00

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{"parentUuid":"bec7693a-5cd8-40e4-b518-06a267f27113","isSidechain":false,"promptId":"4c9038e2-c763-4f23-82bf-037c28776776","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WuCWv5d37WtYT5LQDEqiFX","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 metricstore\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"errors\"\n 11→\t\"fmt\"\n 12→\t\"os\"\n 13→\t\"path/filepath\"\n 14→\t\"sync\"\n 15→\t\"sync/atomic\"\n 16→\t\"time\"\n 17→\n 18→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 19→)\n 20→\n 21→// Worker for either Archiving or Deleting files\n 22→\n 23→func CleanUp(wg *sync.WaitGroup, ctx context.Context) {\n 24→\tif Keys.Cleanup.Mode == \"archive\" {\n 25→\t\tcclog.Info(\"[METRICSTORE]> enable archive cleanup to parquet\")\n 26→\t\t// Run as Archiver\n 27→\t\tcleanUpWorker(wg, ctx,\n 28→\t\t\tKeys.RetentionInMemory,\n 29→\t\t\t\"archiving\",\n 30→\t\t\tKeys.Cleanup.RootDir,\n 31→\t\t\tfalse,\n 32→\t\t)\n 33→\t} else {\n 34→\t\t// Run as Deleter\n 35→\t\tcleanUpWorker(wg, ctx,\n 36→\t\t\tKeys.RetentionInMemory,\n 37→\t\t\t\"deleting\",\n 38→\t\t\t\"\",\n 39→\t\t\ttrue,\n 40→\t\t)\n 41→\t}\n 42→}\n 43→\n 44→// cleanUpWorker takes simple values to configure what it does\n 45→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n 46→\twg.Go(func() {\n 47→\t\td, err := time.ParseDuration(interval)\n 48→\t\tif err != nil {\n 49→\t\t\tcclog.Fatalf(\"[METRICSTORE]> error parsing %s interval duration: %v\\n\", mode, err)\n 50→\t\t}\n 51→\t\tif d <= 0 {\n 52→\t\t\treturn\n 53→\t\t}\n 54→\n 55→\t\tticker := time.NewTicker(d)\n 56→\t\tdefer ticker.Stop()\n 57→\n 58→\t\tfor {\n 59→\t\t\tselect {\n 60→\t\t\tcase <-ctx.Done():\n 61→\t\t\t\treturn\n 62→\t\t\tcase <-ticker.C:\n 63→\t\t\t\tt := time.Now().Add(-d)\n 64→\t\t\t\tcclog.Infof(\"[METRICSTORE]> start %s checkpoints (older than %s)...\", mode, t.Format(time.RFC3339))\n 65→\n 66→\t\t\t\tn, err := CleanupCheckpoints(Keys.Checkpoints.RootDir, cleanupDir, t.Unix(), delete)\n 67→\n 68→\t\t\t\tif err != nil {\n 69→\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> %s failed: %s\", mode, err.Error())\n 70→\t\t\t\t} else {\n 71→\t\t\t\t\tif delete {\n 72→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoints deleted\", n)\n 73→\t\t\t\t\t} else {\n 74→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoint files archived to parquet\", n)\n 75→\t\t\t\t\t}\n 76→\t\t\t\t}\n 77→\t\t\t}\n 78→\t\t}\n 79→\t})\n 80→}\n 81→\n 82→var ErrNoNewArchiveData error = errors.New(\"all data already archived\")\n 83→\n 84→// CleanupCheckpoints deletes or archives all checkpoint files older than `from`.\n 85→// When archiving, consolidates all hosts per cluster into a single Parquet file.\n 86→func CleanupCheckpoints(checkpointsDir, cleanupDir string, from int64, deleteInstead bool) (int, error) {\n 87→\tif deleteInstead {\n 88→\t\treturn deleteCheckpoints(checkpointsDir, from)\n 89→\t}\n 90→\n 91→\treturn archiveCheckpoints(checkpointsDir, cleanupDir, from)\n 92→}\n 93→\n 94→// deleteCheckpoints removes checkpoint files older than `from` across all clusters/hosts.\n 95→func deleteCheckpoints(checkpointsDir string, from int64) (int, error) {\n 96→\tentries1, err := os.ReadDir(checkpointsDir)\n 97→\tif err != nil {\n 98→\t\treturn 0, err\n 99→\t}\n 100→\n 101→\ttype workItem struct {\n 102→\t\tdir string\n 103→\t\tcluster, host string\n 104→\t}\n 105→\n 106→\tvar wg sync.WaitGroup\n 107→\tn, errs := int32(0), int32(0)\n 108→\twork := make(chan workItem, Keys.NumWorkers)\n 109→\n 110→\twg.Add(Keys.NumWorkers)\n 111→\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n 112→\t\tgo func() {\n 113→\t\t\tdefer wg.Done()\n 114→\t\t\tfor item := range work {\n 115→\t\t\t\tentries, err := os.ReadDir(item.dir)\n 116→\t\t\t\tif err != nil {\n 117→\t\t\t\t\tcclog.Errorf(\"error reading %s/%s: %s\", item.cluster, item.host, err.Error())\n 118→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 119→\t\t\t\t\tcontinue\n 120→\t\t\t\t}\n 121→\n 122→\t\t\t\tfiles, err := findFiles(entries, from, false)\n 123→\t\t\t\tif err != nil {\n 124→\t\t\t\t\tcclog.Errorf(\"error finding files in %s/%s: %s\", item.cluster, item.host, err.Error())\n 125→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 126→\t\t\t\t\tcontinue\n 127→\t\t\t\t}\n 128→\n 129→\t\t\t\tfor _, checkpoint := range files {\n 130→\t\t\t\t\tif err := os.Remove(filepath.Join(item.dir, checkpoint)); err != nil {\n 131→\t\t\t\t\t\tcclog.Errorf(\"error deleting %s/%s/%s: %s\", item.cluster, item.host, checkpoint, err.Error())\n 132→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 133→\t\t\t\t\t} else {\n 134→\t\t\t\t\t\tatomic.AddInt32(&n, 1)\n 135→\t\t\t\t\t}\n 136→\t\t\t\t}\n 137→\t\t\t}\n 138→\t\t}()\n 139→\t}\n 140→\n 141→\tfor _, de1 := range entries1 {\n 142→\t\tentries2, e := os.ReadDir(filepath.Join(checkpointsDir, de1.Name()))\n 143→\t\tif e != nil {\n 144→\t\t\terr = e\n 145→\t\t\tcontinue\n 146→\t\t}\n 147→\n 148→\t\tfor _, de2 := range entries2 {\n 149→\t\t\twork <- workItem{\n 150→\t\t\t\tdir: filepath.Join(checkpointsDir, de1.Name(), de2.Name()),\n 151→\t\t\t\tcluster: de1.Name(),\n 152→\t\t\t\thost: de2.Name(),\n 153→\t\t\t}\n 154→\t\t}\n 155→\t}\n 156→\n 157→\tclose(work)\n 158→\twg.Wait()\n 159→\n 160→\tif err != nil {\n 161→\t\treturn int(n), err\n 162→\t}\n 163→\tif errs > 0 {\n 164→\t\treturn int(n), fmt.Errorf(\"%d errors happened while deleting (%d successes)\", errs, n)\n 165→\t}\n 166→\treturn int(n), nil\n 167→}\n 168→\n 169→// archiveCheckpoints archives checkpoint files to Parquet format.\n 170→// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n 171→// Workers load checkpoint files from disk and send CheckpointFile trees on a\n 172→// back-pressured channel. The main thread streams each tree directly to Parquet\n 173→// rows without materializing all rows in memory.\n 174→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n 175→\tcclog.Info(\"[METRICSTORE]> start archiving checkpoints to parquet\")\n 176→\tstartTime := time.Now()\n 177→\n 178→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n 179→\tif err != nil {\n 180→\t\treturn 0, err\n 181→\t}\n 182→\n 183→\ttotalFiles := 0\n 184→\n 185→\tfor _, clusterEntry := range clusterEntries {\n 186→\t\tif !clusterEntry.IsDir() {\n 187→\t\t\tcontinue\n 188→\t\t}\n 189→\n 190→\t\tcluster := clusterEntry.Name()\n 191→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n 192→\t\tif err != nil {\n 193→\t\t\treturn totalFiles, err\n 194→\t\t}\n 195→\n 196→\t\t// Workers load checkpoint files from disk; main thread writes to parquet.\n 197→\t\ttype hostResult struct {\n 198→\t\t\tcheckpoints []*CheckpointFile\n 199→\t\t\thostname string\n 200→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n 201→\t\t\tdir string // checkpoint directory for this host\n 202→\t\t}\n 203→\n 204→\t\t// Small buffer provides back-pressure: at most NumWorkers+2 results in flight.\n 205→\t\tresults := make(chan hostResult, 2)\n 206→\t\twork := make(chan struct {\n 207→\t\t\tdir, host string\n 208→\t\t}, Keys.NumWorkers)\n 209→\n 210→\t\tvar wg sync.WaitGroup\n 211→\t\terrs := int32(0)\n 212→\n 213→\t\twg.Add(Keys.NumWorkers)\n 214→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n 215→\t\t\tgo func() {\n 216→\t\t\t\tdefer wg.Done()\n 217→\t\t\t\tfor item := range work {\n 218→\t\t\t\t\tcheckpoints, files, err := loadCheckpointFiles(item.dir, from)\n 219→\t\t\t\t\tif err != nil {\n 220→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n 221→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 222→\t\t\t\t\t\tcontinue\n 223→\t\t\t\t\t}\n 224→\t\t\t\t\tif len(checkpoints) > 0 {\n 225→\t\t\t\t\t\tresults <- hostResult{\n 226→\t\t\t\t\t\t\tcheckpoints: checkpoints,\n 227→\t\t\t\t\t\t\thostname: item.host,\n 228→\t\t\t\t\t\t\tfiles: files,\n 229→\t\t\t\t\t\t\tdir: item.dir,\n 230→\t\t\t\t\t\t}\n 231→\t\t\t\t\t}\n 232→\t\t\t\t}\n 233→\t\t\t}()\n 234→\t\t}\n 235→\n 236→\t\tgo func() {\n 237→\t\t\tfor _, hostEntry := range hostEntries {\n 238→\t\t\t\tif !hostEntry.IsDir() {\n 239→\t\t\t\t\tcontinue\n 240→\t\t\t\t}\n 241→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n 242→\t\t\t\twork <- struct {\n 243→\t\t\t\t\tdir, host string\n 244→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n 245→\t\t\t}\n 246→\t\t\tclose(work)\n 247→\t\t\twg.Wait()\n 248→\t\t\tclose(results)\n 249→\t\t}()\n 250→\n 251→\t\t// Open streaming writer and write each host's checkpoint files as a row group\n 252→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n 253→\t\twriter, err := newParquetArchiveWriter(parquetFile)\n 254→\t\tif err != nil {\n 255→\t\t\t// Drain results channel to unblock workers\n 256→\t\t\tfor range results {\n 257→\t\t\t}\n 258→\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n 259→\t\t}\n 260→\n 261→\t\ttype deleteItem struct {\n 262→\t\t\tdir string\n 263→\t\t\tfiles []string\n 264→\t\t}\n 265→\t\tvar toDelete []deleteItem\n 266→\t\twriteErr := error(nil)\n 267→\n 268→\t\tfor r := range results {\n 269→\t\t\tif writeErr == nil {\n 270→\t\t\t\t// Stream each checkpoint file directly to parquet rows.\n 271→\t\t\t\t// Each checkpoint is processed and discarded before the next.\n 272→\t\t\t\tfor _, cf := range r.checkpoints {\n 273→\t\t\t\t\tif err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n 274→\t\t\t\t\t\twriteErr = err\n 275→\t\t\t\t\t\tbreak\n 276→\t\t\t\t\t}\n 277→\t\t\t\t}\n 278→\t\t\t}\n 279→\t\t\t// Always track files for deletion (even if write failed, we still drain)\n 280→\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n 281→\t\t}\n 282→\n 283→\t\tif err := writer.Close(); err != nil && writeErr == nil {\n 284→\t\t\twriteErr = err\n 285→\t\t}\n 286→\n 287→\t\tif errs > 0 {\n 288→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n 289→\t\t}\n 290→\n 291→\t\tif writer.count == 0 {\n 292→\t\t\t// No data written — remove empty file\n 293→\t\t\tos.Remove(parquetFile)\n 294→\t\t\tcontinue\n 295→\t\t}\n 296→\n 297→\t\tif writeErr != nil {\n 298→\t\t\tos.Remove(parquetFile)\n 299→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n 300→\t\t}\n 301→\n 302→\t\t// Delete archived checkpoint files\n 303→\t\tfor _, item := range toDelete {\n 304→\t\t\tfor _, file := range item.files {\n 305→\t\t\t\tfilename := filepath.Join(item.dir, file)\n 306→\t\t\t\tif err := os.Remove(filename); err != nil {\n 307→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n 308→\t\t\t\t} else {\n 309→\t\t\t\t\ttotalFiles++\n 310→\t\t\t\t}\n 311→\t\t\t}\n 312→\t\t}\n 313→\n 314→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n 315→\t\t\twriter.count, totalFiles, cluster, parquetFile)\n 316→\t}\n 317→\n 318→\tcclog.Infof(\"[METRICSTORE]> archiving checkpoints completed in %s (%d files)\", time.Since(startTime).Round(time.Millisecond), totalFiles)\n 319→\treturn totalFiles, nil\n 320→}\n 321→"}]},"uuid":"6a4aebd9-219e-4218-b486-e4a805130127","timestamp":"2026-03-23T05:10:07.464Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage metricstore\n\nimport (\n\t\"context\"\n\t\"errors\"\n\t\"fmt\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"sync\"\n\t\"sync/atomic\"\n\t\"time\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n)\n\n// Worker for either Archiving or Deleting files\n\nfunc CleanUp(wg *sync.WaitGroup, ctx context.Context) {\n\tif Keys.Cleanup.Mode == \"archive\" {\n\t\tcclog.Info(\"[METRICSTORE]> enable archive cleanup to parquet\")\n\t\t// Run as Archiver\n\t\tcleanUpWorker(wg, ctx,\n\t\t\tKeys.RetentionInMemory,\n\t\t\t\"archiving\",\n\t\t\tKeys.Cleanup.RootDir,\n\t\t\tfalse,\n\t\t)\n\t} else {\n\t\t// Run as Deleter\n\t\tcleanUpWorker(wg, ctx,\n\t\t\tKeys.RetentionInMemory,\n\t\t\t\"deleting\",\n\t\t\t\"\",\n\t\t\ttrue,\n\t\t)\n\t}\n}\n\n// cleanUpWorker takes simple values to configure what it does\nfunc cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n\twg.Go(func() {\n\t\td, err := time.ParseDuration(interval)\n\t\tif err != nil {\n\t\t\tcclog.Fatalf(\"[METRICSTORE]> error parsing %s interval duration: %v\\n\", mode, err)\n\t\t}\n\t\tif d <= 0 {\n\t\t\treturn\n\t\t}\n\n\t\tticker := time.NewTicker(d)\n\t\tdefer ticker.Stop()\n\n\t\tfor {\n\t\t\tselect {\n\t\t\tcase <-ctx.Done():\n\t\t\t\treturn\n\t\t\tcase <-ticker.C:\n\t\t\t\tt := time.Now().Add(-d)\n\t\t\t\tcclog.Infof(\"[METRICSTORE]> start %s checkpoints (older than %s)...\", mode, t.Format(time.RFC3339))\n\n\t\t\t\tn, err := CleanupCheckpoints(Keys.Checkpoints.RootDir, cleanupDir, t.Unix(), delete)\n\n\t\t\t\tif err != nil {\n\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> %s failed: %s\", mode, err.Error())\n\t\t\t\t} else {\n\t\t\t\t\tif delete {\n\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoints deleted\", n)\n\t\t\t\t\t} else {\n\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoint files archived to parquet\", n)\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t})\n}\n\nvar ErrNoNewArchiveData error = errors.New(\"all data already archived\")\n\n// CleanupCheckpoints deletes or archives all checkpoint files older than `from`.\n// When archiving, consolidates all hosts per cluster into a single Parquet file.\nfunc CleanupCheckpoints(checkpointsDir, cleanupDir string, from int64, deleteInstead bool) (int, error) {\n\tif deleteInstead {\n\t\treturn deleteCheckpoints(checkpointsDir, from)\n\t}\n\n\treturn archiveCheckpoints(checkpointsDir, cleanupDir, from)\n}\n\n// deleteCheckpoints removes checkpoint files older than `from` across all clusters/hosts.\nfunc deleteCheckpoints(checkpointsDir string, from int64) (int, error) {\n\tentries1, err := os.ReadDir(checkpointsDir)\n\tif err != nil {\n\t\treturn 0, err\n\t}\n\n\ttype workItem struct {\n\t\tdir string\n\t\tcluster, host string\n\t}\n\n\tvar wg sync.WaitGroup\n\tn, errs := int32(0), int32(0)\n\twork := make(chan workItem, Keys.NumWorkers)\n\n\twg.Add(Keys.NumWorkers)\n\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n\t\tgo func() {\n\t\t\tdefer wg.Done()\n\t\t\tfor item := range work {\n\t\t\t\tentries, err := os.ReadDir(item.dir)\n\t\t\t\tif err != nil {\n\t\t\t\t\tcclog.Errorf(\"error reading %s/%s: %s\", item.cluster, item.host, err.Error())\n\t\t\t\t\tatomic.AddInt32(&errs, 1)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tfiles, err := findFiles(entries, from, false)\n\t\t\t\tif err != nil {\n\t\t\t\t\tcclog.Errorf(\"error finding files in %s/%s: %s\", item.cluster, item.host, err.Error())\n\t\t\t\t\tatomic.AddInt32(&errs, 1)\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\n\t\t\t\tfor _, checkpoint := range files {\n\t\t\t\t\tif err := os.Remove(filepath.Join(item.dir, checkpoint)); err != nil {\n\t\t\t\t\t\tcclog.Errorf(\"error deleting %s/%s/%s: %s\", item.cluster, item.host, checkpoint, err.Error())\n\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n\t\t\t\t\t} else {\n\t\t\t\t\t\tatomic.AddInt32(&n, 1)\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}()\n\t}\n\n\tfor _, de1 := range entries1 {\n\t\tentries2, e := os.ReadDir(filepath.Join(checkpointsDir, de1.Name()))\n\t\tif e != nil {\n\t\t\terr = e\n\t\t\tcontinue\n\t\t}\n\n\t\tfor _, de2 := range entries2 {\n\t\t\twork <- workItem{\n\t\t\t\tdir: filepath.Join(checkpointsDir, de1.Name(), de2.Name()),\n\t\t\t\tcluster: de1.Name(),\n\t\t\t\thost: de2.Name(),\n\t\t\t}\n\t\t}\n\t}\n\n\tclose(work)\n\twg.Wait()\n\n\tif err != nil {\n\t\treturn int(n), err\n\t}\n\tif errs > 0 {\n\t\treturn int(n), fmt.Errorf(\"%d errors happened while deleting (%d successes)\", errs, n)\n\t}\n\treturn int(n), nil\n}\n\n// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n// Workers load checkpoint files from disk and send CheckpointFile trees on a\n// back-pressured channel. The main thread streams each tree directly to Parquet\n// rows without materializing all rows in memory.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n\tcclog.Info(\"[METRICSTORE]> start archiving checkpoints to parquet\")\n\tstartTime := time.Now()\n\n\tclusterEntries, err := os.ReadDir(checkpointsDir)\n\tif err != nil {\n\t\treturn 0, err\n\t}\n\n\ttotalFiles := 0\n\n\tfor _, clusterEntry := range clusterEntries {\n\t\tif !clusterEntry.IsDir() {\n\t\t\tcontinue\n\t\t}\n\n\t\tcluster := clusterEntry.Name()\n\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n\t\tif err != nil {\n\t\t\treturn totalFiles, err\n\t\t}\n\n\t\t// Workers load checkpoint files from disk; main thread writes to parquet.\n\t\ttype hostResult struct {\n\t\t\tcheckpoints []*CheckpointFile\n\t\t\thostname string\n\t\t\tfiles []string // checkpoint filenames to delete after successful write\n\t\t\tdir string // checkpoint directory for this host\n\t\t}\n\n\t\t// Small buffer provides back-pressure: at most NumWorkers+2 results in flight.\n\t\tresults := make(chan hostResult, 2)\n\t\twork := make(chan struct {\n\t\t\tdir, host string\n\t\t}, Keys.NumWorkers)\n\n\t\tvar wg sync.WaitGroup\n\t\terrs := int32(0)\n\n\t\twg.Add(Keys.NumWorkers)\n\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n\t\t\tgo func() {\n\t\t\t\tdefer wg.Done()\n\t\t\t\tfor item := range work {\n\t\t\t\t\tcheckpoints, files, err := loadCheckpointFiles(item.dir, from)\n\t\t\t\t\tif err != nil {\n\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n\t\t\t\t\t\tcontinue\n\t\t\t\t\t}\n\t\t\t\t\tif len(checkpoints) > 0 {\n\t\t\t\t\t\tresults <- hostResult{\n\t\t\t\t\t\t\tcheckpoints: checkpoints,\n\t\t\t\t\t\t\thostname: item.host,\n\t\t\t\t\t\t\tfiles: files,\n\t\t\t\t\t\t\tdir: item.dir,\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}()\n\t\t}\n\n\t\tgo func() {\n\t\t\tfor _, hostEntry := range hostEntries {\n\t\t\t\tif !hostEntry.IsDir() {\n\t\t\t\t\tcontinue\n\t\t\t\t}\n\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n\t\t\t\twork <- struct {\n\t\t\t\t\tdir, host string\n\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n\t\t\t}\n\t\t\tclose(work)\n\t\t\twg.Wait()\n\t\t\tclose(results)\n\t\t}()\n\n\t\t// Open streaming writer and write each host's checkpoint files as a row group\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\twriter, err := newParquetArchiveWriter(parquetFile)\n\t\tif err != nil {\n\t\t\t// Drain results channel to unblock workers\n\t\t\tfor range results {\n\t\t\t}\n\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\ttype deleteItem struct {\n\t\t\tdir string\n\t\t\tfiles []string\n\t\t}\n\t\tvar toDelete []deleteItem\n\t\twriteErr := error(nil)\n\n\t\tfor r := range results {\n\t\t\tif writeErr == nil {\n\t\t\t\t// Stream each checkpoint file directly to parquet rows.\n\t\t\t\t// Each checkpoint is processed and discarded before the next.\n\t\t\t\tfor _, cf := range r.checkpoints {\n\t\t\t\t\tif err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n\t\t\t\t\t\twriteErr = err\n\t\t\t\t\t\tbreak\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\t// Always track files for deletion (even if write failed, we still drain)\n\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n\t\t}\n\n\t\tif err := writer.Close(); err != nil && writeErr == nil {\n\t\t\twriteErr = err\n\t\t}\n\n\t\tif errs > 0 {\n\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n\t\t}\n\n\t\tif writer.count == 0 {\n\t\t\t// No data written — remove empty file\n\t\t\tos.Remove(parquetFile)\n\t\t\tcontinue\n\t\t}\n\n\t\tif writeErr != nil {\n\t\t\tos.Remove(parquetFile)\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, item := range toDelete {\n\t\t\tfor _, file := range item.files {\n\t\t\t\tfilename := filepath.Join(item.dir, file)\n\t\t\t\tif err := os.Remove(filename); err != nil {\n\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n\t\t\t\t} else {\n\t\t\t\t\ttotalFiles++\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n\t\t\twriter.count, totalFiles, cluster, parquetFile)\n\t}\n\n\tcclog.Infof(\"[METRICSTORE]> archiving checkpoints completed in %s (%d files)\", time.Since(startTime).Round(time.Millisecond), totalFiles)\n\treturn totalFiles, nil\n}\n","numLines":321,"startLine":1,"totalLines":321}},"sourceToolAssistantUUID":"bec7693a-5cd8-40e4-b518-06a267f27113","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→package parquet\n 7→\n 8→import (\n 9→\t\"bytes\"\n 10→\t\"encoding/json\"\n 11→\t\"fmt\"\n 12→\t\"path\"\n 13→\t\"time\"\n 14→\n 15→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 16→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 17→\tpq \"github.com/parquet-go/parquet-go\"\n 18→)\n 19→\n 20→// ParquetWriter batches ParquetJobRows and flushes them to a target\n 21→// when the estimated size exceeds maxSizeBytes.\n 22→type ParquetWriter struct {\n 23→\ttarget ParquetTarget\n 24→\tmaxSizeBytes int64\n 25→\trows []ParquetJobRow\n 26→\tcurrentSize int64\n 27→\tfileCounter int\n 28→\tdatePrefix string\n 29→}\n 30→\n 31→// NewParquetWriter creates a new writer that flushes batches to the given target.\n 32→// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\n 33→func NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n 34→\treturn &ParquetWriter{\n 35→\t\ttarget: target,\n 36→\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n 37→\t\tdatePrefix: time.Now().Format(\"2006-01-02\"),\n 38→\t}\n 39→}\n 40→\n 41→// AddJob adds a row to the current batch. If the estimated batch size\n 42→// exceeds the configured maximum, the batch is flushed to the target first.\n 43→func (pw *ParquetWriter) AddJob(row ParquetJobRow) error {\n 44→\trowSize := estimateRowSize(&row)\n 45→\n 46→\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n 47→\t\tif err := pw.Flush(); err != nil {\n 48→\t\t\treturn err\n 49→\t\t}\n 50→\t}\n 51→\n 52→\tpw.rows = append(pw.rows, row)\n 53→\tpw.currentSize += rowSize\n 54→\treturn nil\n 55→}\n 56→\n 57→// Flush writes the current batch to a parquet file on the target.\n 58→func (pw *ParquetWriter) Flush() error {\n 59→\tif len(pw.rows) == 0 {\n 60→\t\treturn nil\n 61→\t}\n 62→\n 63→\tpw.fileCounter++\n 64→\tfileName := fmt.Sprintf(\"cc-archive-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n 65→\n 66→\tdata, err := writeParquetBytes(pw.rows)\n 67→\tif err != nil {\n 68→\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n 69→\t}\n 70→\n 71→\tif err := pw.target.WriteFile(fileName, data); err != nil {\n 72→\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n 73→\t}\n 74→\n 75→\tcclog.Infof(\"Parquet retention: wrote %s (%d jobs, %d bytes)\", fileName, len(pw.rows), len(data))\n 76→\tpw.rows = pw.rows[:0]\n 77→\tpw.currentSize = 0\n 78→\treturn nil\n 79→}\n 80→\n 81→// Close flushes any remaining rows and finalizes the writer.\n 82→func (pw *ParquetWriter) Close() error {\n 83→\treturn pw.Flush()\n 84→}\n 85→\n 86→func writeParquetBytes(rows []ParquetJobRow) ([]byte, error) {\n 87→\tvar buf bytes.Buffer\n 88→\n 89→\twriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n 90→\t\tpq.Compression(&pq.Zstd),\n 91→\t\tpq.SortingWriterConfig(pq.SortingColumns(\n 92→\t\t\tpq.Ascending(\"sub_cluster\"),\n 93→\t\t\tpq.Ascending(\"project\"),\n 94→\t\t\tpq.Ascending(\"start_time\"),\n 95→\t\t)),\n 96→\t)\n 97→\n 98→\tif _, err := writer.Write(rows); err != nil {\n 99→\t\treturn nil, err\n 100→\t}\n 101→\tif err := writer.Close(); err != nil {\n 102→\t\treturn nil, err\n 103→\t}\n 104→\n 105→\treturn buf.Bytes(), nil\n 106→}\n 107→\n 108→func estimateRowSize(row *ParquetJobRow) int64 {\n 109→\t// Fixed fields: ~100 bytes for numeric fields + strings estimate\n 110→\tsize := int64(200)\n 111→\tsize += int64(len(row.Cluster) + len(row.SubCluster) + len(row.Partition) +\n 112→\t\tlen(row.Project) + len(row.User) + len(row.State))\n 113→\tsize += int64(len(row.ResourcesJSON))\n 114→\tsize += int64(len(row.StatisticsJSON))\n 115→\tsize += int64(len(row.TagsJSON))\n 116→\tsize += int64(len(row.MetaDataJSON))\n 117→\tsize += int64(len(row.FootprintJSON))\n 118→\tsize += int64(len(row.EnergyFootJSON))\n 119→\tsize += int64(len(row.MetricDataGz))\n 120→\treturn size\n 121→}\n 122→\n 123→// prefixedTarget wraps a ParquetTarget and prepends a path prefix to all file names.\n 124→type prefixedTarget struct {\n 125→\tinner ParquetTarget\n 126→\tprefix string\n 127→}\n 128→\n 129→func (pt *prefixedTarget) WriteFile(name string, data []byte) error {\n 130→\treturn pt.inner.WriteFile(path.Join(pt.prefix, name), data)\n 131→}\n 132→\n 133→// ClusterAwareParquetWriter organizes Parquet output by cluster.\n 134→// Each cluster gets its own subdirectory with a cluster.json config file.\n 135→type ClusterAwareParquetWriter struct {\n 136→\ttarget ParquetTarget\n 137→\tmaxSizeMB int\n 138→\twriters map[string]*ParquetWriter\n 139→\tclusterCfgs map[string]*schema.Cluster\n 140→}\n 141→\n 142→// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\n 143→func NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n 144→\treturn &ClusterAwareParquetWriter{\n 145→\t\ttarget: target,\n 146→\t\tmaxSizeMB: maxSizeMB,\n 147→\t\twriters: make(map[string]*ParquetWriter),\n 148→\t\tclusterCfgs: make(map[string]*schema.Cluster),\n 149→\t}\n 150→}\n 151→\n 152→// SetClusterConfig stores a cluster configuration to be written as cluster.json on Close.\n 153→func (cw *ClusterAwareParquetWriter) SetClusterConfig(name string, cfg *schema.Cluster) {\n 154→\tcw.clusterCfgs[name] = cfg\n 155→}\n 156→\n 157→// AddJob routes the job row to the appropriate per-cluster writer.\n 158→func (cw *ClusterAwareParquetWriter) AddJob(row ParquetJobRow) error {\n 159→\tcluster := row.Cluster\n 160→\tpw, ok := cw.writers[cluster]\n 161→\tif !ok {\n 162→\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n 163→\t\tcw.writers[cluster] = pw\n 164→\t}\n 165→\treturn pw.AddJob(row)\n 166→}\n 167→\n 168→// Close writes cluster.json files and flushes all per-cluster writers.\n 169→func (cw *ClusterAwareParquetWriter) Close() error {\n 170→\tfor name, cfg := range cw.clusterCfgs {\n 171→\t\tdata, err := json.MarshalIndent(cfg, \"\", \" \")\n 172→\t\tif err != nil {\n 173→\t\t\treturn fmt.Errorf(\"marshal cluster config %q: %w\", name, err)\n 174→\t\t}\n 175→\t\tif err := cw.target.WriteFile(path.Join(name, \"cluster.json\"), data); err != nil {\n 176→\t\t\treturn fmt.Errorf(\"write cluster.json for %q: %w\", name, err)\n 177→\t\t}\n 178→\t}\n 179→\n 180→\tfor cluster, pw := range cw.writers {\n 181→\t\tif err := pw.Close(); err != nil {\n 182→\t\t\treturn fmt.Errorf(\"close writer for cluster %q: %w\", cluster, err)\n 183→\t\t}\n 184→\t}\n 185→\treturn nil\n 186→}\n 187→"}]},"uuid":"609a5bff-f701-4583-a8f0-015c1239bdd7","timestamp":"2026-03-23T05:10:16.626Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"207e2634-d036-4a1c-8a30-97084c6234f8","timestamp":"2026-03-23T05:10:16.835Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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This file is part of cc-backend.\n 3→// Use of this source code is governed by a MIT-style\n 4→// license that can be found in the LICENSE file.\n 5→\n 6→package parquet\n 7→\n 8→import (\n 9→\t\"bytes\"\n 10→\t\"compress/gzip\"\n 11→\t\"encoding/json\"\n 12→\t\"fmt\"\n 13→\n 14→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 15→)\n 16→\n 17→// JobToParquetRow converts job metadata and metric data into a flat ParquetJobRow.\n 18→// Nested fields are marshaled to JSON; metric data is gzip-compressed JSON.\n 19→func JobToParquetRow(meta *schema.Job, data *schema.JobData) (*ParquetJobRow, error) {\n 20→\tresourcesJSON, err := json.Marshal(meta.Resources)\n 21→\tif err != nil {\n 22→\t\treturn nil, fmt.Errorf(\"marshal resources: %w\", err)\n 23→\t}\n 24→\n 25→\tvar statisticsJSON []byte\n 26→\tif meta.Statistics != nil {\n 27→\t\tstatisticsJSON, err = json.Marshal(meta.Statistics)\n 28→\t\tif err != nil {\n 29→\t\t\treturn nil, fmt.Errorf(\"marshal statistics: %w\", err)\n 30→\t\t}\n 31→\t}\n 32→\n 33→\tvar tagsJSON []byte\n 34→\tif len(meta.Tags) > 0 {\n 35→\t\ttagsJSON, err = json.Marshal(meta.Tags)\n 36→\t\tif err != nil {\n 37→\t\t\treturn nil, fmt.Errorf(\"marshal tags: %w\", err)\n 38→\t\t}\n 39→\t}\n 40→\n 41→\tvar metaDataJSON []byte\n 42→\tif meta.MetaData != nil {\n 43→\t\tmetaDataJSON, err = json.Marshal(meta.MetaData)\n 44→\t\tif err != nil {\n 45→\t\t\treturn nil, fmt.Errorf(\"marshal metadata: %w\", err)\n 46→\t\t}\n 47→\t}\n 48→\n 49→\tvar footprintJSON []byte\n 50→\tif meta.Footprint != nil {\n 51→\t\tfootprintJSON, err = json.Marshal(meta.Footprint)\n 52→\t\tif err != nil {\n 53→\t\t\treturn nil, fmt.Errorf(\"marshal footprint: %w\", err)\n 54→\t\t}\n 55→\t}\n 56→\n 57→\tvar energyFootJSON []byte\n 58→\tif meta.EnergyFootprint != nil {\n 59→\t\tenergyFootJSON, err = json.Marshal(meta.EnergyFootprint)\n 60→\t\tif err != nil {\n 61→\t\t\treturn nil, fmt.Errorf(\"marshal energy footprint: %w\", err)\n 62→\t\t}\n 63→\t}\n 64→\n 65→\tmetricDataGz, err := compressJobData(data)\n 66→\tif err != nil {\n 67→\t\treturn nil, fmt.Errorf(\"compress metric data: %w\", err)\n 68→\t}\n 69→\n 70→\treturn &ParquetJobRow{\n 71→\t\tJobID: meta.JobID,\n 72→\t\tCluster: meta.Cluster,\n 73→\t\tSubCluster: meta.SubCluster,\n 74→\t\tPartition: meta.Partition,\n 75→\t\tProject: meta.Project,\n 76→\t\tUser: meta.User,\n 77→\t\tState: string(meta.State),\n 78→\t\tStartTime: meta.StartTime,\n 79→\t\tDuration: meta.Duration,\n 80→\t\tWalltime: meta.Walltime,\n 81→\t\tNumNodes: meta.NumNodes,\n 82→\t\tNumHWThreads: meta.NumHWThreads,\n 83→\t\tNumAcc: meta.NumAcc,\n 84→\t\tEnergy: meta.Energy,\n 85→\t\tSMT: meta.SMT,\n 86→\t\tResourcesJSON: resourcesJSON,\n 87→\t\tStatisticsJSON: statisticsJSON,\n 88→\t\tTagsJSON: tagsJSON,\n 89→\t\tMetaDataJSON: metaDataJSON,\n 90→\t\tFootprintJSON: footprintJSON,\n 91→\t\tEnergyFootJSON: energyFootJSON,\n 92→\t\tMetricDataGz: metricDataGz,\n 93→\t}, nil\n 94→}\n 95→\n 96→// ParquetRowToJob converts a ParquetJobRow back into job metadata and metric data.\n 97→// This is the reverse of JobToParquetRow.\n 98→func ParquetRowToJob(row *ParquetJobRow) (*schema.Job, *schema.JobData, error) {\n 99→\tmeta := &schema.Job{\n 100→\t\tJobID: row.JobID,\n 101→\t\tCluster: row.Cluster,\n 102→\t\tSubCluster: row.SubCluster,\n 103→\t\tPartition: row.Partition,\n 104→\t\tProject: row.Project,\n 105→\t\tUser: row.User,\n 106→\t\tState: schema.JobState(row.State),\n 107→\t\tStartTime: row.StartTime,\n 108→\t\tDuration: row.Duration,\n 109→\t\tWalltime: row.Walltime,\n 110→\t\tNumNodes: row.NumNodes,\n 111→\t\tNumHWThreads: row.NumHWThreads,\n 112→\t\tNumAcc: row.NumAcc,\n 113→\t\tEnergy: row.Energy,\n 114→\t\tSMT: row.SMT,\n 115→\t}\n 116→\n 117→\tif len(row.ResourcesJSON) > 0 {\n 118→\t\tif err := json.Unmarshal(row.ResourcesJSON, &meta.Resources); err != nil {\n 119→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal resources: %w\", err)\n 120→\t\t}\n 121→\t}\n 122→\n 123→\tif len(row.StatisticsJSON) > 0 {\n 124→\t\tif err := json.Unmarshal(row.StatisticsJSON, &meta.Statistics); err != nil {\n 125→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal statistics: %w\", err)\n 126→\t\t}\n 127→\t}\n 128→\n 129→\tif len(row.TagsJSON) > 0 {\n 130→\t\tif err := json.Unmarshal(row.TagsJSON, &meta.Tags); err != nil {\n 131→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal tags: %w\", err)\n 132→\t\t}\n 133→\t}\n 134→\n 135→\tif len(row.MetaDataJSON) > 0 {\n 136→\t\tif err := json.Unmarshal(row.MetaDataJSON, &meta.MetaData); err != nil {\n 137→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal metadata: %w\", err)\n 138→\t\t}\n 139→\t}\n 140→\n 141→\tif len(row.FootprintJSON) > 0 {\n 142→\t\tif err := json.Unmarshal(row.FootprintJSON, &meta.Footprint); err != nil {\n 143→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal footprint: %w\", err)\n 144→\t\t}\n 145→\t}\n 146→\n 147→\tif len(row.EnergyFootJSON) > 0 {\n 148→\t\tif err := json.Unmarshal(row.EnergyFootJSON, &meta.EnergyFootprint); err != nil {\n 149→\t\t\treturn nil, nil, fmt.Errorf(\"unmarshal energy footprint: %w\", err)\n 150→\t\t}\n 151→\t}\n 152→\n 153→\tdata, err := decompressJobData(row.MetricDataGz)\n 154→\tif err != nil {\n 155→\t\treturn nil, nil, fmt.Errorf(\"decompress metric data: %w\", err)\n 156→\t}\n 157→\n 158→\treturn meta, data, nil\n 159→}\n 160→\n 161→func decompressJobData(data []byte) (*schema.JobData, error) {\n 162→\tgz, err := gzip.NewReader(bytes.NewReader(data))\n 163→\tif err != nil {\n 164→\t\treturn nil, err\n 165→\t}\n 166→\tdefer gz.Close()\n 167→\n 168→\tvar buf bytes.Buffer\n 169→\tif _, err := buf.ReadFrom(gz); err != nil {\n 170→\t\treturn nil, err\n 171→\t}\n 172→\n 173→\tvar jobData schema.JobData\n 174→\tif err := json.Unmarshal(buf.Bytes(), &jobData); err != nil {\n 175→\t\treturn nil, err\n 176→\t}\n 177→\n 178→\treturn &jobData, nil\n 179→}\n 180→\n 181→func compressJobData(data *schema.JobData) ([]byte, error) {\n 182→\tjsonBytes, err := json.Marshal(data)\n 183→\tif err != nil {\n 184→\t\treturn nil, err\n 185→\t}\n 186→\n 187→\tvar buf bytes.Buffer\n 188→\tgz, err := gzip.NewWriterLevel(&buf, gzip.BestCompression)\n 189→\tif err != nil {\n 190→\t\treturn nil, err\n 191→\t}\n 192→\tif _, err := gz.Write(jsonBytes); err != nil {\n 193→\t\treturn nil, err\n 194→\t}\n 195→\tif err := gz.Close(); err != nil {\n 196→\t\treturn nil, err\n 197→\t}\n 198→\n 199→\treturn buf.Bytes(), nil\n 200→}\n 201→"}]},"uuid":"ebee6682-2078-418d-8ea8-8574525c73db","timestamp":"2026-03-23T05:10:16.858Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"ccdaf31e-32f8-4777-b143-8719fd3cf8a6","timestamp":"2026-03-23T05:10:16.977Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"24829fb8-b9b3-422e-8fed-47c527f0080a","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AMcGAunsQaiKqyX1YrYyGC","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 parquet\n 7→\n 8→type ParquetJobRow struct {\n 9→\tJobID int64 `parquet:\"job_id\"`\n 10→\tCluster string `parquet:\"cluster\"`\n 11→\tSubCluster string `parquet:\"sub_cluster\"`\n 12→\tPartition string `parquet:\"partition,optional\"`\n 13→\tProject string `parquet:\"project\"`\n 14→\tUser string `parquet:\"user\"`\n 15→\tState string `parquet:\"job_state\"`\n 16→\tStartTime int64 `parquet:\"start_time\"`\n 17→\tDuration int32 `parquet:\"duration\"`\n 18→\tWalltime int64 `parquet:\"walltime\"`\n 19→\tNumNodes int32 `parquet:\"num_nodes\"`\n 20→\tNumHWThreads int32 `parquet:\"num_hwthreads\"`\n 21→\tNumAcc int32 `parquet:\"num_acc\"`\n 22→\tExclusive int32 `parquet:\"exclusive\"`\n 23→\tEnergy float64 `parquet:\"energy\"`\n 24→\tSMT int32 `parquet:\"smt\"`\n 25→\tResourcesJSON []byte `parquet:\"resources_json\"`\n 26→\tStatisticsJSON []byte `parquet:\"statistics_json,optional\"`\n 27→\tTagsJSON []byte `parquet:\"tags_json,optional\"`\n 28→\tMetaDataJSON []byte `parquet:\"meta_data_json,optional\"`\n 29→\tFootprintJSON []byte `parquet:\"footprint_json,optional\"`\n 30→\tEnergyFootJSON []byte `parquet:\"energy_footprint_json,optional\"`\n 31→\tMetricDataGz []byte `parquet:\"metric_data_gz\"`\n 32→}\n 33→"}]},"uuid":"bfb47490-579c-404b-9a74-86e1c4b0199e","timestamp":"2026-03-23T05:10:17.028Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"d50ac296-0e53-4b79-b095-a1ec48a7c976","timestamp":"2026-03-23T05:10:17.029Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"3291925f-5ce8-4fb0-8d4a-b52ebcff10b7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DoYU3WipTFY1JiW2yivxoA","type":"tool_result","content":"/Users/jan/prg/ClusterCockpit/cc-backend/tools/archive-manager/main.go:\t\tif err := cw.AddJob(*row); err != nil {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:// Flush removes all data from job-related tables (jobtag, tag, job).\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/job.go:func (r *JobRepository) Flush() error {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:// - Counts (JobCountGrouped, AddJobCount): Simple job counts with optional filtering\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:// AddJobCountGrouped augments existing statistics with additional job counts by category.\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:func (r *JobRepository) AddJobCountGrouped(\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:\tcclog.Debugf(\"Timer AddJobCountGrouped %s\", time.Since(start))\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:// AddJobCount augments existing overall statistics with additional job counts by category.\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:// Similar to AddJobCountGrouped but for ungrouped statistics. Applies the same count\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:func (r *JobRepository) AddJobCount(\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/repository/stats.go:\tcclog.Debugf(\"Timer AddJobCount %s\", time.Since(start))\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/taskmanager/retentionService.go:\t\tif err := cw.AddJob(*row); err != nil {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/importer/initDB.go:// 1. Flushes existing job, tag, and jobtag tables\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/importer/initDB.go:\tif err := r.Flush(); err != nil {\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go:\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"short\")\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go:\t\t\t\tstats, err = r.Repo.AddJobCountGrouped(ctx, filter, groupBy, stats, \"running\")\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go:\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"short\")\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/graph/schema.resolvers.go:\t\t\t\tstats, err = r.Repo.AddJobCount(ctx, filter, stats, \"running\")\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/api/job.go:\tdefer bw.Flush()\n/Users/jan/prg/ClusterCockpit/cc-backend/internal/api/job.go:\tdefer bw.Flush()","is_error":false}]},"uuid":"7f8ddd96-86c4-4f45-823e-fac2d124789a","timestamp":"2026-03-23T05:10:24.294Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"0f27eaa6-9a94-4fc0-a0cf-bd758145fdd1","timestamp":"2026-03-23T05:10:24.294Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"60bb1376-533e-469c-8271-4b3d21b9039f","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:10:25.794Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01Di36RRpYeAveDS5EdjX3HD","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UjQuSEtVT2w2kxWjD1Ew3p","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/tools/archive-manager/main.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1074,"cache_read_input_tokens":26101,"cache_creation":{"ephemeral_5m_input_tokens":1074,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSFCTjnyjk6JLR2m77t","uuid":"127c9bbe-1b7e-4d38-912b-eb66917e7ff1"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"d7351412-7111-47af-9be1-a6e668e336ce","timestamp":"2026-03-23T05:10:25.794Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"d7351412-7111-47af-9be1-a6e668e336ce","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CmfrEFA6qiowP6XmMyxDCo","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 taskmanager\n 7→\n 8→import (\n 9→\t\"encoding/json\"\n 10→\t\"fmt\"\n 11→\t\"os\"\n 12→\t\"path/filepath\"\n 13→\t\"strconv\"\n 14→\t\"strings\"\n 15→\t\"time\"\n 16→\n 17→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 18→\tpqarchive \"github.com/ClusterCockpit/cc-backend/pkg/archive/parquet\"\n 19→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 20→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 21→\t\"github.com/go-co-op/gocron/v2\"\n 22→)\n 23→\n 24→// createParquetTarget creates a ParquetTarget (file or S3) from the retention config.\n 25→func createParquetTarget(cfg Retention) (pqarchive.ParquetTarget, error) {\n 26→\tswitch cfg.TargetKind {\n 27→\tcase \"s3\":\n 28→\t\treturn pqarchive.NewS3Target(pqarchive.S3TargetConfig{\n 29→\t\t\tEndpoint: cfg.TargetEndpoint,\n 30→\t\t\tBucket: cfg.TargetBucket,\n 31→\t\t\tAccessKey: cfg.TargetAccessKey,\n 32→\t\t\tSecretKey: cfg.TargetSecretKey,\n 33→\t\t\tRegion: cfg.TargetRegion,\n 34→\t\t\tUsePathStyle: cfg.TargetUsePathStyle,\n 35→\t\t})\n 36→\tdefault:\n 37→\t\treturn pqarchive.NewFileTarget(cfg.TargetPath)\n 38→\t}\n 39→}\n 40→\n 41→// createTargetBackend creates a secondary archive backend (file or S3) for JSON copy/move.\n 42→func createTargetBackend(cfg Retention) (archive.ArchiveBackend, error) {\n 43→\tvar raw json.RawMessage\n 44→\tvar err error\n 45→\n 46→\tswitch cfg.TargetKind {\n 47→\tcase \"s3\":\n 48→\t\traw, err = json.Marshal(map[string]any{\n 49→\t\t\t\"kind\": \"s3\",\n 50→\t\t\t\"endpoint\": cfg.TargetEndpoint,\n 51→\t\t\t\"bucket\": cfg.TargetBucket,\n 52→\t\t\t\"access-key\": cfg.TargetAccessKey,\n 53→\t\t\t\"secret-key\": cfg.TargetSecretKey,\n 54→\t\t\t\"region\": cfg.TargetRegion,\n 55→\t\t\t\"use-path-style\": cfg.TargetUsePathStyle,\n 56→\t\t})\n 57→\tdefault:\n 58→\t\traw, err = json.Marshal(map[string]string{\n 59→\t\t\t\"kind\": \"file\",\n 60→\t\t\t\"path\": cfg.TargetPath,\n 61→\t\t})\n 62→\t}\n 63→\tif err != nil {\n 64→\t\treturn nil, fmt.Errorf(\"marshal target config: %w\", err)\n 65→\t}\n 66→\treturn archive.InitBackend(raw)\n 67→}\n 68→\n 69→// transferJobsJSON copies job data from source archive to target backend in JSON format.\n 70→func transferJobsJSON(jobs []*schema.Job, src archive.ArchiveBackend, dst archive.ArchiveBackend) error {\n 71→\t// Transfer cluster configs for all clusters referenced by jobs\n 72→\tclustersDone := make(map[string]bool)\n 73→\tfor _, job := range jobs {\n 74→\t\tif clustersDone[job.Cluster] {\n 75→\t\t\tcontinue\n 76→\t\t}\n 77→\t\tclusterCfg, err := src.LoadClusterCfg(job.Cluster)\n 78→\t\tif err != nil {\n 79→\t\t\tcclog.Warnf(\"Retention: load cluster config %q: %v\", job.Cluster, err)\n 80→\t\t} else {\n 81→\t\t\tif err := dst.StoreClusterCfg(job.Cluster, clusterCfg); err != nil {\n 82→\t\t\t\tcclog.Warnf(\"Retention: store cluster config %q: %v\", job.Cluster, err)\n 83→\t\t\t}\n 84→\t\t}\n 85→\t\tclustersDone[job.Cluster] = true\n 86→\t}\n 87→\n 88→\tfor _, job := range jobs {\n 89→\t\tmeta, err := src.LoadJobMeta(job)\n 90→\t\tif err != nil {\n 91→\t\t\tcclog.Warnf(\"Retention: load meta for job %d: %v\", job.JobID, err)\n 92→\t\t\tcontinue\n 93→\t\t}\n 94→\t\tdata, err := src.LoadJobData(job)\n 95→\t\tif err != nil {\n 96→\t\t\tcclog.Warnf(\"Retention: load data for job %d: %v\", job.JobID, err)\n 97→\t\t\tcontinue\n 98→\t\t}\n 99→\t\tif err := dst.ImportJob(meta, &data); err != nil {\n 100→\t\t\tcclog.Warnf(\"Retention: import job %d: %v\", job.JobID, err)\n 101→\t\t\tcontinue\n 102→\t\t}\n 103→\t}\n 104→\treturn nil\n 105→}\n 106→\n 107→// transferJobsParquet converts jobs to Parquet format, organized by cluster.\n 108→func transferJobsParquet(jobs []*schema.Job, src archive.ArchiveBackend, target pqarchive.ParquetTarget, maxSizeMB int) error {\n 109→\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n 110→\n 111→\t// Set cluster configs for all clusters referenced by jobs\n 112→\tclustersDone := make(map[string]bool)\n 113→\tfor _, job := range jobs {\n 114→\t\tif clustersDone[job.Cluster] {\n 115→\t\t\tcontinue\n 116→\t\t}\n 117→\t\tclusterCfg, err := src.LoadClusterCfg(job.Cluster)\n 118→\t\tif err != nil {\n 119→\t\t\tcclog.Warnf(\"Retention: load cluster config %q: %v\", job.Cluster, err)\n 120→\t\t} else {\n 121→\t\t\tcw.SetClusterConfig(job.Cluster, clusterCfg)\n 122→\t\t}\n 123→\t\tclustersDone[job.Cluster] = true\n 124→\t}\n 125→\n 126→\tfor _, job := range jobs {\n 127→\t\tmeta, err := src.LoadJobMeta(job)\n 128→\t\tif err != nil {\n 129→\t\t\tcclog.Warnf(\"Retention: load meta for job %d: %v\", job.JobID, err)\n 130→\t\t\tcontinue\n 131→\t\t}\n 132→\t\tdata, err := src.LoadJobData(job)\n 133→\t\tif err != nil {\n 134→\t\t\tcclog.Warnf(\"Retention: load data for job %d: %v\", job.JobID, err)\n 135→\t\t\tcontinue\n 136→\t\t}\n 137→\t\trow, err := pqarchive.JobToParquetRow(meta, &data)\n 138→\t\tif err != nil {\n 139→\t\t\tcclog.Warnf(\"Retention: convert job %d: %v\", job.JobID, err)\n 140→\t\t\tcontinue\n 141→\t\t}\n 142→\t\tif err := cw.AddJob(*row); err != nil {\n 143→\t\t\tcclog.Errorf(\"Retention: add job %d to writer: %v\", job.JobID, err)\n 144→\t\t\tcontinue\n 145→\t\t}\n 146→\t}\n 147→\n 148→\treturn cw.Close()\n 149→}\n 150→\n 151→// cleanupAfterTransfer removes jobs from archive and optionally from DB.\n 152→func cleanupAfterTransfer(jobs []*schema.Job, startTime int64, includeDB bool, omitTagged string) {\n 153→\tarchive.GetHandle().CleanUp(jobs)\n 154→\n 155→\tif includeDB {\n 156→\t\tcnt, err := jobRepo.DeleteJobsBefore(startTime, omitTagged)\n 157→\t\tif err != nil {\n 158→\t\t\tcclog.Errorf(\"Retention: delete jobs from db: %v\", err)\n 159→\t\t} else {\n 160→\t\t\tcclog.Infof(\"Retention: removed %d jobs from db\", cnt)\n 161→\t\t}\n 162→\t\tif err = jobRepo.Optimize(); err != nil {\n 163→\t\t\tcclog.Errorf(\"Retention: db optimization error: %v\", err)\n 164→\t\t}\n 165→\t}\n 166→}\n 167→\n 168→// readCopyMarker reads the last-processed timestamp from a copy marker file.\n 169→func readCopyMarker(cfg Retention) int64 {\n 170→\tvar data []byte\n 171→\tvar err error\n 172→\n 173→\tswitch cfg.TargetKind {\n 174→\tcase \"s3\":\n 175→\t\t// For S3 we store the marker locally alongside the config\n 176→\t\tdata, err = os.ReadFile(copyMarkerPath(cfg))\n 177→\tdefault:\n 178→\t\tdata, err = os.ReadFile(filepath.Join(cfg.TargetPath, \".copy-marker\"))\n 179→\t}\n 180→\tif err != nil {\n 181→\t\treturn 0\n 182→\t}\n 183→\tts, err := strconv.ParseInt(strings.TrimSpace(string(data)), 10, 64)\n 184→\tif err != nil {\n 185→\t\treturn 0\n 186→\t}\n 187→\treturn ts\n 188→}\n 189→\n 190→// writeCopyMarker writes the last-processed timestamp to a copy marker file.\n 191→func writeCopyMarker(cfg Retention, ts int64) {\n 192→\tcontent := []byte(strconv.FormatInt(ts, 10))\n 193→\tvar err error\n 194→\n 195→\tswitch cfg.TargetKind {\n 196→\tcase \"s3\":\n 197→\t\terr = os.WriteFile(copyMarkerPath(cfg), content, 0o640)\n 198→\tdefault:\n 199→\t\terr = os.WriteFile(filepath.Join(cfg.TargetPath, \".copy-marker\"), content, 0o640)\n 200→\t}\n 201→\tif err != nil {\n 202→\t\tcclog.Warnf(\"Retention: write copy marker: %v\", err)\n 203→\t}\n 204→}\n 205→\n 206→func copyMarkerPath(cfg Retention) string {\n 207→\t// For S3 targets, store the marker in a local temp-style path derived from the bucket name\n 208→\treturn filepath.Join(os.TempDir(), fmt.Sprintf(\"cc-copy-marker-%s\", cfg.TargetBucket))\n 209→}\n 210→\n 211→func RegisterRetentionDeleteService(cfg Retention) {\n 212→\tcclog.Info(\"Register retention delete service\")\n 213→\n 214→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(3, 0, 0))),\n 215→\t\tgocron.NewTask(\n 216→\t\t\tfunc() {\n 217→\t\t\t\tstartTime := time.Now().Unix() - int64(cfg.Age*24*3600)\n 218→\t\t\t\tjobs, err := jobRepo.FindJobsBetween(0, startTime, cfg.OmitTagged)\n 219→\t\t\t\tif err != nil {\n 220→\t\t\t\t\tcclog.Warnf(\"Retention delete: error finding jobs: %v\", err)\n 221→\t\t\t\t\treturn\n 222→\t\t\t\t}\n 223→\t\t\t\tif len(jobs) == 0 {\n 224→\t\t\t\t\treturn\n 225→\t\t\t\t}\n 226→\n 227→\t\t\t\tcclog.Infof(\"Retention delete: processing %d jobs\", len(jobs))\n 228→\t\t\t\tcleanupAfterTransfer(jobs, startTime, cfg.IncludeDB, cfg.OmitTagged)\n 229→\t\t\t}))\n 230→}\n 231→\n 232→func RegisterRetentionCopyService(cfg Retention) {\n 233→\tcclog.Infof(\"Register retention copy service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n 234→\n 235→\tmaxFileSizeMB := cfg.MaxFileSizeMB\n 236→\tif maxFileSizeMB <= 0 {\n 237→\t\tmaxFileSizeMB = 512\n 238→\t}\n 239→\n 240→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(4, 0, 0))),\n 241→\t\tgocron.NewTask(\n 242→\t\t\tfunc() {\n 243→\t\t\t\tcutoff := time.Now().Unix() - int64(cfg.Age*24*3600)\n 244→\t\t\t\tlastProcessed := readCopyMarker(cfg)\n 245→\n 246→\t\t\t\tjobs, err := jobRepo.FindJobsBetween(lastProcessed, cutoff, cfg.OmitTagged)\n 247→\t\t\t\tif err != nil {\n 248→\t\t\t\t\tcclog.Warnf(\"Retention copy: error finding jobs: %v\", err)\n 249→\t\t\t\t\treturn\n 250→\t\t\t\t}\n 251→\t\t\t\tif len(jobs) == 0 {\n 252→\t\t\t\t\treturn\n 253→\t\t\t\t}\n 254→\n 255→\t\t\t\tcclog.Infof(\"Retention copy: processing %d jobs\", len(jobs))\n 256→\t\t\t\tar := archive.GetHandle()\n 257→\n 258→\t\t\t\tswitch cfg.Format {\n 259→\t\t\t\tcase \"parquet\":\n 260→\t\t\t\t\ttarget, err := createParquetTarget(cfg)\n 261→\t\t\t\t\tif err != nil {\n 262→\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create parquet target: %v\", err)\n 263→\t\t\t\t\t\treturn\n 264→\t\t\t\t\t}\n 265→\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\n 266→\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n 267→\t\t\t\t\t\treturn\n 268→\t\t\t\t\t}\n 269→\t\t\t\tdefault: // json\n 270→\t\t\t\t\tdst, err := createTargetBackend(cfg)\n 271→\t\t\t\t\tif err != nil {\n 272→\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create target backend: %v\", err)\n 273→\t\t\t\t\t\treturn\n 274→\t\t\t\t\t}\n 275→\t\t\t\t\tif err := transferJobsJSON(jobs, ar, dst); err != nil {\n 276→\t\t\t\t\t\tcclog.Errorf(\"Retention copy: json transfer: %v\", err)\n 277→\t\t\t\t\t\treturn\n 278→\t\t\t\t\t}\n 279→\t\t\t\t}\n 280→\n 281→\t\t\t\twriteCopyMarker(cfg, cutoff)\n 282→\t\t\t}))\n 283→}\n 284→\n 285→func RegisterRetentionMoveService(cfg Retention) {\n 286→\tcclog.Infof(\"Register retention move service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n 287→\n 288→\tmaxFileSizeMB := cfg.MaxFileSizeMB\n 289→\tif maxFileSizeMB <= 0 {\n 290→\t\tmaxFileSizeMB = 512\n 291→\t}\n 292→\n 293→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(5, 0, 0))),\n 294→\t\tgocron.NewTask(\n 295→\t\t\tfunc() {\n 296→\t\t\t\tstartTime := time.Now().Unix() - int64(cfg.Age*24*3600)\n 297→\t\t\t\tjobs, err := jobRepo.FindJobsBetween(0, startTime, cfg.OmitTagged)\n 298→\t\t\t\tif err != nil {\n 299→\t\t\t\t\tcclog.Warnf(\"Retention move: error finding jobs: %v\", err)\n 300→\t\t\t\t\treturn\n 301→\t\t\t\t}\n 302→\t\t\t\tif len(jobs) == 0 {\n 303→\t\t\t\t\treturn\n 304→\t\t\t\t}\n 305→\n 306→\t\t\t\tcclog.Infof(\"Retention move: processing %d jobs\", len(jobs))\n 307→\t\t\t\tar := archive.GetHandle()\n 308→\n 309→\t\t\t\tswitch cfg.Format {\n 310→\t\t\t\tcase \"parquet\":\n 311→\t\t\t\t\ttarget, err := createParquetTarget(cfg)\n 312→\t\t\t\t\tif err != nil {\n 313→\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n 314→\t\t\t\t\t\treturn\n 315→\t\t\t\t\t}\n 316→\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\n 317→\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n 318→\t\t\t\t\t\treturn\n 319→\t\t\t\t\t}\n 320→\t\t\t\tdefault: // json\n 321→\t\t\t\t\tdst, err := createTargetBackend(cfg)\n 322→\t\t\t\t\tif err != nil {\n 323→\t\t\t\t\t\tcclog.Errorf(\"Retention move: create target backend: %v\", err)\n 324→\t\t\t\t\t\treturn\n 325→\t\t\t\t\t}\n 326→\t\t\t\t\tif err := transferJobsJSON(jobs, ar, dst); err != nil {\n 327→\t\t\t\t\t\tcclog.Errorf(\"Retention move: json transfer: %v\", err)\n 328→\t\t\t\t\t\treturn\n 329→\t\t\t\t\t}\n 330→\t\t\t\t}\n 331→\n 332→\t\t\t\tcleanupAfterTransfer(jobs, startTime, cfg.IncludeDB, cfg.OmitTagged)\n 333→\t\t\t}))\n 334→}\n 335→"}]},"uuid":"5f129c99-5ec4-4a71-9373-ac954734ab5c","timestamp":"2026-03-23T05:10:25.818Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"c98aa7f8-4724-47e4-9b1f-6170655b8cf8","timestamp":"2026-03-23T05:10:25.818Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"c98aa7f8-4724-47e4-9b1f-6170655b8cf8","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UjQuSEtVT2w2kxWjD1Ew3p","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→package main\n 6→\n 7→import (\n 8→\t\"context\"\n 9→\t\"encoding/json\"\n 10→\t\"flag\"\n 11→\t\"fmt\"\n 12→\t\"io/fs\"\n 13→\t\"os\"\n 14→\t\"os/exec\"\n 15→\t\"os/signal\"\n 16→\t\"path/filepath\"\n 17→\t\"strconv\"\n 18→\t\"strings\"\n 19→\t\"sync\"\n 20→\t\"sync/atomic\"\n 21→\t\"syscall\"\n 22→\t\"time\"\n 23→\n 24→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n 25→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n 26→\tpqarchive \"github.com/ClusterCockpit/cc-backend/pkg/archive/parquet\"\n 27→\tccconf \"github.com/ClusterCockpit/cc-lib/v2/ccConfig\"\n 28→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 29→)\n 30→\n 31→func parseDate(in string) int64 {\n 32→\tconst shortForm = \"2006-Jan-02\"\n 33→\tloc, _ := time.LoadLocation(\"Local\")\n 34→\tif in != \"\" {\n 35→\t\tt, err := time.ParseInLocation(shortForm, in, loc)\n 36→\t\tif err != nil {\n 37→\t\t\tcclog.Abortf(\"Archive Manager Main: Date parse failed with input: '%s'\\nError: %s\\n\", in, err.Error())\n 38→\t\t}\n 39→\t\treturn t.Unix()\n 40→\t}\n 41→\n 42→\treturn 0\n 43→}\n 44→\n 45→// parseArchivePath extracts the path from the source config JSON.\n 46→func parseArchivePath(srcConfig string) (string, error) {\n 47→\tvar config struct {\n 48→\t\tKind string `json:\"kind\"`\n 49→\t\tPath string `json:\"path\"`\n 50→\t}\n 51→\tif err := json.Unmarshal([]byte(srcConfig), &config); err != nil {\n 52→\t\treturn \"\", fmt.Errorf(\"failed to parse source config: %w\", err)\n 53→\t}\n 54→\n 55→\tif config.Path == \"\" {\n 56→\t\treturn \"\", fmt.Errorf(\"no path found in source config\")\n 57→\t}\n 58→\n 59→\treturn config.Path, nil\n 60→}\n 61→\n 62→// countJobsNative counts jobs using native Go filepath.WalkDir.\n 63→// This is used as a fallback when fd/fdfind is not available.\n 64→func countJobsNative(archivePath string) (int, error) {\n 65→\tcount := 0\n 66→\terr := filepath.WalkDir(archivePath, func(path string, d fs.DirEntry, err error) error {\n 67→\t\tif err != nil {\n 68→\t\t\treturn nil // Skip directories we can't access\n 69→\t\t}\n 70→\t\tif !d.IsDir() && d.Name() == \"meta.json\" {\n 71→\t\t\tcount++\n 72→\t\t}\n 73→\t\treturn nil\n 74→\t})\n 75→\tif err != nil {\n 76→\t\treturn 0, fmt.Errorf(\"failed to walk directory: %w\", err)\n 77→\t}\n 78→\n 79→\treturn count, nil\n 80→}\n 81→\n 82→// countJobsWithFd counts jobs using the external fd command.\n 83→func countJobsWithFd(fdPath, archivePath string) (int, error) {\n 84→\tfdCmd := exec.Command(fdPath, \"meta.json\", archivePath)\n 85→\twcCmd := exec.Command(\"wc\", \"-l\")\n 86→\n 87→\tpipe, err := fdCmd.StdoutPipe()\n 88→\tif err != nil {\n 89→\t\treturn 0, fmt.Errorf(\"failed to create pipe: %w\", err)\n 90→\t}\n 91→\twcCmd.Stdin = pipe\n 92→\n 93→\tif err := fdCmd.Start(); err != nil {\n 94→\t\treturn 0, fmt.Errorf(\"failed to start fd command: %w\", err)\n 95→\t}\n 96→\n 97→\toutput, err := wcCmd.Output()\n 98→\tif err != nil {\n 99→\t\treturn 0, fmt.Errorf(\"failed to run wc command: %w\", err)\n 100→\t}\n 101→\n 102→\tif err := fdCmd.Wait(); err != nil {\n 103→\t\treturn 0, fmt.Errorf(\"fd command failed: %w\", err)\n 104→\t}\n 105→\n 106→\tcountStr := strings.TrimSpace(string(output))\n 107→\tcount, err := strconv.Atoi(countStr)\n 108→\tif err != nil {\n 109→\t\treturn 0, fmt.Errorf(\"failed to parse count from wc output '%s': %w\", countStr, err)\n 110→\t}\n 111→\n 112→\treturn count, nil\n 113→}\n 114→\n 115→// countJobs counts the total number of jobs in the source archive.\n 116→// It tries to use external fd/fdfind command for speed, falling back to\n 117→// native Go filepath.WalkDir if neither is available.\n 118→// The srcConfig parameter should be the JSON configuration string containing the archive path.\n 119→func countJobs(srcConfig string) (int, error) {\n 120→\tarchivePath, err := parseArchivePath(srcConfig)\n 121→\tif err != nil {\n 122→\t\treturn 0, err\n 123→\t}\n 124→\n 125→\t// Try fd first (common name)\n 126→\tif fdPath, err := exec.LookPath(\"fd\"); err == nil {\n 127→\t\treturn countJobsWithFd(fdPath, archivePath)\n 128→\t}\n 129→\n 130→\t// Try fdfind (Debian/Ubuntu package name)\n 131→\tif fdPath, err := exec.LookPath(\"fdfind\"); err == nil {\n 132→\t\treturn countJobsWithFd(fdPath, archivePath)\n 133→\t}\n 134→\n 135→\t// Fall back to native Go implementation\n 136→\tcclog.Debug(\"fd/fdfind not found, using native Go file walker\")\n 137→\treturn countJobsNative(archivePath)\n 138→}\n 139→\n 140→// formatDuration formats a duration as a human-readable string.\n 141→func formatDuration(d time.Duration) string {\n 142→\tif d < time.Minute {\n 143→\t\treturn fmt.Sprintf(\"%ds\", int(d.Seconds()))\n 144→\t} else if d < time.Hour {\n 145→\t\treturn fmt.Sprintf(\"%dm%ds\", int(d.Minutes()), int(d.Seconds())%60)\n 146→\t}\n 147→\treturn fmt.Sprintf(\"%dh%dm\", int(d.Hours()), int(d.Minutes())%60)\n 148→}\n 149→\n 150→// progressMeter displays import progress to the terminal.\n 151→type progressMeter struct {\n 152→\ttotal int\n 153→\tprocessed int32\n 154→\timported int32\n 155→\tskipped int32\n 156→\tfailed int32\n 157→\tstartTime time.Time\n 158→\tdone chan struct{}\n 159→}\n 160→\n 161→func newProgressMeter(total int) *progressMeter {\n 162→\treturn &progressMeter{\n 163→\t\ttotal: total,\n 164→\t\tstartTime: time.Now(),\n 165→\t\tdone: make(chan struct{}),\n 166→\t}\n 167→}\n 168→\n 169→func (p *progressMeter) start() {\n 170→\tgo func() {\n 171→\t\tticker := time.NewTicker(500 * time.Millisecond)\n 172→\t\tdefer ticker.Stop()\n 173→\n 174→\t\tfor {\n 175→\t\t\tselect {\n 176→\t\t\tcase <-ticker.C:\n 177→\t\t\t\tp.render()\n 178→\t\t\tcase <-p.done:\n 179→\t\t\t\tp.render()\n 180→\t\t\t\tfmt.Println()\n 181→\t\t\t\treturn\n 182→\t\t\t}\n 183→\t\t}\n 184→\t}()\n 185→}\n 186→\n 187→func (p *progressMeter) render() {\n 188→\tprocessed := atomic.LoadInt32(&p.processed)\n 189→\timported := atomic.LoadInt32(&p.imported)\n 190→\tskipped := atomic.LoadInt32(&p.skipped)\n 191→\tfailed := atomic.LoadInt32(&p.failed)\n 192→\n 193→\telapsed := time.Since(p.startTime)\n 194→\tpercent := float64(processed) / float64(p.total) * 100\n 195→\tif p.total == 0 {\n 196→\t\tpercent = 0\n 197→\t}\n 198→\n 199→\tvar eta string\n 200→\tvar throughput float64\n 201→\tif processed > 0 {\n 202→\t\tthroughput = float64(processed) / elapsed.Seconds()\n 203→\t\tremaining := float64(p.total-int(processed)) / throughput\n 204→\t\teta = formatDuration(time.Duration(remaining) * time.Second)\n 205→\t} else {\n 206→\t\teta = \"calculating...\"\n 207→\t}\n 208→\n 209→\tbarWidth := 30\n 210→\tfilled := int(float64(barWidth) * float64(processed) / float64(p.total))\n 211→\tif p.total == 0 {\n 212→\t\tfilled = 0\n 213→\t}\n 214→\n 215→\tvar bar strings.Builder\n 216→\tfor i := range barWidth {\n 217→\t\tif i < filled {\n 218→\t\t\tbar.WriteString(\"█\")\n 219→\t\t} else {\n 220→\t\t\tbar.WriteString(\"░\")\n 221→\t\t}\n 222→\t}\n 223→\n 224→\tfmt.Printf(\"\\r[%s] %5.1f%% | %d/%d | %.1f jobs/s | ETA: %s | ✓%d ○%d ✗%d \",\n 225→\t\tbar.String(), percent, processed, p.total, throughput, eta, imported, skipped, failed)\n 226→}\n 227→\n 228→func (p *progressMeter) stop() {\n 229→\tclose(p.done)\n 230→}\n 231→\n 232→// importArchive imports all jobs from a source archive backend to a destination archive backend.\n 233→// It uses parallel processing with a worker pool to improve performance.\n 234→// The import can be interrupted by CTRL-C (SIGINT) and will terminate gracefully.\n 235→// Returns the number of successfully imported jobs, failed jobs, and any error encountered.\n 236→func importArchive(srcBackend, dstBackend archive.ArchiveBackend, srcConfig string) (int, int, error) {\n 237→\tcclog.Info(\"Starting parallel archive import...\")\n 238→\tcclog.Info(\"Press CTRL-C to interrupt (will finish current jobs before exiting)\")\n 239→\n 240→\tctx, cancel := context.WithCancel(context.Background())\n 241→\tdefer cancel()\n 242→\n 243→\tsigChan := make(chan os.Signal, 1)\n 244→\tsignal.Notify(sigChan, os.Interrupt, syscall.SIGTERM)\n 245→\n 246→\tvar interrupted atomic.Bool\n 247→\n 248→\tgo func() {\n 249→\t\t<-sigChan\n 250→\t\tcclog.Warn(\"Interrupt received, stopping import (finishing current jobs)...\")\n 251→\t\tinterrupted.Store(true)\n 252→\t\tcancel()\n 253→\t\t// Stop listening for further signals to allow force quit with second CTRL-C\n 254→\t\tsignal.Stop(sigChan)\n 255→\t}()\n 256→\n 257→\tcclog.Info(\"Counting jobs in source archive (this may take a long time) ...\")\n 258→\ttotalJobs, err := countJobs(srcConfig)\n 259→\tif err != nil {\n 260→\t\treturn 0, 0, fmt.Errorf(\"failed to count jobs: %w\", err)\n 261→\t}\n 262→\tcclog.Infof(\"Found %d jobs to process\", totalJobs)\n 263→\n 264→\tprogress := newProgressMeter(totalJobs)\n 265→\n 266→\tnumWorkers := 4\n 267→\tcclog.Infof(\"Using %d parallel workers\", numWorkers)\n 268→\n 269→\tjobs := make(chan archive.JobContainer, numWorkers*2)\n 270→\n 271→\tvar wg sync.WaitGroup\n 272→\n 273→\tprogress.start()\n 274→\n 275→\tfor i := range numWorkers {\n 276→\t\twg.Add(1)\n 277→\t\tgo func(workerID int) {\n 278→\t\t\tdefer wg.Done()\n 279→\n 280→\t\t\tfor job := range jobs {\n 281→\t\t\t\tif job.Meta == nil {\n 282→\t\t\t\t\tcclog.Warn(\"Skipping job with nil metadata\")\n 283→\t\t\t\t\tatomic.AddInt32(&progress.failed, 1)\n 284→\t\t\t\t\tatomic.AddInt32(&progress.processed, 1)\n 285→\t\t\t\t\tcontinue\n 286→\t\t\t\t}\n 287→\n 288→\t\t\t\tif job.Data == nil {\n 289→\t\t\t\t\tcclog.Warnf(\"Job %d from cluster %s has no metric data, skipping\",\n 290→\t\t\t\t\t\tjob.Meta.JobID, job.Meta.Cluster)\n 291→\t\t\t\t\tatomic.AddInt32(&progress.failed, 1)\n 292→\t\t\t\t\tatomic.AddInt32(&progress.processed, 1)\n 293→\t\t\t\t\tcontinue\n 294→\t\t\t\t}\n 295→\n 296→\t\t\t\tif dstBackend.Exists(job.Meta) {\n 297→\t\t\t\t\tcclog.Debugf(\"Job %d (cluster: %s, start: %d) already exists in destination, skipping\",\n 298→\t\t\t\t\t\tjob.Meta.JobID, job.Meta.Cluster, job.Meta.StartTime)\n 299→\t\t\t\t\tatomic.AddInt32(&progress.skipped, 1)\n 300→\t\t\t\t\tatomic.AddInt32(&progress.processed, 1)\n 301→\t\t\t\t\tcontinue\n 302→\t\t\t\t}\n 303→\n 304→\t\t\t\tif err := dstBackend.ImportJob(job.Meta, job.Data); err != nil {\n 305→\t\t\t\t\tcclog.Errorf(\"Failed to import job %d from cluster %s: %s\",\n 306→\t\t\t\t\t\tjob.Meta.JobID, job.Meta.Cluster, err.Error())\n 307→\t\t\t\t\tatomic.AddInt32(&progress.failed, 1)\n 308→\t\t\t\t\tatomic.AddInt32(&progress.processed, 1)\n 309→\t\t\t\t\tcontinue\n 310→\t\t\t\t}\n 311→\n 312→\t\t\t\tatomic.AddInt32(&progress.imported, 1)\n 313→\t\t\t\tatomic.AddInt32(&progress.processed, 1)\n 314→\t\t\t}\n 315→\t\t}(i)\n 316→\t}\n 317→\n 318→\tgo func() {\n 319→\t\tdefer close(jobs)\n 320→\n 321→\t\tclusters := srcBackend.GetClusters()\n 322→\t\tfor _, clusterName := range clusters {\n 323→\t\t\tif ctx.Err() != nil {\n 324→\t\t\t\treturn\n 325→\t\t\t}\n 326→\n 327→\t\t\tclusterCfg, err := srcBackend.LoadClusterCfg(clusterName)\n 328→\t\t\tif err != nil {\n 329→\t\t\t\tcclog.Errorf(\"Failed to load cluster config for %s: %v\", clusterName, err)\n 330→\t\t\t\tcontinue\n 331→\t\t\t}\n 332→\n 333→\t\t\tif err := dstBackend.StoreClusterCfg(clusterName, clusterCfg); err != nil {\n 334→\t\t\t\tcclog.Errorf(\"Failed to store cluster config for %s: %v\", clusterName, err)\n 335→\t\t\t} else {\n 336→\t\t\t\tcclog.Infof(\"Imported cluster config for %s\", clusterName)\n 337→\t\t\t}\n 338→\t\t}\n 339→\n 340→\t\tfor job := range srcBackend.Iter(true) {\n 341→\t\t\tselect {\n 342→\t\t\tcase <-ctx.Done():\n 343→\t\t\t\t// Drain remaining items from iterator to avoid resource leak\n 344→\t\t\t\t// but don't process them\n 345→\t\t\t\treturn\n 346→\t\t\tcase jobs <- job:\n 347→\t\t\t}\n 348→\t\t}\n 349→\t}()\n 350→\n 351→\twg.Wait()\n 352→\tprogress.stop()\n 353→\n 354→\tfinalImported := int(atomic.LoadInt32(&progress.imported))\n 355→\tfinalFailed := int(atomic.LoadInt32(&progress.failed))\n 356→\tfinalSkipped := int(atomic.LoadInt32(&progress.skipped))\n 357→\n 358→\telapsed := time.Since(progress.startTime)\n 359→\n 360→\tif interrupted.Load() {\n 361→\t\tcclog.Warnf(\"Import interrupted after %s: %d jobs imported, %d skipped, %d failed\",\n 362→\t\t\tformatDuration(elapsed), finalImported, finalSkipped, finalFailed)\n 363→\t\treturn finalImported, finalFailed, fmt.Errorf(\"import interrupted by user\")\n 364→\t}\n 365→\n 366→\tcclog.Infof(\"Import completed in %s: %d jobs imported, %d skipped, %d failed\",\n 367→\t\tformatDuration(elapsed), finalImported, finalSkipped, finalFailed)\n 368→\n 369→\tif finalFailed > 0 {\n 370→\t\treturn finalImported, finalFailed, fmt.Errorf(\"%d jobs failed to import\", finalFailed)\n 371→\t}\n 372→\n 373→\treturn finalImported, finalFailed, nil\n 374→}\n 375→\n 376→// parseSourceConfig parses the common kind/path/s3 fields from a config JSON string.\n 377→type sourceConfig struct {\n 378→\tKind string `json:\"kind\"`\n 379→\tPath string `json:\"path\"`\n 380→\tEndpoint string `json:\"endpoint\"`\n 381→\tBucket string `json:\"bucket\"`\n 382→\tAccessKey string `json:\"accessKey\"`\n 383→\tSecretKey string `json:\"secretKey\"`\n 384→\tRegion string `json:\"region\"`\n 385→\tUsePathStyle bool `json:\"usePathStyle\"`\n 386→}\n 387→\n 388→// createParquetTarget creates a ParquetTarget from a parsed config.\n 389→func createParquetTarget(cfg sourceConfig) (pqarchive.ParquetTarget, error) {\n 390→\tswitch cfg.Kind {\n 391→\tcase \"s3\":\n 392→\t\treturn pqarchive.NewS3Target(pqarchive.S3TargetConfig{\n 393→\t\t\tEndpoint: cfg.Endpoint,\n 394→\t\t\tBucket: cfg.Bucket,\n 395→\t\t\tAccessKey: cfg.AccessKey,\n 396→\t\t\tSecretKey: cfg.SecretKey,\n 397→\t\t\tRegion: cfg.Region,\n 398→\t\t\tUsePathStyle: cfg.UsePathStyle,\n 399→\t\t})\n 400→\tdefault:\n 401→\t\treturn pqarchive.NewFileTarget(cfg.Path)\n 402→\t}\n 403→}\n 404→\n 405→// createParquetSource creates a ParquetSource from a parsed config.\n 406→func createParquetSource(cfg sourceConfig) (pqarchive.ParquetSource, error) {\n 407→\tswitch cfg.Kind {\n 408→\tcase \"s3\":\n 409→\t\treturn pqarchive.NewS3ParquetSource(pqarchive.S3TargetConfig{\n 410→\t\t\tEndpoint: cfg.Endpoint,\n 411→\t\t\tBucket: cfg.Bucket,\n 412→\t\t\tAccessKey: cfg.AccessKey,\n 413→\t\t\tSecretKey: cfg.SecretKey,\n 414→\t\t\tRegion: cfg.Region,\n 415→\t\t\tUsePathStyle: cfg.UsePathStyle,\n 416→\t\t})\n 417→\tdefault:\n 418→\t\tif cfg.Path == \"\" {\n 419→\t\t\treturn nil, fmt.Errorf(\"file source: path is required\")\n 420→\t\t}\n 421→\t\treturn pqarchive.NewFileParquetSource(cfg.Path), nil\n 422→\t}\n 423→}\n 424→\n 425→// convertJSONToParquet converts a JSON archive backend to parquet format.\n 426→func convertJSONToParquet(srcBackend archive.ArchiveBackend, dstCfg sourceConfig, maxSizeMB int) error {\n 427→\ttarget, err := createParquetTarget(dstCfg)\n 428→\tif err != nil {\n 429→\t\treturn fmt.Errorf(\"create parquet target: %w\", err)\n 430→\t}\n 431→\n 432→\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n 433→\n 434→\t// Transfer cluster configs\n 435→\tfor _, clusterName := range srcBackend.GetClusters() {\n 436→\t\tclusterCfg, err := srcBackend.LoadClusterCfg(clusterName)\n 437→\t\tif err != nil {\n 438→\t\t\tcclog.Warnf(\"Convert: load cluster config %q: %v\", clusterName, err)\n 439→\t\t\tcontinue\n 440→\t\t}\n 441→\t\tcw.SetClusterConfig(clusterName, clusterCfg)\n 442→\t}\n 443→\n 444→\tconverted := 0\n 445→\tfailed := 0\n 446→\tstartTime := time.Now()\n 447→\n 448→\tfor job := range srcBackend.Iter(true) {\n 449→\t\tif job.Meta == nil {\n 450→\t\t\tcclog.Warn(\"Skipping job with nil metadata\")\n 451→\t\t\tfailed++\n 452→\t\t\tcontinue\n 453→\t\t}\n 454→\t\tif job.Data == nil {\n 455→\t\t\tcclog.Warnf(\"Job %d has no metric data, skipping\", job.Meta.JobID)\n 456→\t\t\tfailed++\n 457→\t\t\tcontinue\n 458→\t\t}\n 459→\n 460→\t\trow, err := pqarchive.JobToParquetRow(job.Meta, job.Data)\n 461→\t\tif err != nil {\n 462→\t\t\tcclog.Warnf(\"Convert job %d: %v\", job.Meta.JobID, err)\n 463→\t\t\tfailed++\n 464→\t\t\tcontinue\n 465→\t\t}\n 466→\t\tif err := cw.AddJob(*row); err != nil {\n 467→\t\t\tcclog.Errorf(\"Add job %d to writer: %v\", job.Meta.JobID, err)\n 468→\t\t\tfailed++\n 469→\t\t\tcontinue\n 470→\t\t}\n 471→\t\tconverted++\n 472→\n 473→\t\tif converted%1000 == 0 {\n 474→\t\t\tcclog.Infof(\"Converted %d jobs so far...\", converted)\n 475→\t\t}\n 476→\t}\n 477→\n 478→\tif err := cw.Close(); err != nil {\n 479→\t\treturn fmt.Errorf(\"close parquet writer: %w\", err)\n 480→\t}\n 481→\n 482→\telapsed := time.Since(startTime)\n 483→\tcclog.Infof(\"JSON->Parquet conversion completed in %s: %d jobs converted, %d failed\",\n 484→\t\tformatDuration(elapsed), converted, failed)\n 485→\treturn nil\n 486→}\n 487→\n 488→// convertParquetToJSON converts a parquet archive to a JSON archive backend.\n 489→func convertParquetToJSON(srcCfg sourceConfig, dstBackend archive.ArchiveBackend) error {\n 490→\tsrc, err := createParquetSource(srcCfg)\n 491→\tif err != nil {\n 492→\t\treturn fmt.Errorf(\"create parquet source: %w\", err)\n 493→\t}\n 494→\n 495→\tclusters, err := src.GetClusters()\n 496→\tif err != nil {\n 497→\t\treturn fmt.Errorf(\"list clusters: %w\", err)\n 498→\t}\n 499→\n 500→\tconverted := 0\n 501→\tfailed := 0\n 502→\tskipped := 0\n 503→\tstartTime := time.Now()\n 504→\n 505→\tfor _, cluster := range clusters {\n 506→\t\t// Transfer cluster config\n 507→\t\tclusterCfg, err := src.ReadClusterConfig(cluster)\n 508→\t\tif err != nil {\n 509→\t\t\tcclog.Warnf(\"Convert: read cluster config %q: %v\", cluster, err)\n 510→\t\t} else {\n 511→\t\t\tif err := dstBackend.StoreClusterCfg(cluster, clusterCfg); err != nil {\n 512→\t\t\t\tcclog.Warnf(\"Convert: store cluster config %q: %v\", cluster, err)\n 513→\t\t\t} else {\n 514→\t\t\t\tcclog.Infof(\"Imported cluster config for %s\", cluster)\n 515→\t\t\t}\n 516→\t\t}\n 517→\n 518→\t\t// Read and convert parquet files\n 519→\t\tfiles, err := src.ListParquetFiles(cluster)\n 520→\t\tif err != nil {\n 521→\t\t\tcclog.Errorf(\"Convert: list parquet files for %q: %v\", cluster, err)\n 522→\t\t\tcontinue\n 523→\t\t}\n 524→\n 525→\t\tfor _, file := range files {\n 526→\t\t\tdata, err := src.ReadFile(file)\n 527→\t\t\tif err != nil {\n 528→\t\t\t\tcclog.Errorf(\"Convert: read file %q: %v\", file, err)\n 529→\t\t\t\tfailed++\n 530→\t\t\t\tcontinue\n 531→\t\t\t}\n 532→\n 533→\t\t\trows, err := pqarchive.ReadParquetFile(data)\n 534→\t\t\tif err != nil {\n 535→\t\t\t\tcclog.Errorf(\"Convert: parse parquet file %q: %v\", file, err)\n 536→\t\t\t\tfailed++\n 537→\t\t\t\tcontinue\n 538→\t\t\t}\n 539→\n 540→\t\t\tcclog.Infof(\"Processing %s: %d jobs\", file, len(rows))\n 541→\n 542→\t\t\tfor _, row := range rows {\n 543→\t\t\t\tmeta, jobData, err := pqarchive.ParquetRowToJob(&row)\n 544→\t\t\t\tif err != nil {\n 545→\t\t\t\t\tcclog.Warnf(\"Convert row to job: %v\", err)\n 546→\t\t\t\t\tfailed++\n 547→\t\t\t\t\tcontinue\n 548→\t\t\t\t}\n 549→\n 550→\t\t\t\tif dstBackend.Exists(meta) {\n 551→\t\t\t\t\tskipped++\n 552→\t\t\t\t\tcontinue\n 553→\t\t\t\t}\n 554→\n 555→\t\t\t\tif err := dstBackend.ImportJob(meta, jobData); err != nil {\n 556→\t\t\t\t\tcclog.Warnf(\"Import job %d: %v\", meta.JobID, err)\n 557→\t\t\t\t\tfailed++\n 558→\t\t\t\t\tcontinue\n 559→\t\t\t\t}\n 560→\t\t\t\tconverted++\n 561→\t\t\t}\n 562→\t\t}\n 563→\t}\n 564→\n 565→\telapsed := time.Since(startTime)\n 566→\tcclog.Infof(\"Parquet->JSON conversion completed in %s: %d jobs converted, %d skipped, %d failed\",\n 567→\t\tformatDuration(elapsed), converted, skipped, failed)\n 568→\treturn nil\n 569→}\n 570→\n 571→func main() {\n 572→\tvar srcPath, flagConfigFile, flagLogLevel, flagRemoveCluster, flagRemoveAfter, flagRemoveBefore string\n 573→\tvar flagSrcConfig, flagDstConfig string\n 574→\tvar flagLogDateTime, flagValidate, flagImport, flagConvert bool\n 575→\tvar flagFormat string\n 576→\tvar flagMaxFileSize int\n 577→\n 578→\tflag.StringVar(&srcPath, \"s\", \"./var/job-archive\", \"Specify the source job archive path. Default is ./var/job-archive\")\n 579→\tflag.BoolVar(&flagLogDateTime, \"logdate\", false, \"Set this flag to add date and time to log messages\")\n 580→\tflag.StringVar(&flagLogLevel, \"loglevel\", \"info\", \"Sets the logging level: `[debug,info,warn (default),err,fatal,crit]`\")\n 581→\tflag.StringVar(&flagConfigFile, \"config\", \"./config.json\", \"Specify alternative path to `config.json`\")\n 582→\tflag.StringVar(&flagRemoveCluster, \"remove-cluster\", \"\", \"Remove cluster from archive and database\")\n 583→\tflag.StringVar(&flagRemoveBefore, \"remove-before\", \"\", \"Remove all jobs with start time before date (Format: 2006-Jan-04)\")\n 584→\tflag.StringVar(&flagRemoveAfter, \"remove-after\", \"\", \"Remove all jobs with start time after date (Format: 2006-Jan-04)\")\n 585→\tflag.BoolVar(&flagValidate, \"validate\", false, \"Set this flag to validate a job archive against the json schema\")\n 586→\tflag.BoolVar(&flagImport, \"import\", false, \"Import jobs from source archive to destination archive\")\n 587→\tflag.BoolVar(&flagConvert, \"convert\", false, \"Convert archive between JSON and Parquet formats\")\n 588→\tflag.StringVar(&flagFormat, \"format\", \"json\", \"Output format for conversion: 'json' or 'parquet'\")\n 589→\tflag.IntVar(&flagMaxFileSize, \"max-file-size\", 512, \"Max parquet file size in MB (only for parquet output)\")\n 590→\tflag.StringVar(&flagSrcConfig, \"src-config\", \"\", \"Source archive backend configuration (JSON), e.g. '{\\\"kind\\\":\\\"file\\\",\\\"path\\\":\\\"./archive\\\"}'\")\n 591→\tflag.StringVar(&flagDstConfig, \"dst-config\", \"\", \"Destination archive backend configuration (JSON), e.g. '{\\\"kind\\\":\\\"sqlite\\\",\\\"dbPath\\\":\\\"./archive.db\\\"}'\")\n 592→\tflag.Parse()\n 593→\n 594→\tarchiveCfg := fmt.Sprintf(\"{\\\"kind\\\": \\\"file\\\",\\\"path\\\": \\\"%s\\\"}\", srcPath)\n 595→\n 596→\tcclog.Init(flagLogLevel, flagLogDateTime)\n 597→\n 598→\t// Handle import mode\n 599→\tif flagImport {\n 600→\t\tif flagSrcConfig == \"\" || flagDstConfig == \"\" {\n 601→\t\t\tcclog.Fatal(\"Both --src-config and --dst-config must be specified for import mode\")\n 602→\t\t}\n 603→\n 604→\t\tcclog.Info(\"Import mode: initializing source and destination backends...\")\n 605→\n 606→\t\t// Initialize source backend\n 607→\t\tsrcBackend, err := archive.InitBackend(json.RawMessage(flagSrcConfig))\n 608→\t\tif err != nil {\n 609→\t\t\tcclog.Fatalf(\"Failed to initialize source backend: %s\", err.Error())\n 610→\t\t}\n 611→\t\tcclog.Info(\"Source backend initialized successfully\")\n 612→\n 613→\t\t// Initialize destination backend\n 614→\t\tdstBackend, err := archive.InitBackend(json.RawMessage(flagDstConfig))\n 615→\t\tif err != nil {\n 616→\t\t\tcclog.Fatalf(\"Failed to initialize destination backend: %s\", err.Error())\n 617→\t\t}\n 618→\t\tcclog.Info(\"Destination backend initialized successfully\")\n 619→\n 620→\t\t// Perform import\n 621→\t\timported, failed, err := importArchive(srcBackend, dstBackend, flagSrcConfig)\n 622→\t\tif err != nil {\n 623→\t\t\tcclog.Errorf(\"Import completed with errors: %s\", err.Error())\n 624→\t\t\tif failed > 0 {\n 625→\t\t\t\tos.Exit(1)\n 626→\t\t\t}\n 627→\t\t}\n 628→\n 629→\t\tcclog.Infof(\"Import finished successfully: %d jobs imported\", imported)\n 630→\t\tos.Exit(0)\n 631→\t}\n 632→\n 633→\t// Handle convert mode\n 634→\tif flagConvert {\n 635→\t\tif flagSrcConfig == \"\" || flagDstConfig == \"\" {\n 636→\t\t\tcclog.Fatal(\"Both --src-config and --dst-config must be specified for convert mode\")\n 637→\t\t}\n 638→\n 639→\t\tvar srcCfg, dstCfg sourceConfig\n 640→\t\tif err := json.Unmarshal([]byte(flagSrcConfig), &srcCfg); err != nil {\n 641→\t\t\tcclog.Fatalf(\"Failed to parse source config: %s\", err.Error())\n 642→\t\t}\n 643→\t\tif err := json.Unmarshal([]byte(flagDstConfig), &dstCfg); err != nil {\n 644→\t\t\tcclog.Fatalf(\"Failed to parse destination config: %s\", err.Error())\n 645→\t\t}\n 646→\n 647→\t\tswitch flagFormat {\n 648→\t\tcase \"parquet\":\n 649→\t\t\t// JSON archive -> Parquet: source is an archive backend\n 650→\t\t\tcclog.Info(\"Convert mode: JSON -> Parquet\")\n 651→\t\t\tsrcBackend, err := archive.InitBackend(json.RawMessage(flagSrcConfig))\n 652→\t\t\tif err != nil {\n 653→\t\t\t\tcclog.Fatalf(\"Failed to initialize source backend: %s\", err.Error())\n 654→\t\t\t}\n 655→\t\t\tif err := convertJSONToParquet(srcBackend, dstCfg, flagMaxFileSize); err != nil {\n 656→\t\t\t\tcclog.Fatalf(\"Conversion failed: %s\", err.Error())\n 657→\t\t\t}\n 658→\t\tcase \"json\":\n 659→\t\t\t// Parquet -> JSON archive: destination is an archive backend\n 660→\t\t\tcclog.Info(\"Convert mode: Parquet -> JSON\")\n 661→\t\t\tdstBackend, err := archive.InitBackend(json.RawMessage(flagDstConfig))\n 662→\t\t\tif err != nil {\n 663→\t\t\t\tcclog.Fatalf(\"Failed to initialize destination backend: %s\", err.Error())\n 664→\t\t\t}\n 665→\t\t\tif err := convertParquetToJSON(srcCfg, dstBackend); err != nil {\n 666→\t\t\t\tcclog.Fatalf(\"Conversion failed: %s\", err.Error())\n 667→\t\t\t}\n 668→\t\tdefault:\n 669→\t\t\tcclog.Fatalf(\"Unknown format %q: must be 'json' or 'parquet'\", flagFormat)\n 670→\t\t}\n 671→\n 672→\t\tcclog.Info(\"Conversion finished successfully\")\n 673→\t\tos.Exit(0)\n 674→\t}\n 675→\n 676→\tccconf.Init(flagConfigFile)\n 677→\n 678→\t// Load and check main configuration\n 679→\tif cfg := ccconf.GetPackageConfig(\"main\"); cfg != nil {\n 680→\t\tconfig.Init(cfg)\n 681→\t} else {\n 682→\t\tcclog.Abort(\"Main configuration must be present\")\n 683→\t}\n 684→\n 685→\tif err := archive.Init(json.RawMessage(archiveCfg)); err != nil {\n 686→\t\tcclog.Fatal(err)\n 687→\t}\n 688→\tar := archive.GetHandle()\n 689→\n 690→\tif flagValidate {\n 691→\t\tconfig.Keys.Validate = true\n 692→\t\tfor job := range ar.Iter(true) {\n 693→\t\t\tcclog.Debugf(\"Validate %s - %d\", job.Meta.Cluster, job.Meta.JobID)\n 694→\t\t}\n 695→\t\tos.Exit(0)\n 696→\t}\n 697→\n 698→\tif flagRemoveBefore != \"\" || flagRemoveAfter != \"\" {\n 699→\t\tar.Clean(parseDate(flagRemoveBefore), parseDate(flagRemoveAfter))\n 700→\t\tos.Exit(0)\n 701→\t}\n 702→\n 703→\tar.Info()\n 704→}\n 705→"}]},"uuid":"5a9245a5-95d9-4fe5-8a60-f8c060ab2c30","timestamp":"2026-03-23T05:10:26.021Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"e95d837e-6996-4365-a046-7166310de4e2","timestamp":"2026-03-23T05:10:26.024Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"a1182af7-dcec-4427-aaf0-422761622ade","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:10:29.726Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01CJR1beLCNL2nGA6dLhrBQJ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XJQWNZBx7deWvZpPSCYkh5","name":"Bash","input":{"command":"grep -r \"SortingWriter\\|NewGenericWriter\" /Users/jan/prg/ClusterCockpit/cc-backend --include=\"*.go\" -B 2 -A 2"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":181,"cache_read_input_tokens":41841,"cache_creation":{"ephemeral_5m_input_tokens":181,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSFVtywh1ZyY3AAfQyn","uuid":"db34bcea-977e-44bb-a10b-6e2b780fd806"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"e9a0cf9a-3551-42c7-97a4-ec5b7e42e410","timestamp":"2026-03-23T05:10:29.727Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"e9a0cf9a-3551-42c7-97a4-ec5b7e42e410","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XJQWNZBx7deWvZpPSCYkh5","type":"tool_result","content":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go-\tvar buf bytes.Buffer\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go:\twriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go-\t\tpq.Compression(&pq.Zstd),\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go:\t\tpq.SortingWriterConfig(pq.SortingColumns(\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go-\t\t\tpq.Ascending(\"cluster\"),\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/nodestate_writer.go-\t\t\tpq.Ascending(\"subcluster\"),\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go-\tvar buf bytes.Buffer\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go:\twriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go-\t\tpq.Compression(&pq.Zstd),\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go:\t\tpq.SortingWriterConfig(pq.SortingColumns(\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go-\t\t\tpq.Ascending(\"sub_cluster\"),\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go-\t\t\tpq.Ascending(\"project\"),\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go-\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go:\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go-\t\tpq.Compression(&pq.Zstd),\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go-\t)","is_error":false}]},"uuid":"e592f362-7921-466b-84b7-d1acf34ff9b5","timestamp":"2026-03-23T05:10:29.949Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"9e40c552-ede5-41ea-a8b5-29ffbe1eca1f","timestamp":"2026-03-23T05:10:29.950Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"9e40c552-ede5-41ea-a8b5-29ffbe1eca1f","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:10:31.230Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01TXAijUQUFXLQvW66uZjuWp","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CFfmyP9RuZbgYdgnfSMkn5","name":"Bash","input":{"command":"grep -i \"parquet\\|pq\" /Users/jan/prg/ClusterCockpit/cc-backend/go.mod"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1109,"cache_read_input_tokens":42022,"cache_creation":{"ephemeral_5m_input_tokens":1109,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSFcdnkQ42pkr2N8k5G","uuid":"a0ccf14c-da5b-4531-851f-cc8f12b802ea"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"d1ee4020-6319-470c-98a0-a44a15af0818","timestamp":"2026-03-23T05:10:31.231Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"d1ee4020-6319-470c-98a0-a44a15af0818","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CFfmyP9RuZbgYdgnfSMkn5","type":"tool_result","content":"\tgithub.com/parquet-go/parquet-go v0.29.0\n\tgithub.com/parquet-go/bitpack v1.0.0 // indirect\n\tgithub.com/parquet-go/jsonlite v1.4.0 // indirect","is_error":false}]},"uuid":"688d57c7-29fb-48d6-962f-2c5e4d9a4ee0","timestamp":"2026-03-23T05:10:31.272Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"d69a3552-f9d0-4421-bada-9598bb45774f","timestamp":"2026-03-23T05:10:31.273Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"d69a3552-f9d0-4421-bada-9598bb45774f","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:10:32.430Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01HKdTxXERUUj4jwt1d59Gkx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Tu3DmHwSno3ikE163Fkst5","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":0,"cache_creation_input_tokens":469,"cache_read_input_tokens":43131,"cache_creation":{"ephemeral_5m_input_tokens":469,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSFiKM3iCQsjdnRgwXd","uuid":"08d6b531-86f1-4f37-b179-f7658eee6182"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"e16e9852-4a35-455a-a189-e19d47fcfc30","timestamp":"2026-03-23T05:10:32.430Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"e16e9852-4a35-455a-a189-e19d47fcfc30","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Tu3DmHwSno3ikE163Fkst5","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 metricstore\n 7→\n 8→import (\n 9→\t\"bufio\"\n 10→\t\"encoding/binary\"\n 11→\t\"encoding/json\"\n 12→\t\"fmt\"\n 13→\t\"os\"\n 14→\t\"path/filepath\"\n 15→\t\"sort\"\n 16→\n 17→\tpq \"github.com/parquet-go/parquet-go\"\n 18→)\n 19→\n 20→// ParquetMetricRow is the long-format schema for archived metric data.\n 21→// One row per (host, metric, scope, scope_id, timestamp) data point.\n 22→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n 23→type ParquetMetricRow struct {\n 24→\tCluster string `parquet:\"cluster\"`\n 25→\tHostname string `parquet:\"hostname\"`\n 26→\tMetric string `parquet:\"metric\"`\n 27→\tScope string `parquet:\"scope\"`\n 28→\tScopeID string `parquet:\"scope_id\"`\n 29→\tTimestamp int64 `parquet:\"timestamp\"`\n 30→\tFrequency int64 `parquet:\"frequency\"`\n 31→\tValue float32 `parquet:\"value\"`\n 32→}\n 33→\n 34→// parseScopeFromName infers scope and scope_id from a child level name.\n 35→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n 36→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n 37→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n 38→func parseScopeFromName(name string) (string, string) {\n 39→\tprefixes := []struct {\n 40→\t\tprefix string\n 41→\t\tscope string\n 42→\t}{\n 43→\t\t{\"socket\", \"socket\"},\n 44→\t\t{\"memoryDomain\", \"memoryDomain\"},\n 45→\t\t{\"core\", \"core\"},\n 46→\t\t{\"hwthread\", \"hwthread\"},\n 47→\t\t{\"cpu\", \"hwthread\"},\n 48→\t\t{\"accelerator\", \"accelerator\"},\n 49→\t}\n 50→\n 51→\tfor _, p := range prefixes {\n 52→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n 53→\t\t\tid := name[len(p.prefix):]\n 54→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n 55→\t\t\t\treturn p.scope, id\n 56→\t\t\t}\n 57→\t\t}\n 58→\t}\n 59→\n 60→\treturn name, \"\"\n 61→}\n 62→\n 63→// parquetArchiveWriter supports incremental writes to a Parquet file.\n 64→// Uses streaming writes to avoid accumulating all rows in memory.\n 65→type parquetArchiveWriter struct {\n 66→\twriter *pq.GenericWriter[ParquetMetricRow]\n 67→\tbw *bufio.Writer\n 68→\tf *os.File\n 69→\tbatch []ParquetMetricRow // reusable batch buffer\n 70→\tcount int\n 71→}\n 72→\n 73→const parquetBatchSize = 1024\n 74→\n 75→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n 76→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n 77→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n 78→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n 79→\t}\n 80→\n 81→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n 82→\tif err != nil {\n 83→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n 84→\t}\n 85→\n 86→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n 87→\n 88→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n 89→\t\tpq.Compression(&pq.Zstd),\n 90→\t)\n 91→\n 92→\treturn &parquetArchiveWriter{\n 93→\t\twriter: writer,\n 94→\t\tbw: bw,\n 95→\t\tf: f,\n 96→\t\tbatch: make([]ParquetMetricRow, 0, parquetBatchSize),\n 97→\t}, nil\n 98→}\n 99→\n 100→// WriteCheckpointFile streams a CheckpointFile tree directly to Parquet rows,\n 101→// writing metrics in sorted order without materializing all rows in memory.\n 102→// Produces one row group per call (typically one host's data).\n 103→func (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n 104→\tw.writeLevel(cf, cluster, hostname, scope, scopeID)\n 105→\n 106→\t// Flush remaining batch\n 107→\tif len(w.batch) > 0 {\n 108→\t\tif _, err := w.writer.Write(w.batch); err != nil {\n 109→\t\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n 110→\t\t}\n 111→\t\tw.count += len(w.batch)\n 112→\t\tw.batch = w.batch[:0]\n 113→\t}\n 114→\n 115→\tif err := w.writer.Flush(); err != nil {\n 116→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n 117→\t}\n 118→\n 119→\treturn nil\n 120→}\n 121→\n 122→// writeLevel recursively writes metrics from a CheckpointFile level.\n 123→// Metric names and child names are sorted for deterministic, compression-friendly output.\n 124→func (w *parquetArchiveWriter) writeLevel(cf *CheckpointFile, cluster, hostname, scope, scopeID string) {\n 125→\t// Sort metric names for deterministic order\n 126→\tmetricNames := make([]string, 0, len(cf.Metrics))\n 127→\tfor name := range cf.Metrics {\n 128→\t\tmetricNames = append(metricNames, name)\n 129→\t}\n 130→\tsort.Strings(metricNames)\n 131→\n 132→\tfor _, metricName := range metricNames {\n 133→\t\tcm := cf.Metrics[metricName]\n 134→\t\tts := cm.Start\n 135→\t\tfor _, v := range cm.Data {\n 136→\t\t\tif !v.IsNaN() {\n 137→\t\t\t\tw.batch = append(w.batch, ParquetMetricRow{\n 138→\t\t\t\t\tCluster: cluster,\n 139→\t\t\t\t\tHostname: hostname,\n 140→\t\t\t\t\tMetric: metricName,\n 141→\t\t\t\t\tScope: scope,\n 142→\t\t\t\t\tScopeID: scopeID,\n 143→\t\t\t\t\tTimestamp: ts,\n 144→\t\t\t\t\tFrequency: cm.Frequency,\n 145→\t\t\t\t\tValue: float32(v),\n 146→\t\t\t\t})\n 147→\n 148→\t\t\t\tif len(w.batch) >= parquetBatchSize {\n 149→\t\t\t\t\tw.writer.Write(w.batch)\n 150→\t\t\t\t\tw.count += len(w.batch)\n 151→\t\t\t\t\tw.batch = w.batch[:0]\n 152→\t\t\t\t}\n 153→\t\t\t}\n 154→\t\t\tts += cm.Frequency\n 155→\t\t}\n 156→\t}\n 157→\n 158→\t// Sort child names for deterministic order\n 159→\tchildNames := make([]string, 0, len(cf.Children))\n 160→\tfor name := range cf.Children {\n 161→\t\tchildNames = append(childNames, name)\n 162→\t}\n 163→\tsort.Strings(childNames)\n 164→\n 165→\tfor _, childName := range childNames {\n 166→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n 167→\t\tw.writeLevel(cf.Children[childName], cluster, hostname, childScope, childScopeID)\n 168→\t}\n 169→}\n 170→\n 171→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n 172→func (w *parquetArchiveWriter) Close() error {\n 173→\tif err := w.writer.Close(); err != nil {\n 174→\t\tw.f.Close()\n 175→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n 176→\t}\n 177→\n 178→\tif err := w.bw.Flush(); err != nil {\n 179→\t\tw.f.Close()\n 180→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n 181→\t}\n 182→\n 183→\treturn w.f.Close()\n 184→}\n 185→\n 186→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n 187→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n 188→// before converting it to Parquet format.\n 189→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n 190→\tf, err := os.Open(filename)\n 191→\tif err != nil {\n 192→\t\treturn nil, err\n 193→\t}\n 194→\tdefer f.Close()\n 195→\n 196→\text := filepath.Ext(filename)\n 197→\tswitch ext {\n 198→\tcase \".json\":\n 199→\t\tcf := &CheckpointFile{}\n 200→\t\tbr := bufio.NewReader(f)\n 201→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n 202→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n 203→\t\t}\n 204→\t\treturn cf, nil\n 205→\n 206→\tcase \".bin\":\n 207→\t\tbr := bufio.NewReader(f)\n 208→\t\tvar magic uint32\n 209→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n 210→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n 211→\t\t}\n 212→\t\tif magic != snapFileMagic {\n 213→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n 214→\t\t}\n 215→\t\tvar fileFrom, fileTo int64\n 216→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n 217→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n 218→\t\t}\n 219→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n 220→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n 221→\t\t}\n 222→\t\tcf, err := readBinaryLevel(br)\n 223→\t\tif err != nil {\n 224→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n 225→\t\t}\n 226→\t\tcf.From = fileFrom\n 227→\t\tcf.To = fileTo\n 228→\t\treturn cf, nil\n 229→\n 230→\tdefault:\n 231→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n 232→\t}\n 233→}\n 234→\n 235→// loadCheckpointFiles reads checkpoint files for a host directory and returns\n 236→// the loaded CheckpointFiles and their filenames. Processes one file at a time\n 237→// to avoid holding all checkpoint data in memory simultaneously.\n 238→func loadCheckpointFiles(dir string, from int64) ([]*CheckpointFile, []string, error) {\n 239→\tentries, err := os.ReadDir(dir)\n 240→\tif err != nil {\n 241→\t\treturn nil, nil, err\n 242→\t}\n 243→\n 244→\tfiles, err := findFiles(entries, from, false)\n 245→\tif err != nil {\n 246→\t\treturn nil, nil, err\n 247→\t}\n 248→\n 249→\tif len(files) == 0 {\n 250→\t\treturn nil, nil, nil\n 251→\t}\n 252→\n 253→\tvar checkpoints []*CheckpointFile\n 254→\tvar processedFiles []string\n 255→\n 256→\tfor _, checkpoint := range files {\n 257→\t\tfilename := filepath.Join(dir, checkpoint)\n 258→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n 259→\t\tif err != nil {\n 260→\t\t\tcontinue\n 261→\t\t}\n 262→\t\tcheckpoints = append(checkpoints, cf)\n 263→\t\tprocessedFiles = append(processedFiles, checkpoint)\n 264→\t}\n 265→\n 266→\treturn checkpoints, processedFiles, nil\n 267→}\n 268→"}]},"uuid":"210feec7-e91a-4d67-b9f9-63c2efb04b36","timestamp":"2026-03-23T05:10:32.449Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"44a3b1a9-631c-45ea-8061-2d615fff07d7","timestamp":"2026-03-23T05:10:32.450Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"0f1dc2eb-c36a-4721-a322-fd49c714d21f","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0161dB9WaPtujUwEDjyYp3n4","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 parquet\n 7→\n 8→import (\n 9→\t\"bytes\"\n 10→\t\"fmt\"\n 11→\t\"time\"\n 12→\n 13→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 14→\tpq \"github.com/parquet-go/parquet-go\"\n 15→)\n 16→\n 17→// NodeStateParquetWriter batches ParquetNodeStateRows and flushes them to a target\n 18→// when the estimated size exceeds maxSizeBytes.\n 19→type NodeStateParquetWriter struct {\n 20→\ttarget ParquetTarget\n 21→\tmaxSizeBytes int64\n 22→\trows []ParquetNodeStateRow\n 23→\tcurrentSize int64\n 24→\tfileCounter int\n 25→\tdatePrefix string\n 26→}\n 27→\n 28→// NewNodeStateParquetWriter creates a new writer for node state parquet files.\n 29→func NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n 30→\treturn &NodeStateParquetWriter{\n 31→\t\ttarget: target,\n 32→\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n 33→\t\tdatePrefix: time.Now().Format(\"2006-01-02\"),\n 34→\t}\n 35→}\n 36→\n 37→// AddRow adds a row to the current batch. If the estimated batch size\n 38→// exceeds the configured maximum, the batch is flushed first.\n 39→func (pw *NodeStateParquetWriter) AddRow(row ParquetNodeStateRow) error {\n 40→\trowSize := estimateNodeStateRowSize(&row)\n 41→\n 42→\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n 43→\t\tif err := pw.Flush(); err != nil {\n 44→\t\t\treturn err\n 45→\t\t}\n 46→\t}\n 47→\n 48→\tpw.rows = append(pw.rows, row)\n 49→\tpw.currentSize += rowSize\n 50→\treturn nil\n 51→}\n 52→\n 53→// Flush writes the current batch to a parquet file on the target.\n 54→func (pw *NodeStateParquetWriter) Flush() error {\n 55→\tif len(pw.rows) == 0 {\n 56→\t\treturn nil\n 57→\t}\n 58→\n 59→\tpw.fileCounter++\n 60→\tfileName := fmt.Sprintf(\"cc-nodestate-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n 61→\n 62→\tdata, err := writeNodeStateParquetBytes(pw.rows)\n 63→\tif err != nil {\n 64→\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n 65→\t}\n 66→\n 67→\tif err := pw.target.WriteFile(fileName, data); err != nil {\n 68→\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n 69→\t}\n 70→\n 71→\tcclog.Infof(\"NodeState retention: wrote %s (%d rows, %d bytes)\", fileName, len(pw.rows), len(data))\n 72→\tpw.rows = pw.rows[:0]\n 73→\tpw.currentSize = 0\n 74→\treturn nil\n 75→}\n 76→\n 77→// Close flushes any remaining rows and finalizes the writer.\n 78→func (pw *NodeStateParquetWriter) Close() error {\n 79→\treturn pw.Flush()\n 80→}\n 81→\n 82→func writeNodeStateParquetBytes(rows []ParquetNodeStateRow) ([]byte, error) {\n 83→\tvar buf bytes.Buffer\n 84→\n 85→\twriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n 86→\t\tpq.Compression(&pq.Zstd),\n 87→\t\tpq.SortingWriterConfig(pq.SortingColumns(\n 88→\t\t\tpq.Ascending(\"cluster\"),\n 89→\t\t\tpq.Ascending(\"subcluster\"),\n 90→\t\t\tpq.Ascending(\"hostname\"),\n 91→\t\t\tpq.Ascending(\"time_stamp\"),\n 92→\t\t)),\n 93→\t)\n 94→\n 95→\tif _, err := writer.Write(rows); err != nil {\n 96→\t\treturn nil, err\n 97→\t}\n 98→\tif err := writer.Close(); err != nil {\n 99→\t\treturn nil, err\n 100→\t}\n 101→\n 102→\treturn buf.Bytes(), nil\n 103→}\n 104→\n 105→func estimateNodeStateRowSize(row *ParquetNodeStateRow) int64 {\n 106→\tsize := int64(100) // fixed numeric fields\n 107→\tsize += int64(len(row.NodeState) + len(row.HealthState) + len(row.HealthMetrics))\n 108→\tsize += int64(len(row.Hostname) + len(row.Cluster) + len(row.SubCluster))\n 109→\treturn size\n 110→}\n 111→"}]},"uuid":"296b8ccc-56cc-4cb9-b400-a60b58484372","timestamp":"2026-03-23T05:10:37.753Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"b571917c-6b32-4006-a3e5-7a4fb63fbab9","timestamp":"2026-03-23T05:10:37.768Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"b571917c-6b32-4006-a3e5-7a4fb63fbab9","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XX83ZWeaTx5Qr6SAYssooF","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 parquet\n 7→\n 8→import (\n 9→\t\"bytes\"\n 10→\t\"context\"\n 11→\t\"encoding/json\"\n 12→\t\"fmt\"\n 13→\t\"io\"\n 14→\t\"os\"\n 15→\t\"path/filepath\"\n 16→\t\"strings\"\n 17→\n 18→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n 19→\t\"github.com/aws/aws-sdk-go-v2/aws\"\n 20→\tawsconfig \"github.com/aws/aws-sdk-go-v2/config\"\n 21→\t\"github.com/aws/aws-sdk-go-v2/credentials\"\n 22→\t\"github.com/aws/aws-sdk-go-v2/service/s3\"\n 23→\tpq \"github.com/parquet-go/parquet-go\"\n 24→)\n 25→\n 26→// ReadParquetFile reads all ParquetJobRow entries from parquet-encoded bytes.\n 27→func ReadParquetFile(data []byte) ([]ParquetJobRow, error) {\n 28→\tfile, err := pq.OpenFile(bytes.NewReader(data), int64(len(data)))\n 29→\tif err != nil {\n 30→\t\treturn nil, fmt.Errorf(\"open parquet: %w\", err)\n 31→\t}\n 32→\n 33→\treader := pq.NewGenericReader[ParquetJobRow](file)\n 34→\tdefer reader.Close()\n 35→\n 36→\tnumRows := file.NumRows()\n 37→\trows := make([]ParquetJobRow, numRows)\n 38→\tn, err := reader.Read(rows)\n 39→\tif err != nil && err != io.EOF {\n 40→\t\treturn nil, fmt.Errorf(\"read parquet rows: %w\", err)\n 41→\t}\n 42→\n 43→\treturn rows[:n], nil\n 44→}\n 45→\n 46→// ParquetSource abstracts reading parquet archives from different storage backends.\n 47→type ParquetSource interface {\n 48→\tGetClusters() ([]string, error)\n 49→\tListParquetFiles(cluster string) ([]string, error)\n 50→\tReadFile(path string) ([]byte, error)\n 51→\tReadClusterConfig(cluster string) (*schema.Cluster, error)\n 52→}\n 53→\n 54→// FileParquetSource reads parquet archives from a local filesystem directory.\n 55→type FileParquetSource struct {\n 56→\tpath string\n 57→}\n 58→\n 59→func NewFileParquetSource(path string) *FileParquetSource {\n 60→\treturn &FileParquetSource{path: path}\n 61→}\n 62→\n 63→func (fs *FileParquetSource) GetClusters() ([]string, error) {\n 64→\tentries, err := os.ReadDir(fs.path)\n 65→\tif err != nil {\n 66→\t\treturn nil, fmt.Errorf(\"read directory: %w\", err)\n 67→\t}\n 68→\n 69→\tvar clusters []string\n 70→\tfor _, e := range entries {\n 71→\t\tif e.IsDir() {\n 72→\t\t\tclusters = append(clusters, e.Name())\n 73→\t\t}\n 74→\t}\n 75→\treturn clusters, nil\n 76→}\n 77→\n 78→func (fs *FileParquetSource) ListParquetFiles(cluster string) ([]string, error) {\n 79→\tdir := filepath.Join(fs.path, cluster)\n 80→\tentries, err := os.ReadDir(dir)\n 81→\tif err != nil {\n 82→\t\treturn nil, fmt.Errorf(\"read cluster directory: %w\", err)\n 83→\t}\n 84→\n 85→\tvar files []string\n 86→\tfor _, e := range entries {\n 87→\t\tif !e.IsDir() && strings.HasSuffix(e.Name(), \".parquet\") {\n 88→\t\t\tfiles = append(files, filepath.Join(cluster, e.Name()))\n 89→\t\t}\n 90→\t}\n 91→\treturn files, nil\n 92→}\n 93→\n 94→func (fs *FileParquetSource) ReadFile(path string) ([]byte, error) {\n 95→\treturn os.ReadFile(filepath.Join(fs.path, path))\n 96→}\n 97→\n 98→func (fs *FileParquetSource) ReadClusterConfig(cluster string) (*schema.Cluster, error) {\n 99→\tdata, err := os.ReadFile(filepath.Join(fs.path, cluster, \"cluster.json\"))\n 100→\tif err != nil {\n 101→\t\treturn nil, fmt.Errorf(\"read cluster.json: %w\", err)\n 102→\t}\n 103→\tvar cfg schema.Cluster\n 104→\tif err := json.Unmarshal(data, &cfg); err != nil {\n 105→\t\treturn nil, fmt.Errorf(\"unmarshal cluster config: %w\", err)\n 106→\t}\n 107→\treturn &cfg, nil\n 108→}\n 109→\n 110→// S3ParquetSource reads parquet archives from an S3-compatible object store.\n 111→type S3ParquetSource struct {\n 112→\tclient *s3.Client\n 113→\tbucket string\n 114→}\n 115→\n 116→func NewS3ParquetSource(cfg S3TargetConfig) (*S3ParquetSource, error) {\n 117→\tif cfg.Bucket == \"\" {\n 118→\t\treturn nil, fmt.Errorf(\"S3 source: empty bucket name\")\n 119→\t}\n 120→\n 121→\tregion := cfg.Region\n 122→\tif region == \"\" {\n 123→\t\tregion = \"us-east-1\"\n 124→\t}\n 125→\n 126→\tawsCfg, err := awsconfig.LoadDefaultConfig(context.Background(),\n 127→\t\tawsconfig.WithRegion(region),\n 128→\t\tawsconfig.WithCredentialsProvider(\n 129→\t\t\tcredentials.NewStaticCredentialsProvider(cfg.AccessKey, cfg.SecretKey, \"\"),\n 130→\t\t),\n 131→\t)\n 132→\tif err != nil {\n 133→\t\treturn nil, fmt.Errorf(\"S3 source: load AWS config: %w\", err)\n 134→\t}\n 135→\n 136→\topts := func(o *s3.Options) {\n 137→\t\tif cfg.Endpoint != \"\" {\n 138→\t\t\to.BaseEndpoint = aws.String(cfg.Endpoint)\n 139→\t\t}\n 140→\t\to.UsePathStyle = cfg.UsePathStyle\n 141→\t}\n 142→\n 143→\tclient := s3.NewFromConfig(awsCfg, opts)\n 144→\treturn &S3ParquetSource{client: client, bucket: cfg.Bucket}, nil\n 145→}\n 146→\n 147→func (ss *S3ParquetSource) GetClusters() ([]string, error) {\n 148→\tctx := context.Background()\n 149→\tpaginator := s3.NewListObjectsV2Paginator(ss.client, &s3.ListObjectsV2Input{\n 150→\t\tBucket: aws.String(ss.bucket),\n 151→\t\tDelimiter: aws.String(\"/\"),\n 152→\t})\n 153→\n 154→\tvar clusters []string\n 155→\tfor paginator.HasMorePages() {\n 156→\t\tpage, err := paginator.NextPage(ctx)\n 157→\t\tif err != nil {\n 158→\t\t\treturn nil, fmt.Errorf(\"S3 source: list clusters: %w\", err)\n 159→\t\t}\n 160→\t\tfor _, prefix := range page.CommonPrefixes {\n 161→\t\t\tif prefix.Prefix != nil {\n 162→\t\t\t\tname := strings.TrimSuffix(*prefix.Prefix, \"/\")\n 163→\t\t\t\tclusters = append(clusters, name)\n 164→\t\t\t}\n 165→\t\t}\n 166→\t}\n 167→\treturn clusters, nil\n 168→}\n 169→\n 170→func (ss *S3ParquetSource) ListParquetFiles(cluster string) ([]string, error) {\n 171→\tctx := context.Background()\n 172→\tprefix := cluster + \"/\"\n 173→\tpaginator := s3.NewListObjectsV2Paginator(ss.client, &s3.ListObjectsV2Input{\n 174→\t\tBucket: aws.String(ss.bucket),\n 175→\t\tPrefix: aws.String(prefix),\n 176→\t})\n 177→\n 178→\tvar files []string\n 179→\tfor paginator.HasMorePages() {\n 180→\t\tpage, err := paginator.NextPage(ctx)\n 181→\t\tif err != nil {\n 182→\t\t\treturn nil, fmt.Errorf(\"S3 source: list parquet files: %w\", err)\n 183→\t\t}\n 184→\t\tfor _, obj := range page.Contents {\n 185→\t\t\tif obj.Key != nil && strings.HasSuffix(*obj.Key, \".parquet\") {\n 186→\t\t\t\tfiles = append(files, *obj.Key)\n 187→\t\t\t}\n 188→\t\t}\n 189→\t}\n 190→\treturn files, nil\n 191→}\n 192→\n 193→func (ss *S3ParquetSource) ReadFile(path string) ([]byte, error) {\n 194→\tctx := context.Background()\n 195→\tresult, err := ss.client.GetObject(ctx, &s3.GetObjectInput{\n 196→\t\tBucket: aws.String(ss.bucket),\n 197→\t\tKey: aws.String(path),\n 198→\t})\n 199→\tif err != nil {\n 200→\t\treturn nil, fmt.Errorf(\"S3 source: get object %q: %w\", path, err)\n 201→\t}\n 202→\tdefer result.Body.Close()\n 203→\treturn io.ReadAll(result.Body)\n 204→}\n 205→\n 206→func (ss *S3ParquetSource) ReadClusterConfig(cluster string) (*schema.Cluster, error) {\n 207→\tdata, err := ss.ReadFile(cluster + \"/cluster.json\")\n 208→\tif err != nil {\n 209→\t\treturn nil, fmt.Errorf(\"read cluster.json: %w\", err)\n 210→\t}\n 211→\tvar cfg schema.Cluster\n 212→\tif err := json.Unmarshal(data, &cfg); err != nil {\n 213→\t\treturn nil, fmt.Errorf(\"unmarshal cluster config: %w\", err)\n 214→\t}\n 215→\treturn &cfg, nil\n 216→}\n 217→"}]},"uuid":"4b5d42f6-259d-4373-a409-0cd3d8099648","timestamp":"2026-03-23T05:10:37.751Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"fdec8c14-ec5e-4942-8adf-f6aea8df9ea3","timestamp":"2026-03-23T05:10:37.768Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"fdec8c14-ec5e-4942-8adf-f6aea8df9ea3","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:10:39.638Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_018q6L6BKoqyFfkPVNZ2zmfu","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015ssXCApPRyBC58y5LnP3Q3","name":"Bash","input":{"command":"grep -n \"WriteArchive\\|Flush\\|writer.Write\" /Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/*.go | head -30"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4668,"cache_read_input_tokens":48196,"cache_creation":{"ephemeral_5m_input_tokens":4668,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSGC6wVk7kPcPyQSZ3f","uuid":"6ffec1db-a3f5-4019-bd08-134b0e507763"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"882731d8-15c6-4bc3-9af7-90868a58cdf7","timestamp":"2026-03-23T05:10:39.639Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"882731d8-15c6-4bc3-9af7-90868a58cdf7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015ssXCApPRyBC58y5LnP3Q3","type":"tool_result","content":"14 matches in 6 files:\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go (1):\n 273: if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go (1):\n 358: return bw.Flush()\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/debug.go (1):\n 111: return w.Flush()\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go (5):\n 106: // Flush remaining batch\n 108: if _, err := w.writer.Write(w.batch); err != nil {\n 115: if err := w.writer.Flush(); err != nil {\n 149: w.writer.Write(w.batch)\n 178: if err := w.bw.Flush(); err != nil {\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive_test.go (2):\n 79: if err := writer.WriteCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\"); err != nil {\n 208: if err := writer.WriteCheckpointFile(cp, \"testcluster\", \"node001\", \"node\", \"\"); err != nil {\n\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go (4):\n 173: ws.w.Flush()\n 230: ws.w.Flush()\n 244: ws.w.Flush()\n 776: if err := bw.Flush(); err != nil {","is_error":false}]},"uuid":"f39e8e87-48ab-43b9-80e9-0d5973798e9d","timestamp":"2026-03-23T05:10:39.696Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"33316235-b518-4894-a90d-09334a4558e1","timestamp":"2026-03-23T05:10:39.696Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"2d9c829c-bac1-466d-9d4f-d1158f015a81","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B946HL9f6LUoFSzbgu1Bgm","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 metricstore\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"errors\"\n 11→\t\"fmt\"\n 12→\t\"os\"\n 13→\t\"path/filepath\"\n 14→\t\"sync\"\n 15→\t\"sync/atomic\"\n 16→\t\"time\"\n 17→\n 18→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 19→)\n 20→\n 21→// Worker for either Archiving or Deleting files\n 22→\n 23→func CleanUp(wg *sync.WaitGroup, ctx context.Context) {\n 24→\tif Keys.Cleanup.Mode == \"archive\" {\n 25→\t\tcclog.Info(\"[METRICSTORE]> enable archive cleanup to parquet\")\n 26→\t\t// Run as Archiver\n 27→\t\tcleanUpWorker(wg, ctx,\n 28→\t\t\tKeys.RetentionInMemory,\n 29→\t\t\t\"archiving\",\n 30→\t\t\tKeys.Cleanup.RootDir,\n 31→\t\t\tfalse,\n 32→\t\t)\n 33→\t} else {\n 34→\t\t// Run as Deleter\n 35→\t\tcleanUpWorker(wg, ctx,\n 36→\t\t\tKeys.RetentionInMemory,\n 37→\t\t\t\"deleting\",\n 38→\t\t\t\"\",\n 39→\t\t\ttrue,\n 40→\t\t)\n 41→\t}\n 42→}\n 43→\n 44→// cleanUpWorker takes simple values to configure what it does\n 45→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n 46→\twg.Go(func() {\n 47→\t\td, err := time.ParseDuration(interval)\n 48→\t\tif err != nil {\n 49→\t\t\tcclog.Fatalf(\"[METRICSTORE]> error parsing %s interval duration: %v\\n\", mode, err)\n 50→\t\t}\n 51→\t\tif d <= 0 {\n 52→\t\t\treturn\n 53→\t\t}\n 54→\n 55→\t\tticker := time.NewTicker(d)\n 56→\t\tdefer ticker.Stop()\n 57→\n 58→\t\tfor {\n 59→\t\t\tselect {\n 60→\t\t\tcase <-ctx.Done():\n 61→\t\t\t\treturn\n 62→\t\t\tcase <-ticker.C:\n 63→\t\t\t\tt := time.Now().Add(-d)\n 64→\t\t\t\tcclog.Infof(\"[METRICSTORE]> start %s checkpoints (older than %s)...\", mode, t.Format(time.RFC3339))\n 65→\n 66→\t\t\t\tn, err := CleanupCheckpoints(Keys.Checkpoints.RootDir, cleanupDir, t.Unix(), delete)\n 67→\n 68→\t\t\t\tif err != nil {\n 69→\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> %s failed: %s\", mode, err.Error())\n 70→\t\t\t\t} else {\n 71→\t\t\t\t\tif delete {\n 72→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoints deleted\", n)\n 73→\t\t\t\t\t} else {\n 74→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoint files archived to parquet\", n)\n 75→\t\t\t\t\t}\n 76→\t\t\t\t}\n 77→\t\t\t}\n 78→\t\t}\n 79→\t})\n 80→}\n 81→\n 82→var ErrNoNewArchiveData error = errors.New(\"all data already archived\")\n 83→\n 84→// CleanupCheckpoints deletes or archives all checkpoint files older than `from`.\n 85→// When archiving, consolidates all hosts per cluster into a single Parquet file.\n 86→func CleanupCheckpoints(checkpointsDir, cleanupDir string, from int64, deleteInstead bool) (int, error) {\n 87→\tif deleteInstead {\n 88→\t\treturn deleteCheckpoints(checkpointsDir, from)\n 89→\t}\n 90→\n 91→\treturn archiveCheckpoints(checkpointsDir, cleanupDir, from)\n 92→}\n 93→\n 94→// deleteCheckpoints removes checkpoint files older than `from` across all clusters/hosts.\n 95→func deleteCheckpoints(checkpointsDir string, from int64) (int, error) {\n 96→\tentries1, err := os.ReadDir(checkpointsDir)\n 97→\tif err != nil {\n 98→\t\treturn 0, err\n 99→\t}\n 100→\n 101→\ttype workItem struct {\n 102→\t\tdir string\n 103→\t\tcluster, host string\n 104→\t}\n 105→\n 106→\tvar wg sync.WaitGroup\n 107→\tn, errs := int32(0), int32(0)\n 108→\twork := make(chan workItem, Keys.NumWorkers)\n 109→\n 110→\twg.Add(Keys.NumWorkers)\n 111→\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n 112→\t\tgo func() {\n 113→\t\t\tdefer wg.Done()\n 114→\t\t\tfor item := range work {\n 115→\t\t\t\tentries, err := os.ReadDir(item.dir)\n 116→\t\t\t\tif err != nil {\n 117→\t\t\t\t\tcclog.Errorf(\"error reading %s/%s: %s\", item.cluster, item.host, err.Error())\n 118→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 119→\t\t\t\t\tcontinue\n 120→\t\t\t\t}\n 121→\n 122→\t\t\t\tfiles, err := findFiles(entries, from, false)\n 123→\t\t\t\tif err != nil {\n 124→\t\t\t\t\tcclog.Errorf(\"error finding files in %s/%s: %s\", item.cluster, item.host, err.Error())\n 125→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 126→\t\t\t\t\tcontinue\n 127→\t\t\t\t}\n 128→\n 129→\t\t\t\tfor _, checkpoint := range files {\n 130→\t\t\t\t\tif err := os.Remove(filepath.Join(item.dir, checkpoint)); err != nil {\n 131→\t\t\t\t\t\tcclog.Errorf(\"error deleting %s/%s/%s: %s\", item.cluster, item.host, checkpoint, err.Error())\n 132→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 133→\t\t\t\t\t} else {\n 134→\t\t\t\t\t\tatomic.AddInt32(&n, 1)\n 135→\t\t\t\t\t}\n 136→\t\t\t\t}\n 137→\t\t\t}\n 138→\t\t}()\n 139→\t}\n 140→\n 141→\tfor _, de1 := range entries1 {\n 142→\t\tentries2, e := os.ReadDir(filepath.Join(checkpointsDir, de1.Name()))\n 143→\t\tif e != nil {\n 144→\t\t\terr = e\n 145→\t\t\tcontinue\n 146→\t\t}\n 147→\n 148→\t\tfor _, de2 := range entries2 {\n 149→\t\t\twork <- workItem{\n 150→\t\t\t\tdir: filepath.Join(checkpointsDir, de1.Name(), de2.Name()),\n 151→\t\t\t\tcluster: de1.Name(),\n 152→\t\t\t\thost: de2.Name(),\n 153→\t\t\t}\n 154→\t\t}\n 155→\t}\n 156→\n 157→\tclose(work)\n 158→\twg.Wait()\n 159→\n 160→\tif err != nil {\n 161→\t\treturn int(n), err\n 162→\t}\n 163→\tif errs > 0 {\n 164→\t\treturn int(n), fmt.Errorf(\"%d errors happened while deleting (%d successes)\", errs, n)\n 165→\t}\n 166→\treturn int(n), nil\n 167→}\n 168→\n 169→// archiveCheckpoints archives checkpoint files to Parquet format.\n 170→// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n 171→// Workers load checkpoint files from disk and send CheckpointFile trees on a\n 172→// back-pressured channel. The main thread streams each tree directly to Parquet\n 173→// rows without materializing all rows in memory.\n 174→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n 175→\tcclog.Info(\"[METRICSTORE]> start archiving checkpoints to parquet\")\n 176→\tstartTime := time.Now()\n 177→\n 178→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n 179→\tif err != nil {\n 180→\t\treturn 0, err\n 181→\t}\n 182→\n 183→\ttotalFiles := 0\n 184→\n 185→\tfor _, clusterEntry := range clusterEntries {\n 186→\t\tif !clusterEntry.IsDir() {\n 187→\t\t\tcontinue\n 188→\t\t}\n 189→\n 190→\t\tcluster := clusterEntry.Name()\n 191→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n 192→\t\tif err != nil {\n 193→\t\t\treturn totalFiles, err\n 194→\t\t}\n 195→\n 196→\t\t// Workers load checkpoint files from disk; main thread writes to parquet.\n 197→\t\ttype hostResult struct {\n 198→\t\t\tcheckpoints []*CheckpointFile\n 199→\t\t\thostname string\n 200→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n 201→\t\t\tdir string // checkpoint directory for this host\n 202→\t\t}\n 203→\n 204→\t\t// Small buffer provides back-pressure: at most NumWorkers+2 results in flight.\n 205→\t\tresults := make(chan hostResult, 2)\n 206→\t\twork := make(chan struct {\n 207→\t\t\tdir, host string\n 208→\t\t}, Keys.NumWorkers)\n 209→\n 210→\t\tvar wg sync.WaitGroup\n 211→\t\terrs := int32(0)\n 212→\n 213→\t\twg.Add(Keys.NumWorkers)\n 214→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n 215→\t\t\tgo func() {\n 216→\t\t\t\tdefer wg.Done()\n 217→\t\t\t\tfor item := range work {\n 218→\t\t\t\t\tcheckpoints, files, err := loadCheckpointFiles(item.dir, from)\n 219→\t\t\t\t\tif err != nil {\n 220→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n 221→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 222→\t\t\t\t\t\tcontinue\n 223→\t\t\t\t\t}\n 224→\t\t\t\t\tif len(checkpoints) > 0 {\n 225→\t\t\t\t\t\tresults <- hostResult{\n 226→\t\t\t\t\t\t\tcheckpoints: checkpoints,\n 227→\t\t\t\t\t\t\thostname: item.host,\n 228→\t\t\t\t\t\t\tfiles: files,\n 229→\t\t\t\t\t\t\tdir: item.dir,\n 230→\t\t\t\t\t\t}\n 231→\t\t\t\t\t}\n 232→\t\t\t\t}\n 233→\t\t\t}()\n 234→\t\t}\n 235→\n 236→\t\tgo func() {\n 237→\t\t\tfor _, hostEntry := range hostEntries {\n 238→\t\t\t\tif !hostEntry.IsDir() {\n 239→\t\t\t\t\tcontinue\n 240→\t\t\t\t}\n 241→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n 242→\t\t\t\twork <- struct {\n 243→\t\t\t\t\tdir, host string\n 244→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n 245→\t\t\t}\n 246→\t\t\tclose(work)\n 247→\t\t\twg.Wait()\n 248→\t\t\tclose(results)\n 249→\t\t}()\n 250→\n 251→\t\t// Open streaming writer and write each host's checkpoint files as a row group\n 252→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n 253→\t\twriter, err := newParquetArchiveWriter(parquetFile)\n 254→\t\tif err != nil {\n 255→\t\t\t// Drain results channel to unblock workers\n 256→\t\t\tfor range results {\n 257→\t\t\t}\n 258→\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n 259→\t\t}\n 260→\n 261→\t\ttype deleteItem struct {\n 262→\t\t\tdir string\n 263→\t\t\tfiles []string\n 264→\t\t}\n 265→\t\tvar toDelete []deleteItem\n 266→\t\twriteErr := error(nil)\n 267→\n 268→\t\tfor r := range results {\n 269→\t\t\tif writeErr == nil {\n 270→\t\t\t\t// Stream each checkpoint file directly to parquet rows.\n 271→\t\t\t\t// Each checkpoint is processed and discarded before the next.\n 272→\t\t\t\tfor _, cf := range r.checkpoints {\n 273→\t\t\t\t\tif err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n 274→\t\t\t\t\t\twriteErr = err\n 275→\t\t\t\t\t\tbreak\n 276→\t\t\t\t\t}\n 277→\t\t\t\t}\n 278→\t\t\t}\n 279→\t\t\t// Always track files for deletion (even if write failed, we still drain)\n 280→\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n 281→\t\t}\n 282→\n 283→\t\tif err := writer.Close(); err != nil && writeErr == nil {\n 284→\t\t\twriteErr = err\n 285→\t\t}\n 286→\n 287→\t\tif errs > 0 {\n 288→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n 289→\t\t}\n 290→\n 291→\t\tif writer.count == 0 {\n 292→\t\t\t// No data written — remove empty file\n 293→\t\t\tos.Remove(parquetFile)\n 294→\t\t\tcontinue\n 295→\t\t}\n 296→\n 297→\t\tif writeErr != nil {\n 298→\t\t\tos.Remove(parquetFile)\n 299→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n 300→\t\t}\n 301→\n 302→\t\t// Delete archived checkpoint files\n 303→\t\tfor _, item := range toDelete {\n 304→\t\t\tfor _, file := range item.files {\n 305→\t\t\t\tfilename := filepath.Join(item.dir, file)\n 306→\t\t\t\tif err := os.Remove(filename); err != nil {\n 307→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n 308→\t\t\t\t} else {\n 309→\t\t\t\t\ttotalFiles++\n 310→\t\t\t\t}\n 311→\t\t\t}\n 312→\t\t}\n 313→\n 314→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n 315→\t\t\twriter.count, totalFiles, cluster, parquetFile)\n 316→\t}\n 317→\n 318→\tcclog.Infof(\"[METRICSTORE]> archiving checkpoints completed in %s (%d files)\", time.Since(startTime).Round(time.Millisecond), totalFiles)\n 319→\treturn totalFiles, nil\n 320→}\n 321→"}]},"uuid":"27213b27-c1ff-4baa-b297-bf190837015d","timestamp":"2026-03-23T05:10:43.358Z"},"type":"agent_progress","prompt":"","agentId":"a364ab7c51b6f5a98"},"toolUseID":"agent_msg_01JGPhgFYB4d688VLqEGPdeJ","parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","uuid":"93546047-4257-4e03-9363-d6e5afd3c93b","timestamp":"2026-03-23T05:10:43.361Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"93546047-4257-4e03-9363-d6e5afd3c93b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","toolUseID":"toolu_01DuefwCcxNqSKQnxU8QYAVi","timestamp":"2026-03-23T05:10:56.995Z","uuid":"974e8683-c3ba-4530-a2f8-6f37848f9d3b","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"020a1b5d-9a6f-4777-b583-b81ce67b011f","isSidechain":false,"promptId":"4c9038e2-c763-4f23-82bf-037c28776776","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DuefwCcxNqSKQnxU8QYAVi","type":"tool_result","content":[{"type":"text","text":"Perfect! Now I have a complete understanding. Let me create a comprehensive summary document for the user:\n\n## Summary: Parquet Archive Writing Investigation\n\nI've thoroughly investigated the parquet writing implementation in ClusterCockpit. Here's what I found regarding row group creation and the 32767 limit issue:\n\n### **1. Parquet Writer Implementation**\n\n#### **Two Main Parquet Writers:**\n\n1. **`pkg/archive/parquet/writer.go` - ParquetWriter** (for job metadata)\n - Batches `ParquetJobRow` objects in memory\n - Flushes to disk when batch size exceeds `maxSizeBytes` (configurable in MB)\n - **Creates ONE parquet file per flush** with sorting applied\n - Used in: retention copy/move services and archive-manager conversion tool\n\n2. **`pkg/metricstore/parquetArchive.go` - parquetArchiveWriter** (for metric data)\n - Streams metric rows directly during archiving\n - **Creates ONE row group per checkpoint file** (via `WriteCheckpointFile()` + `writer.Flush()`)\n - Used in: metric store cleanup/archiving (converts checkpoints to parquet)\n\n#### **Row Group Creation Mechanism:**\n\nThe issue is in `parquetArchive.go`. Here's how row groups are created:\n\n```go\n// Line 103: Called once per checkpoint file\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n \n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n }\n \n // THIS CREATES A ROW GROUP\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n**Critical Problem:** Each call to `writer.Flush()` creates a new row group in the same parquet file. The parquet-go library has a **hard limit of 32767 row groups per file**.\n\n### **2. How the 32767 Limit is Reached**\n\nThe `archiveCheckpoints()` function (line 174-320 in `archive.go`):\n\n1. Creates ONE parquet writer per cluster\n2. For EACH host in the cluster, loads ALL checkpoint files\n3. For EACH checkpoint file, calls `writer.WriteCheckpointFile()` which:\n - Writes metric data to a batch buffer\n - Calls `writer.Flush()` to finalize - **this creates a new row group**\n\n**Example:** If a single cluster has:\n- 100 hosts\n- Each with 500 checkpoint files\n- Total: 100 × 500 = 50,000 flushes = 50,000 row groups\n\nThis **exceeds the 32767 limit**, causing the error.\n\n### **3. Key Code Locations**\n\n**Metric archiving flow:**\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go:174-320` - `archiveCheckpoints()` \n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go:63-184` - `parquetArchiveWriter` implementation\n\n**Parquet library used:**\n- `github.com/parquet-go/parquet-go v0.29.0`\n- The `SortingWriterConfig` is used for job archives, but the metric archive writer doesn't use it\n\n**Job metadata archiving flow:**\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go:20-106` - `ParquetWriter` implementation\n- `/Users/jan/prg/ClusterCockpit/cc-backend/internal/taskmanager/retentionService.go:107-149` - `transferJobsParquet()`\n\n### **4. Buffering/Batching Logic**\n\n**Metric archive:**\n- Batch size: `1024` rows (constant, line 73 in `parquetArchive.go`)\n- Writes batches incrementally during metric traversal\n- **But flushes row group after EVERY checkpoint file** - this is the bottleneck\n\n**Job archive:**\n- Batch size: configurable (default 512 MB, command-line: `-max-file-size`)\n- Size estimated based on JSON fields and metadata\n- **Creates NEW FILES when batch exceeds max size** (not row groups in same file)\n- Much safer approach\n\n### **5. Root Cause Summary**\n\nThe 32767 row group limit is reached in the **metric store archiving** (not job archiving) because:\n\n1. **One file per cluster** - all hosts' metrics go to a single parquet file\n2. **One row group per checkpoint** - every checkpoint triggers a `Flush()` call\n3. **Many checkpoints** - large clusters with many hosts accumulate thousands of checkpoints\n4. Result: Single parquet file accumulates too many row groups\n\n### **File Paths for Reference**\n\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go` - problematic writer\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go` - archiving orchestration\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go` - safer job writer (uses separate files)\n- `/Users/jan/prg/ClusterCockpit/cc-backend/internal/taskmanager/retentionService.go` - retention service integration"},{"type":"text","text":"agentId: a364ab7c51b6f5a98 (use SendMessage with to: 'a364ab7c51b6f5a98' to continue this agent)\n<usage>total_tokens: 59464\ntool_uses: 22\nduration_ms: 44506</usage>"}]}]},"uuid":"11670761-efb7-4de9-b0de-4af582682db7","timestamp":"2026-03-23T05:10:56.994Z","toolUseResult":{"status":"completed","prompt":"Investigate how parquet archives are written in this codebase. I need to understand:\n\n1. The parquet writer implementation - how row groups are created and flushed\n2. How metric data is structured into parquet rows/row groups\n3. Any buffering or batching logic for parquet writes\n\nKey areas to explore:\n- `pkg/archive/parquet/` directory - the parquet writer implementation\n- Any parquet-related code in `pkg/metricstore/`\n- Look for how `WriteArchive`, `NewWriter`, row group flushing, etc. work\n\nThe error is: \"the limit of 32767 row groups has been reached\" - so I need to understand what triggers new row groups and why there could be so many.","agentId":"a364ab7c51b6f5a98","content":[{"type":"text","text":"Perfect! Now I have a complete understanding. Let me create a comprehensive summary document for the user:\n\n## Summary: Parquet Archive Writing Investigation\n\nI've thoroughly investigated the parquet writing implementation in ClusterCockpit. Here's what I found regarding row group creation and the 32767 limit issue:\n\n### **1. Parquet Writer Implementation**\n\n#### **Two Main Parquet Writers:**\n\n1. **`pkg/archive/parquet/writer.go` - ParquetWriter** (for job metadata)\n - Batches `ParquetJobRow` objects in memory\n - Flushes to disk when batch size exceeds `maxSizeBytes` (configurable in MB)\n - **Creates ONE parquet file per flush** with sorting applied\n - Used in: retention copy/move services and archive-manager conversion tool\n\n2. **`pkg/metricstore/parquetArchive.go` - parquetArchiveWriter** (for metric data)\n - Streams metric rows directly during archiving\n - **Creates ONE row group per checkpoint file** (via `WriteCheckpointFile()` + `writer.Flush()`)\n - Used in: metric store cleanup/archiving (converts checkpoints to parquet)\n\n#### **Row Group Creation Mechanism:**\n\nThe issue is in `parquetArchive.go`. Here's how row groups are created:\n\n```go\n// Line 103: Called once per checkpoint file\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n \n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n }\n \n // THIS CREATES A ROW GROUP\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n**Critical Problem:** Each call to `writer.Flush()` creates a new row group in the same parquet file. The parquet-go library has a **hard limit of 32767 row groups per file**.\n\n### **2. How the 32767 Limit is Reached**\n\nThe `archiveCheckpoints()` function (line 174-320 in `archive.go`):\n\n1. Creates ONE parquet writer per cluster\n2. For EACH host in the cluster, loads ALL checkpoint files\n3. For EACH checkpoint file, calls `writer.WriteCheckpointFile()` which:\n - Writes metric data to a batch buffer\n - Calls `writer.Flush()` to finalize - **this creates a new row group**\n\n**Example:** If a single cluster has:\n- 100 hosts\n- Each with 500 checkpoint files\n- Total: 100 × 500 = 50,000 flushes = 50,000 row groups\n\nThis **exceeds the 32767 limit**, causing the error.\n\n### **3. Key Code Locations**\n\n**Metric archiving flow:**\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go:174-320` - `archiveCheckpoints()` \n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go:63-184` - `parquetArchiveWriter` implementation\n\n**Parquet library used:**\n- `github.com/parquet-go/parquet-go v0.29.0`\n- The `SortingWriterConfig` is used for job archives, but the metric archive writer doesn't use it\n\n**Job metadata archiving flow:**\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go:20-106` - `ParquetWriter` implementation\n- `/Users/jan/prg/ClusterCockpit/cc-backend/internal/taskmanager/retentionService.go:107-149` - `transferJobsParquet()`\n\n### **4. Buffering/Batching Logic**\n\n**Metric archive:**\n- Batch size: `1024` rows (constant, line 73 in `parquetArchive.go`)\n- Writes batches incrementally during metric traversal\n- **But flushes row group after EVERY checkpoint file** - this is the bottleneck\n\n**Job archive:**\n- Batch size: configurable (default 512 MB, command-line: `-max-file-size`)\n- Size estimated based on JSON fields and metadata\n- **Creates NEW FILES when batch exceeds max size** (not row groups in same file)\n- Much safer approach\n\n### **5. Root Cause Summary**\n\nThe 32767 row group limit is reached in the **metric store archiving** (not job archiving) because:\n\n1. **One file per cluster** - all hosts' metrics go to a single parquet file\n2. **One row group per checkpoint** - every checkpoint triggers a `Flush()` call\n3. **Many checkpoints** - large clusters with many hosts accumulate thousands of checkpoints\n4. Result: Single parquet file accumulates too many row groups\n\n### **File Paths for Reference**\n\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go` - problematic writer\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go` - archiving orchestration\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/archive/parquet/writer.go` - safer job writer (uses separate files)\n- `/Users/jan/prg/ClusterCockpit/cc-backend/internal/taskmanager/retentionService.go` - retention service integration"}],"totalDurationMs":44506,"totalTokens":59464,"totalToolUseCount":22,"usage":{"input_tokens":0,"cache_creation_input_tokens":4084,"cache_read_input_tokens":53971,"output_tokens":1409,"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":4084},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"020a1b5d-9a6f-4777-b583-b81ce67b011f","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"98ee4a18-3258-4ffe-a5ef-1821eeb9f7bc","isSidechain":false,"promptId":"4c9038e2-c763-4f23-82bf-037c28776776","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AtiuHeVgX9u4UJteRJPYWu","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 metricstore\n 7→\n 8→import (\n 9→\t\"bufio\"\n 10→\t\"encoding/binary\"\n 11→\t\"encoding/json\"\n 12→\t\"fmt\"\n 13→\t\"os\"\n 14→\t\"path/filepath\"\n 15→\t\"sort\"\n 16→\n 17→\tpq \"github.com/parquet-go/parquet-go\"\n 18→)\n 19→\n 20→// ParquetMetricRow is the long-format schema for archived metric data.\n 21→// One row per (host, metric, scope, scope_id, timestamp) data point.\n 22→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n 23→type ParquetMetricRow struct {\n 24→\tCluster string `parquet:\"cluster\"`\n 25→\tHostname string `parquet:\"hostname\"`\n 26→\tMetric string `parquet:\"metric\"`\n 27→\tScope string `parquet:\"scope\"`\n 28→\tScopeID string `parquet:\"scope_id\"`\n 29→\tTimestamp int64 `parquet:\"timestamp\"`\n 30→\tFrequency int64 `parquet:\"frequency\"`\n 31→\tValue float32 `parquet:\"value\"`\n 32→}\n 33→\n 34→// parseScopeFromName infers scope and scope_id from a child level name.\n 35→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n 36→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n 37→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n 38→func parseScopeFromName(name string) (string, string) {\n 39→\tprefixes := []struct {\n 40→\t\tprefix string\n 41→\t\tscope string\n 42→\t}{\n 43→\t\t{\"socket\", \"socket\"},\n 44→\t\t{\"memoryDomain\", \"memoryDomain\"},\n 45→\t\t{\"core\", \"core\"},\n 46→\t\t{\"hwthread\", \"hwthread\"},\n 47→\t\t{\"cpu\", \"hwthread\"},\n 48→\t\t{\"accelerator\", \"accelerator\"},\n 49→\t}\n 50→\n 51→\tfor _, p := range prefixes {\n 52→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n 53→\t\t\tid := name[len(p.prefix):]\n 54→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n 55→\t\t\t\treturn p.scope, id\n 56→\t\t\t}\n 57→\t\t}\n 58→\t}\n 59→\n 60→\treturn name, \"\"\n 61→}\n 62→\n 63→// parquetArchiveWriter supports incremental writes to a Parquet file.\n 64→// Uses streaming writes to avoid accumulating all rows in memory.\n 65→type parquetArchiveWriter struct {\n 66→\twriter *pq.GenericWriter[ParquetMetricRow]\n 67→\tbw *bufio.Writer\n 68→\tf *os.File\n 69→\tbatch []ParquetMetricRow // reusable batch buffer\n 70→\tcount int\n 71→}\n 72→\n 73→const parquetBatchSize = 1024\n 74→\n 75→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n 76→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n 77→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n 78→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n 79→\t}\n 80→\n 81→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n 82→\tif err != nil {\n 83→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n 84→\t}\n 85→\n 86→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n 87→\n 88→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n 89→\t\tpq.Compression(&pq.Zstd),\n 90→\t)\n 91→\n 92→\treturn &parquetArchiveWriter{\n 93→\t\twriter: writer,\n 94→\t\tbw: bw,\n 95→\t\tf: f,\n 96→\t\tbatch: make([]ParquetMetricRow, 0, parquetBatchSize),\n 97→\t}, nil\n 98→}\n 99→\n 100→// WriteCheckpointFile streams a CheckpointFile tree directly to Parquet rows,\n 101→// writing metrics in sorted order without materializing all rows in memory.\n 102→// Produces one row group per call (typically one host's data).\n 103→func (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n 104→\tw.writeLevel(cf, cluster, hostname, scope, scopeID)\n 105→\n 106→\t// Flush remaining batch\n 107→\tif len(w.batch) > 0 {\n 108→\t\tif _, err := w.writer.Write(w.batch); err != nil {\n 109→\t\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n 110→\t\t}\n 111→\t\tw.count += len(w.batch)\n 112→\t\tw.batch = w.batch[:0]\n 113→\t}\n 114→\n 115→\tif err := w.writer.Flush(); err != nil {\n 116→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n 117→\t}\n 118→\n 119→\treturn nil\n 120→}\n 121→\n 122→// writeLevel recursively writes metrics from a CheckpointFile level.\n 123→// Metric names and child names are sorted for deterministic, compression-friendly output.\n 124→func (w *parquetArchiveWriter) writeLevel(cf *CheckpointFile, cluster, hostname, scope, scopeID string) {\n 125→\t// Sort metric names for deterministic order\n 126→\tmetricNames := make([]string, 0, len(cf.Metrics))\n 127→\tfor name := range cf.Metrics {\n 128→\t\tmetricNames = append(metricNames, name)\n 129→\t}\n 130→\tsort.Strings(metricNames)\n 131→\n 132→\tfor _, metricName := range metricNames {\n 133→\t\tcm := cf.Metrics[metricName]\n 134→\t\tts := cm.Start\n 135→\t\tfor _, v := range cm.Data {\n 136→\t\t\tif !v.IsNaN() {\n 137→\t\t\t\tw.batch = append(w.batch, ParquetMetricRow{\n 138→\t\t\t\t\tCluster: cluster,\n 139→\t\t\t\t\tHostname: hostname,\n 140→\t\t\t\t\tMetric: metricName,\n 141→\t\t\t\t\tScope: scope,\n 142→\t\t\t\t\tScopeID: scopeID,\n 143→\t\t\t\t\tTimestamp: ts,\n 144→\t\t\t\t\tFrequency: cm.Frequency,\n 145→\t\t\t\t\tValue: float32(v),\n 146→\t\t\t\t})\n 147→\n 148→\t\t\t\tif len(w.batch) >= parquetBatchSize {\n 149→\t\t\t\t\tw.writer.Write(w.batch)\n 150→\t\t\t\t\tw.count += len(w.batch)\n 151→\t\t\t\t\tw.batch = w.batch[:0]\n 152→\t\t\t\t}\n 153→\t\t\t}\n 154→\t\t\tts += cm.Frequency\n 155→\t\t}\n 156→\t}\n 157→\n 158→\t// Sort child names for deterministic order\n 159→\tchildNames := make([]string, 0, len(cf.Children))\n 160→\tfor name := range cf.Children {\n 161→\t\tchildNames = append(childNames, name)\n 162→\t}\n 163→\tsort.Strings(childNames)\n 164→\n 165→\tfor _, childName := range childNames {\n 166→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n 167→\t\tw.writeLevel(cf.Children[childName], cluster, hostname, childScope, childScopeID)\n 168→\t}\n 169→}\n 170→\n 171→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n 172→func (w *parquetArchiveWriter) Close() error {\n 173→\tif err := w.writer.Close(); err != nil {\n 174→\t\tw.f.Close()\n 175→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n 176→\t}\n 177→\n 178→\tif err := w.bw.Flush(); err != nil {\n 179→\t\tw.f.Close()\n 180→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n 181→\t}\n 182→\n 183→\treturn w.f.Close()\n 184→}\n 185→\n 186→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n 187→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n 188→// before converting it to Parquet format.\n 189→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n 190→\tf, err := os.Open(filename)\n 191→\tif err != nil {\n 192→\t\treturn nil, err\n 193→\t}\n 194→\tdefer f.Close()\n 195→\n 196→\text := filepath.Ext(filename)\n 197→\tswitch ext {\n 198→\tcase \".json\":\n 199→\t\tcf := &CheckpointFile{}\n 200→\t\tbr := bufio.NewReader(f)\n 201→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n 202→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n 203→\t\t}\n 204→\t\treturn cf, nil\n 205→\n 206→\tcase \".bin\":\n 207→\t\tbr := bufio.NewReader(f)\n 208→\t\tvar magic uint32\n 209→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n 210→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n 211→\t\t}\n 212→\t\tif magic != snapFileMagic {\n 213→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n 214→\t\t}\n 215→\t\tvar fileFrom, fileTo int64\n 216→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n 217→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n 218→\t\t}\n 219→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n 220→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n 221→\t\t}\n 222→\t\tcf, err := readBinaryLevel(br)\n 223→\t\tif err != nil {\n 224→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n 225→\t\t}\n 226→\t\tcf.From = fileFrom\n 227→\t\tcf.To = fileTo\n 228→\t\treturn cf, nil\n 229→\n 230→\tdefault:\n 231→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n 232→\t}\n 233→}\n 234→\n 235→// loadCheckpointFiles reads checkpoint files for a host directory and returns\n 236→// the loaded CheckpointFiles and their filenames. Processes one file at a time\n 237→// to avoid holding all checkpoint data in memory simultaneously.\n 238→func loadCheckpointFiles(dir string, from int64) ([]*CheckpointFile, []string, error) {\n 239→\tentries, err := os.ReadDir(dir)\n 240→\tif err != nil {\n 241→\t\treturn nil, nil, err\n 242→\t}\n 243→\n 244→\tfiles, err := findFiles(entries, from, false)\n 245→\tif err != nil {\n 246→\t\treturn nil, nil, err\n 247→\t}\n 248→\n 249→\tif len(files) == 0 {\n 250→\t\treturn nil, nil, nil\n 251→\t}\n 252→\n 253→\tvar checkpoints []*CheckpointFile\n 254→\tvar processedFiles []string\n 255→\n 256→\tfor _, checkpoint := range files {\n 257→\t\tfilename := filepath.Join(dir, checkpoint)\n 258→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n 259→\t\tif err != nil {\n 260→\t\t\tcontinue\n 261→\t\t}\n 262→\t\tcheckpoints = append(checkpoints, cf)\n 263→\t\tprocessedFiles = append(processedFiles, checkpoint)\n 264→\t}\n 265→\n 266→\treturn checkpoints, processedFiles, nil\n 267→}\n 268→"}]},"uuid":"05e7fdbd-d994-4f81-bbca-42e16f640fb1","timestamp":"2026-03-23T05:11:00.855Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage metricstore\n\nimport (\n\t\"bufio\"\n\t\"encoding/binary\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"sort\"\n\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\n// ParquetMetricRow is the long-format schema for archived metric data.\n// One row per (host, metric, scope, scope_id, timestamp) data point.\n// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\ntype ParquetMetricRow struct {\n\tCluster string `parquet:\"cluster\"`\n\tHostname string `parquet:\"hostname\"`\n\tMetric string `parquet:\"metric\"`\n\tScope string `parquet:\"scope\"`\n\tScopeID string `parquet:\"scope_id\"`\n\tTimestamp int64 `parquet:\"timestamp\"`\n\tFrequency int64 `parquet:\"frequency\"`\n\tValue float32 `parquet:\"value\"`\n}\n\n// parseScopeFromName infers scope and scope_id from a child level name.\n// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\nfunc parseScopeFromName(name string) (string, string) {\n\tprefixes := []struct {\n\t\tprefix string\n\t\tscope string\n\t}{\n\t\t{\"socket\", \"socket\"},\n\t\t{\"memoryDomain\", \"memoryDomain\"},\n\t\t{\"core\", \"core\"},\n\t\t{\"hwthread\", \"hwthread\"},\n\t\t{\"cpu\", \"hwthread\"},\n\t\t{\"accelerator\", \"accelerator\"},\n\t}\n\n\tfor _, p := range prefixes {\n\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n\t\t\tid := name[len(p.prefix):]\n\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n\t\t\t\treturn p.scope, id\n\t\t\t}\n\t\t}\n\t}\n\n\treturn name, \"\"\n}\n\n// parquetArchiveWriter supports incremental writes to a Parquet file.\n// Uses streaming writes to avoid accumulating all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw *bufio.Writer\n\tf *os.File\n\tbatch []ParquetMetricRow // reusable batch buffer\n\tcount int\n}\n\nconst parquetBatchSize = 1024\n\n// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n\t}\n\n\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\n\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n\n\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n\t\tpq.Compression(&pq.Zstd),\n\t)\n\n\treturn &parquetArchiveWriter{\n\t\twriter: writer,\n\t\tbw: bw,\n\t\tf: f,\n\t\tbatch: make([]ParquetMetricRow, 0, parquetBatchSize),\n\t}, nil\n}\n\n// WriteCheckpointFile streams a CheckpointFile tree directly to Parquet rows,\n// writing metrics in sorted order without materializing all rows in memory.\n// Produces one row group per call (typically one host's data).\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n\tw.writeLevel(cf, cluster, hostname, scope, scopeID)\n\n\t// Flush remaining batch\n\tif len(w.batch) > 0 {\n\t\tif _, err := w.writer.Write(w.batch); err != nil {\n\t\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t\t}\n\t\tw.count += len(w.batch)\n\t\tw.batch = w.batch[:0]\n\t}\n\n\tif err := w.writer.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n\t}\n\n\treturn nil\n}\n\n// writeLevel recursively writes metrics from a CheckpointFile level.\n// Metric names and child names are sorted for deterministic, compression-friendly output.\nfunc (w *parquetArchiveWriter) writeLevel(cf *CheckpointFile, cluster, hostname, scope, scopeID string) {\n\t// Sort metric names for deterministic order\n\tmetricNames := make([]string, 0, len(cf.Metrics))\n\tfor name := range cf.Metrics {\n\t\tmetricNames = append(metricNames, name)\n\t}\n\tsort.Strings(metricNames)\n\n\tfor _, metricName := range metricNames {\n\t\tcm := cf.Metrics[metricName]\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\tw.batch = append(w.batch, ParquetMetricRow{\n\t\t\t\t\tCluster: cluster,\n\t\t\t\t\tHostname: hostname,\n\t\t\t\t\tMetric: metricName,\n\t\t\t\t\tScope: scope,\n\t\t\t\t\tScopeID: scopeID,\n\t\t\t\t\tTimestamp: ts,\n\t\t\t\t\tFrequency: cm.Frequency,\n\t\t\t\t\tValue: float32(v),\n\t\t\t\t})\n\n\t\t\t\tif len(w.batch) >= parquetBatchSize {\n\t\t\t\t\tw.writer.Write(w.batch)\n\t\t\t\t\tw.count += len(w.batch)\n\t\t\t\t\tw.batch = w.batch[:0]\n\t\t\t\t}\n\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\t// Sort child names for deterministic order\n\tchildNames := make([]string, 0, len(cf.Children))\n\tfor name := range cf.Children {\n\t\tchildNames = append(childNames, name)\n\t}\n\tsort.Strings(childNames)\n\n\tfor _, childName := range childNames {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\tw.writeLevel(cf.Children[childName], cluster, hostname, childScope, childScopeID)\n\t}\n}\n\n// Close finalises the Parquet file (footer, buffered I/O, file handle).\nfunc (w *parquetArchiveWriter) Close() error {\n\tif err := w.writer.Close(); err != nil {\n\t\tw.f.Close()\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := w.bw.Flush(); err != nil {\n\t\tw.f.Close()\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn w.f.Close()\n}\n\n// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n// before converting it to Parquet format.\nfunc loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n\tf, err := os.Open(filename)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tdefer f.Close()\n\n\text := filepath.Ext(filename)\n\tswitch ext {\n\tcase \".json\":\n\t\tcf := &CheckpointFile{}\n\t\tbr := bufio.NewReader(f)\n\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n\t\t}\n\t\treturn cf, nil\n\n\tcase \".bin\":\n\t\tbr := bufio.NewReader(f)\n\t\tvar magic uint32\n\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n\t\t}\n\t\tif magic != snapFileMagic {\n\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n\t\t}\n\t\tvar fileFrom, fileTo int64\n\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n\t\t}\n\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n\t\t}\n\t\tcf, err := readBinaryLevel(br)\n\t\tif err != nil {\n\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n\t\t}\n\t\tcf.From = fileFrom\n\t\tcf.To = fileTo\n\t\treturn cf, nil\n\n\tdefault:\n\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n\t}\n}\n\n// loadCheckpointFiles reads checkpoint files for a host directory and returns\n// the loaded CheckpointFiles and their filenames. Processes one file at a time\n// to avoid holding all checkpoint data in memory simultaneously.\nfunc loadCheckpointFiles(dir string, from int64) ([]*CheckpointFile, []string, error) {\n\tentries, err := os.ReadDir(dir)\n\tif err != nil {\n\t\treturn nil, nil, err\n\t}\n\n\tfiles, err := findFiles(entries, from, false)\n\tif err != nil {\n\t\treturn nil, nil, err\n\t}\n\n\tif len(files) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\tvar checkpoints []*CheckpointFile\n\tvar processedFiles []string\n\n\tfor _, checkpoint := range files {\n\t\tfilename := filepath.Join(dir, checkpoint)\n\t\tcf, err := loadCheckpointFileFromDisk(filename)\n\t\tif err != nil {\n\t\t\tcontinue\n\t\t}\n\t\tcheckpoints = append(checkpoints, cf)\n\t\tprocessedFiles = append(processedFiles, checkpoint)\n\t}\n\n\treturn checkpoints, processedFiles, nil\n}\n","numLines":268,"startLine":1,"totalLines":268}},"sourceToolAssistantUUID":"98ee4a18-3258-4ffe-a5ef-1821eeb9f7bc","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"05e7fdbd-d994-4f81-bbca-42e16f640fb1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AywFyehZf2Ne6jcf86zbv2","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3708,"cache_read_input_tokens":26549,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3708},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZKSHtsfB2rcYQ5AnJ3if","type":"assistant","uuid":"712b0736-1cf2-4915-b825-dbef0cd35f0c","timestamp":"2026-03-23T05:11:09.051Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"712b0736-1cf2-4915-b825-dbef0cd35f0c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AywFyehZf2Ne6jcf86zbv2","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have a clear understanding of the issue. Let me launch a Plan agent to design the fix."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3708,"cache_read_input_tokens":26549,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3708},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZKSHtsfB2rcYQ5AnJ3if","type":"assistant","uuid":"0e94b9b4-9140-4a62-9bf2-d7fce8f5e16d","timestamp":"2026-03-23T05:11:09.465Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"0e94b9b4-9140-4a62-9bf2-d7fce8f5e16d","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AywFyehZf2Ne6jcf86zbv2","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01U4xejxv1iKPYqAB72CNr5W","name":"Agent","input":{"subagent_type":"Plan","description":"Plan parquet row group fix","prompt":"Design a fix for a parquet row group limit issue in the metric store archiver.\n\n## Problem\n\nThe error is: \"the limit of 32767 row groups has been reached\"\n\nThis happens in `pkg/metricstore/archive.go:archiveCheckpoints()` which creates ONE parquet file per cluster. For each host's checkpoint file, `WriteCheckpointFile()` in `pkg/metricstore/parquetArchive.go` calls `writer.Flush()`, creating one row group per checkpoint file.\n\nFor large clusters like \"fritz\" with many hosts (e.g., 1000+) and multiple checkpoint files per host, total flushes easily exceed 32767.\n\n## Current flow (archive.go lines 268-280):\n\n```go\nfor r := range results {\n for _, cf := range r.checkpoints {\n // Each call creates a row group via Flush()\n writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\")\n }\n}\n```\n\n## WriteCheckpointFile (parquetArchive.go lines 103-120):\n\n```go\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, ...) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n w.count += len(w.batch)\n w.batch = w.batch[:0]\n }\n // THIS creates a new row group every time\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n## Design constraints\n\n- The parquet-go library hard-limits row groups to 32767 per file\n- We want good compression (data sorted by cluster, hostname, metric, timestamp)\n- Don't accumulate all rows in memory — streaming is important\n- Performance: this is HPC monitoring at scale\n\n## Possible approaches\n\n1. **Remove per-checkpoint Flush, flush periodically instead**: Instead of flushing after every checkpoint file, flush after accumulating a certain number of rows (e.g., every 100k rows or every N checkpoints). This reduces row groups dramatically while still bounding memory.\n\n2. **Split into multiple parquet files**: When approaching the row group limit, close the current file and open a new one.\n\n3. **Flush per host instead of per checkpoint**: Since multiple checkpoints can belong to the same host, only flush once per host rather than per checkpoint file.\n\nWhich approach is best? Consider that:\n- A host may have 1 to ~hundreds of checkpoint files\n- A cluster may have ~100 to ~3000+ hosts\n- Flushing per host would give at most ~3000 row groups (within limit for most clusters)\n- But combining approaches 1+2 would be most robust\n\nPlease design the recommended implementation approach with specific code changes needed."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3708,"cache_read_input_tokens":26549,"output_tokens":1067,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3708,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZKSHtsfB2rcYQ5AnJ3if","type":"assistant","uuid":"ce620e78-df86-4300-a26d-b30ccc052b1c","timestamp":"2026-03-23T05:11:22.827Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"ce620e78-df86-4300-a26d-b30ccc052b1c","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PreToolUse","hookName":"PreToolUse:Agent","command":"entire hooks claude-code pre-task"},"toolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"efc26d57-d1ef-4f93-8f1f-bf04164736fe","timestamp":"2026-03-23T05:11:22.830Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"efc26d57-d1ef-4f93-8f1f-bf04164736fe","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"Design a fix for a parquet row group limit issue in the metric store archiver.\n\n## Problem\n\nThe error is: \"the limit of 32767 row groups has been reached\"\n\nThis happens in `pkg/metricstore/archive.go:archiveCheckpoints()` which creates ONE parquet file per cluster. For each host's checkpoint file, `WriteCheckpointFile()` in `pkg/metricstore/parquetArchive.go` calls `writer.Flush()`, creating one row group per checkpoint file.\n\nFor large clusters like \"fritz\" with many hosts (e.g., 1000+) and multiple checkpoint files per host, total flushes easily exceed 32767.\n\n## Current flow (archive.go lines 268-280):\n\n```go\nfor r := range results {\n for _, cf := range r.checkpoints {\n // Each call creates a row group via Flush()\n writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\")\n }\n}\n```\n\n## WriteCheckpointFile (parquetArchive.go lines 103-120):\n\n```go\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, ...) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n w.count += len(w.batch)\n w.batch = w.batch[:0]\n }\n // THIS creates a new row group every time\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n## Design constraints\n\n- The parquet-go library hard-limits row groups to 32767 per file\n- We want good compression (data sorted by cluster, hostname, metric, timestamp)\n- Don't accumulate all rows in memory — streaming is important\n- Performance: this is HPC monitoring at scale\n\n## Possible approaches\n\n1. **Remove per-checkpoint Flush, flush periodically instead**: Instead of flushing after every checkpoint file, flush after accumulating a certain number of rows (e.g., every 100k rows or every N checkpoints). This reduces row groups dramatically while still bounding memory.\n\n2. **Split into multiple parquet files**: When approaching the row group limit, close the current file and open a new one.\n\n3. **Flush per host instead of per checkpoint**: Since multiple checkpoints can belong to the same host, only flush once per host rather than per checkpoint file.\n\nWhich approach is best? Consider that:\n- A host may have 1 to ~hundreds of checkpoint files\n- A cluster may have ~100 to ~3000+ hosts\n- Flushing per host would give at most ~3000 row groups (within limit for most clusters)\n- But combining approaches 1+2 would be most robust\n\nPlease design the recommended implementation approach with specific code changes needed."}]},"uuid":"7eff74db-4a1e-4090-91cd-e11df667c11b","timestamp":"2026-03-23T05:11:23.120Z"},"type":"agent_progress","prompt":"Design a fix for a parquet row group limit issue in the metric store archiver.\n\n## Problem\n\nThe error is: \"the limit of 32767 row groups has been reached\"\n\nThis happens in `pkg/metricstore/archive.go:archiveCheckpoints()` which creates ONE parquet file per cluster. For each host's checkpoint file, `WriteCheckpointFile()` in `pkg/metricstore/parquetArchive.go` calls `writer.Flush()`, creating one row group per checkpoint file.\n\nFor large clusters like \"fritz\" with many hosts (e.g., 1000+) and multiple checkpoint files per host, total flushes easily exceed 32767.\n\n## Current flow (archive.go lines 268-280):\n\n```go\nfor r := range results {\n for _, cf := range r.checkpoints {\n // Each call creates a row group via Flush()\n writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\")\n }\n}\n```\n\n## WriteCheckpointFile (parquetArchive.go lines 103-120):\n\n```go\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, ...) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n w.count += len(w.batch)\n w.batch = w.batch[:0]\n }\n // THIS creates a new row group every time\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n## Design constraints\n\n- The parquet-go library hard-limits row groups to 32767 per file\n- We want good compression (data sorted by cluster, hostname, metric, timestamp)\n- Don't accumulate all rows in memory — streaming is important\n- Performance: this is HPC monitoring at scale\n\n## Possible approaches\n\n1. **Remove per-checkpoint Flush, flush periodically instead**: Instead of flushing after every checkpoint file, flush after accumulating a certain number of rows (e.g., every 100k rows or every N checkpoints). This reduces row groups dramatically while still bounding memory.\n\n2. **Split into multiple parquet files**: When approaching the row group limit, close the current file and open a new one.\n\n3. **Flush per host instead of per checkpoint**: Since multiple checkpoints can belong to the same host, only flush once per host rather than per checkpoint file.\n\nWhich approach is best? Consider that:\n- A host may have 1 to ~hundreds of checkpoint files\n- A cluster may have ~100 to ~3000+ hosts\n- Flushing per host would give at most ~3000 row groups (within limit for most clusters)\n- But combining approaches 1+2 would be most robust\n\nPlease design the recommended implementation approach with specific code changes needed.","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"c907c6d2-b67e-4fe4-b6e0-882d3c2257d1","timestamp":"2026-03-23T05:11:23.120Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"c907c6d2-b67e-4fe4-b6e0-882d3c2257d1","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-23T05:11:26.424Z","message":{"model":"claude-opus-4-6","id":"msg_01P55WgwoQLFHWFF83TsySJQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VubzskxP8yWsEegKte6oDq","name":"Read","input":{"file_path":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":12060,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":12060,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZKSKXyMxdua6awVdGRwK","uuid":"8f59eca2-e2f4-4a2e-9920-41e26b2bce65"},"type":"agent_progress","prompt":"","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"f58f9246-e978-4a8d-8a51-f3fd9084221f","timestamp":"2026-03-23T05:11:26.424Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"f58f9246-e978-4a8d-8a51-f3fd9084221f","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VubzskxP8yWsEegKte6oDq","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 metricstore\n 7→\n 8→import (\n 9→\t\"context\"\n 10→\t\"errors\"\n 11→\t\"fmt\"\n 12→\t\"os\"\n 13→\t\"path/filepath\"\n 14→\t\"sync\"\n 15→\t\"sync/atomic\"\n 16→\t\"time\"\n 17→\n 18→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n 19→)\n 20→\n 21→// Worker for either Archiving or Deleting files\n 22→\n 23→func CleanUp(wg *sync.WaitGroup, ctx context.Context) {\n 24→\tif Keys.Cleanup.Mode == \"archive\" {\n 25→\t\tcclog.Info(\"[METRICSTORE]> enable archive cleanup to parquet\")\n 26→\t\t// Run as Archiver\n 27→\t\tcleanUpWorker(wg, ctx,\n 28→\t\t\tKeys.RetentionInMemory,\n 29→\t\t\t\"archiving\",\n 30→\t\t\tKeys.Cleanup.RootDir,\n 31→\t\t\tfalse,\n 32→\t\t)\n 33→\t} else {\n 34→\t\t// Run as Deleter\n 35→\t\tcleanUpWorker(wg, ctx,\n 36→\t\t\tKeys.RetentionInMemory,\n 37→\t\t\t\"deleting\",\n 38→\t\t\t\"\",\n 39→\t\t\ttrue,\n 40→\t\t)\n 41→\t}\n 42→}\n 43→\n 44→// cleanUpWorker takes simple values to configure what it does\n 45→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n 46→\twg.Go(func() {\n 47→\t\td, err := time.ParseDuration(interval)\n 48→\t\tif err != nil {\n 49→\t\t\tcclog.Fatalf(\"[METRICSTORE]> error parsing %s interval duration: %v\\n\", mode, err)\n 50→\t\t}\n 51→\t\tif d <= 0 {\n 52→\t\t\treturn\n 53→\t\t}\n 54→\n 55→\t\tticker := time.NewTicker(d)\n 56→\t\tdefer ticker.Stop()\n 57→\n 58→\t\tfor {\n 59→\t\t\tselect {\n 60→\t\t\tcase <-ctx.Done():\n 61→\t\t\t\treturn\n 62→\t\t\tcase <-ticker.C:\n 63→\t\t\t\tt := time.Now().Add(-d)\n 64→\t\t\t\tcclog.Infof(\"[METRICSTORE]> start %s checkpoints (older than %s)...\", mode, t.Format(time.RFC3339))\n 65→\n 66→\t\t\t\tn, err := CleanupCheckpoints(Keys.Checkpoints.RootDir, cleanupDir, t.Unix(), delete)\n 67→\n 68→\t\t\t\tif err != nil {\n 69→\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> %s failed: %s\", mode, err.Error())\n 70→\t\t\t\t} else {\n 71→\t\t\t\t\tif delete {\n 72→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoints deleted\", n)\n 73→\t\t\t\t\t} else {\n 74→\t\t\t\t\t\tcclog.Infof(\"[METRICSTORE]> done: %d checkpoint files archived to parquet\", n)\n 75→\t\t\t\t\t}\n 76→\t\t\t\t}\n 77→\t\t\t}\n 78→\t\t}\n 79→\t})\n 80→}\n 81→\n 82→var ErrNoNewArchiveData error = errors.New(\"all data already archived\")\n 83→\n 84→// CleanupCheckpoints deletes or archives all checkpoint files older than `from`.\n 85→// When archiving, consolidates all hosts per cluster into a single Parquet file.\n 86→func CleanupCheckpoints(checkpointsDir, cleanupDir string, from int64, deleteInstead bool) (int, error) {\n 87→\tif deleteInstead {\n 88→\t\treturn deleteCheckpoints(checkpointsDir, from)\n 89→\t}\n 90→\n 91→\treturn archiveCheckpoints(checkpointsDir, cleanupDir, from)\n 92→}\n 93→\n 94→// deleteCheckpoints removes checkpoint files older than `from` across all clusters/hosts.\n 95→func deleteCheckpoints(checkpointsDir string, from int64) (int, error) {\n 96→\tentries1, err := os.ReadDir(checkpointsDir)\n 97→\tif err != nil {\n 98→\t\treturn 0, err\n 99→\t}\n 100→\n 101→\ttype workItem struct {\n 102→\t\tdir string\n 103→\t\tcluster, host string\n 104→\t}\n 105→\n 106→\tvar wg sync.WaitGroup\n 107→\tn, errs := int32(0), int32(0)\n 108→\twork := make(chan workItem, Keys.NumWorkers)\n 109→\n 110→\twg.Add(Keys.NumWorkers)\n 111→\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n 112→\t\tgo func() {\n 113→\t\t\tdefer wg.Done()\n 114→\t\t\tfor item := range work {\n 115→\t\t\t\tentries, err := os.ReadDir(item.dir)\n 116→\t\t\t\tif err != nil {\n 117→\t\t\t\t\tcclog.Errorf(\"error reading %s/%s: %s\", item.cluster, item.host, err.Error())\n 118→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 119→\t\t\t\t\tcontinue\n 120→\t\t\t\t}\n 121→\n 122→\t\t\t\tfiles, err := findFiles(entries, from, false)\n 123→\t\t\t\tif err != nil {\n 124→\t\t\t\t\tcclog.Errorf(\"error finding files in %s/%s: %s\", item.cluster, item.host, err.Error())\n 125→\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 126→\t\t\t\t\tcontinue\n 127→\t\t\t\t}\n 128→\n 129→\t\t\t\tfor _, checkpoint := range files {\n 130→\t\t\t\t\tif err := os.Remove(filepath.Join(item.dir, checkpoint)); err != nil {\n 131→\t\t\t\t\t\tcclog.Errorf(\"error deleting %s/%s/%s: %s\", item.cluster, item.host, checkpoint, err.Error())\n 132→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 133→\t\t\t\t\t} else {\n 134→\t\t\t\t\t\tatomic.AddInt32(&n, 1)\n 135→\t\t\t\t\t}\n 136→\t\t\t\t}\n 137→\t\t\t}\n 138→\t\t}()\n 139→\t}\n 140→\n 141→\tfor _, de1 := range entries1 {\n 142→\t\tentries2, e := os.ReadDir(filepath.Join(checkpointsDir, de1.Name()))\n 143→\t\tif e != nil {\n 144→\t\t\terr = e\n 145→\t\t\tcontinue\n 146→\t\t}\n 147→\n 148→\t\tfor _, de2 := range entries2 {\n 149→\t\t\twork <- workItem{\n 150→\t\t\t\tdir: filepath.Join(checkpointsDir, de1.Name(), de2.Name()),\n 151→\t\t\t\tcluster: de1.Name(),\n 152→\t\t\t\thost: de2.Name(),\n 153→\t\t\t}\n 154→\t\t}\n 155→\t}\n 156→\n 157→\tclose(work)\n 158→\twg.Wait()\n 159→\n 160→\tif err != nil {\n 161→\t\treturn int(n), err\n 162→\t}\n 163→\tif errs > 0 {\n 164→\t\treturn int(n), fmt.Errorf(\"%d errors happened while deleting (%d successes)\", errs, n)\n 165→\t}\n 166→\treturn int(n), nil\n 167→}\n 168→\n 169→// archiveCheckpoints archives checkpoint files to Parquet format.\n 170→// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n 171→// Workers load checkpoint files from disk and send CheckpointFile trees on a\n 172→// back-pressured channel. The main thread streams each tree directly to Parquet\n 173→// rows without materializing all rows in memory.\n 174→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n 175→\tcclog.Info(\"[METRICSTORE]> start archiving checkpoints to parquet\")\n 176→\tstartTime := time.Now()\n 177→\n 178→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n 179→\tif err != nil {\n 180→\t\treturn 0, err\n 181→\t}\n 182→\n 183→\ttotalFiles := 0\n 184→\n 185→\tfor _, clusterEntry := range clusterEntries {\n 186→\t\tif !clusterEntry.IsDir() {\n 187→\t\t\tcontinue\n 188→\t\t}\n 189→\n 190→\t\tcluster := clusterEntry.Name()\n 191→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n 192→\t\tif err != nil {\n 193→\t\t\treturn totalFiles, err\n 194→\t\t}\n 195→\n 196→\t\t// Workers load checkpoint files from disk; main thread writes to parquet.\n 197→\t\ttype hostResult struct {\n 198→\t\t\tcheckpoints []*CheckpointFile\n 199→\t\t\thostname string\n 200→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n 201→\t\t\tdir string // checkpoint directory for this host\n 202→\t\t}\n 203→\n 204→\t\t// Small buffer provides back-pressure: at most NumWorkers+2 results in flight.\n 205→\t\tresults := make(chan hostResult, 2)\n 206→\t\twork := make(chan struct {\n 207→\t\t\tdir, host string\n 208→\t\t}, Keys.NumWorkers)\n 209→\n 210→\t\tvar wg sync.WaitGroup\n 211→\t\terrs := int32(0)\n 212→\n 213→\t\twg.Add(Keys.NumWorkers)\n 214→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n 215→\t\t\tgo func() {\n 216→\t\t\t\tdefer wg.Done()\n 217→\t\t\t\tfor item := range work {\n 218→\t\t\t\t\tcheckpoints, files, err := loadCheckpointFiles(item.dir, from)\n 219→\t\t\t\t\tif err != nil {\n 220→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n 221→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n 222→\t\t\t\t\t\tcontinue\n 223→\t\t\t\t\t}\n 224→\t\t\t\t\tif len(checkpoints) > 0 {\n 225→\t\t\t\t\t\tresults <- hostResult{\n 226→\t\t\t\t\t\t\tcheckpoints: checkpoints,\n 227→\t\t\t\t\t\t\thostname: item.host,\n 228→\t\t\t\t\t\t\tfiles: files,\n 229→\t\t\t\t\t\t\tdir: item.dir,\n 230→\t\t\t\t\t\t}\n 231→\t\t\t\t\t}\n 232→\t\t\t\t}\n 233→\t\t\t}()\n 234→\t\t}\n 235→\n 236→\t\tgo func() {\n 237→\t\t\tfor _, hostEntry := range hostEntries {\n 238→\t\t\t\tif !hostEntry.IsDir() {\n 239→\t\t\t\t\tcontinue\n 240→\t\t\t\t}\n 241→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n 242→\t\t\t\twork <- struct {\n 243→\t\t\t\t\tdir, host string\n 244→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n 245→\t\t\t}\n 246→\t\t\tclose(work)\n 247→\t\t\twg.Wait()\n 248→\t\t\tclose(results)\n 249→\t\t}()\n 250→\n 251→\t\t// Open streaming writer and write each host's checkpoint files as a row group\n 252→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n 253→\t\twriter, err := newParquetArchiveWriter(parquetFile)\n 254→\t\tif err != nil {\n 255→\t\t\t// Drain results channel to unblock workers\n 256→\t\t\tfor range results {\n 257→\t\t\t}\n 258→\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n 259→\t\t}\n 260→\n 261→\t\ttype deleteItem struct {\n 262→\t\t\tdir string\n 263→\t\t\tfiles []string\n 264→\t\t}\n 265→\t\tvar toDelete []deleteItem\n 266→\t\twriteErr := error(nil)\n 267→\n 268→\t\tfor r := range results {\n 269→\t\t\tif writeErr == nil {\n 270→\t\t\t\t// Stream each checkpoint file directly to parquet rows.\n 271→\t\t\t\t// Each checkpoint is processed and discarded before the next.\n 272→\t\t\t\tfor _, cf := range r.checkpoints {\n 273→\t\t\t\t\tif err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n 274→\t\t\t\t\t\twriteErr = err\n 275→\t\t\t\t\t\tbreak\n 276→\t\t\t\t\t}\n 277→\t\t\t\t}\n 278→\t\t\t}\n 279→\t\t\t// Always track files for deletion (even if write failed, we still drain)\n 280→\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n 281→\t\t}\n 282→\n 283→\t\tif err := writer.Close(); err != nil && writeErr == nil {\n 284→\t\t\twriteErr = err\n 285→\t\t}\n 286→\n 287→\t\tif errs > 0 {\n 288→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n 289→\t\t}\n 290→\n 291→\t\tif writer.count == 0 {\n 292→\t\t\t// No data written — remove empty file\n 293→\t\t\tos.Remove(parquetFile)\n 294→\t\t\tcontinue\n 295→\t\t}\n 296→\n 297→\t\tif writeErr != nil {\n 298→\t\t\tos.Remove(parquetFile)\n 299→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n 300→\t\t}\n 301→\n 302→\t\t// Delete archived checkpoint files\n 303→\t\tfor _, item := range toDelete {\n 304→\t\t\tfor _, file := range item.files {\n 305→\t\t\t\tfilename := filepath.Join(item.dir, file)\n 306→\t\t\t\tif err := os.Remove(filename); err != nil {\n 307→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n 308→\t\t\t\t} else {\n 309→\t\t\t\t\ttotalFiles++\n 310→\t\t\t\t}\n 311→\t\t\t}\n 312→\t\t}\n 313→\n 314→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n 315→\t\t\twriter.count, totalFiles, cluster, parquetFile)\n 316→\t}\n 317→\n 318→\tcclog.Infof(\"[METRICSTORE]> archiving checkpoints completed in %s (%d files)\", time.Since(startTime).Round(time.Millisecond), totalFiles)\n 319→\treturn totalFiles, nil\n 320→}\n 321→"}]},"uuid":"a0a58bc6-ab4c-438c-8419-4b5a79e7d5d5","timestamp":"2026-03-23T05:11:26.447Z"},"type":"agent_progress","prompt":"","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"165c50b1-8585-40fc-bd0f-7043c46d78f0","timestamp":"2026-03-23T05:11:26.638Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"46f6f3c9-ad7e-46ae-a0f1-d2423a0085b9","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01W65ZT2GJPGEtTfodj1BmiK","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 metricstore\n 7→\n 8→import (\n 9→\t\"bufio\"\n 10→\t\"encoding/binary\"\n 11→\t\"encoding/json\"\n 12→\t\"fmt\"\n 13→\t\"os\"\n 14→\t\"path/filepath\"\n 15→\t\"sort\"\n 16→\n 17→\tpq \"github.com/parquet-go/parquet-go\"\n 18→)\n 19→\n 20→// ParquetMetricRow is the long-format schema for archived metric data.\n 21→// One row per (host, metric, scope, scope_id, timestamp) data point.\n 22→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n 23→type ParquetMetricRow struct {\n 24→\tCluster string `parquet:\"cluster\"`\n 25→\tHostname string `parquet:\"hostname\"`\n 26→\tMetric string `parquet:\"metric\"`\n 27→\tScope string `parquet:\"scope\"`\n 28→\tScopeID string `parquet:\"scope_id\"`\n 29→\tTimestamp int64 `parquet:\"timestamp\"`\n 30→\tFrequency int64 `parquet:\"frequency\"`\n 31→\tValue float32 `parquet:\"value\"`\n 32→}\n 33→\n 34→// parseScopeFromName infers scope and scope_id from a child level name.\n 35→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n 36→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n 37→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n 38→func parseScopeFromName(name string) (string, string) {\n 39→\tprefixes := []struct {\n 40→\t\tprefix string\n 41→\t\tscope string\n 42→\t}{\n 43→\t\t{\"socket\", \"socket\"},\n 44→\t\t{\"memoryDomain\", \"memoryDomain\"},\n 45→\t\t{\"core\", \"core\"},\n 46→\t\t{\"hwthread\", \"hwthread\"},\n 47→\t\t{\"cpu\", \"hwthread\"},\n 48→\t\t{\"accelerator\", \"accelerator\"},\n 49→\t}\n 50→\n 51→\tfor _, p := range prefixes {\n 52→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n 53→\t\t\tid := name[len(p.prefix):]\n 54→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n 55→\t\t\t\treturn p.scope, id\n 56→\t\t\t}\n 57→\t\t}\n 58→\t}\n 59→\n 60→\treturn name, \"\"\n 61→}\n 62→\n 63→// parquetArchiveWriter supports incremental writes to a Parquet file.\n 64→// Uses streaming writes to avoid accumulating all rows in memory.\n 65→type parquetArchiveWriter struct {\n 66→\twriter *pq.GenericWriter[ParquetMetricRow]\n 67→\tbw *bufio.Writer\n 68→\tf *os.File\n 69→\tbatch []ParquetMetricRow // reusable batch buffer\n 70→\tcount int\n 71→}\n 72→\n 73→const parquetBatchSize = 1024\n 74→\n 75→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n 76→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n 77→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n 78→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n 79→\t}\n 80→\n 81→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n 82→\tif err != nil {\n 83→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n 84→\t}\n 85→\n 86→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n 87→\n 88→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n 89→\t\tpq.Compression(&pq.Zstd),\n 90→\t)\n 91→\n 92→\treturn &parquetArchiveWriter{\n 93→\t\twriter: writer,\n 94→\t\tbw: bw,\n 95→\t\tf: f,\n 96→\t\tbatch: make([]ParquetMetricRow, 0, parquetBatchSize),\n 97→\t}, nil\n 98→}\n 99→\n 100→// WriteCheckpointFile streams a CheckpointFile tree directly to Parquet rows,\n 101→// writing metrics in sorted order without materializing all rows in memory.\n 102→// Produces one row group per call (typically one host's data).\n 103→func (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string) error {\n 104→\tw.writeLevel(cf, cluster, hostname, scope, scopeID)\n 105→\n 106→\t// Flush remaining batch\n 107→\tif len(w.batch) > 0 {\n 108→\t\tif _, err := w.writer.Write(w.batch); err != nil {\n 109→\t\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n 110→\t\t}\n 111→\t\tw.count += len(w.batch)\n 112→\t\tw.batch = w.batch[:0]\n 113→\t}\n 114→\n 115→\tif err := w.writer.Flush(); err != nil {\n 116→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n 117→\t}\n 118→\n 119→\treturn nil\n 120→}\n 121→\n 122→// writeLevel recursively writes metrics from a CheckpointFile level.\n 123→// Metric names and child names are sorted for deterministic, compression-friendly output.\n 124→func (w *parquetArchiveWriter) writeLevel(cf *CheckpointFile, cluster, hostname, scope, scopeID string) {\n 125→\t// Sort metric names for deterministic order\n 126→\tmetricNames := make([]string, 0, len(cf.Metrics))\n 127→\tfor name := range cf.Metrics {\n 128→\t\tmetricNames = append(metricNames, name)\n 129→\t}\n 130→\tsort.Strings(metricNames)\n 131→\n 132→\tfor _, metricName := range metricNames {\n 133→\t\tcm := cf.Metrics[metricName]\n 134→\t\tts := cm.Start\n 135→\t\tfor _, v := range cm.Data {\n 136→\t\t\tif !v.IsNaN() {\n 137→\t\t\t\tw.batch = append(w.batch, ParquetMetricRow{\n 138→\t\t\t\t\tCluster: cluster,\n 139→\t\t\t\t\tHostname: hostname,\n 140→\t\t\t\t\tMetric: metricName,\n 141→\t\t\t\t\tScope: scope,\n 142→\t\t\t\t\tScopeID: scopeID,\n 143→\t\t\t\t\tTimestamp: ts,\n 144→\t\t\t\t\tFrequency: cm.Frequency,\n 145→\t\t\t\t\tValue: float32(v),\n 146→\t\t\t\t})\n 147→\n 148→\t\t\t\tif len(w.batch) >= parquetBatchSize {\n 149→\t\t\t\t\tw.writer.Write(w.batch)\n 150→\t\t\t\t\tw.count += len(w.batch)\n 151→\t\t\t\t\tw.batch = w.batch[:0]\n 152→\t\t\t\t}\n 153→\t\t\t}\n 154→\t\t\tts += cm.Frequency\n 155→\t\t}\n 156→\t}\n 157→\n 158→\t// Sort child names for deterministic order\n 159→\tchildNames := make([]string, 0, len(cf.Children))\n 160→\tfor name := range cf.Children {\n 161→\t\tchildNames = append(childNames, name)\n 162→\t}\n 163→\tsort.Strings(childNames)\n 164→\n 165→\tfor _, childName := range childNames {\n 166→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n 167→\t\tw.writeLevel(cf.Children[childName], cluster, hostname, childScope, childScopeID)\n 168→\t}\n 169→}\n 170→\n 171→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n 172→func (w *parquetArchiveWriter) Close() error {\n 173→\tif err := w.writer.Close(); err != nil {\n 174→\t\tw.f.Close()\n 175→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n 176→\t}\n 177→\n 178→\tif err := w.bw.Flush(); err != nil {\n 179→\t\tw.f.Close()\n 180→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n 181→\t}\n 182→\n 183→\treturn w.f.Close()\n 184→}\n 185→\n 186→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n 187→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n 188→// before converting it to Parquet format.\n 189→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n 190→\tf, err := os.Open(filename)\n 191→\tif err != nil {\n 192→\t\treturn nil, err\n 193→\t}\n 194→\tdefer f.Close()\n 195→\n 196→\text := filepath.Ext(filename)\n 197→\tswitch ext {\n 198→\tcase \".json\":\n 199→\t\tcf := &CheckpointFile{}\n 200→\t\tbr := bufio.NewReader(f)\n 201→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n 202→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n 203→\t\t}\n 204→\t\treturn cf, nil\n 205→\n 206→\tcase \".bin\":\n 207→\t\tbr := bufio.NewReader(f)\n 208→\t\tvar magic uint32\n 209→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n 210→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n 211→\t\t}\n 212→\t\tif magic != snapFileMagic {\n 213→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n 214→\t\t}\n 215→\t\tvar fileFrom, fileTo int64\n 216→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n 217→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n 218→\t\t}\n 219→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n 220→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n 221→\t\t}\n 222→\t\tcf, err := readBinaryLevel(br)\n 223→\t\tif err != nil {\n 224→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n 225→\t\t}\n 226→\t\tcf.From = fileFrom\n 227→\t\tcf.To = fileTo\n 228→\t\treturn cf, nil\n 229→\n 230→\tdefault:\n 231→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n 232→\t}\n 233→}\n 234→\n 235→// loadCheckpointFiles reads checkpoint files for a host directory and returns\n 236→// the loaded CheckpointFiles and their filenames. 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{"parentUuid":"9572ce05-7066-4f83-9b9f-9413217f7eb8","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GtTMcJ8ofZYj5M8SYFtU3g","type":"tool_result","content":"271-\treturn w.base.WriteRows(rows)\n272-}\n273-\n274:func (w *GenericWriter[T]) WriteRowGroup(rowGroup RowGroup) (int64, error) {\n275:\treturn w.base.WriteRowGroup(rowGroup)\n276-}\n277-\n278-// SetKeyValueMetadata sets a key/value pair in the Parquet file metadata.\n--\n312-\treturn w.base.File()\n313-}\n314-\n315:// ConcurrentRowGroupWriter is a row group writer that can be used to write row groups\n316:// in parallel. Multiple row groups can be created concurrently and written to independently,\n317:// but they must be committed serially to maintain the order of row groups in the file.\n318-//\n319-// See BeginRowGroup for more information on how this can be used.\n320-//\n321:// While multiple row groups can be created concurrently, a single row group must be written\n322-// sequentially.\n323-type ConcurrentRowGroupWriter struct {\n324-\twriter *writer\n--\n333-}\n334-\n335-// BeginRowGroup returns a new ConcurrentRowGroupWriter that can be written to in parallel with\n336:// other row groups. However these need to be committed back to the writer serially using the\n337:// Commit method on the row group.\n338-//\n339-/ Example usage could look something like:\n340-//\n--\n401-// The Writer type optimizes for minimal memory usage, each page is written as\n402-// soon as it has been filled so only a single page per column needs to be held\n403-// in memory and as a result, there are no opportunities to sort rows within an\n404:// entire row group. Programs that need to produce parquet files with sorted\n405:// row groups should use the Buffer type to buffer and sort the rows prior to\n406-// writing them to a Writer.\n407-//\n408-// For programs building with Go 1.18 or later, the GenericWriter[T] type\n--\n468-\treturn nil\n469-}\n470-\n471:// Flush flushes all buffers into a row group to the underlying io.Writer.\n472-//\n473-// Flush is called automatically on Close, it is only useful to call explicitly\n474:// if the application needs to limit the size of row groups or wants to produce\n475:// multiple row groups per file.\n476-//\n477:// If the writer attempts to create more than MaxRowGroups row groups the method\n478-// returns ErrTooManyRowGroups.\n479-func (w *Writer) Flush() error {\n480-\tif w.writer != nil {\n--\n526-\treturn w.writer.WriteRows(rows)\n527-}\n528-\n529:// WriteRowGroup writes a row group to the parquet file.\n530-//\n531-// Buffered rows will be flushed prior to writing rows from the group, unless\n532:// the row group was empty in which case nothing is written to the file.\n533-//\n534:// The content of the row group is flushed to the writer; after the method\n535:// returns successfully, the row group will be empty and in ready to be reused.\n536:func (w *Writer) WriteRowGroup(rowGroup RowGroup) (int64, error) {\n537:\trowGroupSchema := rowGroup.Schema()\n538-\tswitch {\n539:\tcase rowGroupSchema == nil:\n540-\t\treturn 0, ErrRowGroupSchemaMissing\n541-\tcase w.schema == nil:\n542:\t\tw.configure(rowGroupSchema)\n543:\tcase !EqualNodes(w.schema, rowGroupSchema):\n544-\t\treturn 0, ErrRowGroupSchemaMismatch\n545-\t}\n546-\tif err := w.writer.flush(); err != nil {\n547-\t\treturn 0, err\n548-\t}\n549:\tw.writer.currentRowGroup.configureBloomFilters(rowGroup.ColumnChunks())\n550:\trows := rowGroup.Rows()\n551-\tdefer rows.Close()\n552-\tn, err := CopyRows(w.writer, rows)\n553-\tif err != nil {\n554-\t\treturn n, err\n555-\t}\n556:\treturn w.writer.writeRowGroup(w.writer.currentRowGroup, rowGroup.Schema(), rowGroup.SortingColumns())\n557-}\n558-\n559-// ReadRowsFrom reads rows from the reader passed as arguments and writes them\n--\n581-func (w *Writer) Schema() *Schema { return w.schema }\n582-\n583-// Size returns an estimate of the current file size in bytes, including all\n584:// completed row groups and the current in-progress row group.\n585-//\n586-// The estimate includes bytes already written to the underlying writer plus\n587:// the estimated size of buffered data in the current row group. The buffered\n588-// data has not been compressed yet, so this is an upper-bound estimate.\n589-//\n590-// The size of the footer metadata is not included because it is variable and\n--\n628-func (w *Writer) ColumnWriters() []*ColumnWriter { return w.writer.currentRowGroup.columns }\n629-\n630-// BeginRowGroup returns a new ConcurrentRowGroupWriter that can be written to in parallel with\n631:// other row groups. However these need to be committed back to the writer serially using the\n632:// Commit method on the row group.\n633-func (w *Writer) BeginRowGroup() *ConcurrentRowGroupWriter {\n634-\treturn newConcurrentRowGroupWriter(w.writer, w.config)\n635-}\n--\n839-\t}\n840-}\n841-\n842:// Schema returns the schema for this row group.\n843-func (rg *ConcurrentRowGroupWriter) Schema() *Schema {\n844-\treturn rg.config.Schema\n845-}\n846-\n847:// ColumnWriters returns the column writers for this row group, allowing\n848-// direct access to write values to individual columns.\n849-func (rg *ConcurrentRowGroupWriter) ColumnWriters() []*ColumnWriter {\n850-\treturn rg.columns\n851-}\n852-\n853:// Flush flushes any buffered data in the row group's column writers.\n854-// This could be called before Commit to ensure all data pages are flushed.\n855-func (rg *ConcurrentRowGroupWriter) Flush() error {\n856-\tfor _, c := range rg.columns {\n--\n861-\treturn nil\n862-}\n863-\n864:// Size returns an estimate of the current row group size in bytes.\n865-//\n866-// The estimate sums encoded pages, buffered values not yet encoded, dictionary\n867-// pages, and bloom filters for each column. Because buffered values have not\n--\n881-\treturn size\n882-}\n883-\n884:// Commit commits the row group to the parent writer, returning the number\n885-// of rows written and an error if any. This method must be called serially\n886:// (not concurrently) to maintain row group order in the file.\n887-//\n888-// If the parent writer has any pending rows buffered, they will be flushed\n889:// before this row group is written.\n890-//\n891:// After Commit returns successfully, the row group will be empty and can\n892-// be reused.\n893-func (rg *ConcurrentRowGroupWriter) Commit() (int64, error) {\n894-\tif err := rg.writer.flush(); err != nil {\n--\n897-\treturn rg.writer.writeRowGroup(rg, nil, nil)\n898-}\n899-\n900:// WriteRows writes rows to the row group.\n901-func (rg *ConcurrentRowGroupWriter) WriteRows(rows []Row) (int, error) {\n902-\treturn rg.writeRows(len(rows), func(start, end int) (int, error) {\n903-\t\tdefer func() {\n--\n974-\n975-\tcolumnOrders []format.ColumnOrder\n976-\tschemaElements []format.SchemaElement\n977:\trowGroups []format.RowGroup\n978-\tcolumnIndexes [][]format.ColumnIndex\n979-\toffsetIndexes [][]format.OffsetIndex\n980-\tsortingColumns []format.SortingColumn\n--\n1074-\t\tw.writer.Reset(w.buffer)\n1075-\t}\n1076-\tw.currentRowGroup.reset()\n1077:\tfor i := range w.rowGroups {\n1078:\t\tw.rowGroups[i].Reset()\n1079-\t}\n1080-\tfor i := range w.columnIndexes {\n1081-\t\tfor j := range w.columnIndexes[i] {\n--\n1089-\t\t}\n1090-\t\tw.offsetIndexes[i] = w.offsetIndexes[i][:0]\n1091-\t}\n1092:\tw.rowGroups = w.rowGroups[:0]\n1093-\tw.columnIndexes = w.columnIndexes[:0]\n1094-\tw.offsetIndexes = w.offsetIndexes[:0]\n1095-\tw.fileMetaData = format.FileMetaData{}\n--\n1129-\n1130-func (w *writer) writeFileFooter() error {\n1131-\t/ The page index is composed of two sections: column and offset indexes.\n1132:\t// They are written after the row groups, right before the footer (which\n1133-\t// is written by the parent Writer.Close call).\n1134-\t//\n1135-\t// This section both writes the page index and generates the values of\n--\n1144-\tencoder := thrift.NewEncoder(protocol.NewWriter(&w.writer))\n1145-\n1146-\tfor i, columnIndexes := range w.columnIndexes {\n1147:\t\trowGroup := &w.rowGroups[i]\n1148-\t\tfor j := range columnIndexes {\n1149:\t\t\tcolumn := &rowGroup.Columns[j]\n1150-\t\t\tcolumn.ColumnIndexOffset = w.writer.offset\n1151-\t\t\tif err := encoder.Encode(&columnIndexes[j]); err != nil {\n1152-\t\t\t\treturn err\n--\n1156-\t}\n1157-\n1158-\tfor i, offsetIndexes := range w.offsetIndexes {\n1159:\t\trowGroup := &w.rowGroups[i]\n1160-\t\tfor j := range offsetIndexes {\n1161:\t\t\tcolumn := &rowGroup.Columns[j]\n1162-\t\t\tcolumn.OffsetIndexOffset = w.writer.offset\n1163-\t\t\tif err := encoder.Encode(&offsetIndexes[j]); err != nil {\n1164-\t\t\t\treturn err\n--\n1168-\t}\n1169-\n1170-\tnumRows := int64(0)\n1171:\tfor rowGroupIndex := range w.rowGroups {\n1172:\t\tnumRows += w.rowGroups[rowGroupIndex].NumRows\n1173-\t}\n1174-\n1175-\t// We implemented the parquet specification version 2+, which is represented\n--\n1183-\t\tVersion: parquetFileFormatVersion,\n1184-\t\tSchema: w.schemaElements,\n1185-\t\tNumRows: numRows,\n1186:\t\tRowGroups: w.rowGroups,\n1187-\t\tKeyValueMetadata: w.metadata,\n1188-\t\tCreatedBy: w.createdBy,\n1189-\t\tColumnOrders: w.columnOrders,\n--\n1201-\treturn err\n1202-}\n1203-\n1204:func (w *writer) writeRowGroup(rg *ConcurrentRowGroupWriter, rowGroupSchema *Schema, rowGroupSortingColumns []SortingColumn) (int64, error) {\n1205-\tif len(rg.columns) == 0 {\n1206-\t\treturn 0, nil\n1207-\t}\n--\n1210-\t\treturn 0, nil\n1211-\t}\n1212-\n1213:\trowGroupIndex := len(w.rowGroups)\n1214-\tcolumnIndexIndex := len(w.columnIndexes)\n1215-\toffsetIndexIndex := len(w.offsetIndexes)\n1216-\n1217:\tif len(w.rowGroups) == MaxRowGroups {\n1218-\t\treturn 0, ErrTooManyRowGroups\n1219-\t}\n1220-\n--\n1250-\t\tif c.dictionary != nil {\n1251-\t\t\tc.columnChunk.MetaData.DictionaryPageOffset = w.writer.offset\n1252-\t\t\tif err := c.writeDictionaryPage(&w.writer, c.dictionary); err != nil {\n1253:\t\t\t\treturn 0, fmt.Errorf(\"writing dictionary page of row group colum %d: %w\", i, err)\n1254-\t\t\t}\n1255-\t\t}\n1256-\n--\n1271-\t\t\treturn 0, fmt.Errorf(\"resetting parquet page buffer to the start expected offset zero but got %d\", offset)\n1272-\t\t}\n1273-\t\tif _, err := io.Copy(&w.writer, c.pageBuffer); err != nil {\n1274:\t\t\treturn 0, fmt.Errorf(\"writing buffered pages of row group column %d: %w\", i, err)\n1275-\t\t}\n1276-\t}\n1277-\n--\n1298-\t}\n1299-\n1300-\tvar reuseRowGroup *format.RowGroup = nil\n1301:\tif cap(w.rowGroups) > rowGroupIndex {\n1302:\t\tw.rowGroups = w.rowGroups[:rowGroupIndex+1] // Extend the slice by one element\n1303:\t\treuseRowGroup = &w.rowGroups[rowGroupIndex] // Pointer to the last element\n1304-\t}\n1305-\n1306-\tsortingColumns := w.sortingColumns\n1307:\tif len(sortingColumns) == 0 && len(rowGroupSortingColumns) > 0 {\n1308:\t\tscLen := len(rowGroupSortingColumns)\n1309-\t\tif reuseRowGroup == nil {\n1310-\t\t\tsortingColumns = make([]format.SortingColumn, 0, scLen)\n1311-\t\t} else {\n1312-\t\t\tsortingColumns = reuseRowGroup.SortingColumns\n1313-\t\t}\n1314:\t\tforEachLeafColumnOf(rowGroupSchema, func(leaf leafColumn) {\n1315:\t\t\tif sortingIndex := searchSortingColumn(rowGroupSortingColumns, leaf.path); sortingIndex < len(sortingColumns) {\n1316-\t\t\t\tsortingColumns[sortingIndex] = format.SortingColumn{\n1317-\t\t\t\t\tColumnIdx: int32(leaf.columnIndex),\n1318:\t\t\t\t\tDescending: rowGroupSortingColumns[sortingIndex].Descending(),\n1319:\t\t\t\t\tNullsFirst: rowGroupSortingColumns[sortingIndex].NullsFirst(),\n1320-\t\t\t\t}\n1321-\t\t\t}\n1322-\t\t})\n--\n1353-\t\tw.offsetIndexes = append(w.offsetIndexes, offsetIndex)\n1354-\t}\n1355-\n1356:\t// If the existing row group slice is full, we need to create a new element\n1357-\tvar columns []format.ColumnChunk = nil\n1358-\tif reuseRowGroup == nil {\n1359-\t\tcolumns = slices.Clone(rg.columnChunk)\n--\n1371-\t}\n1372-\n1373-\tif reuseRowGroup == nil {\n1374:\t\tw.rowGroups = append(w.rowGroups, format.RowGroup{\n1375-\t\t\tColumns: columns,\n1376-\t\t\tTotalByteSize: totalByteSize,\n1377-\t\t\tNumRows: numRows,\n1378-\t\t\tSortingColumns: sortingColumns,\n1379-\t\t\tFileOffset: fileOffset,\n1380-\t\t\tTotalCompressedSize: totalCompressedSize,\n1381:\t\t\tOrdinal: int16(len(w.rowGroups)),\n1382-\t\t})\n1383-\t} else {\n1384-\t\treuseRowGroup.Columns = columns\n--\n1387-\t\treuseRowGroup.SortingColumns = sortingColumns\n1388-\t\treuseRowGroup.FileOffset = fileOffset\n1389-\t\treuseRowGroup.TotalCompressedSize = totalCompressedSize\n1390:\t\treuseRowGroup.Ordinal = int16(len(w.rowGroups) - 1)\n1391-\t}\n1392-\n1393-\treturn numRows, nil\n--\n1528-\tcolumnIndex ColumnIndexer\n1529-\tcolumnBuffer ColumnBuffer\n1530-\tplainColumnBuffer ColumnBuffer // Retained plain buffer for fallback after lazy creation\n1531:\toriginalColumnBuffer ColumnBuffer // Original buffer to restore after row group flush\n1532-\tcolumnFilter BloomFilterColumn\n1533-\tencoding encoding.Encoding\n1534-\toriginalEncoding encoding.Encoding // Original encoding before any changes\n--\n1591-\t\tc.pageBuffer = nil\n1592-\t}\n1593-\tc.numPages = 0\n1594:\t// Bloom filters may change in size between row groups, but we retain the\n1595-\t// buffer to avoid reallocating large memory blocks.\n1596-\tc.filter = c.filter[:0]\n1597-\tc.numRows = 0\n1598:\t// Reset the fields of column chunks that change between row groups,\n1599-\t// but keep the ones that remain unchanged.\n1600-\tc.columnChunk.MetaData.NumValues = 0\n1601-\tc.columnChunk.MetaData.TotalUncompressedSize = 0\n--\n1808-func (c *ColumnWriter) WriteRowValues(rows []Value) (int, error) {\n1809-\tvar startingRows int64\n1810-\tif c.columnBuffer == nil {\n1811:\t\t// Lazily create the row group column so we don't need to allocate it if\n1812-\t\t// rows are not written individually to the column.\n1813-\t\tc.columnBuffer = c.newColumnBuffer()\n1814-\t\tc.originalColumnBuffer = c.columnBuffer\n--\n1841-func (c *ColumnWriter) writeValues(values []Value) (numValues int, err error) {\n1842-\tif c.columnBuffer == nil {\n1843-\t\tc.columnBuffer = c.newColumnBuffer()\n1844:\t\t// Save the original dictionary-encoding buffer to restore after row group flush\n1845-\t\tif c.originalColumnBuffer == nil {\n1846-\t\t\tc.originalColumnBuffer = c.columnBuffer\n1847-\t\t}\n--\n1896-\n1897-\tif page.Dictionary() == nil && len(c.filter) > 0 {\n1898-\t\t// When the writer knows the number of values in advance (e.g. when\n1899:\t\t// writing a full row group), the filter encoding is set and the page\n1900-\t\t// can be directly applied to the filter, which minimizes memory usage\n1901-\t\t// since there is no need to buffer the values in order to determine\n1902-\t\t// the size of the filter.\n--\n2080-\t/ Note: We are NOT re-encoding existing pages. This means:\n2081-\t// - Pages written before the limit was hit will remain dictionary-encoded\n2082-\t// - Pages written after will be PLAIN-encoded\n2083:\t// - The dictionary page will still be written at row group flush\n2084-\t// - Mixed encodings in the same column chunk are valid per Parquet spec\n2085-\tc.hasSwitchedToPlain = true\n2086-\treturn nil"}]},"uuid":"2c8eca66-3655-434f-968f-26e777e06460","timestamp":"2026-03-23T05:12:57.689Z"},"type":"agent_progress","prompt":"","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"8db7580c-1b97-48bb-9e73-ce09eac54cc7","timestamp":"2026-03-23T05:12:57.696Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"4f1dd8d2-40d4-4a5f-938b-d8a6ab859493","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013gxmr4n71pLpMC3VSKqE69","type":"tool_result","content":"/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/errors.go:54:\t// ErrTooManyRowGroups is returned when attempting to generate a parquet\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/errors.go:55:\t// file with more than MaxRowGroups row groups.\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/errors.go:56:\tErrTooManyRowGroups = errors.New(\"the limit of 32767 row groups has been reached\")\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:260:\t\tif err != ErrTooManyRowGroups {\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:477:// If the writer attempts to create more than MaxRowGroups row groups the method\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:478:// returns ErrTooManyRowGroups.\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:940:\t\t\treturn written, ErrTooManyRowGroups\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:1217:\tif len(w.rowGroups) == MaxRowGroups {\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:1218:\t\treturn 0, ErrTooManyRowGroups\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go:1402:\t\tif err != ErrTooManyRowGroups {\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/limits.go:23:\t// MaxRowGroups is the maximum number of row groups which can be contained\n/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/limits.go:29:\tMaxRowGroups = math.MaxInt16"}]},"uuid":"edb4a3f3-430b-416a-a3f3-cb4ea008ead3","timestamp":"2026-03-23T05:13:02.334Z"},"type":"agent_progress","prompt":"","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"59529870-cdfa-4a5e-9602-5981073bbdca","timestamp":"2026-03-23T05:13:02.385Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"8c173cd4-8f53-47d3-8874-b7bd4622132f","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01S7xNu5pAify5GoHtWyF4Yg","type":"tool_result","content":"/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-134-\t}\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-135-\npkg/metricstore/metricstore.go:136:\t// Set NumWorkers from config or use default\npkg/metricstore/metricstore.go:137:\tif Keys.NumWorkers <= 0 {\npkg/metricstore/metricstore.go:138:\t\tKeys.NumWorkers = min(runtime.NumCPU()/2+1, DefaultMaxWorkers)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-139-\t}\npkg/metricstore/metricstore.go:140:\tcclog.Debugf(\"[METRICSTORE]> Using %d workers for checkpoint/archive operations\\n\", Keys.NumWorkers)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-141-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-142-\t// Pass the config.MetricStoreKeys\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-186-\tif Keys.Subscriptions != nil {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-187-\t\twg.Go(func() {\npkg/metricstore/metricstore.go:188:\t\t\tif err := ReceiveNats(ms, Keys.NumWorkers, ctx); err != nil {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-189-\t\t\t\tcclog.Fatal(err)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/metricstore.go-190-\t\t\t}\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-106-\tvar wg sync.WaitGroup\npkg/metricstore/archive.go-107-\tn, errs := int32(0), int32(0)\npkg/metricstore/archive.go:108:\twork := make(chan workItem, Keys.NumWorkers)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-109-\npkg/metricstore/archive.go:110:\twg.Add(Keys.NumWorkers)\npkg/metricstore/archive.go:111:\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-112-\t\tgo func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-113-\t\t\tdefer wg.Done()\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-202-\t\t}\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-203-\npkg/metricstore/archive.go:204:\t\t// Small buffer provides back-pressure: at most NumWorkers+2 results in flight.\npkg/metricstore/archive.go-205-\t\tresults := make(chan hostResult, 2)\npkg/metricstore/archive.go-206-\t\twork := make(chan struct {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-207-\t\t\tdir, host string\npkg/metricstore/archive.go:208:\t\t}, Keys.NumWorkers)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-209-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-210-\t\tvar wg sync.WaitGroup\npkg/metricstore/archive.go-211-\t\terrs := int32(0)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-212-\npkg/metricstore/archive.go:213:\t\twg.Add(Keys.NumWorkers)\npkg/metricstore/archive.go:214:\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-215-\t\t\tgo func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go-216-\t\t\t\tdefer wg.Done()\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/config.go-11-//\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/config.go-12-//\tMetricStoreConfig (Keys)\npkg/metricstore/config.go:13://\t├─ NumWorkers: Parallel checkpoint/archive workers\npkg/metricstore/config.go-14-/\t├─ RetentionInMemory: How long to keep data in RAM (also used as cleanup interval)\npkg/metricstore/config.go-15-/\t├─ MemoryCap: Memory limit in bytes (triggers forceFree)\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/config.go-112-//\npkg/metricstore/config.go-113-/ Fields:\npkg/metricstore/config.go:114:// - NumWorkers: Parallel workers for checkpoint/archive (0 = auto: min(NumCPU/2+1, 10))\npkg/metricstore/config.go-115-/ - RetentionInMemory: Duration string (e.g., \"48h\") for in-memory data retention\npkg/metricstore/config.go-116-/ - MemoryCap: Max memory in GB for buffer data (0 = unlimited); triggers forceFree when exceeded\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/config.go-122-\t// Number of concurrent workers for checkpoint and archive operations.\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/config.go-123-\t// If not set or 0, defaults to min(runtime.NumCPU()/2+1, 10)\npkg/metricstore/config.go:124:\tNumWorkers int `json:\"num-workers\"`\npkg/metricstore/config.go-125-\tRetentionInMemory string `json:\"retention-in-memory\"`\npkg/metricstore/config.go-126-\tCheckpointInterval string `json:\"checkpoint-interval,omitempty\"`\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-182-//\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-183-// Metrics at root and cluster levels are skipped. One file per host is created.\npkg/metricstore/checkpoint.go:184:// Uses worker pool (Keys.NumWorkers) for parallel processing. Only locks one host\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-185-// at a time, allowing concurrent writes/reads to other hosts.\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-186-//\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-220-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-221-\tvar wg sync.WaitGroup\npkg/metricstore/checkpoint.go:222:\twg.Add(Keys.NumWorkers)\npkg/metricstore/checkpoint.go:223:\twork := make(chan workItem, Keys.NumWorkers*2)\npkg/metricstore/checkpoint.go:224:\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-225-\t\tgo func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-226-\t\t\tdefer wg.Done()\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-395-func (m *MemoryStore) FromCheckpoint(dir string, from int64) (int, error) {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-396-\tvar wg sync.WaitGroup\npkg/metricstore/checkpoint.go:397:\twork := make(chan [2]string, Keys.NumWorkers*4)\npkg/metricstore/checkpoint.go-398-\tn, errs := int32(0), int32(0)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-399-\npkg/metricstore/checkpoint.go:400:\twg.Add(Keys.NumWorkers)\npkg/metricstore/checkpoint.go:401:\tfor worker := 0; worker < Keys.NumWorkers; worker++ {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-402-\t\tgo func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/checkpoint.go-403-\t\t\tdefer wg.Done()\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-150-\t}\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-151-\npkg/metricstore/walCheckpoint.go:152:\twalNumShards = max(Keys.NumWorkers, 1)\npkg/metricstore/walCheckpoint.go-153-\tchBufSize := max(65536/walNumShards, 1024)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-154-\n--\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-703-\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-704-\tvar wg sync.WaitGroup\npkg/metricstore/walCheckpoint.go:705:\twg.Add(Keys.NumWorkers)\npkg/metricstore/walCheckpoint.go:706:\twork := make(chan workItem, Keys.NumWorkers*2)\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-707-\npkg/metricstore/walCheckpoint.go:708:\tfor range Keys.NumWorkers {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-709-\t\tgo func() {\n/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/walCheckpoint.go-710-\t\t\tdefer wg.Done()"}]},"uuid":"817963a3-1414-4ecc-830b-70508d54f45f","timestamp":"2026-03-23T05:13:06.734Z"},"type":"agent_progress","prompt":"","agentId":"a74b5803a0410fec5"},"toolUseID":"agent_msg_01AywFyehZf2Ne6jcf86zbv2","parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","uuid":"677ce842-0fb2-40f4-81c2-9a7cbb8778ef","timestamp":"2026-03-23T05:13:06.735Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"5dc0fa0b-9656-4e6f-9978-c7466eaddeb7","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","toolUseID":"toolu_01U4xejxv1iKPYqAB72CNr5W","timestamp":"2026-03-23T05:13:43.369Z","uuid":"c362780b-10c8-42aa-988e-7e7028c0942a","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"ce620e78-df86-4300-a26d-b30ccc052b1c","isSidechain":false,"promptId":"4c9038e2-c763-4f23-82bf-037c28776776","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01U4xejxv1iKPYqAB72CNr5W","type":"tool_result","content":[{"type":"text","text":"Good. Now I have full context. Here is the implementation plan.\n\n---\n\n## Implementation Plan: Fix Parquet Row Group Limit\n\n### Problem Analysis\n\nEvery call to `WriteCheckpointFile()` ends with `w.writer.Flush()`, which creates one row group. The parquet-go library hard-limits this to `MaxRowGroups = 32767` (math.MaxInt16). For a cluster with 3000 hosts and even just 11 checkpoint files per host, that is 33000 flushes, exceeding the limit.\n\n### Recommended Approach: Combined Strategy (Approaches 1 + 3)\n\nThe fix has two parts:\n\n1. **Move the `Flush()` call out of `WriteCheckpointFile` and into the caller in `archive.go`**, flushing once per host (after all checkpoint files for that host are written). This is the primary fix -- it is the natural boundary since each `hostResult` groups all checkpoints for a single host.\n\n2. **Add a safety counter to `parquetArchiveWriter`** that tracks flush count. If the counter approaches the limit (e.g., at 30000), return a specific sentinel error so the caller can handle it gracefully.\n\nThis gives at most ~3000 row groups for a 3000-node cluster, well within the 32767 limit. The safety counter protects against future scenarios (e.g., if clusters grow to 30000+ nodes, or if the code is called differently).\n\n### Detailed Changes\n\n#### File 1: `pkg/metricstore/parquetArchive.go`\n\n**Change A: Remove `Flush()` from `WriteCheckpointFile`, add separate `FlushRowGroup` method**\n\nIn `WriteCheckpointFile` (lines 103-120):\n- Remove the `w.writer.Flush()` call (lines 115-117)\n- Keep only the batch-draining logic (writing remaining rows in `w.batch`)\n\nAdd a new public method:\n\n```go\n// FlushRowGroup finalizes the current buffered rows as a row group.\n// Should be called after writing all checkpoint files for one logical unit (e.g., one host).\nfunc (w *parquetArchiveWriter) FlushRowGroup() error {\n w.rowGroupCount++\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n**Change B: Add `rowGroupCount` field to `parquetArchiveWriter` struct**\n\nAdd a `rowGroupCount int` field to the struct (line 65-71). This is informational -- the parquet-go library already enforces the hard limit, but having this counter lets us log useful diagnostics.\n\n#### File 2: `pkg/metricstore/archive.go`\n\n**Change: Flush once per host instead of per checkpoint file**\n\nIn `archiveCheckpoints()`, the loop at lines 268-281 currently calls `WriteCheckpointFile` for each checkpoint (which flushes each time). Change to:\n\n```go\nfor r := range results {\n if writeErr == nil {\n for _, cf := range r.checkpoints {\n if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n writeErr = err\n break\n }\n }\n // Flush one row group per host (all checkpoints combined)\n if writeErr == nil {\n if err := writer.FlushRowGroup(); err != nil {\n writeErr = err\n }\n }\n }\n toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n}\n```\n\nThis ensures exactly one row group per host per cluster, giving at most ~3000 row groups for a 3000-node cluster.\n\n### Why Not the Other Approaches\n\n- **Approach 2 (split files)**: Adds significant complexity -- tracking multiple files, naming conventions, readers needing to handle multi-file archives. Unnecessary since per-host flushing keeps us well under the limit.\n\n- **Periodic flush by row count**: Would break the natural host-boundary grouping. A row group per host is semantically clean and gives excellent compression (all data for one host is contiguous and sorted by metric+timestamp).\n\n### Compression Benefit\n\nFlushing per host instead of per checkpoint is actually better for compression. Multiple checkpoint files for the same host now end up in a single row group, keeping hostname, cluster, and metric columns highly repetitive within each group. The data is already sorted by (cluster, hostname, metric, timestamp) due to `writeLevel`'s sorted iteration.\n\n### Edge Case: Very Large Clusters (30000+ nodes)\n\nIf this ever becomes a concern, the fix would be to add file splitting at that point. But since even the largest known HPC clusters (Frontier at ~9400 nodes) are well under 32767, this is not needed now. The `rowGroupCount` field makes it easy to add later.\n\n### Testing\n\n- Verify the existing test patterns for the parquet archiver. The key assertion is that `WriteCheckpointFile` no longer calls `Flush()` and `FlushRowGroup()` is called from the archive loop.\n- For a cluster with N hosts, the parquet file should contain exactly N row groups.\n\n### Critical Files for Implementation\n\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go` - Remove Flush from WriteCheckpointFile, add FlushRowGroup method, add rowGroupCount field\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go` - Call FlushRowGroup once per host in the archiveCheckpoints loop\n- `/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go` - Reference: understand Flush/row group semantics (read-only, library code)"},{"type":"text","text":"agentId: a74b5803a0410fec5 (use SendMessage with to: 'a74b5803a0410fec5' to continue this agent)\n<usage>total_tokens: 33433\ntool_uses: 12\nduration_ms: 140246</usage>"}]}]},"uuid":"35235ed5-59fb-476b-b27d-ee54922dfe89","timestamp":"2026-03-23T05:13:43.367Z","toolUseResult":{"status":"completed","prompt":"Design a fix for a parquet row group limit issue in the metric store archiver.\n\n## Problem\n\nThe error is: \"the limit of 32767 row groups has been reached\"\n\nThis happens in `pkg/metricstore/archive.go:archiveCheckpoints()` which creates ONE parquet file per cluster. For each host's checkpoint file, `WriteCheckpointFile()` in `pkg/metricstore/parquetArchive.go` calls `writer.Flush()`, creating one row group per checkpoint file.\n\nFor large clusters like \"fritz\" with many hosts (e.g., 1000+) and multiple checkpoint files per host, total flushes easily exceed 32767.\n\n## Current flow (archive.go lines 268-280):\n\n```go\nfor r := range results {\n for _, cf := range r.checkpoints {\n // Each call creates a row group via Flush()\n writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\")\n }\n}\n```\n\n## WriteCheckpointFile (parquetArchive.go lines 103-120):\n\n```go\nfunc (w *parquetArchiveWriter) WriteCheckpointFile(cf *CheckpointFile, ...) error {\n w.writeLevel(cf, cluster, hostname, scope, scopeID)\n // Flush remaining batch\n if len(w.batch) > 0 {\n w.writer.Write(w.batch)\n w.count += len(w.batch)\n w.batch = w.batch[:0]\n }\n // THIS creates a new row group every time\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n## Design constraints\n\n- The parquet-go library hard-limits row groups to 32767 per file\n- We want good compression (data sorted by cluster, hostname, metric, timestamp)\n- Don't accumulate all rows in memory — streaming is important\n- Performance: this is HPC monitoring at scale\n\n## Possible approaches\n\n1. **Remove per-checkpoint Flush, flush periodically instead**: Instead of flushing after every checkpoint file, flush after accumulating a certain number of rows (e.g., every 100k rows or every N checkpoints). This reduces row groups dramatically while still bounding memory.\n\n2. **Split into multiple parquet files**: When approaching the row group limit, close the current file and open a new one.\n\n3. **Flush per host instead of per checkpoint**: Since multiple checkpoints can belong to the same host, only flush once per host rather than per checkpoint file.\n\nWhich approach is best? Consider that:\n- A host may have 1 to ~hundreds of checkpoint files\n- A cluster may have ~100 to ~3000+ hosts\n- Flushing per host would give at most ~3000 row groups (within limit for most clusters)\n- But combining approaches 1+2 would be most robust\n\nPlease design the recommended implementation approach with specific code changes needed.","agentId":"a74b5803a0410fec5","content":[{"type":"text","text":"Good. Now I have full context. Here is the implementation plan.\n\n---\n\n## Implementation Plan: Fix Parquet Row Group Limit\n\n### Problem Analysis\n\nEvery call to `WriteCheckpointFile()` ends with `w.writer.Flush()`, which creates one row group. The parquet-go library hard-limits this to `MaxRowGroups = 32767` (math.MaxInt16). For a cluster with 3000 hosts and even just 11 checkpoint files per host, that is 33000 flushes, exceeding the limit.\n\n### Recommended Approach: Combined Strategy (Approaches 1 + 3)\n\nThe fix has two parts:\n\n1. **Move the `Flush()` call out of `WriteCheckpointFile` and into the caller in `archive.go`**, flushing once per host (after all checkpoint files for that host are written). This is the primary fix -- it is the natural boundary since each `hostResult` groups all checkpoints for a single host.\n\n2. **Add a safety counter to `parquetArchiveWriter`** that tracks flush count. If the counter approaches the limit (e.g., at 30000), return a specific sentinel error so the caller can handle it gracefully.\n\nThis gives at most ~3000 row groups for a 3000-node cluster, well within the 32767 limit. The safety counter protects against future scenarios (e.g., if clusters grow to 30000+ nodes, or if the code is called differently).\n\n### Detailed Changes\n\n#### File 1: `pkg/metricstore/parquetArchive.go`\n\n**Change A: Remove `Flush()` from `WriteCheckpointFile`, add separate `FlushRowGroup` method**\n\nIn `WriteCheckpointFile` (lines 103-120):\n- Remove the `w.writer.Flush()` call (lines 115-117)\n- Keep only the batch-draining logic (writing remaining rows in `w.batch`)\n\nAdd a new public method:\n\n```go\n// FlushRowGroup finalizes the current buffered rows as a row group.\n// Should be called after writing all checkpoint files for one logical unit (e.g., one host).\nfunc (w *parquetArchiveWriter) FlushRowGroup() error {\n w.rowGroupCount++\n if err := w.writer.Flush(); err != nil {\n return fmt.Errorf(\"flushing parquet row group: %w\", err)\n }\n return nil\n}\n```\n\n**Change B: Add `rowGroupCount` field to `parquetArchiveWriter` struct**\n\nAdd a `rowGroupCount int` field to the struct (line 65-71). This is informational -- the parquet-go library already enforces the hard limit, but having this counter lets us log useful diagnostics.\n\n#### File 2: `pkg/metricstore/archive.go`\n\n**Change: Flush once per host instead of per checkpoint file**\n\nIn `archiveCheckpoints()`, the loop at lines 268-281 currently calls `WriteCheckpointFile` for each checkpoint (which flushes each time). Change to:\n\n```go\nfor r := range results {\n if writeErr == nil {\n for _, cf := range r.checkpoints {\n if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n writeErr = err\n break\n }\n }\n // Flush one row group per host (all checkpoints combined)\n if writeErr == nil {\n if err := writer.FlushRowGroup(); err != nil {\n writeErr = err\n }\n }\n }\n toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n}\n```\n\nThis ensures exactly one row group per host per cluster, giving at most ~3000 row groups for a 3000-node cluster.\n\n### Why Not the Other Approaches\n\n- **Approach 2 (split files)**: Adds significant complexity -- tracking multiple files, naming conventions, readers needing to handle multi-file archives. Unnecessary since per-host flushing keeps us well under the limit.\n\n- **Periodic flush by row count**: Would break the natural host-boundary grouping. A row group per host is semantically clean and gives excellent compression (all data for one host is contiguous and sorted by metric+timestamp).\n\n### Compression Benefit\n\nFlushing per host instead of per checkpoint is actually better for compression. Multiple checkpoint files for the same host now end up in a single row group, keeping hostname, cluster, and metric columns highly repetitive within each group. The data is already sorted by (cluster, hostname, metric, timestamp) due to `writeLevel`'s sorted iteration.\n\n### Edge Case: Very Large Clusters (30000+ nodes)\n\nIf this ever becomes a concern, the fix would be to add file splitting at that point. But since even the largest known HPC clusters (Frontier at ~9400 nodes) are well under 32767, this is not needed now. The `rowGroupCount` field makes it easy to add later.\n\n### Testing\n\n- Verify the existing test patterns for the parquet archiver. The key assertion is that `WriteCheckpointFile` no longer calls `Flush()` and `FlushRowGroup()` is called from the archive loop.\n- For a cluster with N hosts, the parquet file should contain exactly N row groups.\n\n### Critical Files for Implementation\n\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/parquetArchive.go` - Remove Flush from WriteCheckpointFile, add FlushRowGroup method, add rowGroupCount field\n- `/Users/jan/prg/ClusterCockpit/cc-backend/pkg/metricstore/archive.go` - Call FlushRowGroup once per host in the archiveCheckpoints loop\n- `/Users/jan/go/pkg/mod/github.com/parquet-go/parquet-go@v0.29.0/writer.go` - Reference: understand Flush/row group semantics (read-only, library code)"}],"totalDurationMs":140246,"totalTokens":33433,"totalToolUseCount":12,"usage":{"input_tokens":1,"cache_creation_input_tokens":219,"cache_read_input_tokens":31791,"output_tokens":1422,"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":219},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"ce620e78-df86-4300-a26d-b30ccc052b1c","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"35235ed5-59fb-476b-b27d-ee54922dfe89","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01MSAnk2kk9zhbCqp2SLm367","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Tbi9SbC8x1zePwXcQjNidu","name":"Write","input":{"file_path":"/Users/jan/.claude/plans/agile-napping-otter.md","content":"# Fix: Parquet Row Group Limit in Metric Store Archiving\n\n## Context\n\nThe cleanup archiver creates one parquet file per cluster and calls `writer.Flush()` after every checkpoint file, creating one row group per checkpoint. The parquet-go library hard-limits row groups to 32767 per file. Large clusters like \"fritz\" with many hosts and multiple checkpoint files per host exceed this limit, causing: `flushing parquet row group: the limit of 32767 row groups has been reached`\n\n## Root Cause\n\nIn `WriteCheckpointFile()` (`parquetArchive.go:115`), `w.writer.Flush()` is called after **every** checkpoint file. For a cluster with e.g. 1000 hosts × 40 checkpoint files = 40,000 flushes → 40,000 row groups → exceeds 32767.\n\n## Fix\n\nMove the `Flush()` out of `WriteCheckpointFile` and into the caller, flushing **once per host** instead of once per checkpoint file. This gives at most one row group per host (e.g. ~3000 for a large cluster), well within the limit.\n\nThis also improves compression — all checkpoint data for a single host is now in one row group with highly repetitive column values.\n\n### File 1: `pkg/metricstore/parquetArchive.go`\n\n1. **Remove `Flush()` from `WriteCheckpointFile`** (lines 115-117) — keep only the batch-drain logic\n2. **Add `FlushRowGroup()` method** — wraps `w.writer.Flush()` for the caller to invoke explicitly\n\n### File 2: `pkg/metricstore/archive.go`\n\n3. **Call `FlushRowGroup()` once per host** in the `for r := range results` loop (after all checkpoint files for that host are written), instead of relying on per-checkpoint flushes:\n\n```go\nfor r := range results {\n if writeErr == nil {\n for _, cf := range r.checkpoints {\n if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n writeErr = err\n break\n }\n }\n if writeErr == nil {\n if err := writer.FlushRowGroup(); err != nil {\n writeErr = err\n }\n }\n }\n toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n}\n```\n\n## Verification\n\n- `go build ./pkg/metricstore/...` — compiles\n- `go test ./pkg/metricstore/...` — existing tests pass\n- Manually verify: for a cluster with N hosts, the parquet file should contain N row groups (not N × checkpoints-per-host)\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":2665,"cache_read_input_tokens":30257,"output_tokens":755,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2665,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZKSVu4tyXSGB7FuvQYTW","type":"assistant","uuid":"d90f1129-1552-47bb-9c08-c4f2ba803b69","timestamp":"2026-03-23T05:13:55.257Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"d90f1129-1552-47bb-9c08-c4f2ba803b69","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Write","command":"callback"},"parentToolUseID":"toolu_01Tbi9SbC8x1zePwXcQjNidu","toolUseID":"toolu_01Tbi9SbC8x1zePwXcQjNidu","timestamp":"2026-03-23T05:13:55.266Z","uuid":"359f2720-5aab-4f15-ad58-d4e10217555d","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
{"parentUuid":"d90f1129-1552-47bb-9c08-c4f2ba803b69","isSidechain":false,"promptId":"4c9038e2-c763-4f23-82bf-037c28776776","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Tbi9SbC8x1zePwXcQjNidu","type":"tool_result","content":"File created successfully at: /Users/jan/.claude/plans/agile-napping-otter.md"}]},"uuid":"db61b395-e25e-45d0-b129-0d80b658b5c2","timestamp":"2026-03-23T05:13:55.266Z","toolUseResult":{"type":"create","filePath":"/Users/jan/.claude/plans/agile-napping-otter.md","content":"# Fix: Parquet Row Group Limit in Metric Store Archiving\n\n## Context\n\nThe cleanup archiver creates one parquet file per cluster and calls `writer.Flush()` after every checkpoint file, creating one row group per checkpoint. The parquet-go library hard-limits row groups to 32767 per file. Large clusters like \"fritz\" with many hosts and multiple checkpoint files per host exceed this limit, causing: `flushing parquet row group: the limit of 32767 row groups has been reached`\n\n## Root Cause\n\nIn `WriteCheckpointFile()` (`parquetArchive.go:115`), `w.writer.Flush()` is called after **every** checkpoint file. For a cluster with e.g. 1000 hosts × 40 checkpoint files = 40,000 flushes → 40,000 row groups → exceeds 32767.\n\n## Fix\n\nMove the `Flush()` out of `WriteCheckpointFile` and into the caller, flushing **once per host** instead of once per checkpoint file. This gives at most one row group per host (e.g. ~3000 for a large cluster), well within the limit.\n\nThis also improves compression — all checkpoint data for a single host is now in one row group with highly repetitive column values.\n\n### File 1: `pkg/metricstore/parquetArchive.go`\n\n1. **Remove `Flush()` from `WriteCheckpointFile`** (lines 115-117) — keep only the batch-drain logic\n2. **Add `FlushRowGroup()` method** — wraps `w.writer.Flush()` for the caller to invoke explicitly\n\n### File 2: `pkg/metricstore/archive.go`\n\n3. **Call `FlushRowGroup()` once per host** in the `for r := range results` loop (after all checkpoint files for that host are written), instead of relying on per-checkpoint flushes:\n\n```go\nfor r := range results {\n if writeErr == nil {\n for _, cf := range r.checkpoints {\n if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n writeErr = err\n break\n }\n }\n if writeErr == nil {\n if err := writer.FlushRowGroup(); err != nil {\n writeErr = err\n }\n }\n }\n toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n}\n```\n\n## Verification\n\n- `go build ./pkg/metricstore/...` — compiles\n- `go test ./pkg/metricstore/...` — existing tests pass\n- Manually verify: for a cluster with N hosts, the parquet file should contain N row groups (not N × checkpoints-per-host)\n","structuredPatch":[],"originalFile":null},"sourceToolAssistantUUID":"d90f1129-1552-47bb-9c08-c4f2ba803b69","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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{"parentUuid":"659e2c26-3af0-49ff-b68b-f1fcde466b2c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_017fHgZL7ckrEFA61G23w2ML","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017D7YQGr36TBJ3FZ78YxzdX","name":"ExitPlanMode","input":{"allowedPrompts":[{"tool":"Bash","prompt":"run go build and go test for metricstore package"}],"plan":"# Fix: Parquet Row Group Limit in Metric Store Archiving\n\n## Context\n\nThe cleanup archiver creates one parquet file per cluster and calls `writer.Flush()` after every checkpoint file, creating one row group per checkpoint. The parquet-go library hard-limits row groups to 32767 per file. Large clusters like \"fritz\" with many hosts and multiple checkpoint files per host exceed this limit, causing: `flushing parquet row group: the limit of 32767 row groups has been reached`\n\n## Root Cause\n\nIn `WriteCheckpointFile()` (`parquetArchive.go:115`), `w.writer.Flush()` is called after **every** checkpoint file. For a cluster with e.g. 1000 hosts × 40 checkpoint files = 40,000 flushes → 40,000 row groups → exceeds 32767.\n\n## Fix\n\nMove the `Flush()` out of `WriteCheckpointFile` and into the caller, flushing **once per host** instead of once per checkpoint file. This gives at most one row group per host (e.g. ~3000 for a large cluster), well within the limit.\n\nThis also improves compression — all checkpoint data for a single host is now in one row group with highly repetitive column values.\n\n### File 1: `pkg/metricstore/parquetArchive.go`\n\n1. **Remove `Flush()` from `WriteCheckpointFile`** (lines 115-117) — keep only the batch-drain logic\n2. **Add `FlushRowGroup()` method** — wraps `w.writer.Flush()` for the caller to invoke explicitly\n\n### File 2: `pkg/metricstore/archive.go`\n\n3. **Call `FlushRowGroup()` once per host** in the `for r := range results` loop (after all checkpoint files for that host are written), instead of relying on per-checkpoint flushes:\n\n```go\nfor r := range results {\n if writeErr == nil {\n for _, cf := range r.checkpoints {\n if err := writer.WriteCheckpointFile(cf, cluster, r.hostname, \"node\", \"\"); err != nil {\n writeErr = err\n break\n }\n }\n if writeErr == nil {\n if err := writer.FlushRowGroup(); err != nil {\n writeErr = err\n }\n }\n }\n toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n}\n```\n\n## Verification\n\n- `go build ./pkg/metricstore/...` — compiles\n- `go test ./pkg/metricstore/...` — existing tests pass\n- Manually verify: for a cluster with N hosts, the parquet file should contain N row groups (not N × checkpoints-per-host)\n","planFilePath":"/Users/jan/.claude/plans/agile-napping-otter.md"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1531,"cache_read_input_tokens":32922,"output_tokens":83,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1531,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZKSWy6mSBfqTauBbt7r9","type":"assistant","uuid":"64199922-8e88-44bb-a298-3571ac285d39","timestamp":"2026-03-23T05:14:01.626Z","userType":"external","entrypoint":"cli","cwd":"/Users/jan/prg/ClusterCockpit/cc-backend","sessionId":"94e2d90e-5772-4423-a4fb-75c7caa1e1c4","version":"2.1.80","gitBranch":"hotfix","slug":"agile-napping-otter"}
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