diff --git a/20/746187d135/0/content_hash.txt b/20/746187d135/0/content_hash.txt
new file mode 100644
index 00000000..9c251a76
--- /dev/null
+++ b/20/746187d135/0/content_hash.txt
@@ -0,0 +1 @@
+sha256:9afbd2231cd2de94d00602cda5fece31185c1a0c488b63391fed94963950b039
\ No newline at end of file
diff --git a/20/746187d135/0/context.md b/20/746187d135/0/context.md
new file mode 100644
index 00000000..bd62cb32
--- /dev/null
+++ b/20/746187d135/0/context.md
@@ -0,0 +1,17 @@
+# Session Context
+
+## User Prompts
+
+### Prompt 1
+
+Implement the following plan:
+
+# Plan: Improve GetUser logging
+
+## Context
+
+`GetUser` in `internal/repository/user.go` (line 75) logs a `Warn` for every query error, including the common `sql.ErrNoRows` case (user not found). Two problems:
+
+1. `sql.ErrNoRows` is a normal, expected condition — many callers check for it explicitly. It should not produce a warning.
+2. The log message **omits the actual error**: `"Error while querying user '%v' from database"` gives no clue what went wrong for re...
+
diff --git a/20/746187d135/0/full.jsonl b/20/746187d135/0/full.jsonl
new file mode 100644
index 00000000..25e24e49
--- /dev/null
+++ b/20/746187d135/0/full.jsonl
@@ -0,0 +1,27 @@
+{"type":"file-history-snapshot","messageId":"7fbf4291-37f3-41e7-80e6-5c696ecb5872","snapshot":{"messageId":"7fbf4291-37f3-41e7-80e6-5c696ecb5872","trackedFileBackups":{},"timestamp":"2026-03-16T19:07:02.416Z"},"isSnapshotUpdate":false}
+{"parentUuid":null,"isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"9cd6d0b7-b1c2-4124-ae15-70ad9bba24be","toolUseID":"9cd6d0b7-b1c2-4124-ae15-70ad9bba24be","timestamp":"2026-03-16T19:07:02.372Z","uuid":"218ef109-ae6a-464b-83c4-e53227c0722e","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"218ef109-ae6a-464b-83c4-e53227c0722e","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Plan: Improve GetUser logging\n\n## Context\n\n`GetUser` in `internal/repository/user.go` (line 75) logs a `Warn` for every query error, including the common `sql.ErrNoRows` case (user not found). Two problems:\n\n1. `sql.ErrNoRows` is a normal, expected condition — many callers check for it explicitly. It should not produce a warning.\n2. The log message **omits the actual error**: `\"Error while querying user '%v' from database\"` gives no clue what went wrong for real failures.\n\nThis is the same pattern just fixed in `scanJob` (job.go). The established approach: suppress `sql.ErrNoRows`, add `runtime.Caller(1)` context and include `err` in real-error logs.\n\n## Approach\n\nModify the `Scan` error block in `GetUser` (`internal/repository/user.go`, lines 75-79):\n\n```go\nif err := sq.Select(...).QueryRow().Scan(...); err != nil {\n    if err != sql.ErrNoRows {\n        _, file, line, _ := runtime.Caller(1)\n        cclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",\n            username, filepath.Base(file), line, err)\n    }\n    return nil, err\n}\n```\n\nAdd `\"path/filepath\"` and `\"runtime\"` to imports (not currently present in user.go).\n\n## Critical File\n\n- `internal/repository/user.go` — only file to change (lines ~7-24 for imports, ~75-79 for error block)\n\n## Verification\n\n1. `go build ./...` — must compile cleanly\n2. `go test ./internal/repository/...` — existing tests must pass\n\n\nIf you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd.jsonl"},"uuid":"7fbf4291-37f3-41e7-80e6-5c696ecb5872","timestamp":"2026-03-16T19:07:02.269Z","planContent":"# Plan: Improve GetUser logging\n\n## Context\n\n`GetUser` in `internal/repository/user.go` (line 75) logs a `Warn` for every query error, including the common `sql.ErrNoRows` case (user not found). Two problems:\n\n1. `sql.ErrNoRows` is a normal, expected condition — many callers check for it explicitly. It should not produce a warning.\n2. The log message **omits the actual error**: `\"Error while querying user '%v' from database\"` gives no clue what went wrong for real failures.\n\nThis is the same pattern just fixed in `scanJob` (job.go). The established approach: suppress `sql.ErrNoRows`, add `runtime.Caller(1)` context and include `err` in real-error logs.\n\n## Approach\n\nModify the `Scan` error block in `GetUser` (`internal/repository/user.go`, lines 75-79):\n\n```go\nif err := sq.Select(...).QueryRow().Scan(...); err != nil {\n    if err != sql.ErrNoRows {\n        _, file, line, _ := runtime.Caller(1)\n        cclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",\n            username, filepath.Base(file), line, err)\n    }\n    return nil, err\n}\n```\n\nAdd `\"path/filepath\"` and `\"runtime\"` to imports (not currently present in user.go).\n\n## Critical File\n\n- `internal/repository/user.go` — only file to change (lines ~7-24 for imports, ~75-79 for error block)\n\n## Verification\n\n1. `go build ./...` — must compile cleanly\n2. `go test ./internal/repository/...` — existing tests must pass\n","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"6948b02d-eada-484e-bbcb-6b9dce5c65c7","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011PJX5Vvedcskvx3GzzctG7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KGYRPm2UjfLALSdWfEgrhz","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/user.go","limit":90},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":9386,"cache_read_input_tokens":8667,"output_tokens":122,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":9386,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ7HP7M3bgkxEBxNqyME4","type":"assistant","uuid":"e7306f16-6e8c-45b6-8809-d84c34ba063b","timestamp":"2026-03-16T19:07:06.975Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"e7306f16-6e8c-45b6-8809-d84c34ba063b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01KGYRPm2UjfLALSdWfEgrhz","toolUseID":"toolu_01KGYRPm2UjfLALSdWfEgrhz","timestamp":"2026-03-16T19:07:06.992Z","uuid":"54ebb7c9-247d-450b-a866-1e55fc42b898","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"e7306f16-6e8c-45b6-8809-d84c34ba063b","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KGYRPm2UjfLALSdWfEgrhz","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 repository\n     6→\n     7→import (\n     8→\t\"context\"\n     9→\t\"database/sql\"\n    10→\t\"encoding/json\"\n    11→\t\"errors\"\n    12→\t\"fmt\"\n    13→\t\"reflect\"\n    14→\t\"strings\"\n    15→\t\"sync\"\n    16→\n    17→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n    18→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n    19→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    20→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    21→\tsq \"github.com/Masterminds/squirrel\"\n    22→\t\"github.com/jmoiron/sqlx\"\n    23→\t\"golang.org/x/crypto/bcrypt\"\n    24→)\n    25→\n    26→// Authentication and Role System:\n    27→//\n    28→// ClusterCockpit supports multiple authentication sources:\n    29→//   - Local: Username/password stored in database (password hashed with bcrypt)\n    30→//   - LDAP: External LDAP/Active Directory authentication\n    31→//   - JWT: Token-based authentication for API access\n    32→//\n    33→// Role Hierarchy (from highest to lowest privilege):\n    34→//   1. \"admin\" - Full system access, can manage all users and jobs\n    35→//   2. \"support\" - Can view all jobs but limited management capabilities\n    36→//   3. \"manager\" - Can manage specific projects and their users\n    37→//   4. \"api\" - Programmatic access for job submission/management\n    38→//   5. \"user\" - Default role, can only view own jobs\n    39→//\n    40→// Project Association:\n    41→//   - Managers have a list of projects they oversee\n    42→//   - Regular users' project membership is determined by job data\n    43→//   - Managers can view/manage all jobs within their projects\n    44→\n    45→var (\n    46→\tuserRepoOnce     sync.Once\n    47→\tuserRepoInstance *UserRepository\n    48→)\n    49→\n    50→type UserRepository struct {\n    51→\tDB     *sqlx.DB\n    52→\tdriver string\n    53→}\n    54→\n    55→func GetUserRepository() *UserRepository {\n    56→\tuserRepoOnce.Do(func() {\n    57→\t\tdb := GetConnection()\n    58→\n    59→\t\tuserRepoInstance = &UserRepository{\n    60→\t\t\tDB:     db.DB,\n    61→\t\t\tdriver: db.Driver,\n    62→\t\t}\n    63→\t})\n    64→\treturn userRepoInstance\n    65→}\n    66→\n    67→// GetUser retrieves a user by username from the database.\n    68→// Returns the complete user record including hashed password, roles, and projects.\n    69→// Password field contains bcrypt hash for local auth users, empty for LDAP users.\n    70→func (r *UserRepository) GetUser(username string) (*schema.User, error) {\n    71→\tuser := &schema.User{Username: username}\n    72→\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n    73→\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n    74→\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n    75→\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n    76→\t\tcclog.Warnf(\"Error while querying user '%v' from database\", username)\n    77→\t\treturn nil, err\n    78→\t}\n    79→\n    80→\tuser.Password = hashedPassword.String\n    81→\tuser.Name = name.String\n    82→\tuser.Email = email.String\n    83→\tif rawRoles.Valid {\n    84→\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n    85→\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n    86→\t\t\treturn nil, err\n    87→\t\t}\n    88→\t}\n    89→\tif rawProjects.Valid {\n    90→\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"7719bb17-00b5-4ad4-9b66-dea2045a44eb","timestamp":"2026-03-16T19:07:06.992Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/user.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.\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"reflect\"\n\t\"strings\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n\t\"golang.org/x/crypto/bcrypt\"\n)\n\n// Authentication and Role System:\n//\n// ClusterCockpit supports multiple authentication sources:\n//   - Local: Username/password stored in database (password hashed with bcrypt)\n//   - LDAP: External LDAP/Active Directory authentication\n//   - JWT: Token-based authentication for API access\n//\n// Role Hierarchy (from highest to lowest privilege):\n//   1. \"admin\" - Full system access, can manage all users and jobs\n//   2. \"support\" - Can view all jobs but limited management capabilities\n//   3. \"manager\" - Can manage specific projects and their users\n//   4. \"api\" - Programmatic access for job submission/management\n//   5. \"user\" - Default role, can only view own jobs\n//\n// Project Association:\n//   - Managers have a list of projects they oversee\n//   - Regular users' project membership is determined by job data\n//   - Managers can view/manage all jobs within their projects\n\nvar (\n\tuserRepoOnce     sync.Once\n\tuserRepoInstance *UserRepository\n)\n\ntype UserRepository struct {\n\tDB     *sqlx.DB\n\tdriver string\n}\n\nfunc GetUserRepository() *UserRepository {\n\tuserRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tuserRepoInstance = &UserRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\t\t}\n\t})\n\treturn userRepoInstance\n}\n\n// GetUser retrieves a user by username from the database.\n// Returns the complete user record including hashed password, roles, and projects.\n// Password field contains bcrypt hash for local auth users, empty for LDAP users.\nfunc (r *UserRepository) GetUser(username string) (*schema.User, error) {\n\tuser := &schema.User{Username: username}\n\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tcclog.Warnf(\"Error while querying user '%v' from database\", username)\n\t\treturn nil, err\n\t}\n\n\tuser.Password = hashedPassword.String\n\tuser.Name = name.String\n\tuser.Email = email.String\n\tif rawRoles.Valid {\n\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n\t\t\treturn nil, err\n\t\t}\n\t}\n\tif rawProjects.Valid {\n\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {","numLines":90,"startLine":1,"totalLines":518}},"sourceToolAssistantUUID":"e7306f16-6e8c-45b6-8809-d84c34ba063b","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"2acd4789-2101-4173-9075-92cead753c40","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MQUtPMj2fG3dhJctDh1Aw4","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/internal/repository/user.go has been updated successfully."}]},"uuid":"50d8f9cf-693b-41f2-9dd1-e01d1278eeb5","timestamp":"2026-03-16T19:07:12.058Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/user.go","oldString":"import (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"reflect\"\n\t\"strings\"\n\t\"sync\"","newString":"import (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"path/filepath\"\n\t\"reflect\"\n\t\"runtime\"\n\t\"strings\"\n\t\"sync\"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"reflect\"\n\t\"strings\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n\t\"golang.org/x/crypto/bcrypt\"\n)\n\n// Authentication and Role System:\n//\n// ClusterCockpit supports multiple authentication sources:\n//   - Local: Username/password stored in database (password hashed with bcrypt)\n//   - LDAP: External LDAP/Active Directory authentication\n//   - JWT: Token-based authentication for API access\n//\n// Role Hierarchy (from highest to lowest privilege):\n//   1. \"admin\" - Full system access, can manage all users and jobs\n//   2. \"support\" - Can view all jobs but limited management capabilities\n//   3. \"manager\" - Can manage specific projects and their users\n//   4. \"api\" - Programmatic access for job submission/management\n//   5. \"user\" - Default role, can only view own jobs\n//\n// Project Association:\n//   - Managers have a list of projects they oversee\n//   - Regular users' project membership is determined by job data\n//   - Managers can view/manage all jobs within their projects\n\nvar (\n\tuserRepoOnce     sync.Once\n\tuserRepoInstance *UserRepository\n)\n\ntype UserRepository struct {\n\tDB     *sqlx.DB\n\tdriver string\n}\n\nfunc GetUserRepository() *UserRepository {\n\tuserRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tuserRepoInstance = &UserRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\t\t}\n\t})\n\treturn userRepoInstance\n}\n\n// GetUser retrieves a user by username from the database.\n// Returns the complete user record including hashed password, roles, and projects.\n// Password field contains bcrypt hash for local auth users, empty for LDAP users.\nfunc (r *UserRepository) GetUser(username string) (*schema.User, error) {\n\tuser := &schema.User{Username: username}\n\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tcclog.Warnf(\"Error while querying user '%v' from database\", username)\n\t\treturn nil, err\n\t}\n\n\tuser.Password = hashedPassword.String\n\tuser.Name = name.String\n\tuser.Email = email.String\n\tif rawRoles.Valid {\n\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n\t\t\treturn nil, err\n\t\t}\n\t}\n\tif rawProjects.Valid {\n\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {\n\t\t\treturn nil, err\n\t\t}\n\t}\n\n\treturn user, nil\n}\n\nfunc (r *UserRepository) GetLdapUsernames() ([]string, error) {\n\tvar users []string\n\trows, err := r.DB.Query(`SELECT username FROM hpc_user WHERE hpc_user.ldap = 1`)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying usernames\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tfor rows.Next() {\n\t\tvar username string\n\t\tif err := rows.Scan(&username); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning for user '%s'\", username)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tusers = append(users, username)\n\t}\n\n\treturn users, nil\n}\n\n// AddUser creates a new user in the database.\n// Passwords are automatically hashed with bcrypt before storage.\n// Auth source determines authentication method (local, LDAP, etc.).\n//\n// Required fields: Username, Roles\n// Optional fields: Name, Email, Password, Projects, AuthSource\nfunc (r *UserRepository) AddUser(user *schema.User) error {\n\trolesJson, _ := json.Marshal(user.Roles)\n\tprojectsJson, _ := json.Marshal(user.Projects)\n\n\tcols := []string{\"username\", \"roles\", \"projects\"}\n\tvals := []any{user.Username, string(rolesJson), string(projectsJson)}\n\n\tif user.Name != \"\" {\n\t\tcols = append(cols, \"name\")\n\t\tvals = append(vals, user.Name)\n\t}\n\tif user.Email != \"\" {\n\t\tcols = append(cols, \"email\")\n\t\tvals = append(vals, user.Email)\n\t}\n\tif user.Password != \"\" {\n\t\tpassword, err := bcrypt.GenerateFromPassword([]byte(user.Password), bcrypt.DefaultCost)\n\t\tif err != nil {\n\t\t\tcclog.Error(\"Error while encrypting new user password\")\n\t\t\treturn err\n\t\t}\n\t\tcols = append(cols, \"password\")\n\t\tvals = append(vals, string(password))\n\t}\n\tif user.AuthSource != -1 {\n\t\tcols = append(cols, \"ldap\")\n\t\tvals = append(vals, int(user.AuthSource))\n\t}\n\n\tif _, err := sq.Insert(\"hpc_user\").Columns(cols...).Values(vals...).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while inserting new user '%v' into DB\", user.Username)\n\t\treturn err\n\t}\n\n\tcclog.Infof(\"new user %#v created (roles: %s, auth-source: %d, projects: %s)\", user.Username, rolesJson, user.AuthSource, projectsJson)\n\n\t// DEPRECATED: SUPERSEDED BY NEW USER CONFIG - userConfig.go / web.go\n\tdefaultMetricsCfg, err := config.LoadDefaultMetricsConfig()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error loading default metrics config: %v\", err)\n\t} else if defaultMetricsCfg != nil {\n\t\tfor _, cluster := range defaultMetricsCfg.Clusters {\n\t\t\tmetricsArray := config.ParseMetricsString(cluster.DefaultMetrics)\n\t\t\tmetricsJSON, err := json.Marshal(metricsArray)\n\t\t\tif err != nil {\n\t\t\t\tcclog.Errorf(\"Error marshaling default metrics for cluster %s: %v\", cluster.Name, err)\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\t// Note: StatisticsTable now has different key (metricConfig_jobViewTableMetrics): Not updated here.\n\t\t\tconfKey := \"metricConfig_jobViewPlotMetrics:\" + cluster.Name\n\t\t\tif _, err := sq.Insert(\"configuration\").\n\t\t\t\tColumns(\"username\", \"confkey\", \"value\").\n\t\t\t\tValues(user.Username, confKey, string(metricsJSON)).\n\t\t\t\tRunWith(r.DB).Exec(); err != nil {\n\t\t\t\tcclog.Errorf(\"Error inserting default job view metrics for user %s and cluster %s: %v\", user.Username, cluster.Name, err)\n\t\t\t} else {\n\t\t\t\tcclog.Infof(\"Default job view metrics for user %s and cluster %s set to %s\", user.Username, cluster.Name, string(metricsJSON))\n\t\t\t}\n\t\t}\n\t}\n\t// END DEPRECATION\n\n\treturn nil\n}\n\n// AddUserIfNotExists inserts a user only if the username does not already exist.\n// Uses INSERT OR IGNORE to avoid UNIQUE constraint errors when a user is\n// concurrently created (e.g., by a login while LDAP sync is running).\n// Unlike AddUser, this intentionally skips the deprecated default metrics config insertion.\nfunc (r *UserRepository) AddUserIfNotExists(user *schema.User) error {\n\trolesJson, _ := json.Marshal(user.Roles)\n\tprojectsJson, _ := json.Marshal(user.Projects)\n\n\tcols := \"username, name, roles, projects, ldap\"\n\t_, err := r.DB.Exec(\n\t\t`INSERT OR IGNORE INTO hpc_user (`+cols+`) VALUES (?, ?, ?, ?, ?)`,\n\t\tuser.Username, user.Name, string(rolesJson), string(projectsJson), int(user.AuthSource))\n\treturn err\n}\n\nfunc (r *UserRepository) UpdateUser(dbUser *schema.User, user *schema.User) error {\n\t// user contains updated info -> Apply to dbUser\n\t// --- Simple Name Update ---\n\tif dbUser.Name != user.Name {\n\t\tif _, err := sq.Update(\"hpc_user\").Set(\"name\", user.Name).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec(); err != nil {\n\t\t\tcclog.Errorf(\"error while updating name of user '%s'\", user.Username)\n\t\t\treturn err\n\t\t}\n\t}\n\n\t// --- Def Helpers ---\n\t// Helper to update roles\n\tupdateRoles := func(roles []string) error {\n\t\trolesJSON, _ := json.Marshal(roles)\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"roles\", rolesJSON).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// Helper to update projects\n\tupdateProjects := func(projects []string) error {\n\t\tprojectsJSON, _ := json.Marshal(projects)\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"projects\", projectsJSON).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// Helper to clear projects\n\tclearProjects := func() error {\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"projects\", \"[]\").Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// --- Manager Role Handling ---\n\tif dbUser.HasRole(schema.RoleManager) && user.HasRole(schema.RoleManager) && !reflect.DeepEqual(dbUser.Projects, user.Projects) {\n\t\t// Existing Manager: update projects\n\t\tif err := updateProjects(user.Projects); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleUser) && user.HasRole(schema.RoleManager) && user.HasNotRoles([]schema.Role{schema.RoleAdmin}) {\n\t\t// New Manager: update roles and projects\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t\tif err := updateProjects(user.Projects); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleManager) && user.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleManager}) {\n\t\t// Remove Manager: update roles and clear projects\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t\tif err := clearProjects(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\t// --- Support Role Handling ---\n\tif dbUser.HasRole(schema.RoleUser) && dbUser.HasNotRoles([]schema.Role{schema.RoleSupport}) &&\n\t\tuser.HasRole(schema.RoleSupport) && user.HasNotRoles([]schema.Role{schema.RoleAdmin}) {\n\t\t// New Support: update roles\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleSupport) && user.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n\t\t// Remove Support: update roles\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\treturn nil\n}\n\nfunc (r *UserRepository) DelUser(username string) error {\n\t_, err := r.DB.Exec(`DELETE FROM hpc_user WHERE hpc_user.username = ?`, username)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while deleting user '%s' from DB\", username)\n\t\treturn err\n\t}\n\tcclog.Infof(\"deleted user '%s' from DB\", username)\n\treturn nil\n}\n\nfunc (r *UserRepository) ListUsers(specialsOnly bool) ([]*schema.User, error) {\n\tq := sq.Select(\"username\", \"name\", \"email\", \"roles\", \"projects\").From(\"hpc_user\")\n\tif specialsOnly {\n\t\tq = q.Where(\"(roles != '[\\\"user\\\"]' AND roles != '[]')\")\n\t}\n\n\trows, err := q.RunWith(r.DB).Query()\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying user list\")\n\t\treturn nil, err\n\t}\n\n\tusers := make([]*schema.User, 0)\n\tdefer rows.Close()\n\tfor rows.Next() {\n\t\trawroles := \"\"\n\t\trawprojects := \"\"\n\t\tuser := &schema.User{}\n\t\tvar name, email sql.NullString\n\t\tif err := rows.Scan(&user.Username, &name, &email, &rawroles, &rawprojects); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning user list\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif err := json.Unmarshal([]byte(rawroles), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw role list\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif err := json.Unmarshal([]byte(rawprojects), &user.Projects); err != nil {\n\t\t\treturn nil, err\n\t\t}\n\n\t\tuser.Name = name.String\n\t\tuser.Email = email.String\n\t\tusers = append(users, user)\n\t}\n\treturn users, nil\n}\n\n// AddRole adds a role to a user's role list.\n// Role string is automatically lowercased.\n// Valid roles: admin, support, manager, api, user\n//\n// Returns error if:\n//   - User doesn't exist\n//   - Role is invalid\n//   - User already has the role\nfunc (r *UserRepository) AddRole(\n\tctx context.Context,\n\tusername string,\n\tqueryrole string,\n) error {\n\tnewRole := strings.ToLower(queryrole)\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\tcclog.Warnf(\"Could not load user '%s'\", username)\n\t\treturn err\n\t}\n\n\texists, valid := user.HasValidRole(newRole)\n\n\tif !valid {\n\t\treturn fmt.Errorf(\"supplied role is no valid option : %v\", newRole)\n\t}\n\tif exists {\n\t\treturn fmt.Errorf(\"user %v already has role %v\", username, newRole)\n\t}\n\n\troles, _ := json.Marshal(append(user.Roles, newRole))\n\tif _, err := sq.Update(\"hpc_user\").Set(\"roles\", roles).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"error while adding new role for user '%s'\", user.Username)\n\t\treturn err\n\t}\n\treturn nil\n}\n\n// RemoveRole removes a role from a user's role list.\n//\n// Special rules:\n//   - Cannot remove \"manager\" role while user has assigned projects\n//   - Must remove all projects first before removing manager role\nfunc (r *UserRepository) RemoveRole(ctx context.Context, username string, queryrole string) error {\n\toldRole := strings.ToLower(queryrole)\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\tcclog.Warnf(\"Could not load user '%s'\", username)\n\t\treturn err\n\t}\n\n\texists, valid := user.HasValidRole(oldRole)\n\n\tif !valid {\n\t\treturn fmt.Errorf(\"supplied role is no valid option : %v\", oldRole)\n\t}\n\tif !exists {\n\t\treturn fmt.Errorf(\"role already deleted for user '%v': %v\", username, oldRole)\n\t}\n\n\tif oldRole == schema.GetRoleString(schema.RoleManager) && len(user.Projects) != 0 {\n\t\treturn fmt.Errorf(\"cannot remove role 'manager' while user %s still has assigned project(s) : %v\", username, user.Projects)\n\t}\n\n\tvar newroles []string\n\tfor _, r := range user.Roles {\n\t\tif r != oldRole {\n\t\t\tnewroles = append(newroles, r) // Append all roles not matching requested to be deleted role\n\t\t}\n\t}\n\n\tmroles, _ := json.Marshal(newroles)\n\tif _, err := sq.Update(\"hpc_user\").Set(\"roles\", mroles).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while removing role for user '%s'\", user.Username)\n\t\treturn err\n\t}\n\treturn nil\n}\n\n// AddProject assigns a project to a manager user.\n// Only users with the \"manager\" role can have assigned projects.\n//\n// Returns error if:\n//   - User doesn't have manager role\n//   - User already manages the project\nfunc (r *UserRepository) AddProject(\n\tctx context.Context,\n\tusername string,\n\tproject string,\n) error {\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif !user.HasRole(schema.RoleManager) {\n\t\treturn fmt.Errorf(\"user '%s' is not a manager\", username)\n\t}\n\n\tif user.HasProject(project) {\n\t\treturn fmt.Errorf(\"user '%s' already manages project '%s'\", username, project)\n\t}\n\n\tprojects, _ := json.Marshal(append(user.Projects, project))\n\tif _, err := sq.Update(\"hpc_user\").Set(\"projects\", projects).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\treturn err\n\t}\n\n\treturn nil\n}\n\nfunc (r *UserRepository) RemoveProject(ctx context.Context, username string, project string) error {\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif !user.HasRole(schema.RoleManager) {\n\t\treturn fmt.Errorf(\"user '%#v' is not a manager\", username)\n\t}\n\n\tif !user.HasProject(project) {\n\t\treturn fmt.Errorf(\"user '%#v': Cannot remove project '%#v' - Does not match\", username, project)\n\t}\n\n\tvar exists bool\n\tvar newprojects []string\n\tfor _, p := range user.Projects {\n\t\tif p != project {\n\t\t\tnewprojects = append(newprojects, p) // Append all projects not matching requested to be deleted project\n\t\t} else {\n\t\t\texists = true\n\t\t}\n\t}\n\n\tif exists {\n\t\tvar result any\n\t\tif len(newprojects) == 0 {\n\t\t\tresult = \"[]\"\n\t\t} else {\n\t\t\tresult, _ = json.Marshal(newprojects)\n\t\t}\n\t\tif _, err := sq.Update(\"hpc_user\").Set(\"projects\", result).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\t\treturn err\n\t\t}\n\t\treturn nil\n\t} else {\n\t\treturn fmt.Errorf(\"user %s already does not manage project %s\", username, project)\n\t}\n}\n\ntype ContextKey string\n\nconst ContextUserKey ContextKey = \"user\"\n\nfunc GetUserFromContext(ctx context.Context) *schema.User {\n\tx := ctx.Value(ContextUserKey)\n\tif x == nil {\n\t\tcclog.Warnf(\"no user retrieved from context\")\n\t\treturn nil\n\t}\n\t// cclog.Infof(\"user retrieved from context: %v\", x.(*schema.User))\n\treturn x.(*schema.User)\n}\n\nfunc (r *UserRepository) FetchUserInCtx(ctx context.Context, username string) (*model.User, error) {\n\tme := GetUserFromContext(ctx)\n\tif me != nil && me.Username != username &&\n\t\tme.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\treturn nil, errors.New(\"forbidden\")\n\t}\n\n\tuser := &model.User{Username: username}\n\tvar name, email sql.NullString\n\tif err := sq.Select(\"name\", \"email\").From(\"hpc_user\").Where(\"hpc_user.username = ?\", username).\n\t\tRunWith(r.DB).QueryRow().Scan(&name, &email); err != nil {\n\t\tif err == sql.ErrNoRows {\n\t\t\t/* This warning will be logged *often* for non-local users, i.e. users mentioned only in job-table or archive, */\n\t\t\t/* since FetchUser will be called to retrieve full name and mail for every job in query/list\t\t\t\t\t\t\t\t\t */\n\t\t\t// cclog.Warnf(\"User '%s' Not found in DB\", username)\n\t\t\treturn nil, nil\n\t\t}\n\n\t\tcclog.Warnf(\"Error while fetching user '%s'\", username)\n\t\treturn nil, err\n\t}\n\n\tuser.Name = name.String\n\tuser.Email = email.String\n\treturn user, nil\n}\n","structuredPatch":[{"oldStart":10,"oldLines":7,"newStart":10,"newLines":9,"lines":["   \"encoding/json\"","   \"errors\"","   \"fmt\"","+  \"path/filepath\"","   \"reflect\"","+  \"runtime\"","   \"strings\"","   \"sync\""," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"2acd4789-2101-4173-9075-92cead753c40","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"54afad83-3b10-4b24-9972-609b4915b1c9","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014MYB93LDFRKCGo8NwbLq7Q","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/internal/repository/user.go has been updated successfully."}]},"uuid":"4548479b-8d63-40eb-8914-cdfcccfb5ed3","timestamp":"2026-03-16T19:07:18.098Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/user.go","oldString":"\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tcclog.Warnf(\"Error while querying user '%v' from database\", username)\n\t\treturn nil, err\n\t}","newString":"\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tif err != sql.ErrNoRows {\n\t\t\t_, file, line, _ := runtime.Caller(1)\n\t\t\tcclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",\n\t\t\t\tusername, filepath.Base(file), line, err)\n\t\t}\n\t\treturn nil, err\n\t}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"path/filepath\"\n\t\"reflect\"\n\t\"runtime\"\n\t\"strings\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n\t\"golang.org/x/crypto/bcrypt\"\n)\n\n// Authentication and Role System:\n//\n// ClusterCockpit supports multiple authentication sources:\n//   - Local: Username/password stored in database (password hashed with bcrypt)\n//   - LDAP: External LDAP/Active Directory authentication\n//   - JWT: Token-based authentication for API access\n//\n// Role Hierarchy (from highest to lowest privilege):\n//   1. \"admin\" - Full system access, can manage all users and jobs\n//   2. \"support\" - Can view all jobs but limited management capabilities\n//   3. \"manager\" - Can manage specific projects and their users\n//   4. \"api\" - Programmatic access for job submission/management\n//   5. \"user\" - Default role, can only view own jobs\n//\n// Project Association:\n//   - Managers have a list of projects they oversee\n//   - Regular users' project membership is determined by job data\n//   - Managers can view/manage all jobs within their projects\n\nvar (\n\tuserRepoOnce     sync.Once\n\tuserRepoInstance *UserRepository\n)\n\ntype UserRepository struct {\n\tDB     *sqlx.DB\n\tdriver string\n}\n\nfunc GetUserRepository() *UserRepository {\n\tuserRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tuserRepoInstance = &UserRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\t\t}\n\t})\n\treturn userRepoInstance\n}\n\n// GetUser retrieves a user by username from the database.\n// Returns the complete user record including hashed password, roles, and projects.\n// Password field contains bcrypt hash for local auth users, empty for LDAP users.\nfunc (r *UserRepository) GetUser(username string) (*schema.User, error) {\n\tuser := &schema.User{Username: username}\n\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tcclog.Warnf(\"Error while querying user '%v' from database\", username)\n\t\treturn nil, err\n\t}\n\n\tuser.Password = hashedPassword.String\n\tuser.Name = name.String\n\tuser.Email = email.String\n\tif rawRoles.Valid {\n\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n\t\t\treturn nil, err\n\t\t}\n\t}\n\tif rawProjects.Valid {\n\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {\n\t\t\treturn nil, err\n\t\t}\n\t}\n\n\treturn user, nil\n}\n\nfunc (r *UserRepository) GetLdapUsernames() ([]string, error) {\n\tvar users []string\n\trows, err := r.DB.Query(`SELECT username FROM hpc_user WHERE hpc_user.ldap = 1`)\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying usernames\")\n\t\treturn nil, err\n\t}\n\tdefer rows.Close()\n\n\tfor rows.Next() {\n\t\tvar username string\n\t\tif err := rows.Scan(&username); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning for user '%s'\", username)\n\t\t\treturn nil, err\n\t\t}\n\n\t\tusers = append(users, username)\n\t}\n\n\treturn users, nil\n}\n\n// AddUser creates a new user in the database.\n// Passwords are automatically hashed with bcrypt before storage.\n// Auth source determines authentication method (local, LDAP, etc.).\n//\n// Required fields: Username, Roles\n// Optional fields: Name, Email, Password, Projects, AuthSource\nfunc (r *UserRepository) AddUser(user *schema.User) error {\n\trolesJson, _ := json.Marshal(user.Roles)\n\tprojectsJson, _ := json.Marshal(user.Projects)\n\n\tcols := []string{\"username\", \"roles\", \"projects\"}\n\tvals := []any{user.Username, string(rolesJson), string(projectsJson)}\n\n\tif user.Name != \"\" {\n\t\tcols = append(cols, \"name\")\n\t\tvals = append(vals, user.Name)\n\t}\n\tif user.Email != \"\" {\n\t\tcols = append(cols, \"email\")\n\t\tvals = append(vals, user.Email)\n\t}\n\tif user.Password != \"\" {\n\t\tpassword, err := bcrypt.GenerateFromPassword([]byte(user.Password), bcrypt.DefaultCost)\n\t\tif err != nil {\n\t\t\tcclog.Error(\"Error while encrypting new user password\")\n\t\t\treturn err\n\t\t}\n\t\tcols = append(cols, \"password\")\n\t\tvals = append(vals, string(password))\n\t}\n\tif user.AuthSource != -1 {\n\t\tcols = append(cols, \"ldap\")\n\t\tvals = append(vals, int(user.AuthSource))\n\t}\n\n\tif _, err := sq.Insert(\"hpc_user\").Columns(cols...).Values(vals...).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while inserting new user '%v' into DB\", user.Username)\n\t\treturn err\n\t}\n\n\tcclog.Infof(\"new user %#v created (roles: %s, auth-source: %d, projects: %s)\", user.Username, rolesJson, user.AuthSource, projectsJson)\n\n\t// DEPRECATED: SUPERSEDED BY NEW USER CONFIG - userConfig.go / web.go\n\tdefaultMetricsCfg, err := config.LoadDefaultMetricsConfig()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error loading default metrics config: %v\", err)\n\t} else if defaultMetricsCfg != nil {\n\t\tfor _, cluster := range defaultMetricsCfg.Clusters {\n\t\t\tmetricsArray := config.ParseMetricsString(cluster.DefaultMetrics)\n\t\t\tmetricsJSON, err := json.Marshal(metricsArray)\n\t\t\tif err != nil {\n\t\t\t\tcclog.Errorf(\"Error marshaling default metrics for cluster %s: %v\", cluster.Name, err)\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\t// Note: StatisticsTable now has different key (metricConfig_jobViewTableMetrics): Not updated here.\n\t\t\tconfKey := \"metricConfig_jobViewPlotMetrics:\" + cluster.Name\n\t\t\tif _, err := sq.Insert(\"configuration\").\n\t\t\t\tColumns(\"username\", \"confkey\", \"value\").\n\t\t\t\tValues(user.Username, confKey, string(metricsJSON)).\n\t\t\t\tRunWith(r.DB).Exec(); err != nil {\n\t\t\t\tcclog.Errorf(\"Error inserting default job view metrics for user %s and cluster %s: %v\", user.Username, cluster.Name, err)\n\t\t\t} else {\n\t\t\t\tcclog.Infof(\"Default job view metrics for user %s and cluster %s set to %s\", user.Username, cluster.Name, string(metricsJSON))\n\t\t\t}\n\t\t}\n\t}\n\t// END DEPRECATION\n\n\treturn nil\n}\n\n// AddUserIfNotExists inserts a user only if the username does not already exist.\n// Uses INSERT OR IGNORE to avoid UNIQUE constraint errors when a user is\n// concurrently created (e.g., by a login while LDAP sync is running).\n// Unlike AddUser, this intentionally skips the deprecated default metrics config insertion.\nfunc (r *UserRepository) AddUserIfNotExists(user *schema.User) error {\n\trolesJson, _ := json.Marshal(user.Roles)\n\tprojectsJson, _ := json.Marshal(user.Projects)\n\n\tcols := \"username, name, roles, projects, ldap\"\n\t_, err := r.DB.Exec(\n\t\t`INSERT OR IGNORE INTO hpc_user (`+cols+`) VALUES (?, ?, ?, ?, ?)`,\n\t\tuser.Username, user.Name, string(rolesJson), string(projectsJson), int(user.AuthSource))\n\treturn err\n}\n\nfunc (r *UserRepository) UpdateUser(dbUser *schema.User, user *schema.User) error {\n\t// user contains updated info -> Apply to dbUser\n\t// --- Simple Name Update ---\n\tif dbUser.Name != user.Name {\n\t\tif _, err := sq.Update(\"hpc_user\").Set(\"name\", user.Name).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec(); err != nil {\n\t\t\tcclog.Errorf(\"error while updating name of user '%s'\", user.Username)\n\t\t\treturn err\n\t\t}\n\t}\n\n\t// --- Def Helpers ---\n\t// Helper to update roles\n\tupdateRoles := func(roles []string) error {\n\t\trolesJSON, _ := json.Marshal(roles)\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"roles\", rolesJSON).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// Helper to update projects\n\tupdateProjects := func(projects []string) error {\n\t\tprojectsJSON, _ := json.Marshal(projects)\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"projects\", projectsJSON).Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// Helper to clear projects\n\tclearProjects := func() error {\n\t\t_, err := sq.Update(\"hpc_user\").Set(\"projects\", \"[]\").Where(\"hpc_user.username = ?\", dbUser.Username).RunWith(r.DB).Exec()\n\t\treturn err\n\t}\n\n\t// --- Manager Role Handling ---\n\tif dbUser.HasRole(schema.RoleManager) && user.HasRole(schema.RoleManager) && !reflect.DeepEqual(dbUser.Projects, user.Projects) {\n\t\t// Existing Manager: update projects\n\t\tif err := updateProjects(user.Projects); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleUser) && user.HasRole(schema.RoleManager) && user.HasNotRoles([]schema.Role{schema.RoleAdmin}) {\n\t\t// New Manager: update roles and projects\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t\tif err := updateProjects(user.Projects); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleManager) && user.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleManager}) {\n\t\t// Remove Manager: update roles and clear projects\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t\tif err := clearProjects(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\t// --- Support Role Handling ---\n\tif dbUser.HasRole(schema.RoleUser) && dbUser.HasNotRoles([]schema.Role{schema.RoleSupport}) &&\n\t\tuser.HasRole(schema.RoleSupport) && user.HasNotRoles([]schema.Role{schema.RoleAdmin}) {\n\t\t// New Support: update roles\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t} else if dbUser.HasRole(schema.RoleSupport) && user.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport}) {\n\t\t// Remove Support: update roles\n\t\tif err := updateRoles(user.Roles); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\treturn nil\n}\n\nfunc (r *UserRepository) DelUser(username string) error {\n\t_, err := r.DB.Exec(`DELETE FROM hpc_user WHERE hpc_user.username = ?`, username)\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while deleting user '%s' from DB\", username)\n\t\treturn err\n\t}\n\tcclog.Infof(\"deleted user '%s' from DB\", username)\n\treturn nil\n}\n\nfunc (r *UserRepository) ListUsers(specialsOnly bool) ([]*schema.User, error) {\n\tq := sq.Select(\"username\", \"name\", \"email\", \"roles\", \"projects\").From(\"hpc_user\")\n\tif specialsOnly {\n\t\tq = q.Where(\"(roles != '[\\\"user\\\"]' AND roles != '[]')\")\n\t}\n\n\trows, err := q.RunWith(r.DB).Query()\n\tif err != nil {\n\t\tcclog.Warn(\"Error while querying user list\")\n\t\treturn nil, err\n\t}\n\n\tusers := make([]*schema.User, 0)\n\tdefer rows.Close()\n\tfor rows.Next() {\n\t\trawroles := \"\"\n\t\trawprojects := \"\"\n\t\tuser := &schema.User{}\n\t\tvar name, email sql.NullString\n\t\tif err := rows.Scan(&user.Username, &name, &email, &rawroles, &rawprojects); err != nil {\n\t\t\tcclog.Warn(\"Error while scanning user list\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif err := json.Unmarshal([]byte(rawroles), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw role list\")\n\t\t\treturn nil, err\n\t\t}\n\n\t\tif err := json.Unmarshal([]byte(rawprojects), &user.Projects); err != nil {\n\t\t\treturn nil, err\n\t\t}\n\n\t\tuser.Name = name.String\n\t\tuser.Email = email.String\n\t\tusers = append(users, user)\n\t}\n\treturn users, nil\n}\n\n// AddRole adds a role to a user's role list.\n// Role string is automatically lowercased.\n// Valid roles: admin, support, manager, api, user\n//\n// Returns error if:\n//   - User doesn't exist\n//   - Role is invalid\n//   - User already has the role\nfunc (r *UserRepository) AddRole(\n\tctx context.Context,\n\tusername string,\n\tqueryrole string,\n) error {\n\tnewRole := strings.ToLower(queryrole)\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\tcclog.Warnf(\"Could not load user '%s'\", username)\n\t\treturn err\n\t}\n\n\texists, valid := user.HasValidRole(newRole)\n\n\tif !valid {\n\t\treturn fmt.Errorf(\"supplied role is no valid option : %v\", newRole)\n\t}\n\tif exists {\n\t\treturn fmt.Errorf(\"user %v already has role %v\", username, newRole)\n\t}\n\n\troles, _ := json.Marshal(append(user.Roles, newRole))\n\tif _, err := sq.Update(\"hpc_user\").Set(\"roles\", roles).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"error while adding new role for user '%s'\", user.Username)\n\t\treturn err\n\t}\n\treturn nil\n}\n\n// RemoveRole removes a role from a user's role list.\n//\n// Special rules:\n//   - Cannot remove \"manager\" role while user has assigned projects\n//   - Must remove all projects first before removing manager role\nfunc (r *UserRepository) RemoveRole(ctx context.Context, username string, queryrole string) error {\n\toldRole := strings.ToLower(queryrole)\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\tcclog.Warnf(\"Could not load user '%s'\", username)\n\t\treturn err\n\t}\n\n\texists, valid := user.HasValidRole(oldRole)\n\n\tif !valid {\n\t\treturn fmt.Errorf(\"supplied role is no valid option : %v\", oldRole)\n\t}\n\tif !exists {\n\t\treturn fmt.Errorf(\"role already deleted for user '%v': %v\", username, oldRole)\n\t}\n\n\tif oldRole == schema.GetRoleString(schema.RoleManager) && len(user.Projects) != 0 {\n\t\treturn fmt.Errorf(\"cannot remove role 'manager' while user %s still has assigned project(s) : %v\", username, user.Projects)\n\t}\n\n\tvar newroles []string\n\tfor _, r := range user.Roles {\n\t\tif r != oldRole {\n\t\t\tnewroles = append(newroles, r) // Append all roles not matching requested to be deleted role\n\t\t}\n\t}\n\n\tmroles, _ := json.Marshal(newroles)\n\tif _, err := sq.Update(\"hpc_user\").Set(\"roles\", mroles).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while removing role for user '%s'\", user.Username)\n\t\treturn err\n\t}\n\treturn nil\n}\n\n// AddProject assigns a project to a manager user.\n// Only users with the \"manager\" role can have assigned projects.\n//\n// Returns error if:\n//   - User doesn't have manager role\n//   - User already manages the project\nfunc (r *UserRepository) AddProject(\n\tctx context.Context,\n\tusername string,\n\tproject string,\n) error {\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif !user.HasRole(schema.RoleManager) {\n\t\treturn fmt.Errorf(\"user '%s' is not a manager\", username)\n\t}\n\n\tif user.HasProject(project) {\n\t\treturn fmt.Errorf(\"user '%s' already manages project '%s'\", username, project)\n\t}\n\n\tprojects, _ := json.Marshal(append(user.Projects, project))\n\tif _, err := sq.Update(\"hpc_user\").Set(\"projects\", projects).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\treturn err\n\t}\n\n\treturn nil\n}\n\nfunc (r *UserRepository) RemoveProject(ctx context.Context, username string, project string) error {\n\tuser, err := r.GetUser(username)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tif !user.HasRole(schema.RoleManager) {\n\t\treturn fmt.Errorf(\"user '%#v' is not a manager\", username)\n\t}\n\n\tif !user.HasProject(project) {\n\t\treturn fmt.Errorf(\"user '%#v': Cannot remove project '%#v' - Does not match\", username, project)\n\t}\n\n\tvar exists bool\n\tvar newprojects []string\n\tfor _, p := range user.Projects {\n\t\tif p != project {\n\t\t\tnewprojects = append(newprojects, p) // Append all projects not matching requested to be deleted project\n\t\t} else {\n\t\t\texists = true\n\t\t}\n\t}\n\n\tif exists {\n\t\tvar result any\n\t\tif len(newprojects) == 0 {\n\t\t\tresult = \"[]\"\n\t\t} else {\n\t\t\tresult, _ = json.Marshal(newprojects)\n\t\t}\n\t\tif _, err := sq.Update(\"hpc_user\").Set(\"projects\", result).Where(\"hpc_user.username = ?\", username).RunWith(r.DB).Exec(); err != nil {\n\t\t\treturn err\n\t\t}\n\t\treturn nil\n\t} else {\n\t\treturn fmt.Errorf(\"user %s already does not manage project %s\", username, project)\n\t}\n}\n\ntype ContextKey string\n\nconst ContextUserKey ContextKey = \"user\"\n\nfunc GetUserFromContext(ctx context.Context) *schema.User {\n\tx := ctx.Value(ContextUserKey)\n\tif x == nil {\n\t\tcclog.Warnf(\"no user retrieved from context\")\n\t\treturn nil\n\t}\n\t// cclog.Infof(\"user retrieved from context: %v\", x.(*schema.User))\n\treturn x.(*schema.User)\n}\n\nfunc (r *UserRepository) FetchUserInCtx(ctx context.Context, username string) (*model.User, error) {\n\tme := GetUserFromContext(ctx)\n\tif me != nil && me.Username != username &&\n\t\tme.HasNotRoles([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\treturn nil, errors.New(\"forbidden\")\n\t}\n\n\tuser := &model.User{Username: username}\n\tvar name, email sql.NullString\n\tif err := sq.Select(\"name\", \"email\").From(\"hpc_user\").Where(\"hpc_user.username = ?\", username).\n\t\tRunWith(r.DB).QueryRow().Scan(&name, &email); err != nil {\n\t\tif err == sql.ErrNoRows {\n\t\t\t/* This warning will be logged *often* for non-local users, i.e. users mentioned only in job-table or archive, */\n\t\t\t/* since FetchUser will be called to retrieve full name and mail for every job in query/list\t\t\t\t\t\t\t\t\t */\n\t\t\t// cclog.Warnf(\"User '%s' Not found in DB\", username)\n\t\t\treturn nil, nil\n\t\t}\n\n\t\tcclog.Warnf(\"Error while fetching user '%s'\", username)\n\t\treturn nil, err\n\t}\n\n\tuser.Name = name.String\n\tuser.Email = email.String\n\treturn user, nil\n}\n","structuredPatch":[{"oldStart":75,"oldLines":7,"newStart":75,"newLines":11,"lines":["   if err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").","     Where(\"hpc_user.username = ?\", username).RunWith(r.DB).","     QueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {","-    cclog.Warnf(\"Error while querying user '%v' from database\", username)","+    if err != sql.ErrNoRows {","+      _, file, line, _ := runtime.Caller(1)","+      cclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",","+        username, filepath.Base(file), line, err)","+    }","     return nil, err","   }"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"54afad83-3b10-4b24-9972-609b4915b1c9","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"e71965a0-7ca9-40d4-99a2-34c038300bdc","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01J5ADM42LKZHSrQLqtWaND7","type":"message","role":"assistant","content":[{"type":"text","text":"Hmm, the diagnostics say the imports are unused. Let me check the actual file state."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":453,"cache_read_input_tokens":20084,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":453},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ7HQGHaxTnztmAzcZgCW","type":"assistant","uuid":"5761812a-ce96-48cf-80c3-b4493d2effc8","timestamp":"2026-03-16T19:07:22.069Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"5761812a-ce96-48cf-80c3-b4493d2effc8","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01J5ADM42LKZHSrQLqtWaND7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VZnP6qPheN8BEayBiYrGvr","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/user.go","limit":100},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":453,"cache_read_input_tokens":20084,"output_tokens":169,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":453,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ7HQGHaxTnztmAzcZgCW","type":"assistant","uuid":"6f77b87a-0646-41e0-a3b8-bb04430358b4","timestamp":"2026-03-16T19:07:22.275Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"6f77b87a-0646-41e0-a3b8-bb04430358b4","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01VZnP6qPheN8BEayBiYrGvr","toolUseID":"toolu_01VZnP6qPheN8BEayBiYrGvr","timestamp":"2026-03-16T19:07:22.295Z","uuid":"9f21c1cb-e9c5-42c0-8269-56f6f99763a2","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"6f77b87a-0646-41e0-a3b8-bb04430358b4","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VZnP6qPheN8BEayBiYrGvr","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 repository\n     6→\n     7→import (\n     8→\t\"context\"\n     9→\t\"database/sql\"\n    10→\t\"encoding/json\"\n    11→\t\"errors\"\n    12→\t\"fmt\"\n    13→\t\"path/filepath\"\n    14→\t\"reflect\"\n    15→\t\"runtime\"\n    16→\t\"strings\"\n    17→\t\"sync\"\n    18→\n    19→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n    20→\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n    21→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    22→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    23→\tsq \"github.com/Masterminds/squirrel\"\n    24→\t\"github.com/jmoiron/sqlx\"\n    25→\t\"golang.org/x/crypto/bcrypt\"\n    26→)\n    27→\n    28→// Authentication and Role System:\n    29→//\n    30→// ClusterCockpit supports multiple authentication sources:\n    31→//   - Local: Username/password stored in database (password hashed with bcrypt)\n    32→//   - LDAP: External LDAP/Active Directory authentication\n    33→//   - JWT: Token-based authentication for API access\n    34→//\n    35→// Role Hierarchy (from highest to lowest privilege):\n    36→//   1. \"admin\" - Full system access, can manage all users and jobs\n    37→//   2. \"support\" - Can view all jobs but limited management capabilities\n    38→//   3. \"manager\" - Can manage specific projects and their users\n    39→//   4. \"api\" - Programmatic access for job submission/management\n    40→//   5. \"user\" - Default role, can only view own jobs\n    41→//\n    42→// Project Association:\n    43→//   - Managers have a list of projects they oversee\n    44→//   - Regular users' project membership is determined by job data\n    45→//   - Managers can view/manage all jobs within their projects\n    46→\n    47→var (\n    48→\tuserRepoOnce     sync.Once\n    49→\tuserRepoInstance *UserRepository\n    50→)\n    51→\n    52→type UserRepository struct {\n    53→\tDB     *sqlx.DB\n    54→\tdriver string\n    55→}\n    56→\n    57→func GetUserRepository() *UserRepository {\n    58→\tuserRepoOnce.Do(func() {\n    59→\t\tdb := GetConnection()\n    60→\n    61→\t\tuserRepoInstance = &UserRepository{\n    62→\t\t\tDB:     db.DB,\n    63→\t\t\tdriver: db.Driver,\n    64→\t\t}\n    65→\t})\n    66→\treturn userRepoInstance\n    67→}\n    68→\n    69→// GetUser retrieves a user by username from the database.\n    70→// Returns the complete user record including hashed password, roles, and projects.\n    71→// Password field contains bcrypt hash for local auth users, empty for LDAP users.\n    72→func (r *UserRepository) GetUser(username string) (*schema.User, error) {\n    73→\tuser := &schema.User{Username: username}\n    74→\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n    75→\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n    76→\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n    77→\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n    78→\t\tif err != sql.ErrNoRows {\n    79→\t\t\t_, file, line, _ := runtime.Caller(1)\n    80→\t\t\tcclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",\n    81→\t\t\t\tusername, filepath.Base(file), line, err)\n    82→\t\t}\n    83→\t\treturn nil, err\n    84→\t}\n    85→\n    86→\tuser.Password = hashedPassword.String\n    87→\tuser.Name = name.String\n    88→\tuser.Email = email.String\n    89→\tif rawRoles.Valid {\n    90→\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n    91→\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n    92→\t\t\treturn nil, err\n    93→\t\t}\n    94→\t}\n    95→\tif rawProjects.Valid {\n    96→\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {\n    97→\t\t\treturn nil, err\n    98→\t\t}\n    99→\t}\n   100→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"49337e48-3747-4685-8e1b-486246169888","timestamp":"2026-03-16T19:07:22.295Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/user.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.\npackage repository\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"path/filepath\"\n\t\"reflect\"\n\t\"runtime\"\n\t\"strings\"\n\t\"sync\"\n\n\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n\t\"github.com/ClusterCockpit/cc-backend/internal/graph/model\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n\t\"golang.org/x/crypto/bcrypt\"\n)\n\n// Authentication and Role System:\n//\n// ClusterCockpit supports multiple authentication sources:\n//   - Local: Username/password stored in database (password hashed with bcrypt)\n//   - LDAP: External LDAP/Active Directory authentication\n//   - JWT: Token-based authentication for API access\n//\n// Role Hierarchy (from highest to lowest privilege):\n//   1. \"admin\" - Full system access, can manage all users and jobs\n//   2. \"support\" - Can view all jobs but limited management capabilities\n//   3. \"manager\" - Can manage specific projects and their users\n//   4. \"api\" - Programmatic access for job submission/management\n//   5. \"user\" - Default role, can only view own jobs\n//\n// Project Association:\n//   - Managers have a list of projects they oversee\n//   - Regular users' project membership is determined by job data\n//   - Managers can view/manage all jobs within their projects\n\nvar (\n\tuserRepoOnce     sync.Once\n\tuserRepoInstance *UserRepository\n)\n\ntype UserRepository struct {\n\tDB     *sqlx.DB\n\tdriver string\n}\n\nfunc GetUserRepository() *UserRepository {\n\tuserRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tuserRepoInstance = &UserRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\t\t}\n\t})\n\treturn userRepoInstance\n}\n\n// GetUser retrieves a user by username from the database.\n// Returns the complete user record including hashed password, roles, and projects.\n// Password field contains bcrypt hash for local auth users, empty for LDAP users.\nfunc (r *UserRepository) GetUser(username string) (*schema.User, error) {\n\tuser := &schema.User{Username: username}\n\tvar hashedPassword, name, rawRoles, email, rawProjects sql.NullString\n\tif err := sq.Select(\"password\", \"ldap\", \"name\", \"roles\", \"email\", \"projects\").From(\"hpc_user\").\n\t\tWhere(\"hpc_user.username = ?\", username).RunWith(r.DB).\n\t\tQueryRow().Scan(&hashedPassword, &user.AuthSource, &name, &rawRoles, &email, &rawProjects); err != nil {\n\t\tif err != sql.ErrNoRows {\n\t\t\t_, file, line, _ := runtime.Caller(1)\n\t\t\tcclog.Warnf(\"Error while querying user '%v' from database (%s:%d): %v\",\n\t\t\t\tusername, filepath.Base(file), line, err)\n\t\t}\n\t\treturn nil, err\n\t}\n\n\tuser.Password = hashedPassword.String\n\tuser.Name = name.String\n\tuser.Email = email.String\n\tif rawRoles.Valid {\n\t\tif err := json.Unmarshal([]byte(rawRoles.String), &user.Roles); err != nil {\n\t\t\tcclog.Warn(\"Error while unmarshaling raw roles from DB\")\n\t\t\treturn nil, err\n\t\t}\n\t}\n\tif rawProjects.Valid {\n\t\tif err := json.Unmarshal([]byte(rawProjects.String), &user.Projects); err != nil {\n\t\t\treturn nil, err\n\t\t}\n\t}\n","numLines":100,"startLine":1,"totalLines":524}},"sourceToolAssistantUUID":"6f77b87a-0646-41e0-a3b8-bb04430358b4","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"49337e48-3747-4685-8e1b-486246169888","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_017d9mbWaQyJLKPTkRhqxoxU","type":"message","role":"assistant","content":[{"type":"text","text":"The file looks correct. The LSP diagnostics are likely stale — the code on lines 79-81 clearly uses both `runtime` and `filepath`. Let me verify with a build."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1610,"cache_read_input_tokens":20537,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1610},"output_tokens":6,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ7HQaEazf51bRkuWzeTL","type":"assistant","uuid":"81794742-22e1-43ce-9a2f-3ca38bb192e2","timestamp":"2026-03-16T19:07:24.790Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"81794742-22e1-43ce-9a2f-3ca38bb192e2","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_017d9mbWaQyJLKPTkRhqxoxU","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XoiTjLsrpNBALhLpGs4nLA","name":"Bash","input":{"command":"go build ./... 2>&1","description":"Build to verify compilation"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1610,"cache_read_input_tokens":20537,"output_tokens":136,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1610,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ7HQaEazf51bRkuWzeTL","type":"assistant","uuid":"ab5f8633-c48a-453b-8918-a067c2a9ea1a","timestamp":"2026-03-16T19:07:25.469Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"ab5f8633-c48a-453b-8918-a067c2a9ea1a","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XoiTjLsrpNBALhLpGs4nLA","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"uuid":"c04ff3d0-ff62-4b15-8a7e-e41da6240cba","timestamp":"2026-03-16T19:07:31.072Z","toolUseResult":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"ab5f8633-c48a-453b-8918-a067c2a9ea1a","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"c04ff3d0-ff62-4b15-8a7e-e41da6240cba","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_015yhQrgAgNFNMozD6N2kyah","type":"message","role":"assistant","content":[{"type":"text","text":"Clean build. Let me run the repository tests."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":139,"cache_read_input_tokens":22147,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":139},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ7HRDkowkk8WyTmWjo7k","type":"assistant","uuid":"5ff00ef8-7cf8-4570-8547-0e93ceb83fe2","timestamp":"2026-03-16T19:07:34.051Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"1b3c2e2f-4994-4442-a7ad-9d2fcea8cf34","isSidechain":false,"promptId":"04ac757c-e21e-4aa4-9121-fb278bd10e02","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LFfyTpBz6k3Sp983yiE2W2","type":"tool_result","content":"ok  \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.951s","is_error":false}]},"uuid":"bf959b3e-0775-4033-be08-4e90cb729fec","timestamp":"2026-03-16T19:07:36.469Z","toolUseResult":{"stdout":"ok  \tgithub.com/ClusterCockpit/cc-backend/internal/repository\t0.951s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"1b3c2e2f-4994-4442-a7ad-9d2fcea8cf34","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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diff --git a/20/746187d135/0/metadata.json b/20/746187d135/0/metadata.json
new file mode 100644
index 00000000..b9129e53
--- /dev/null
+++ b/20/746187d135/0/metadata.json
@@ -0,0 +1,30 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "20746187d135",
+  "session_id": "cee37f8b-4e17-4b3b-b57e-6ed3ccc8fba7",
+  "strategy": "manual-commit",
+  "created_at": "2026-03-16T19:09:46.19279Z",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "internal/repository/user.go"
+  ],
+  "agent": "Claude Code",
+  "turn_id": "8655b74a6705",
+  "token_usage": {
+    "input_tokens": 9,
+    "cache_creation_tokens": 13749,
+    "cache_read_tokens": 131587,
+    "output_tokens": 1095,
+    "api_call_count": 7
+  },
+  "initial_attribution": {
+    "calculated_at": "2026-03-16T19:09:46.15026Z",
+    "agent_lines": 0,
+    "human_added": 1,
+    "human_modified": 7,
+    "human_removed": 0,
+    "total_committed": 8,
+    "agent_percentage": 0
+  }
+}
diff --git a/20/746187d135/0/prompt.txt b/20/746187d135/0/prompt.txt
new file mode 100644
index 00000000..dbe99a18
--- /dev/null
+++ b/20/746187d135/0/prompt.txt
@@ -0,0 +1,41 @@
+Implement the following plan:
+
+# Plan: Improve GetUser logging
+
+## Context
+
+`GetUser` in `internal/repository/user.go` (line 75) logs a `Warn` for every query error, including the common `sql.ErrNoRows` case (user not found). Two problems:
+
+1. `sql.ErrNoRows` is a normal, expected condition — many callers check for it explicitly. It should not produce a warning.
+2. The log message **omits the actual error**: `"Error while querying user '%v' from database"` gives no clue what went wrong for real failures.
+
+This is the same pattern just fixed in `scanJob` (job.go). The established approach: suppress `sql.ErrNoRows`, add `runtime.Caller(1)` context and include `err` in real-error logs.
+
+## Approach
+
+Modify the `Scan` error block in `GetUser` (`internal/repository/user.go`, lines 75-79):
+
+```go
+if err := sq.Select(...).QueryRow().Scan(...); err != nil {
+    if err != sql.ErrNoRows {
+        _, file, line, _ := runtime.Caller(1)
+        cclog.Warnf("Error while querying user '%v' from database (%s:%d): %v",
+            username, filepath.Base(file), line, err)
+    }
+    return nil, err
+}
+```
+
+Add `"path/filepath"` and `"runtime"` to imports (not currently present in user.go).
+
+## Critical File
+
+- `internal/repository/user.go` — only file to change (lines ~7-24 for imports, ~75-79 for error block)
+
+## Verification
+
+1. `go build ./...` — must compile cleanly
+2. `go test ./internal/repository/...` — existing tests must pass
+
+
+If you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd.jsonl
\ No newline at end of file
diff --git a/20/746187d135/metadata.json b/20/746187d135/metadata.json
new file mode 100644
index 00000000..2d93abb4
--- /dev/null
+++ b/20/746187d135/metadata.json
@@ -0,0 +1,26 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "20746187d135",
+  "strategy": "manual-commit",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "internal/repository/user.go"
+  ],
+  "sessions": [
+    {
+      "metadata": "/20/746187d135/0/metadata.json",
+      "transcript": "/20/746187d135/0/full.jsonl",
+      "context": "/20/746187d135/0/context.md",
+      "content_hash": "/20/746187d135/0/content_hash.txt",
+      "prompt": "/20/746187d135/0/prompt.txt"
+    }
+  ],
+  "token_usage": {
+    "input_tokens": 9,
+    "cache_creation_tokens": 13749,
+    "cache_read_tokens": 131587,
+    "output_tokens": 1095,
+    "api_call_count": 7
+  }
+}
diff --git a/4a/675b8352a2/0/content_hash.txt b/4a/675b8352a2/0/content_hash.txt
new file mode 100644
index 00000000..d8b23e5a
--- /dev/null
+++ b/4a/675b8352a2/0/content_hash.txt
@@ -0,0 +1 @@
+sha256:845109d4cb30fba60756c58e6a29176c1ba31c59551025ef12f38bcebe20c68a
\ No newline at end of file
diff --git a/4a/675b8352a2/0/context.md b/4a/675b8352a2/0/context.md
new file mode 100644
index 00000000..c21922a0
--- /dev/null
+++ b/4a/675b8352a2/0/context.md
@@ -0,0 +1,26 @@
+# Session Context
+
+## User Prompts
+
+### Prompt 1
+
+Implement the following plan:
+
+# Fix: Memory Escalation in flattenCheckpointFile (68GB+)
+
+## Context
+
+Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.
+
+## Root Cause
+
+Two-layer unbounde...
+
+### Prompt 2
+
+Are the any other cases with memory spikes using the Parquet Writer, e.g. in the nodestate retention?
+
+### Prompt 3
+
+[Request interrupted by user for tool use]
+
diff --git a/4a/675b8352a2/0/full.jsonl b/4a/675b8352a2/0/full.jsonl
new file mode 100644
index 00000000..51952af4
--- /dev/null
+++ b/4a/675b8352a2/0/full.jsonl
@@ -0,0 +1,124 @@
+{"type":"file-history-snapshot","messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","snapshot":{"messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","trackedFileBackups":{},"timestamp":"2026-03-17T18:14:06.692Z"},"isSnapshotUpdate":false}
+{"parentUuid":null,"isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"d78d8e9c-5382-4185-9219-683f79dd3065","toolUseID":"d78d8e9c-5382-4185-9219-683f79dd3065","timestamp":"2026-03-17T18:14:06.646Z","uuid":"1ccea021-492e-4f7f-8ce8-eb5cd2377954","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"1ccea021-492e-4f7f-8ce8-eb5cd2377954","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n\n\nIf you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/71340843-de3d-4e83-9dcb-2fc130c50e0d.jsonl"},"uuid":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","timestamp":"2026-03-17T18:14:06.473Z","planContent":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"8c2533e3-d964-4a82-9cba-cec560086bc5","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AyF6Jg771Hu8xTwZKEMzV6","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01TTkqqEZu8i9v4aSq57ZyF8","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":12307,"cache_read_input_tokens":6489,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":12307},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ979w6ddKngVT3C7ef14","type":"assistant","uuid":"4704a1bc-5253-41ee-b057-59f5c34430a8","timestamp":"2026-03-17T18:14:10.766Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"4704a1bc-5253-41ee-b057-59f5c34430a8","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01JW7rVTjQ4z7YAw3jsNrSDY","toolUseID":"toolu_01JW7rVTjQ4z7YAw3jsNrSDY","timestamp":"2026-03-17T18:14:10.794Z","uuid":"556b02fa-39c3-4e63-b1ea-f8b1feb78977","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"8c2533e3-d964-4a82-9cba-cec560086bc5","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JW7rVTjQ4z7YAw3jsNrSDY","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→\n    16→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n    35→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    36→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    37→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n    38→\tfor metricName, cm := range cf.Metrics {\n    39→\t\tts := cm.Start\n    40→\t\tfor _, v := range cm.Data {\n    41→\t\t\tif !v.IsNaN() {\n    42→\t\t\t\trows = append(rows, ParquetMetricRow{\n    43→\t\t\t\t\tCluster:   cluster,\n    44→\t\t\t\t\tHostname:  hostname,\n    45→\t\t\t\t\tMetric:    metricName,\n    46→\t\t\t\t\tScope:     scope,\n    47→\t\t\t\t\tScopeID:   scopeID,\n    48→\t\t\t\t\tTimestamp: ts,\n    49→\t\t\t\t\tFrequency: cm.Frequency,\n    50→\t\t\t\t\tValue:     float32(v),\n    51→\t\t\t\t})\n    52→\t\t\t}\n    53→\t\t\tts += cm.Frequency\n    54→\t\t}\n    55→\t}\n    56→\n    57→\tfor childName, childCf := range cf.Children {\n    58→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    59→\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n    60→\t}\n    61→\n    62→\treturn rows\n    63→}\n    64→\n    65→// parseScopeFromName infers scope and scope_id from a child level name.\n    66→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    67→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    68→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    69→func parseScopeFromName(name string) (string, string) {\n    70→\tprefixes := []struct {\n    71→\t\tprefix string\n    72→\t\tscope  string\n    73→\t}{\n    74→\t\t{\"socket\", \"socket\"},\n    75→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    76→\t\t{\"core\", \"core\"},\n    77→\t\t{\"hwthread\", \"hwthread\"},\n    78→\t\t{\"cpu\", \"hwthread\"},\n    79→\t\t{\"accelerator\", \"accelerator\"},\n    80→\t}\n    81→\n    82→\tfor _, p := range prefixes {\n    83→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    84→\t\t\tid := name[len(p.prefix):]\n    85→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    86→\t\t\t\treturn p.scope, id\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\n    91→\treturn name, \"\"\n    92→}\n    93→\n    94→// writeParquetArchive writes rows to a Parquet file with Zstd compression.\n    95→func writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n    96→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n    97→\t\treturn fmt.Errorf(\"creating archive directory: %w\", err)\n    98→\t}\n    99→\n   100→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   101→\tif err != nil {\n   102→\t\treturn fmt.Errorf(\"creating parquet file: %w\", err)\n   103→\t}\n   104→\tdefer f.Close()\n   105→\n   106→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   107→\n   108→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   109→\t\tpq.Compression(&pq.Zstd),\n   110→\t\tpq.SortingWriterConfig(pq.SortingColumns(\n   111→\t\t\tpq.Ascending(\"cluster\"),\n   112→\t\t\tpq.Ascending(\"hostname\"),\n   113→\t\t\tpq.Ascending(\"metric\"),\n   114→\t\t\tpq.Ascending(\"timestamp\"),\n   115→\t\t)),\n   116→\t)\n   117→\n   118→\tif _, err := writer.Write(rows); err != nil {\n   119→\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n   120→\t}\n   121→\n   122→\tif err := writer.Close(); err != nil {\n   123→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n   124→\t}\n   125→\n   126→\tif err := bw.Flush(); err != nil {\n   127→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n   128→\t}\n   129→\n   130→\treturn nil\n   131→}\n   132→\n   133→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   134→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   135→// before converting it to Parquet format.\n   136→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   137→\tf, err := os.Open(filename)\n   138→\tif err != nil {\n   139→\t\treturn nil, err\n   140→\t}\n   141→\tdefer f.Close()\n   142→\n   143→\text := filepath.Ext(filename)\n   144→\tswitch ext {\n   145→\tcase \".json\":\n   146→\t\tcf := &CheckpointFile{}\n   147→\t\tbr := bufio.NewReader(f)\n   148→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   149→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   150→\t\t}\n   151→\t\treturn cf, nil\n   152→\n   153→\tcase \".bin\":\n   154→\t\tbr := bufio.NewReader(f)\n   155→\t\tvar magic uint32\n   156→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   157→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   158→\t\t}\n   159→\t\tif magic != snapFileMagic {\n   160→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   161→\t\t}\n   162→\t\tvar fileFrom, fileTo int64\n   163→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   164→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   165→\t\t}\n   166→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   167→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   168→\t\t}\n   169→\t\tcf, err := readBinaryLevel(br)\n   170→\t\tif err != nil {\n   171→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   172→\t\t}\n   173→\t\tcf.From = fileFrom\n   174→\t\tcf.To = fileTo\n   175→\t\treturn cf, nil\n   176→\n   177→\tdefault:\n   178→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   179→\t}\n   180→}\n   181→\n   182→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   183→// converts them to Parquet rows. Returns the rows and filenames that were processed.\n   184→func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {\n   185→\tentries, err := os.ReadDir(dir)\n   186→\tif err != nil {\n   187→\t\treturn nil, nil, err\n   188→\t}\n   189→\n   190→\tfiles, err := findFiles(entries, from, false)\n   191→\tif err != nil {\n   192→\t\treturn nil, nil, err\n   193→\t}\n   194→\n   195→\tif len(files) == 0 {\n   196→\t\treturn nil, nil, nil\n   197→\t}\n   198→\n   199→\tvar rows []ParquetMetricRow\n   200→\n   201→\tfor _, checkpoint := range files {\n   202→\t\tfilename := filepath.Join(dir, checkpoint)\n   203→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   204→\t\tif err != nil {\n   205→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   206→\t\t\tcontinue\n   207→\t\t}\n   208→\n   209→\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n   210→\t}\n   211→\n   212→\treturn rows, files, nil\n   213→}\n   214→"}]},"uuid":"7b2d9ff8-b786-4c43-aceb-98f92f903d5c","timestamp":"2026-03-17T18:14:10.793Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/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\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","numLines":214,"startLine":1,"totalLines":214}},"sourceToolAssistantUUID":"8c2533e3-d964-4a82-9cba-cec560086bc5","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"4704a1bc-5253-41ee-b057-59f5c34430a8","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TTkqqEZu8i9v4aSq57ZyF8","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\t// Run as Archiver\n    26→\t\tcleanUpWorker(wg, ctx,\n    27→\t\t\tKeys.RetentionInMemory,\n    28→\t\t\t\"archiving\",\n    29→\t\t\tKeys.Cleanup.RootDir,\n    30→\t\t\tfalse,\n    31→\t\t)\n    32→\t} else {\n    33→\t\t// Run as Deleter\n    34→\t\tcleanUpWorker(wg, ctx,\n    35→\t\t\tKeys.RetentionInMemory,\n    36→\t\t\t\"deleting\",\n    37→\t\t\t\"\",\n    38→\t\t\ttrue,\n    39→\t\t)\n    40→\t}\n    41→}\n    42→\n    43→// cleanUpWorker takes simple values to configure what it does\n    44→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n    45→\twg.Go(func() {\n    46→\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→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n   172→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n   173→\tif err != nil {\n   174→\t\treturn 0, err\n   175→\t}\n   176→\n   177→\ttotalFiles := 0\n   178→\n   179→\tfor _, clusterEntry := range clusterEntries {\n   180→\t\tif !clusterEntry.IsDir() {\n   181→\t\t\tcontinue\n   182→\t\t}\n   183→\n   184→\t\tcluster := clusterEntry.Name()\n   185→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n   186→\t\tif err != nil {\n   187→\t\t\treturn totalFiles, err\n   188→\t\t}\n   189→\n   190→\t\t// Collect rows from all hosts in this cluster using worker pool\n   191→\t\ttype hostResult struct {\n   192→\t\t\trows  []ParquetMetricRow\n   193→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n   194→\t\t\tdir   string   // checkpoint directory for this host\n   195→\t\t}\n   196→\n   197→\t\tresults := make(chan hostResult, len(hostEntries))\n   198→\t\twork := make(chan struct {\n   199→\t\t\tdir, host string\n   200→\t\t}, Keys.NumWorkers)\n   201→\n   202→\t\tvar wg sync.WaitGroup\n   203→\t\terrs := int32(0)\n   204→\n   205→\t\twg.Add(Keys.NumWorkers)\n   206→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n   207→\t\t\tgo func() {\n   208→\t\t\t\tdefer wg.Done()\n   209→\t\t\t\tfor item := range work {\n   210→\t\t\t\t\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, from)\n   211→\t\t\t\t\tif err != nil {\n   212→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n   213→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n   214→\t\t\t\t\t\tcontinue\n   215→\t\t\t\t\t}\n   216→\t\t\t\t\tif len(rows) > 0 {\n   217→\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\n   218→\t\t\t\t\t}\n   219→\t\t\t\t}\n   220→\t\t\t}()\n   221→\t\t}\n   222→\n   223→\t\tgo func() {\n   224→\t\t\tfor _, hostEntry := range hostEntries {\n   225→\t\t\t\tif !hostEntry.IsDir() {\n   226→\t\t\t\t\tcontinue\n   227→\t\t\t\t}\n   228→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n   229→\t\t\t\twork <- struct {\n   230→\t\t\t\t\tdir, host string\n   231→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n   232→\t\t\t}\n   233→\t\t\tclose(work)\n   234→\t\t\twg.Wait()\n   235→\t\t\tclose(results)\n   236→\t\t}()\n   237→\n   238→\t\t// Collect all rows and file info\n   239→\t\tvar allRows []ParquetMetricRow\n   240→\t\tvar allResults []hostResult\n   241→\t\tfor r := range results {\n   242→\t\t\tallRows = append(allRows, r.rows...)\n   243→\t\t\tallResults = append(allResults, r)\n   244→\t\t}\n   245→\n   246→\t\tif errs > 0 {\n   247→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n   248→\t\t}\n   249→\n   250→\t\tif len(allRows) == 0 {\n   251→\t\t\tcontinue\n   252→\t\t}\n   253→\n   254→\t\t// Write one Parquet file per cluster\n   255→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n   256→\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n   257→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n   258→\t\t}\n   259→\n   260→\t\t// Delete archived checkpoint files\n   261→\t\tfor _, result := range allResults {\n   262→\t\t\tfor _, file := range result.files {\n   263→\t\t\t\tfilename := filepath.Join(result.dir, file)\n   264→\t\t\t\tif err := os.Remove(filename); err != nil {\n   265→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n   266→\t\t\t\t} else {\n   267→\t\t\t\t\ttotalFiles++\n   268→\t\t\t\t}\n   269→\t\t\t}\n   270→\t\t}\n   271→\n   272→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n   273→\t\t\tlen(allRows), totalFiles, cluster, parquetFile)\n   274→\t}\n   275→\n   276→\treturn totalFiles, nil\n   277→}\n   278→"}]},"uuid":"5c641ce2-75b5-4d5f-8b5c-fd0a8d05eefe","timestamp":"2026-03-17T18:14:10.792Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/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\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\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\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}\n","numLines":278,"startLine":1,"totalLines":278}},"sourceToolAssistantUUID":"4704a1bc-5253-41ee-b057-59f5c34430a8","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"530dbdcc-8f1e-4870-a1c5-88215ce6a729","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AdHt5nZpLoZxxyDJ4BAorq","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\"encoding/json\"\n    10→\t\"os\"\n    11→\t\"path/filepath\"\n    12→\t\"testing\"\n    13→\n    14→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    15→\tpq \"github.com/parquet-go/parquet-go\"\n    16→)\n    17→\n    18→func TestParseScopeFromName(t *testing.T) {\n    19→\ttests := []struct {\n    20→\t\tname      string\n    21→\t\twantScope string\n    22→\t\twantID    string\n    23→\t}{\n    24→\t\t{\"socket0\", \"socket\", \"0\"},\n    25→\t\t{\"socket12\", \"socket\", \"12\"},\n    26→\t\t{\"core0\", \"core\", \"0\"},\n    27→\t\t{\"core127\", \"core\", \"127\"},\n    28→\t\t{\"cpu0\", \"hwthread\", \"0\"},\n    29→\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n    30→\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n    31→\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n    32→\t\t{\"unknown\", \"unknown\", \"\"},\n    33→\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n    34→\t}\n    35→\n    36→\tfor _, tt := range tests {\n    37→\t\tt.Run(tt.name, func(t *testing.T) {\n    38→\t\t\tscope, id := parseScopeFromName(tt.name)\n    39→\t\t\tif scope != tt.wantScope || id != tt.wantID {\n    40→\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n    41→\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n    42→\t\t\t}\n    43→\t\t})\n    44→\t}\n    45→}\n    46→\n    47→func TestFlattenCheckpointFile(t *testing.T) {\n    48→\tcf := &CheckpointFile{\n    49→\t\tFrom: 1000,\n    50→\t\tTo:   1060,\n    51→\t\tMetrics: map[string]*CheckpointMetrics{\n    52→\t\t\t\"cpu_load\": {\n    53→\t\t\t\tFrequency: 60,\n    54→\t\t\t\tStart:     1000,\n    55→\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n    56→\t\t\t},\n    57→\t\t},\n    58→\t\tChildren: map[string]*CheckpointFile{\n    59→\t\t\t\"socket0\": {\n    60→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n    61→\t\t\t\t\t\"mem_bw\": {\n    62→\t\t\t\t\t\tFrequency: 60,\n    63→\t\t\t\t\t\tStart:     1000,\n    64→\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n    65→\t\t\t\t\t},\n    66→\t\t\t\t},\n    67→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n    68→\t\t\t},\n    69→\t\t},\n    70→\t}\n    71→\n    72→\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n    73→\n    74→\t// cpu_load: 2 non-NaN values at node scope\n    75→\t// mem_bw: 2 non-NaN values at socket0 scope\n    76→\tif len(rows) != 4 {\n    77→\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n    78→\t}\n    79→\n    80→\t// Verify a node-scope row\n    81→\tfound := false\n    82→\tfor _, r := range rows {\n    83→\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n    84→\t\t\tfound = true\n    85→\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n    86→\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\tif !found {\n    91→\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n    92→\t}\n    93→\n    94→\t// Verify a socket-scope row\n    95→\tfound = false\n    96→\tfor _, r := range rows {\n    97→\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n    98→\t\t\tfound = true\n    99→\t\t}\n   100→\t}\n   101→\tif !found {\n   102→\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n   103→\t}\n   104→}\n   105→\n   106→func TestParquetArchiveRoundtrip(t *testing.T) {\n   107→\ttmpDir := t.TempDir()\n   108→\n   109→\t// Create checkpoint files on disk (JSON format)\n   110→\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n   111→\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n   112→\t\tt.Fatal(err)\n   113→\t}\n   114→\n   115→\tcf := &CheckpointFile{\n   116→\t\tFrom: 1000,\n   117→\t\tTo:   1180,\n   118→\t\tMetrics: map[string]*CheckpointMetrics{\n   119→\t\t\t\"cpu_load\": {\n   120→\t\t\t\tFrequency: 60,\n   121→\t\t\t\tStart:     1000,\n   122→\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n   123→\t\t\t},\n   124→\t\t\t\"mem_used\": {\n   125→\t\t\t\tFrequency: 60,\n   126→\t\t\t\tStart:     1000,\n   127→\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n   128→\t\t\t},\n   129→\t\t},\n   130→\t\tChildren: map[string]*CheckpointFile{\n   131→\t\t\t\"socket0\": {\n   132→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n   133→\t\t\t\t\t\"mem_bw\": {\n   134→\t\t\t\t\t\tFrequency: 60,\n   135→\t\t\t\t\t\tStart:     1000,\n   136→\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n   137→\t\t\t\t\t},\n   138→\t\t\t\t},\n   139→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n   140→\t\t\t},\n   141→\t\t},\n   142→\t}\n   143→\n   144→\t// Write JSON checkpoint\n   145→\tcpFile := filepath.Join(cpDir, \"1000.json\")\n   146→\tdata, err := json.Marshal(cf)\n   147→\tif err != nil {\n   148→\t\tt.Fatal(err)\n   149→\t}\n   150→\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n   151→\t\tt.Fatal(err)\n   152→\t}\n   153→\n   154→\t// Archive to Parquet\n   155→\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n   156→\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n   157→\tif err != nil {\n   158→\t\tt.Fatal(err)\n   159→\t}\n   160→\tif len(files) != 1 || files[0] != \"1000.json\" {\n   161→\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n   162→\t}\n   163→\n   164→\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n   165→\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n   166→\t\tt.Fatal(err)\n   167→\t}\n   168→\n   169→\t// Read back and verify\n   170→\tf, err := os.Open(parquetFile)\n   171→\tif err != nil {\n   172→\t\tt.Fatal(err)\n   173→\t}\n   174→\tdefer f.Close()\n   175→\n   176→\tstat, _ := f.Stat()\n   177→\tpf, err := pq.OpenFile(f, stat.Size())\n   178→\tif err != nil {\n   179→\t\tt.Fatal(err)\n   180→\t}\n   181→\n   182→\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n   183→\treadRows := make([]ParquetMetricRow, 100)\n   184→\tn, err := reader.Read(readRows)\n   185→\tif err != nil && n == 0 {\n   186→\t\tt.Fatal(err)\n   187→\t}\n   188→\treadRows = readRows[:n]\n   189→\treader.Close()\n   190→\n   191→\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n   192→\tif n != 9 {\n   193→\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n   194→\t}\n   195→\n   196→\t// Verify cluster and hostname are set correctly\n   197→\tfor _, r := range readRows {\n   198→\t\tif r.Cluster != \"testcluster\" {\n   199→\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n   200→\t\t}\n   201→\t\tif r.Hostname != \"node001\" {\n   202→\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n   203→\t\t}\n   204→\t}\n   205→\n   206→\t// Verify parquet file is smaller than JSON (compression working)\n   207→\tif stat.Size() == 0 {\n   208→\t\tt.Error(\"parquet file is empty\")\n   209→\t}\n   210→\n   211→\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n   212→}\n   213→\n   214→func TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n   215→\ttmpDir := t.TempDir()\n   216→\n   217→\tcf := &CheckpointFile{\n   218→\t\tFrom: 1000,\n   219→\t\tTo:   1060,\n   220→\t\tMetrics: map[string]*CheckpointMetrics{\n   221→\t\t\t\"test_metric\": {\n   222→\t\t\t\tFrequency: 60,\n   223→\t\t\t\tStart:     1000,\n   224→\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n   225→\t\t\t},\n   226→\t\t},\n   227→\t\tChildren: make(map[string]*CheckpointFile),\n   228→\t}\n   229→\n   230→\tfilename := filepath.Join(tmpDir, \"1000.json\")\n   231→\tdata, err := json.Marshal(cf)\n   232→\tif err != nil {\n   233→\t\tt.Fatal(err)\n   234→\t}\n   235→\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n   236→\t\tt.Fatal(err)\n   237→\t}\n   238→\n   239→\tloaded, err := loadCheckpointFileFromDisk(filename)\n   240→\tif err != nil {\n   241→\t\tt.Fatal(err)\n   242→\t}\n   243→\n   244→\tif loaded.From != 1000 || loaded.To != 1060 {\n   245→\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n   246→\t}\n   247→\n   248→\tm, ok := loaded.Metrics[\"test_metric\"]\n   249→\tif !ok {\n   250→\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n   251→\t}\n   252→\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n   253→\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n   254→\t}\n   255→}\n   256→"}]},"uuid":"4a0aef1c-e87c-4f66-9d2e-f9bec302737c","timestamp":"2026-03-17T18:14:11.268Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive_test.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\"encoding/json\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\nfunc TestParseScopeFromName(t *testing.T) {\n\ttests := []struct {\n\t\tname      string\n\t\twantScope string\n\t\twantID    string\n\t}{\n\t\t{\"socket0\", \"socket\", \"0\"},\n\t\t{\"socket12\", \"socket\", \"12\"},\n\t\t{\"core0\", \"core\", \"0\"},\n\t\t{\"core127\", \"core\", \"127\"},\n\t\t{\"cpu0\", \"hwthread\", \"0\"},\n\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n\t\t{\"unknown\", \"unknown\", \"\"},\n\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tscope, id := parseScopeFromName(tt.name)\n\t\t\tif scope != tt.wantScope || id != tt.wantID {\n\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestFlattenCheckpointFile(t *testing.T) {\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n\n\t// cpu_load: 2 non-NaN values at node scope\n\t// mem_bw: 2 non-NaN values at socket0 scope\n\tif len(rows) != 4 {\n\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n\t}\n\n\t// Verify a node-scope row\n\tfound := false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n\t\t\tfound = true\n\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n\t\t\t}\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n\t}\n\n\t// Verify a socket-scope row\n\tfound = false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n\t\t\tfound = true\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n\t}\n}\n\nfunc TestParquetArchiveRoundtrip(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\t// Create checkpoint files on disk (JSON format)\n\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1180,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n\t\t\t},\n\t\t\t\"mem_used\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\t// Write JSON checkpoint\n\tcpFile := filepath.Join(cpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Archive to Parquet\n\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif len(files) != 1 || files[0] != \"1000.json\" {\n\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n\t}\n\n\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Read back and verify\n\tf, err := os.Open(parquetFile)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tdefer f.Close()\n\n\tstat, _ := f.Stat()\n\tpf, err := pq.OpenFile(f, stat.Size())\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n\treadRows := make([]ParquetMetricRow, 100)\n\tn, err := reader.Read(readRows)\n\tif err != nil && n == 0 {\n\t\tt.Fatal(err)\n\t}\n\treadRows = readRows[:n]\n\treader.Close()\n\n\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n\tif n != 9 {\n\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n\t}\n\n\t// Verify cluster and hostname are set correctly\n\tfor _, r := range readRows {\n\t\tif r.Cluster != \"testcluster\" {\n\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n\t\t}\n\t\tif r.Hostname != \"node001\" {\n\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n\t\t}\n\t}\n\n\t// Verify parquet file is smaller than JSON (compression working)\n\tif stat.Size() == 0 {\n\t\tt.Error(\"parquet file is empty\")\n\t}\n\n\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n}\n\nfunc TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"test_metric\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n\t\t\t},\n\t\t},\n\t\tChildren: make(map[string]*CheckpointFile),\n\t}\n\n\tfilename := filepath.Join(tmpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tloaded, err := loadCheckpointFileFromDisk(filename)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tif loaded.From != 1000 || loaded.To != 1060 {\n\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n\t}\n\n\tm, ok := loaded.Metrics[\"test_metric\"]\n\tif !ok {\n\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n\t}\n\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n\t}\n}\n","numLines":256,"startLine":1,"totalLines":256}},"sourceToolAssistantUUID":"530dbdcc-8f1e-4870-a1c5-88215ce6a729","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c275b193-e533-456b-9230-e0ee1ea0fa1c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01RMdmF6xH1mm2DpsrqgJrgu","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have a clear picture. Let me implement the changes.\n\n**Step 1: Update `parquetArchive.go`** - Add streaming writer, remove old `writeParquetArchive`"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":10208,"cache_read_input_tokens":18796,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":10208},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ97AGSxvMsprpByJkyy2","type":"assistant","uuid":"98760d2a-e3cc-42e4-8777-b0c8be9375ea","timestamp":"2026-03-17T18:14:18.228Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"type":"file-history-snapshot","messageId":"66271b96-1bbf-4446-bc30-dc4fe8513046","snapshot":{"messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","trackedFileBackups":{"pkg/metricstore/parquetArchive.go":{"backupFileName":"d23fbf0a668003f6@v1","version":1,"backupTime":"2026-03-17T18:14:21.260Z"}},"timestamp":"2026-03-17T18:14:06.692Z"},"isSnapshotUpdate":true}
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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":12,"oldLines":6,"newStart":12,"newLines":7,"lines":["   \"fmt\"","   \"os\"","   \"path/filepath\"","+  \"sort\""," ","   cclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"","   pq \"github.com/parquet-go/parquet-go\""]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"66271b96-1bbf-4446-bc30-dc4fe8513046","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"8ea10542-c017-448f-9afb-91498f3807c8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01DPuC6qZGeRor7sj16J9WjX","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01LEFj1LSgwARFjJfDqJypBn","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","old_string":"// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\n}","new_string":"// parquetArchiveWriter supports incremental writes to a Parquet file.\n// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":513,"cache_read_input_tokens":29004,"output_tokens":1391,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":513,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97B37JmQrRhr5sZtBP6","type":"assistant","uuid":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","timestamp":"2026-03-17T18:14:38.960Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LEFj1LSgwARFjJfDqJypBn","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go has been updated successfully."}]},"uuid":"36701fa4-3179-4da4-89fa-9bfce3b3f37d","timestamp":"2026-03-17T18:14:38.984Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","oldString":"// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\n}","newString":"// parquetArchiveWriter supports incremental writes to a Parquet file.\n// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":92,"oldLines":45,"newStart":92,"newLines":83,"lines":["   return name, \"\""," }"," ","-// writeParquetArchive writes rows to a Parquet file with Zstd compression.","-func writeParquetArchive(filename string, rows []ParquetMetricRow) error {","+// parquetArchiveWriter supports incremental writes to a Parquet file.","+// Each call to WriteHostRows writes one row group (typically one host's data),","+// avoiding accumulation of all rows in memory.","+type parquetArchiveWriter struct {","+  writer *pq.GenericWriter[ParquetMetricRow]","+  bw     *bufio.Writer","+  f      *os.File","+  count  int","+}","+","+// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.","+func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {","   if err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {","-    return fmt.Errorf(\"creating archive directory: %w\", err)","+    return nil, fmt.Errorf(\"creating archive directory: %w\", err)","   }"," ","   f, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)","   if err != nil {","-    return fmt.Errorf(\"creating parquet file: %w\", err)","+    return nil, fmt.Errorf(\"creating parquet file: %w\", err)","   }","-  defer f.Close()"," ","   bw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer"," ","   writer := pq.NewGenericWriter[ParquetMetricRow](bw,","     pq.Compression(&pq.Zstd),","-    pq.SortingWriterConfig(pq.SortingColumns(","-      pq.Ascending(\"cluster\"),","-      pq.Ascending(\"hostname\"),","-      pq.Ascending(\"metric\"),","-      pq.Ascending(\"timestamp\"),","-    )),","   )"," ","-  if _, err := writer.Write(rows); err != nil {","+  return &parquetArchiveWriter{writer: writer, bw: bw, f: f}, nil","+}","+","+// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,","+// and flushes to create a separate row group.","+func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {","+  sort.Slice(rows, func(i, j int) bool {","+    if rows[i].Metric != rows[j].Metric {","+      return rows[i].Metric < rows[j].Metric","+    }","+    return rows[i].Timestamp < rows[j].Timestamp","+  })","+","+  if _, err := w.writer.Write(rows); err != nil {","     return fmt.Errorf(\"writing parquet rows: %w\", err)","   }"," ","-  if err := writer.Close(); err != nil {","+  if err := w.writer.Flush(); err != nil {","+    return fmt.Errorf(\"flushing parquet row group: %w\", err)","+  }","+","+  w.count += len(rows)","+  return nil","+}","+","+// Close finalises the Parquet file (footer, buffered I/O, file handle).","+func (w *parquetArchiveWriter) Close() error {","+  if err := w.writer.Close(); err != nil {","+    w.f.Close()","     return fmt.Errorf(\"closing parquet writer: %w\", err)","   }"," ","-  if err := bw.Flush(); err != nil {","+  if err := w.bw.Flush(); err != nil {","+    w.f.Close()","     return fmt.Errorf(\"flushing parquet file: %w\", err)","   }"," ","-  return nil","+  return w.f.Close()"," }"," ","+// sortParquetRows sorts rows by (metric, timestamp) in-place.","+func sortParquetRows(rows []ParquetMetricRow) {","+  sort.Slice(rows, func(i, j int) bool {","+    if rows[i].Metric != rows[j].Metric {","+      return rows[i].Metric < rows[j].Metric","+    }","+    return rows[i].Timestamp < rows[j].Timestamp","+  })","+}","+"," // loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns"," // a CheckpointFile. Used by the Parquet archiver to read checkpoint data"," // before converting it to Parquet format."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"b1545362-e02b-4a3e-a599-0260932338f4","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01VfefjavQzgZsqg8hHTVosW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01L18aviRMvE979p3KoRTiow","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","old_string":"// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}","new_string":"// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n// Used for pre-allocating the rows slice to avoid repeated append doubling.\nfunc estimateRowCount(cf *CheckpointFile) int {\n\tn := 0\n\tfor _, cm := range cf.Metrics {\n\t\tn += len(cm.Data)\n\t}\n\tfor _, child := range cf.Children {\n\t\tn += estimateRowCount(child)\n\t}\n\treturn n\n}\n\n// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n\ttype loaded struct {\n\t\tcf       *CheckpointFile\n\t\tfilename string\n\t}\n\tvar checkpoints []loaded\n\ttotalEstimate := 0\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\t\ttotalEstimate += estimateRowCount(cf)\n\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n\t}\n\n\tif len(checkpoints) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\trows := make([]ParquetMetricRow, 0, totalEstimate)\n\tprocessedFiles := make([]string, 0, len(checkpoints))\n\n\tfor _, cp := range checkpoints {\n\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n\t\tprocessedFiles = append(processedFiles, cp.filename)\n\t}\n\n\treturn rows, processedFiles, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1526,"cache_read_input_tokens":29517,"output_tokens":1038,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1526,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97CJzZck3MZdNy2tP5h","type":"assistant","uuid":"4f5d24ca-a19c-4d0c-821d-792a973286f3","timestamp":"2026-03-17T18:14:53.263Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}","newString":"// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n// Used for pre-allocating the rows slice to avoid repeated append doubling.\nfunc estimateRowCount(cf *CheckpointFile) int {\n\tn := 0\n\tfor _, cm := range cf.Metrics {\n\t\tn += len(cm.Data)\n\t}\n\tfor _, child := range cf.Children {\n\t\tn += estimateRowCount(child)\n\t}\n\treturn n\n}\n\n// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n\ttype loaded struct {\n\t\tcf       *CheckpointFile\n\t\tfilename string\n\t}\n\tvar checkpoints []loaded\n\ttotalEstimate := 0\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\t\ttotalEstimate += estimateRowCount(cf)\n\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n\t}\n\n\tif len(checkpoints) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\trows := make([]ParquetMetricRow, 0, totalEstimate)\n\tprocessedFiles := make([]string, 0, len(checkpoints))\n\n\tfor _, cp := range checkpoints {\n\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n\t\tprocessedFiles = append(processedFiles, cp.filename)\n\t}\n\n\treturn rows, processedFiles, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":218,"oldLines":6,"newStart":218,"newLines":19,"lines":["   }"," }"," ","+// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.","+// Used for pre-allocating the rows slice to avoid repeated append doubling.","+func estimateRowCount(cf *CheckpointFile) int {","+  n := 0","+  for _, cm := range cf.Metrics {","+    n += len(cm.Data)","+  }","+  for _, child := range cf.Children {","+    n += estimateRowCount(child)","+  }","+  return n","+}","+"," // archiveCheckpointsToParquet reads checkpoint files for a host directory,"," // converts them to Parquet rows. Returns the rows and filenames that were processed."," func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {"]},{"oldStart":235,"oldLines":7,"newStart":248,"newLines":13,"lines":["     return nil, nil, nil","   }"," ","-  var rows []ParquetMetricRow","+  // First pass: load checkpoints and estimate total rows for pre-allocation.","+  type loaded struct {","+    cf       *CheckpointFile","+    filename string","+  }","+  var checkpoints []loaded","+  totalEstimate := 0"," ","   for _, checkpoint := range files {","     filename := filepath.Join(dir, checkpoint)"]},{"oldStart":244,"oldLines":9,"newStart":263,"newLines":21,"lines":["       cclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)","       continue","     }","+    totalEstimate += estimateRowCount(cf)","+    checkpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})","+  }"," ","-    rows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)","+  if len(checkpoints) == 0 {","+    return nil, nil, nil","   }"," ","-  return rows, files, nil","+  rows := make([]ParquetMetricRow, 0, totalEstimate)","+  processedFiles := make([]string, 0, len(checkpoints))","+","+  for _, cp := range checkpoints {","+    rows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)","+    processedFiles = append(processedFiles, cp.filename)","+  }","+","+  return rows, processedFiles, nil"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"4f5d24ca-a19c-4d0c-821d-792a973286f3","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"2c2d7e52-c2d4-4eb8-95df-c41b6b08c910","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_012Lax8yyV7unZDoBkvqzsAQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01F2NUeSmUXJ526j3VVko9pD","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go","old_string":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}","new_string":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1193,"cache_read_input_tokens":31043,"output_tokens":2500,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1193,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97DNEoZArSeP2DNLgPJ","type":"assistant","uuid":"9d120e45-e7dc-43fe-9300-b76eeb8d8ff4","timestamp":"2026-03-17T18:15:23.085Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}","newString":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\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\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\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}\n","structuredPatch":[{"oldStart":168,"oldLines":6,"newStart":168,"newLines":8,"lines":[" "," // archiveCheckpoints archives checkpoint files to Parquet format."," // Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet","+// Each host's rows are written as a separate row group to avoid accumulating","+// all data in memory at once."," func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {","   clusterEntries, err := os.ReadDir(checkpointsDir)","   if err != nil {"]},{"oldStart":187,"oldLines":7,"newStart":189,"newLines":7,"lines":["       return totalFiles, err","     }"," ","-    // Collect rows from all hosts in this cluster using worker pool","+    // Stream per-host rows to parquet writer via worker pool","     type hostResult struct {","       rows  []ParquetMetricRow","       files []string // checkpoint filenames to delete after successful write"]},{"oldStart":235,"oldLines":32,"newStart":237,"newLines":57,"lines":["       close(results)","     }()"," ","-    // Collect all rows and file info","-    var allRows []ParquetMetricRow","-    var allResults []hostResult","+    // Open streaming writer and write each host's rows as a row group","+    parquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))","+    writer, err := newParquetArchiveWriter(parquetFile)","+    if err != nil {","+      // Drain results channel to unblock workers","+      for range results {","+      }","+      return totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)","+    }","+","+    type deleteItem struct {","+      dir   string","+      files []string","+    }","+    var toDelete []deleteItem","+    writeErr := error(nil)","+","     for r := range results {","-      allRows = append(allRows, r.rows...)","-      allResults = append(allResults, r)","+      if writeErr == nil {","+        sortParquetRows(r.rows)","+        if err := writer.WriteHostRows(r.rows); err != nil {","+          writeErr = err","+        }","+      }","+      // Always track files for deletion (even if write failed, we still drain)","+      toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})","     }"," ","+    if err := writer.Close(); err != nil && writeErr == nil {","+      writeErr = err","+    }","+","     if errs > 0 {","       return totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)","     }"," ","-    if len(allRows) == 0 {","+    if writer.count == 0 {","+      // No data written — remove empty file","+      os.Remove(parquetFile)","       continue","     }"," ","-    // Write one Parquet file per cluster","-    parquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))","-    if err := writeParquetArchive(parquetFile, allRows); err != nil {","-      return totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)","+    if writeErr != nil {","+      os.Remove(parquetFile)","+      return totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)","     }"," ","     // Delete archived checkpoint files","-    for _, result := range allResults {","-      for _, file := range result.files {","-        filename := filepath.Join(result.dir, file)","+    for _, item := range toDelete {","+      for _, file := range item.files {","+        filename := filepath.Join(item.dir, file)","         if err := os.Remove(filename); err != nil {","           cclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)","         } else {"]},{"oldStart":270,"oldLines":7,"newStart":297,"newLines":7,"lines":["     }"," ","     cclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",","-      len(allRows), totalFiles, cluster, parquetFile)","+      writer.count, totalFiles, cluster, parquetFile)","   }"," ","   return totalFiles, nil"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"9d120e45-e7dc-43fe-9300-b76eeb8d8ff4","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage metricstore\n\nimport (\n\t\"encoding/json\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\nfunc TestParseScopeFromName(t *testing.T) {\n\ttests := []struct {\n\t\tname      string\n\t\twantScope string\n\t\twantID    string\n\t}{\n\t\t{\"socket0\", \"socket\", \"0\"},\n\t\t{\"socket12\", \"socket\", \"12\"},\n\t\t{\"core0\", \"core\", \"0\"},\n\t\t{\"core127\", \"core\", \"127\"},\n\t\t{\"cpu0\", \"hwthread\", \"0\"},\n\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n\t\t{\"unknown\", \"unknown\", \"\"},\n\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tscope, id := parseScopeFromName(tt.name)\n\t\t\tif scope != tt.wantScope || id != tt.wantID {\n\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestFlattenCheckpointFile(t *testing.T) {\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n\n\t// cpu_load: 2 non-NaN values at node scope\n\t// mem_bw: 2 non-NaN values at socket0 scope\n\tif len(rows) != 4 {\n\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n\t}\n\n\t// Verify a node-scope row\n\tfound := false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n\t\t\tfound = true\n\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n\t\t\t}\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n\t}\n\n\t// Verify a socket-scope row\n\tfound = false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n\t\t\tfound = true\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n\t}\n}\n\nfunc TestParquetArchiveRoundtrip(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\t// Create checkpoint files on disk (JSON format)\n\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1180,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n\t\t\t},\n\t\t\t\"mem_used\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\t// Write JSON checkpoint\n\tcpFile := filepath.Join(cpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Archive to Parquet\n\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif len(files) != 1 || files[0] != \"1000.json\" {\n\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n\t}\n\n\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Read back and verify\n\tf, err := os.Open(parquetFile)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tdefer f.Close()\n\n\tstat, _ := f.Stat()\n\tpf, err := pq.OpenFile(f, stat.Size())\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n\treadRows := make([]ParquetMetricRow, 100)\n\tn, err := reader.Read(readRows)\n\tif err != nil && n == 0 {\n\t\tt.Fatal(err)\n\t}\n\treadRows = readRows[:n]\n\treader.Close()\n\n\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n\tif n != 9 {\n\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n\t}\n\n\t// Verify cluster and hostname are set correctly\n\tfor _, r := range readRows {\n\t\tif r.Cluster != \"testcluster\" {\n\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n\t\t}\n\t\tif r.Hostname != \"node001\" {\n\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n\t\t}\n\t}\n\n\t// Verify parquet file is smaller than JSON (compression working)\n\tif stat.Size() == 0 {\n\t\tt.Error(\"parquet file is empty\")\n\t}\n\n\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n}\n\nfunc TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"test_metric\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n\t\t\t},\n\t\t},\n\t\tChildren: make(map[string]*CheckpointFile),\n\t}\n\n\tfilename := filepath.Join(tmpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tloaded, err := loadCheckpointFileFromDisk(filename)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tif loaded.From != 1000 || loaded.To != 1060 {\n\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n\t}\n\n\tm, ok := loaded.Metrics[\"test_metric\"]\n\tif !ok {\n\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n\t}\n\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n\t}\n}\n","structuredPatch":[{"oldStart":162,"oldLines":9,"newStart":162,"newLines":17,"lines":["   }"," ","   parquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")","-  if err := writeParquetArchive(parquetFile, rows); err != nil {","+  writer, err := newParquetArchiveWriter(parquetFile)","+  if err != nil {","     t.Fatal(err)","   }","+  sortParquetRows(rows)","+  if err := writer.WriteHostRows(rows); err != nil {","+    t.Fatal(err)","+  }","+  if err := writer.Close(); err != nil {","+    t.Fatal(err)","+  }"," ","   // Read back and verify","   f, err := os.Open(parquetFile)"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"53cbcd29-7347-43e9-909c-86cbb06de2ee","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"442aef62-2c74-45f6-8858-79e6b9da2e9f","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Y1VTXV4w6gCfFBDTJRRJiU","type":"tool_result","content":"=== RUN   TestBufferPoolGetReuse\n--- PASS: TestBufferPoolGetReuse (0.00s)\n=== RUN   TestBufferPoolClear\n--- PASS: TestBufferPoolClear (0.00s)\n=== RUN   TestBufferEndFirstWrite\n--- PASS: TestBufferEndFirstWrite (0.00s)\n=== RUN   TestBufferWriteNaNFill\n--- PASS: TestBufferWriteNaNFill (0.00s)\n=== RUN   TestBufferWriteCapacityOverflow\n--- PASS: TestBufferWriteCapacityOverflow (0.00s)\n=== RUN   TestBufferWriteOverwrite\n--- PASS: TestBufferWriteOverwrite (0.00s)\n=== RUN   TestBufferReadBeforeFirstWrite\n--- PASS: TestBufferReadBeforeFirstWrite (0.00s)\n=== RUN   TestBufferReadChain\n--- PASS: TestBufferReadChain (0.00s)\n=== RUN   TestBufferReadIdxAfterSwitch\n--- PASS: TestBufferReadIdxAfterSwitch (0.00s)\n=== RUN   TestBufferReadNaNValues\n--- PASS: TestBufferReadNaNValues (0.00s)\n=== RUN   TestBufferReadAccumulation\n--- PASS: TestBufferReadAccumulation (0.00s)\n=== RUN   TestBufferFreeRetention\n--- PASS: TestBufferFreeRetention (0.00s)\n=== RUN   TestBufferFreeAll\n--- PASS: TestBufferFreeAll (0.00s)\n=== RUN   TestForceFreeOldestPoolReturn\n--- PASS: TestForceFreeOldestPoolReturn (0.00s)\n=== RUN   TestForceFreeOldestSingleBuffer\n--- PASS: TestForceFreeOldestSingleBuffer (0.00s)\n=== RUN   TestBufferIterFromToOrder\n--- PASS: TestBufferIterFromToOrder (0.00s)\n=== RUN   TestBufferIterFromToFiltered\n--- PASS: TestBufferIterFromToFiltered (0.00s)\n=== RUN   TestBufferIterFromToNilBuffer\n--- PASS: TestBufferIterFromToNilBuffer (0.00s)\n=== RUN   TestBufferCount\n--- PASS: TestBufferCount (0.00s)\n=== RUN   TestAssignAggregationStrategy\n=== RUN   TestAssignAggregationStrategy/empty_string\n=== RUN   TestAssignAggregationStrategy/sum\n=== RUN   TestAssignAggregationStrategy/avg\n=== RUN   TestAssignAggregationStrategy/invalid\n--- PASS: TestAssignAggregationStrategy (0.00s)\n    --- PASS: TestAssignAggregationStrategy/empty_string (0.00s)\n    --- PASS: TestAssignAggregationStrategy/sum (0.00s)\n    --- PASS: TestAssignAggregationStrategy/avg (0.00s)\n    --- PASS: TestAssignAggregationStrategy/invalid (0.00s)\n=== RUN   TestBufferWrite\n--- PASS: TestBufferWrite (0.00s)\n=== RUN   TestBufferRead\n--- PASS: TestBufferRead (0.00s)\n=== RUN   TestHealthCheck\n=== RUN   TestHealthCheck/all_metrics_healthy\n=== RUN   TestHealthCheck/some_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node002degraded metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/some_metrics_missing\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node003missing metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/node_not_found\n=== RUN   TestHealthCheck/all_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used cpu_user cpu_system]\n=== RUN   TestHealthCheck/multiple_nodes_mixed_states\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used]\n--- PASS: TestHealthCheck (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_healthy (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_missing (0.00s)\n    --- PASS: TestHealthCheck/node_not_found (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/multiple_nodes_mixed_states (0.00s)\n=== RUN   TestGetHealthyMetrics\n=== RUN   TestGetHealthyMetrics/mixed_health_states\n=== RUN   TestGetHealthyMetrics/node_not_found\n=== RUN   TestGetHealthyMetrics/check_only_healthy_metric\n--- PASS: TestGetHealthyMetrics (0.00s)\n    --- PASS: TestGetHealthyMetrics/mixed_health_states (0.00s)\n    --- PASS: TestGetHealthyMetrics/node_not_found (0.00s)\n    --- PASS: TestGetHealthyMetrics/check_only_healthy_metric (0.00s)\n=== RUN   TestBufferHealthChecks\n=== RUN   TestBufferHealthChecks/nil_buffer\n=== RUN   TestBufferHealthChecks/empty_buffer\n=== RUN   TestBufferHealthChecks/healthy_buffer_with_recent_data\n=== RUN   TestBufferHealthChecks/stale_buffer_beyond_threshold\n=== RUN   TestBufferHealthChecks/buffer_at_threshold_boundary\n--- PASS: TestBufferHealthChecks (0.00s)\n    --- PASS: TestBufferHealthChecks/nil_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/empty_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/healthy_buffer_with_recent_data (0.00s)\n    --- PASS: TestBufferHealthChecks/stale_buffer_beyond_threshold (0.00s)\n    --- PASS: TestBufferHealthChecks/buffer_at_threshold_boundary (0.00s)\n=== RUN   TestBufferPoolClean\n--- PASS: TestBufferPoolClean (0.00s)\n=== RUN   TestParseScopeFromName\n=== RUN   TestParseScopeFromName/socket0\n=== RUN   TestParseScopeFromName/socket12\n=== RUN   TestParseScopeFromName/core0\n=== RUN   TestParseScopeFromName/core127\n=== RUN   TestParseScopeFromName/cpu0\n=== RUN   TestParseScopeFromName/hwthread5\n=== RUN   TestParseScopeFromName/memoryDomain0\n=== RUN   TestParseScopeFromName/accelerator0\n=== RUN   TestParseScopeFromName/unknown\n=== RUN   TestParseScopeFromName/socketX\n--- PASS: TestParseScopeFromName (0.00s)\n    --- PASS: TestParseScopeFromName/socket0 (0.00s)\n    --- PASS: TestParseScopeFromName/socket12 (0.00s)\n    --- PASS: TestParseScopeFromName/core0 (0.00s)\n    --- PASS: TestParseScopeFromName/core127 (0.00s)\n    --- PASS: TestParseScopeFromName/cpu0 (0.00s)\n    --- PASS: TestParseScopeFromName/hwthread5 (0.00s)\n    --- PASS: TestParseScopeFromName/memoryDomain0 (0.00s)\n    --- PASS: TestParseScopeFromName/accelerator0 (0.00s)\n    --- PASS: TestParseScopeFromName/unknown (0.00s)\n    --- PASS: TestParseScopeFromName/socketX (0.00s)\n=== RUN   TestFlattenCheckpointFile\n--- PASS: TestFlattenCheckpointFile (0.00s)\n=== RUN   TestParquetArchiveRoundtrip\n    parquetArchive_test.go:219: Parquet file size: 2060 bytes for 9 rows\n--- PASS: TestParquetArchiveRoundtrip (0.01s)\n=== RUN   TestLoadCheckpointFileFromDisk_JSON\n--- PASS: TestLoadCheckpointFileFromDisk_JSON (0.00s)\n=== RUN   TestBuildScopeQueries\n=== RUN   TestBuildScopeQueries/HWThread->HWThread\n=== RUN   TestBuildScopeQueries/Core->Core\n=== RUN   TestBuildScopeQueries/Socket->Socket\n=== RUN   TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN   TestBuildScopeQueries/Node->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN   TestBuildScopeQueries/HWThread->Core\n=== RUN   TestBuildScopeQueries/HWThread->Socket\n=== RUN   TestBuildScopeQueries/HWThread->Node\n=== RUN   TestBuildScopeQueries/Core->Socket\n=== RUN   TestBuildScopeQueries/Core->Node\n=== RUN   TestBuildScopeQueries/Socket->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN   TestBuildScopeQueries/Accelerator->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n    --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN   TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN   TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN   TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN   TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok  \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.496s","is_error":false}]},"uuid":"0793b054-000b-44b7-98f9-e872d7349770","timestamp":"2026-03-17T18:15:40.202Z","toolUseResult":{"stdout":"=== RUN   TestBufferPoolGetReuse\n--- PASS: TestBufferPoolGetReuse (0.00s)\n=== RUN   TestBufferPoolClear\n--- PASS: TestBufferPoolClear (0.00s)\n=== RUN   TestBufferEndFirstWrite\n--- PASS: TestBufferEndFirstWrite (0.00s)\n=== RUN   TestBufferWriteNaNFill\n--- PASS: TestBufferWriteNaNFill (0.00s)\n=== RUN   TestBufferWriteCapacityOverflow\n--- PASS: TestBufferWriteCapacityOverflow (0.00s)\n=== RUN   TestBufferWriteOverwrite\n--- PASS: TestBufferWriteOverwrite (0.00s)\n=== RUN   TestBufferReadBeforeFirstWrite\n--- PASS: TestBufferReadBeforeFirstWrite (0.00s)\n=== RUN   TestBufferReadChain\n--- PASS: TestBufferReadChain (0.00s)\n=== RUN   TestBufferReadIdxAfterSwitch\n--- PASS: TestBufferReadIdxAfterSwitch (0.00s)\n=== RUN   TestBufferReadNaNValues\n--- PASS: TestBufferReadNaNValues (0.00s)\n=== RUN   TestBufferReadAccumulation\n--- PASS: TestBufferReadAccumulation (0.00s)\n=== RUN   TestBufferFreeRetention\n--- PASS: TestBufferFreeRetention (0.00s)\n=== RUN   TestBufferFreeAll\n--- PASS: TestBufferFreeAll (0.00s)\n=== RUN   TestForceFreeOldestPoolReturn\n--- PASS: TestForceFreeOldestPoolReturn (0.00s)\n=== RUN   TestForceFreeOldestSingleBuffer\n--- PASS: TestForceFreeOldestSingleBuffer (0.00s)\n=== RUN   TestBufferIterFromToOrder\n--- PASS: TestBufferIterFromToOrder (0.00s)\n=== RUN   TestBufferIterFromToFiltered\n--- PASS: TestBufferIterFromToFiltered (0.00s)\n=== RUN   TestBufferIterFromToNilBuffer\n--- PASS: TestBufferIterFromToNilBuffer (0.00s)\n=== RUN   TestBufferCount\n--- PASS: TestBufferCount (0.00s)\n=== RUN   TestAssignAggregationStrategy\n=== RUN   TestAssignAggregationStrategy/empty_string\n=== RUN   TestAssignAggregationStrategy/sum\n=== RUN   TestAssignAggregationStrategy/avg\n=== RUN   TestAssignAggregationStrategy/invalid\n--- PASS: TestAssignAggregationStrategy (0.00s)\n    --- PASS: TestAssignAggregationStrategy/empty_string (0.00s)\n    --- PASS: TestAssignAggregationStrategy/sum (0.00s)\n    --- PASS: TestAssignAggregationStrategy/avg (0.00s)\n    --- PASS: TestAssignAggregationStrategy/invalid (0.00s)\n=== RUN   TestBufferWrite\n--- PASS: TestBufferWrite (0.00s)\n=== RUN   TestBufferRead\n--- PASS: TestBufferRead (0.00s)\n=== RUN   TestHealthCheck\n=== RUN   TestHealthCheck/all_metrics_healthy\n=== RUN   TestHealthCheck/some_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node002degraded metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/some_metrics_missing\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node003missing metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/node_not_found\n=== RUN   TestHealthCheck/all_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used cpu_user cpu_system]\n=== RUN   TestHealthCheck/multiple_nodes_mixed_states\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used]\n--- PASS: TestHealthCheck (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_healthy (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_missing (0.00s)\n    --- PASS: TestHealthCheck/node_not_found (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/multiple_nodes_mixed_states (0.00s)\n=== RUN   TestGetHealthyMetrics\n=== RUN   TestGetHealthyMetrics/mixed_health_states\n=== RUN   TestGetHealthyMetrics/node_not_found\n=== RUN   TestGetHealthyMetrics/check_only_healthy_metric\n--- PASS: TestGetHealthyMetrics (0.00s)\n    --- PASS: TestGetHealthyMetrics/mixed_health_states (0.00s)\n    --- PASS: TestGetHealthyMetrics/node_not_found (0.00s)\n    --- PASS: TestGetHealthyMetrics/check_only_healthy_metric (0.00s)\n=== RUN   TestBufferHealthChecks\n=== RUN   TestBufferHealthChecks/nil_buffer\n=== RUN   TestBufferHealthChecks/empty_buffer\n=== RUN   TestBufferHealthChecks/healthy_buffer_with_recent_data\n=== RUN   TestBufferHealthChecks/stale_buffer_beyond_threshold\n=== RUN   TestBufferHealthChecks/buffer_at_threshold_boundary\n--- PASS: TestBufferHealthChecks (0.00s)\n    --- PASS: TestBufferHealthChecks/nil_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/empty_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/healthy_buffer_with_recent_data (0.00s)\n    --- PASS: TestBufferHealthChecks/stale_buffer_beyond_threshold (0.00s)\n    --- PASS: TestBufferHealthChecks/buffer_at_threshold_boundary (0.00s)\n=== RUN   TestBufferPoolClean\n--- PASS: TestBufferPoolClean (0.00s)\n=== RUN   TestParseScopeFromName\n=== RUN   TestParseScopeFromName/socket0\n=== RUN   TestParseScopeFromName/socket12\n=== RUN   TestParseScopeFromName/core0\n=== RUN   TestParseScopeFromName/core127\n=== RUN   TestParseScopeFromName/cpu0\n=== RUN   TestParseScopeFromName/hwthread5\n=== RUN   TestParseScopeFromName/memoryDomain0\n=== RUN   TestParseScopeFromName/accelerator0\n=== RUN   TestParseScopeFromName/unknown\n=== RUN   TestParseScopeFromName/socketX\n--- PASS: TestParseScopeFromName (0.00s)\n    --- PASS: TestParseScopeFromName/socket0 (0.00s)\n    --- PASS: TestParseScopeFromName/socket12 (0.00s)\n    --- PASS: TestParseScopeFromName/core0 (0.00s)\n    --- PASS: TestParseScopeFromName/core127 (0.00s)\n    --- PASS: TestParseScopeFromName/cpu0 (0.00s)\n    --- PASS: TestParseScopeFromName/hwthread5 (0.00s)\n    --- PASS: TestParseScopeFromName/memoryDomain0 (0.00s)\n    --- PASS: TestParseScopeFromName/accelerator0 (0.00s)\n    --- PASS: TestParseScopeFromName/unknown (0.00s)\n    --- PASS: TestParseScopeFromName/socketX (0.00s)\n=== RUN   TestFlattenCheckpointFile\n--- PASS: TestFlattenCheckpointFile (0.00s)\n=== RUN   TestParquetArchiveRoundtrip\n    parquetArchive_test.go:219: Parquet file size: 2060 bytes for 9 rows\n--- PASS: TestParquetArchiveRoundtrip (0.01s)\n=== RUN   TestLoadCheckpointFileFromDisk_JSON\n--- PASS: TestLoadCheckpointFileFromDisk_JSON (0.00s)\n=== RUN   TestBuildScopeQueries\n=== RUN   TestBuildScopeQueries/HWThread->HWThread\n=== RUN   TestBuildScopeQueries/Core->Core\n=== RUN   TestBuildScopeQueries/Socket->Socket\n=== RUN   TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN   TestBuildScopeQueries/Node->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN   TestBuildScopeQueries/HWThread->Core\n=== RUN   TestBuildScopeQueries/HWThread->Socket\n=== RUN   TestBuildScopeQueries/HWThread->Node\n=== RUN   TestBuildScopeQueries/Core->Socket\n=== RUN   TestBuildScopeQueries/Core->Node\n=== RUN   TestBuildScopeQueries/Socket->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN   TestBuildScopeQueries/Accelerator->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n    --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN   TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN   TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN   TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN   TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok  \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.496s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"442aef62-2c74-45f6-8858-79e6b9da2e9f","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"0793b054-000b-44b7-98f9-e872d7349770","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0141zKHqUaRE5ZzPG2dBZwmN","type":"message","role":"assistant","content":[{"type":"text","text":"All tests pass and `go vet` is clean. Here's a summary of the changes:\n\n### Changes Made\n\n**`pkg/metricstore/parquetArchive.go`**:\n- Added `parquetArchiveWriter` struct with `newParquetArchiveWriter()`, `WriteHostRows()`, and `Close()` methods — streams rows incrementally instead of buffering everything\n- Removed `writeParquetArchive()` which buffered all rows + used `SortingWriterConfig` (the double-buffering culprit)\n- Each `WriteHostRows()` call sorts in-place and flushes, creating one row group per host\n- Added `estimateRowCount()` to pre-allocate the per-host rows slice\n- Added `sortParquetRows()` helper\n- `archiveCheckpointsToParquet()` now pre-allocates rows using `estimateRowCount()`\n\n**`pkg/metricstore/archive.go`**:\n- `archiveCheckpoints()` now opens a `parquetArchiveWriter` before consuming results\n- Each host's rows are written and flushed immediately via `WriteHostRows()`, then the rows are GC'd\n- Only one host's data lives in memory at a time instead of all hosts\n- Empty file cleanup if no data was written\n\n**`pkg/metricstore/parquetArchive_test.go`**:\n- Updated `TestParquetArchiveRoundtrip` to use the new streaming writer API\n\n### Memory Impact\n- **Before**: ~3x raw data (all rows + sorting writer copy + append overhead) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3493,"cache_read_input_tokens":35270,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3493},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ97Gpd8w1yQHh3JNoHUn","type":"assistant","uuid":"cb8ce8a5-8c94-457e-92f2-d57e5590614f","timestamp":"2026-03-17T18:15:51.621Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"2430868c-673d-479b-8db3-af90c85f7921","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015JSipUSkSXoxHkMsaNbZTP","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→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    18→\tpq \"github.com/parquet-go/parquet-go\"\n    19→)\n    20→\n    21→// ParquetMetricRow is the long-format schema for archived metric data.\n    22→// One row per (host, metric, scope, scope_id, timestamp) data point.\n    23→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n    24→type ParquetMetricRow struct {\n    25→\tCluster   string  `parquet:\"cluster\"`\n    26→\tHostname  string  `parquet:\"hostname\"`\n    27→\tMetric    string  `parquet:\"metric\"`\n    28→\tScope     string  `parquet:\"scope\"`\n    29→\tScopeID   string  `parquet:\"scope_id\"`\n    30→\tTimestamp int64   `parquet:\"timestamp\"`\n    31→\tFrequency int64   `parquet:\"frequency\"`\n    32→\tValue     float32 `parquet:\"value\"`\n    33→}\n    34→\n    35→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n    36→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    37→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    38→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n    39→\tfor metricName, cm := range cf.Metrics {\n    40→\t\tts := cm.Start\n    41→\t\tfor _, v := range cm.Data {\n    42→\t\t\tif !v.IsNaN() {\n    43→\t\t\t\trows = append(rows, ParquetMetricRow{\n    44→\t\t\t\t\tCluster:   cluster,\n    45→\t\t\t\t\tHostname:  hostname,\n    46→\t\t\t\t\tMetric:    metricName,\n    47→\t\t\t\t\tScope:     scope,\n    48→\t\t\t\t\tScopeID:   scopeID,\n    49→\t\t\t\t\tTimestamp: ts,\n    50→\t\t\t\t\tFrequency: cm.Frequency,\n    51→\t\t\t\t\tValue:     float32(v),\n    52→\t\t\t\t})\n    53→\t\t\t}\n    54→\t\t\tts += cm.Frequency\n    55→\t\t}\n    56→\t}\n    57→\n    58→\tfor childName, childCf := range cf.Children {\n    59→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    60→\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n    61→\t}\n    62→\n    63→\treturn rows\n    64→}\n    65→\n    66→// parseScopeFromName infers scope and scope_id from a child level name.\n    67→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    68→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    69→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    70→func parseScopeFromName(name string) (string, string) {\n    71→\tprefixes := []struct {\n    72→\t\tprefix string\n    73→\t\tscope  string\n    74→\t}{\n    75→\t\t{\"socket\", \"socket\"},\n    76→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    77→\t\t{\"core\", \"core\"},\n    78→\t\t{\"hwthread\", \"hwthread\"},\n    79→\t\t{\"cpu\", \"hwthread\"},\n    80→\t\t{\"accelerator\", \"accelerator\"},\n    81→\t}\n    82→\n    83→\tfor _, p := range prefixes {\n    84→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    85→\t\t\tid := name[len(p.prefix):]\n    86→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    87→\t\t\t\treturn p.scope, id\n    88→\t\t\t}\n    89→\t\t}\n    90→\t}\n    91→\n    92→\treturn name, \"\"\n    93→}\n    94→\n    95→// parquetArchiveWriter supports incremental writes to a Parquet file.\n    96→// Each call to WriteHostRows writes one row group (typically one host's data),\n    97→// avoiding accumulation of all rows in memory.\n    98→type parquetArchiveWriter struct {\n    99→\twriter *pq.GenericWriter[ParquetMetricRow]\n   100→\tbw     *bufio.Writer\n   101→\tf      *os.File\n   102→\tcount  int\n   103→}\n   104→\n   105→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n   106→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n   107→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n   108→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n   109→\t}\n   110→\n   111→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   112→\tif err != nil {\n   113→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n   114→\t}\n   115→\n   116→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   117→\n   118→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   119→\t\tpq.Compression(&pq.Zstd),\n   120→\t)\n   121→\n   122→\treturn &parquetArchiveWriter{writer: writer, bw: bw, f: f}, nil\n   123→}\n   124→\n   125→// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n   126→// and flushes to create a separate row group.\n   127→func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n   128→\tsort.Slice(rows, func(i, j int) bool {\n   129→\t\tif rows[i].Metric != rows[j].Metric {\n   130→\t\t\treturn rows[i].Metric < rows[j].Metric\n   131→\t\t}\n   132→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   133→\t})\n   134→\n   135→\tif _, err := w.writer.Write(rows); err != nil {\n   136→\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n   137→\t}\n   138→\n   139→\tif err := w.writer.Flush(); err != nil {\n   140→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n   141→\t}\n   142→\n   143→\tw.count += len(rows)\n   144→\treturn nil\n   145→}\n   146→\n   147→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n   148→func (w *parquetArchiveWriter) Close() error {\n   149→\tif err := w.writer.Close(); err != nil {\n   150→\t\tw.f.Close()\n   151→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n   152→\t}\n   153→\n   154→\tif err := w.bw.Flush(); err != nil {\n   155→\t\tw.f.Close()\n   156→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n   157→\t}\n   158→\n   159→\treturn w.f.Close()\n   160→}\n   161→\n   162→// sortParquetRows sorts rows by (metric, timestamp) in-place.\n   163→func sortParquetRows(rows []ParquetMetricRow) {\n   164→\tsort.Slice(rows, func(i, j int) bool {\n   165→\t\tif rows[i].Metric != rows[j].Metric {\n   166→\t\t\treturn rows[i].Metric < rows[j].Metric\n   167→\t\t}\n   168→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   169→\t})\n   170→}\n   171→\n   172→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   173→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   174→// before converting it to Parquet format.\n   175→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   176→\tf, err := os.Open(filename)\n   177→\tif err != nil {\n   178→\t\treturn nil, err\n   179→\t}\n   180→\tdefer f.Close()\n   181→\n   182→\text := filepath.Ext(filename)\n   183→\tswitch ext {\n   184→\tcase \".json\":\n   185→\t\tcf := &CheckpointFile{}\n   186→\t\tbr := bufio.NewReader(f)\n   187→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   188→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   189→\t\t}\n   190→\t\treturn cf, nil\n   191→\n   192→\tcase \".bin\":\n   193→\t\tbr := bufio.NewReader(f)\n   194→\t\tvar magic uint32\n   195→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   196→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   197→\t\t}\n   198→\t\tif magic != snapFileMagic {\n   199→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   200→\t\t}\n   201→\t\tvar fileFrom, fileTo int64\n   202→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   203→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   204→\t\t}\n   205→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   206→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   207→\t\t}\n   208→\t\tcf, err := readBinaryLevel(br)\n   209→\t\tif err != nil {\n   210→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   211→\t\t}\n   212→\t\tcf.From = fileFrom\n   213→\t\tcf.To = fileTo\n   214→\t\treturn cf, nil\n   215→\n   216→\tdefault:\n   217→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   218→\t}\n   219→}\n   220→\n   221→// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n   222→// Used for pre-allocating the rows slice to avoid repeated append doubling.\n   223→func estimateRowCount(cf *CheckpointFile) int {\n   224→\tn := 0\n   225→\tfor _, cm := range cf.Metrics {\n   226→\t\tn += len(cm.Data)\n   227→\t}\n   228→\tfor _, child := range cf.Children {\n   229→\t\tn += estimateRowCount(child)\n   230→\t}\n   231→\treturn n\n   232→}\n   233→\n   234→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   235→// converts them to Parquet rows. Returns the rows and filenames that were processed.\n   236→func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {\n   237→\tentries, err := os.ReadDir(dir)\n   238→\tif err != nil {\n   239→\t\treturn nil, nil, err\n   240→\t}\n   241→\n   242→\tfiles, err := findFiles(entries, from, false)\n   243→\tif err != nil {\n   244→\t\treturn nil, nil, err\n   245→\t}\n   246→\n   247→\tif len(files) == 0 {\n   248→\t\treturn nil, nil, nil\n   249→\t}\n   250→\n   251→\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n   252→\ttype loaded struct {\n   253→\t\tcf       *CheckpointFile\n   254→\t\tfilename string\n   255→\t}\n   256→\tvar checkpoints []loaded\n   257→\ttotalEstimate := 0\n   258→\n   259→\tfor _, checkpoint := range files {\n   260→\t\tfilename := filepath.Join(dir, checkpoint)\n   261→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   262→\t\tif err != nil {\n   263→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   264→\t\t\tcontinue\n   265→\t\t}\n   266→\t\ttotalEstimate += estimateRowCount(cf)\n   267→\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n   268→\t}\n   269→\n   270→\tif len(checkpoints) == 0 {\n   271→\t\treturn nil, nil, nil\n   272→\t}\n   273→\n   274→\trows := make([]ParquetMetricRow, 0, totalEstimate)\n   275→\tprocessedFiles := make([]string, 0, len(checkpoints))\n   276→\n   277→\tfor _, cp := range checkpoints {\n   278→\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n   279→\t\tprocessedFiles = append(processedFiles, cp.filename)\n   280→\t}\n   281→\n   282→\treturn rows, processedFiles, nil\n   283→}\n   284→"}]},"uuid":"0b8f00ca-48da-4b9c-a3e9-265029b39781","timestamp":"2026-03-18T04:02:36.395Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"3fbe0910-10c9-48c1-9b6b-7929c4eba811","timestamp":"2026-03-18T04:02:36.577Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"912f12d8-7474-41e1-8f48-739a31adb3d8","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LEnHcZQkV5PNC7XPaU6Pgb","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\"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":"1112516e-76fc-42b2-9709-8c6466b84dd7","timestamp":"2026-03-18T04:02:36.604Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"dbd83243-3f80-41dd-a55a-79a9516936db","timestamp":"2026-03-18T04:02:36.837Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"5143d6be-379b-4abf-a157-a66bd9488b93","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GNs92J7Re4V1XiEhUdVFzR","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":"5139460a-6d14-44e6-83e4-ce582368071b","timestamp":"2026-03-18T04:02:36.857Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"f80b2e80-bf73-4f8f-bf82-05cad2523928","timestamp":"2026-03-18T04:02:37.006Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"e994be56-621a-458a-9404-8649dd75d275","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019UUYjj6J4QJS6RmAgcJTSo","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":"9c55ee61-e630-466b-8ade-4bc796ede8ec","timestamp":"2026-03-18T04:02:39.550Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"5fcacfb4-089a-4e6c-aa2c-47de7b6497db","timestamp":"2026-03-18T04:02:39.550Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"021c6590-b1e0-4880-a2ac-ed0a85ce8b0b","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01N4KBTu1ntjU3HDvgueA7nE","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\"time\"\n    10→\n    11→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n    12→\t\"github.com/ClusterCockpit/cc-backend/internal/repository\"\n    13→\tpqarchive \"github.com/ClusterCockpit/cc-backend/pkg/archive/parquet\"\n    14→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    15→\t\"github.com/go-co-op/gocron/v2\"\n    16→)\n    17→\n    18→func RegisterNodeStateRetentionDeleteService(ageHours int) {\n    19→\tcclog.Info(\"Register node state retention delete service\")\n    20→\n    21→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(2, 0, 0))),\n    22→\t\tgocron.NewTask(\n    23→\t\t\tfunc() {\n    24→\t\t\t\tcutoff := time.Now().Unix() - int64(ageHours*3600)\n    25→\t\t\t\tnodeRepo := repository.GetNodeRepository()\n    26→\t\t\t\tcnt, err := nodeRepo.DeleteNodeStatesBefore(cutoff)\n    27→\t\t\t\tif err != nil {\n    28→\t\t\t\t\tcclog.Errorf(\"NodeState retention: error deleting old rows: %v\", err)\n    29→\t\t\t\t} else if cnt > 0 {\n    30→\t\t\t\t\tcclog.Infof(\"NodeState retention: deleted %d old rows\", cnt)\n    31→\t\t\t\t}\n    32→\t\t\t}))\n    33→}\n    34→\n    35→func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n    36→\tcclog.Info(\"Register node state retention move service\")\n    37→\n    38→\tmaxFileSizeMB := cfg.MaxFileSizeMB\n    39→\tif maxFileSizeMB <= 0 {\n    40→\t\tmaxFileSizeMB = 128\n    41→\t}\n    42→\n    43→\tageHours := cfg.Age\n    44→\tif ageHours <= 0 {\n    45→\t\tageHours = 24\n    46→\t}\n    47→\n    48→\tvar target pqarchive.ParquetTarget\n    49→\tvar err error\n    50→\n    51→\tswitch cfg.TargetKind {\n    52→\tcase \"s3\":\n    53→\t\ttarget, err = pqarchive.NewS3Target(pqarchive.S3TargetConfig{\n    54→\t\t\tEndpoint:     cfg.TargetEndpoint,\n    55→\t\t\tBucket:       cfg.TargetBucket,\n    56→\t\t\tAccessKey:    cfg.TargetAccessKey,\n    57→\t\t\tSecretKey:    cfg.TargetSecretKey,\n    58→\t\t\tRegion:       cfg.TargetRegion,\n    59→\t\t\tUsePathStyle: cfg.TargetUsePathStyle,\n    60→\t\t})\n    61→\tdefault:\n    62→\t\ttarget, err = pqarchive.NewFileTarget(cfg.TargetPath)\n    63→\t}\n    64→\n    65→\tif err != nil {\n    66→\t\tcclog.Errorf(\"NodeState move retention: failed to create target: %v\", err)\n    67→\t\treturn\n    68→\t}\n    69→\n    70→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(2, 30, 0))),\n    71→\t\tgocron.NewTask(\n    72→\t\t\tfunc() {\n    73→\t\t\t\tcutoff := time.Now().Unix() - int64(ageHours*3600)\n    74→\t\t\t\tnodeRepo := repository.GetNodeRepository()\n    75→\n    76→\t\t\t\trows, err := nodeRepo.FindNodeStatesBefore(cutoff)\n    77→\t\t\t\tif err != nil {\n    78→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: error finding rows: %v\", err)\n    79→\t\t\t\t\treturn\n    80→\t\t\t\t}\n    81→\t\t\t\tif len(rows) == 0 {\n    82→\t\t\t\t\treturn\n    83→\t\t\t\t}\n    84→\n    85→\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\n    86→\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n    87→\n    88→\t\t\t\tfor _, ns := range rows {\n    89→\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{\n    90→\t\t\t\t\t\tTimeStamp:       ns.TimeStamp,\n    91→\t\t\t\t\t\tNodeState:       ns.NodeState,\n    92→\t\t\t\t\t\tHealthState:     ns.HealthState,\n    93→\t\t\t\t\t\tHealthMetrics:   ns.HealthMetrics,\n    94→\t\t\t\t\t\tCpusAllocated:   int32(ns.CpusAllocated),\n    95→\t\t\t\t\t\tMemoryAllocated: ns.MemoryAllocated,\n    96→\t\t\t\t\t\tGpusAllocated:   int32(ns.GpusAllocated),\n    97→\t\t\t\t\t\tJobsRunning:     int32(ns.JobsRunning),\n    98→\t\t\t\t\t\tHostname:        ns.Hostname,\n    99→\t\t\t\t\t\tCluster:         ns.Cluster,\n   100→\t\t\t\t\t\tSubCluster:      ns.SubCluster,\n   101→\t\t\t\t\t}\n   102→\t\t\t\t\tif err := pw.AddRow(row); err != nil {\n   103→\t\t\t\t\t\tcclog.Errorf(\"NodeState move retention: add row: %v\", err)\n   104→\t\t\t\t\t\tcontinue\n   105→\t\t\t\t\t}\n   106→\t\t\t\t}\n   107→\n   108→\t\t\t\tif err := pw.Close(); err != nil {\n   109→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: close writer: %v\", err)\n   110→\t\t\t\t\treturn\n   111→\t\t\t\t}\n   112→\n   113→\t\t\t\tcnt, err := nodeRepo.DeleteNodeStatesBefore(cutoff)\n   114→\t\t\t\tif err != nil {\n   115→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: error deleting rows: %v\", err)\n   116→\t\t\t\t} else {\n   117→\t\t\t\t\tcclog.Infof(\"NodeState move retention: deleted %d rows from db\", cnt)\n   118→\t\t\t\t}\n   119→\t\t\t}))\n   120→}\n   121→"}]},"uuid":"ef5b2bb2-c6c2-4ad6-8de9-f17ad72570d6","timestamp":"2026-03-18T04:02:39.609Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"16ae8feb-f59c-44fd-b541-6d2b7553859c","timestamp":"2026-03-18T04:02:39.610Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"16ae8feb-f59c-44fd-b541-6d2b7553859c","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-18T04:02:39.755Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01AGhRwzpLPizPqmLZJmbUqk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01B3qau1at87zKUnxbhjYBLe","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go","limit":300},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":8899,"cache_read_input_tokens":20542,"cache_creation":{"ephemeral_5m_input_tokens":8899,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ9t2qQ8AnpMjGLdf6L1a","uuid":"a785207e-c3ee-4e7b-884e-ac18e3bc423e"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"4371f6de-6875-46f4-9168-dc00b1848578","timestamp":"2026-03-18T04:02:39.755Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"4371f6de-6875-46f4-9168-dc00b1848578","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B3qau1at87zKUnxbhjYBLe","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\t// Run as Archiver\n    26→\t\tcleanUpWorker(wg, ctx,\n    27→\t\t\tKeys.RetentionInMemory,\n    28→\t\t\t\"archiving\",\n    29→\t\t\tKeys.Cleanup.RootDir,\n    30→\t\t\tfalse,\n    31→\t\t)\n    32→\t} else {\n    33→\t\t// Run as Deleter\n    34→\t\tcleanUpWorker(wg, ctx,\n    35→\t\t\tKeys.RetentionInMemory,\n    36→\t\t\t\"deleting\",\n    37→\t\t\t\"\",\n    38→\t\t\ttrue,\n    39→\t\t)\n    40→\t}\n    41→}\n    42→\n    43→// cleanUpWorker takes simple values to configure what it does\n    44→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n    45→\twg.Go(func() {\n    46→\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→// Each host's rows are written as a separate row group to avoid accumulating\n   172→// all data in memory at once.\n   173→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n   174→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n   175→\tif err != nil {\n   176→\t\treturn 0, err\n   177→\t}\n   178→\n   179→\ttotalFiles := 0\n   180→\n   181→\tfor _, clusterEntry := range clusterEntries {\n   182→\t\tif !clusterEntry.IsDir() {\n   183→\t\t\tcontinue\n   184→\t\t}\n   185→\n   186→\t\tcluster := clusterEntry.Name()\n   187→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n   188→\t\tif err != nil {\n   189→\t\t\treturn totalFiles, err\n   190→\t\t}\n   191→\n   192→\t\t// Stream per-host rows to parquet writer via worker pool\n   193→\t\ttype hostResult struct {\n   194→\t\t\trows  []ParquetMetricRow\n   195→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n   196→\t\t\tdir   string   // checkpoint directory for this host\n   197→\t\t}\n   198→\n   199→\t\tresults := make(chan hostResult, len(hostEntries))\n   200→\t\twork := make(chan struct {\n   201→\t\t\tdir, host string\n   202→\t\t}, Keys.NumWorkers)\n   203→\n   204→\t\tvar wg sync.WaitGroup\n   205→\t\terrs := int32(0)\n   206→\n   207→\t\twg.Add(Keys.NumWorkers)\n   208→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n   209→\t\t\tgo func() {\n   210→\t\t\t\tdefer wg.Done()\n   211→\t\t\t\tfor item := range work {\n   212→\t\t\t\t\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, from)\n   213→\t\t\t\t\tif err != nil {\n   214→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n   215→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n   216→\t\t\t\t\t\tcontinue\n   217→\t\t\t\t\t}\n   218→\t\t\t\t\tif len(rows) > 0 {\n   219→\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\n   220→\t\t\t\t\t}\n   221→\t\t\t\t}\n   222→\t\t\t}()\n   223→\t\t}\n   224→\n   225→\t\tgo func() {\n   226→\t\t\tfor _, hostEntry := range hostEntries {\n   227→\t\t\t\tif !hostEntry.IsDir() {\n   228→\t\t\t\t\tcontinue\n   229→\t\t\t\t}\n   230→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n   231→\t\t\t\twork <- struct {\n   232→\t\t\t\t\tdir, host string\n   233→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n   234→\t\t\t}\n   235→\t\t\tclose(work)\n   236→\t\t\twg.Wait()\n   237→\t\t\tclose(results)\n   238→\t\t}()\n   239→\n   240→\t\t// Open streaming writer and write each host's rows as a row group\n   241→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n   242→\t\twriter, err := newParquetArchiveWriter(parquetFile)\n   243→\t\tif err != nil {\n   244→\t\t\t// Drain results channel to unblock workers\n   245→\t\t\tfor range results {\n   246→\t\t\t}\n   247→\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n   248→\t\t}\n   249→\n   250→\t\ttype deleteItem struct {\n   251→\t\t\tdir   string\n   252→\t\t\tfiles []string\n   253→\t\t}\n   254→\t\tvar toDelete []deleteItem\n   255→\t\twriteErr := error(nil)\n   256→\n   257→\t\tfor r := range results {\n   258→\t\t\tif writeErr == nil {\n   259→\t\t\t\tsortParquetRows(r.rows)\n   260→\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n   261→\t\t\t\t\twriteErr = err\n   262→\t\t\t\t}\n   263→\t\t\t}\n   264→\t\t\t// Always track files for deletion (even if write failed, we still drain)\n   265→\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n   266→\t\t}\n   267→\n   268→\t\tif err := writer.Close(); err != nil && writeErr == nil {\n   269→\t\t\twriteErr = err\n   270→\t\t}\n   271→\n   272→\t\tif errs > 0 {\n   273→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n   274→\t\t}\n   275→\n   276→\t\tif writer.count == 0 {\n   277→\t\t\t// No data written — remove empty file\n   278→\t\t\tos.Remove(parquetFile)\n   279→\t\t\tcontinue\n   280→\t\t}\n   281→\n   282→\t\tif writeErr != nil {\n   283→\t\t\tos.Remove(parquetFile)\n   284→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n   285→\t\t}\n   286→\n   287→\t\t// Delete archived checkpoint files\n   288→\t\tfor _, item := range toDelete {\n   289→\t\t\tfor _, file := range item.files {\n   290→\t\t\t\tfilename := filepath.Join(item.dir, file)\n   291→\t\t\t\tif err := os.Remove(filename); err != nil {\n   292→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n   293→\t\t\t\t} else {\n   294→\t\t\t\t\ttotalFiles++\n   295→\t\t\t\t}\n   296→\t\t\t}\n   297→\t\t}\n   298→\n   299→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n   300→\t\t\twriter.count, totalFiles, cluster, parquetFile)"}]},"uuid":"9ba823f7-f70b-408c-85a5-d24ed2584aea","timestamp":"2026-03-18T04:02:39.767Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"c60873cc-1254-4214-8fd0-17084b70fe7c","timestamp":"2026-03-18T04:02:39.768Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"91d42c01-6b72-4d41-9852-696f364e6edb","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013LMkXWdTD9Mrr8mFng5HZw","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\"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,"}]},"uuid":"7b6a47be-a2c0-488e-ba31-b52aea20f0ea","timestamp":"2026-03-18T04:02:43.724Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"1c7c8ba0-45fa-4dcf-a87d-03f5d8f26168","timestamp":"2026-03-18T04:02:43.726Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"1c7c8ba0-45fa-4dcf-a87d-03f5d8f26168","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-18T04:02:45.376Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01AeDDgdidv1BEeCrQFmdBTc","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RR1p1p9GmJcZsKdnHvrmY8","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer_test.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":1586,"cache_read_input_tokens":41470,"cache_creation":{"ephemeral_5m_input_tokens":1586,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ9t3JEAaXHwUp2qQFHHG","uuid":"be8ab130-3d8c-4c5e-be06-5c6e300b2aa4"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"b86b4a2f-0e5a-4339-aa72-47e83065dde7","timestamp":"2026-03-18T04:02:45.376Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"b86b4a2f-0e5a-4339-aa72-47e83065dde7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RR1p1p9GmJcZsKdnHvrmY8","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\"compress/gzip\"\n    11→\t\"encoding/json\"\n    12→\t\"io\"\n    13→\t\"os\"\n    14→\t\"path/filepath\"\n    15→\t\"strings\"\n    16→\t\"sync\"\n    17→\t\"testing\"\n    18→\n    19→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    20→\tpq \"github.com/parquet-go/parquet-go\"\n    21→)\n    22→\n    23→// memTarget collects written files in memory for testing.\n    24→type memTarget struct {\n    25→\tmu    sync.Mutex\n    26→\tfiles map[string][]byte\n    27→}\n    28→\n    29→func newMemTarget() *memTarget {\n    30→\treturn &memTarget{files: make(map[string][]byte)}\n    31→}\n    32→\n    33→func (m *memTarget) WriteFile(name string, data []byte) error {\n    34→\tm.mu.Lock()\n    35→\tdefer m.mu.Unlock()\n    36→\tm.files[name] = append([]byte(nil), data...)\n    37→\treturn nil\n    38→}\n    39→\n    40→func makeTestJob(jobID int64) (*schema.Job, *schema.JobData) {\n    41→\tmeta := &schema.Job{\n    42→\t\tJobID:        jobID,\n    43→\t\tCluster:      \"testcluster\",\n    44→\t\tSubCluster:   \"sc0\",\n    45→\t\tProject:      \"testproject\",\n    46→\t\tUser:         \"testuser\",\n    47→\t\tState:        schema.JobStateCompleted,\n    48→\t\tStartTime:    1700000000,\n    49→\t\tDuration:     3600,\n    50→\t\tWalltime:     7200,\n    51→\t\tNumNodes:     2,\n    52→\t\tNumHWThreads: 16,\n    53→\t\tSMT:          1,\n    54→\t\tResources: []*schema.Resource{\n    55→\t\t\t{Hostname: \"node001\"},\n    56→\t\t\t{Hostname: \"node002\"},\n    57→\t\t},\n    58→\t}\n    59→\n    60→\tdata := schema.JobData{\n    61→\t\t\"cpu_load\": {\n    62→\t\t\tschema.MetricScopeNode: &schema.JobMetric{\n    63→\t\t\t\tUnit:     schema.Unit{Base: \"\"},\n    64→\t\t\t\tTimestep: 60,\n    65→\t\t\t\tSeries: []schema.Series{\n    66→\t\t\t\t\t{\n    67→\t\t\t\t\t\tHostname: \"node001\",\n    68→\t\t\t\t\t\tData:     []schema.Float{1.0, 2.0, 3.0},\n    69→\t\t\t\t\t},\n    70→\t\t\t\t},\n    71→\t\t\t},\n    72→\t\t},\n    73→\t}\n    74→\n    75→\treturn meta, &data\n    76→}\n    77→\n    78→func TestJobToParquetRowConversion(t *testing.T) {\n    79→\tmeta, data := makeTestJob(1001)\n    80→\tmeta.Tags = []*schema.Tag{{Type: \"test\", Name: \"tag1\"}}\n    81→\tmeta.MetaData = map[string]string{\"key\": \"value\"}\n    82→\n    83→\trow, err := JobToParquetRow(meta, data)\n    84→\tif err != nil {\n    85→\t\tt.Fatalf(\"JobToParquetRow: %v\", err)\n    86→\t}\n    87→\n    88→\tif row.JobID != 1001 {\n    89→\t\tt.Errorf(\"JobID = %d, want 1001\", row.JobID)\n    90→\t}\n    91→\tif row.Cluster != \"testcluster\" {\n    92→\t\tt.Errorf(\"Cluster = %q, want %q\", row.Cluster, \"testcluster\")\n    93→\t}\n    94→\tif row.User != \"testuser\" {\n    95→\t\tt.Errorf(\"User = %q, want %q\", row.User, \"testuser\")\n    96→\t}\n    97→\tif row.State != \"completed\" {\n    98→\t\tt.Errorf(\"State = %q, want %q\", row.State, \"completed\")\n    99→\t}\n   100→\tif row.NumNodes != 2 {\n   101→\t\tt.Errorf(\"NumNodes = %d, want 2\", row.NumNodes)\n   102→\t}\n   103→\n   104→\t// Verify resources JSON\n   105→\tvar resources []*schema.Resource\n   106→\tif err := json.Unmarshal(row.ResourcesJSON, &resources); err != nil {\n   107→\t\tt.Fatalf(\"unmarshal resources: %v\", err)\n   108→\t}\n   109→\tif len(resources) != 2 {\n   110→\t\tt.Errorf(\"resources len = %d, want 2\", len(resources))\n   111→\t}\n   112→\n   113→\t// Verify tags JSON\n   114→\tvar tags []*schema.Tag\n   115→\tif err := json.Unmarshal(row.TagsJSON, &tags); err != nil {\n   116→\t\tt.Fatalf(\"unmarshal tags: %v\", err)\n   117→\t}\n   118→\tif len(tags) != 1 || tags[0].Name != \"tag1\" {\n   119→\t\tt.Errorf(\"tags = %v, want [{test tag1}]\", tags)\n   120→\t}\n   121→\n   122→\t// Verify metric data is gzip-compressed valid JSON\n   123→\tgz, err := gzip.NewReader(bytes.NewReader(row.MetricDataGz))\n   124→\tif err != nil {\n   125→\t\tt.Fatalf(\"gzip reader: %v\", err)\n   126→\t}\n   127→\tdecompressed, err := io.ReadAll(gz)\n   128→\tif err != nil {\n   129→\t\tt.Fatalf(\"gzip read: %v\", err)\n   130→\t}\n   131→\tvar jobData schema.JobData\n   132→\tif err := json.Unmarshal(decompressed, &jobData); err != nil {\n   133→\t\tt.Fatalf(\"unmarshal metric data: %v\", err)\n   134→\t}\n   135→\tif _, ok := jobData[\"cpu_load\"]; !ok {\n   136→\t\tt.Error(\"metric data missing cpu_load key\")\n   137→\t}\n   138→}\n   139→\n   140→func TestParquetWriterSingleBatch(t *testing.T) {\n   141→\ttarget := newMemTarget()\n   142→\tpw := NewParquetWriter(target, 512)\n   143→\n   144→\tfor i := range int64(5) {\n   145→\t\tmeta, data := makeTestJob(i)\n   146→\t\trow, err := JobToParquetRow(meta, data)\n   147→\t\tif err != nil {\n   148→\t\t\tt.Fatalf(\"convert job %d: %v\", i, err)\n   149→\t\t}\n   150→\t\tif err := pw.AddJob(*row); err != nil {\n   151→\t\t\tt.Fatalf(\"add job %d: %v\", i, err)\n   152→\t\t}\n   153→\t}\n   154→\n   155→\tif err := pw.Close(); err != nil {\n   156→\t\tt.Fatalf(\"close: %v\", err)\n   157→\t}\n   158→\n   159→\tif len(target.files) != 1 {\n   160→\t\tt.Fatalf(\"expected 1 file, got %d\", len(target.files))\n   161→\t}\n   162→\n   163→\t// Verify the parquet file is readable\n   164→\tfor name, data := range target.files {\n   165→\t\tfile := bytes.NewReader(data)\n   166→\t\tpf, err := pq.OpenFile(file, int64(len(data)))\n   167→\t\tif err != nil {\n   168→\t\t\tt.Fatalf(\"open parquet %s: %v\", name, err)\n   169→\t\t}\n   170→\t\tif pf.NumRows() != 5 {\n   171→\t\t\tt.Errorf(\"parquet rows = %d, want 5\", pf.NumRows())\n   172→\t\t}\n   173→\t}\n   174→}\n   175→\n   176→func TestParquetWriterBatching(t *testing.T) {\n   177→\ttarget := newMemTarget()\n   178→\t// Use a very small max size to force multiple files\n   179→\tpw := NewParquetWriter(target, 0) // 0 MB means every job triggers a flush\n   180→\tpw.maxSizeBytes = 1               // Force flush after every row\n   181→\n   182→\tfor i := range int64(3) {\n   183→\t\tmeta, data := makeTestJob(i)\n   184→\t\trow, err := JobToParquetRow(meta, data)\n   185→\t\tif err != nil {\n   186→\t\t\tt.Fatalf(\"convert job %d: %v\", i, err)\n   187→\t\t}\n   188→\t\tif err := pw.AddJob(*row); err != nil {\n   189→\t\t\tt.Fatalf(\"add job %d: %v\", i, err)\n   190→\t\t}\n   191→\t}\n   192→\n   193→\tif err := pw.Close(); err != nil {\n   194→\t\tt.Fatalf(\"close: %v\", err)\n   195→\t}\n   196→\n   197→\t// With maxSizeBytes=1, each AddJob should flush the previous batch,\n   198→\t// resulting in multiple files\n   199→\tif len(target.files) < 2 {\n   200→\t\tt.Errorf(\"expected multiple files due to batching, got %d\", len(target.files))\n   201→\t}\n   202→\n   203→\t// Verify all files are valid parquet\n   204→\tfor name, data := range target.files {\n   205→\t\tfile := bytes.NewReader(data)\n   206→\t\t_, err := pq.OpenFile(file, int64(len(data)))\n   207→\t\tif err != nil {\n   208→\t\t\tt.Errorf(\"invalid parquet file %s: %v\", name, err)\n   209→\t\t}\n   210→\t}\n   211→}\n   212→\n   213→func TestFileTarget(t *testing.T) {\n   214→\tdir := t.TempDir()\n   215→\tft, err := NewFileTarget(dir)\n   216→\tif err != nil {\n   217→\t\tt.Fatalf(\"NewFileTarget: %v\", err)\n   218→\t}\n   219→\n   220→\ttestData := []byte(\"test parquet data\")\n   221→\tif err := ft.WriteFile(\"test.parquet\", testData); err != nil {\n   222→\t\tt.Fatalf(\"WriteFile: %v\", err)\n   223→\t}\n   224→\n   225→\t// Verify file exists and has correct content\n   226→\t// (using the target itself is sufficient; we just check no error)\n   227→}\n   228→\n   229→func TestFileTargetSubdirectories(t *testing.T) {\n   230→\tdir := t.TempDir()\n   231→\tft, err := NewFileTarget(dir)\n   232→\tif err != nil {\n   233→\t\tt.Fatalf(\"NewFileTarget: %v\", err)\n   234→\t}\n   235→\n   236→\ttestData := []byte(\"test data in subdir\")\n   237→\tif err := ft.WriteFile(\"fritz/cc-archive-2025-01-20-001.parquet\", testData); err != nil {\n   238→\t\tt.Fatalf(\"WriteFile with subdir: %v\", err)\n   239→\t}\n   240→\n   241→\t// Verify file was created in subdirectory\n   242→\tcontent, err := os.ReadFile(filepath.Join(dir, \"fritz\", \"cc-archive-2025-01-20-001.parquet\"))\n   243→\tif err != nil {\n   244→\t\tt.Fatalf(\"read file in subdir: %v\", err)\n   245→\t}\n   246→\tif !bytes.Equal(content, testData) {\n   247→\t\tt.Error(\"file content mismatch\")\n   248→\t}\n   249→}\n   250→\n   251→func makeTestJobForCluster(jobID int64, cluster string) (*schema.Job, *schema.JobData) {\n   252→\tmeta, data := makeTestJob(jobID)\n   253→\tmeta.Cluster = cluster\n   254→\treturn meta, data\n   255→}\n   256→\n   257→func TestClusterAwareParquetWriter(t *testing.T) {\n   258→\ttarget := newMemTarget()\n   259→\tcw := NewClusterAwareParquetWriter(target, 512)\n   260→\n   261→\t// Set cluster configs\n   262→\tcw.SetClusterConfig(\"fritz\", &schema.Cluster{Name: \"fritz\"})\n   263→\tcw.SetClusterConfig(\"alex\", &schema.Cluster{Name: \"alex\"})\n   264→\n   265→\t// Add jobs from different clusters\n   266→\tfor i := range int64(3) {\n   267→\t\tmeta, data := makeTestJobForCluster(i, \"fritz\")\n   268→\t\trow, err := JobToParquetRow(meta, data)\n   269→\t\tif err != nil {\n   270→\t\t\tt.Fatalf(\"convert fritz job %d: %v\", i, err)\n   271→\t\t}\n   272→\t\tif err := cw.AddJob(*row); err != nil {\n   273→\t\t\tt.Fatalf(\"add fritz job %d: %v\", i, err)\n   274→\t\t}\n   275→\t}\n   276→\n   277→\tfor i := int64(10); i < 12; i++ {\n   278→\t\tmeta, data := makeTestJobForCluster(i, \"alex\")\n   279→\t\trow, err := JobToParquetRow(meta, data)\n   280→\t\tif err != nil {\n   281→\t\t\tt.Fatalf(\"convert alex job %d: %v\", i, err)\n   282→\t\t}\n   283→\t\tif err := cw.AddJob(*row); err != nil {\n   284→\t\t\tt.Fatalf(\"add alex job %d: %v\", i, err)\n   285→\t\t}\n   286→\t}\n   287→\n   288→\tif err := cw.Close(); err != nil {\n   289→\t\tt.Fatalf(\"close: %v\", err)\n   290→\t}\n   291→\n   292→\ttarget.mu.Lock()\n   293→\tdefer target.mu.Unlock()\n   294→\n   295→\t// Check cluster.json files were written\n   296→\tif _, ok := target.files[\"fritz/cluster.json\"]; !ok {\n   297→\t\tt.Error(\"missing fritz/cluster.json\")\n   298→\t}\n   299→\tif _, ok := target.files[\"alex/cluster.json\"]; !ok {\n   300→\t\tt.Error(\"missing alex/cluster.json\")\n   301→\t}\n   302→\n   303→\t// Verify cluster.json content\n   304→\tvar clusterCfg schema.Cluster\n   305→\tif err := json.Unmarshal(target.files[\"fritz/cluster.json\"], &clusterCfg); err != nil {\n   306→\t\tt.Fatalf(\"unmarshal fritz cluster.json: %v\", err)\n   307→\t}\n   308→\tif clusterCfg.Name != \"fritz\" {\n   309→\t\tt.Errorf(\"fritz cluster name = %q, want %q\", clusterCfg.Name, \"fritz\")\n   310→\t}\n   311→\n   312→\t// Check parquet files are in cluster subdirectories\n   313→\tfritzParquets := 0\n   314→\talexParquets := 0\n   315→\tfor name := range target.files {\n   316→\t\tif strings.HasPrefix(name, \"fritz/\") && strings.HasSuffix(name, \".parquet\") {\n   317→\t\t\tfritzParquets++\n   318→\t\t}\n   319→\t\tif strings.HasPrefix(name, \"alex/\") && strings.HasSuffix(name, \".parquet\") {\n   320→\t\t\talexParquets++\n   321→\t\t}\n   322→\t}\n   323→\tif fritzParquets == 0 {\n   324→\t\tt.Error(\"no parquet files in fritz/\")\n   325→\t}\n   326→\tif alexParquets == 0 {\n   327→\t\tt.Error(\"no parquet files in alex/\")\n   328→\t}\n   329→\n   330→\t// Verify parquet files are readable and have correct row counts\n   331→\tfor name, data := range target.files {\n   332→\t\tif !strings.HasSuffix(name, \".parquet\") {\n   333→\t\t\tcontinue\n   334→\t\t}\n   335→\t\tfile := bytes.NewReader(data)\n   336→\t\tpf, err := pq.OpenFile(file, int64(len(data)))\n   337→\t\tif err != nil {\n   338→\t\t\tt.Errorf(\"open parquet %s: %v\", name, err)\n   339→\t\t\tcontinue\n   340→\t\t}\n   341→\t\tif strings.HasPrefix(name, \"fritz/\") && pf.NumRows() != 3 {\n   342→\t\t\tt.Errorf(\"fritz parquet rows = %d, want 3\", pf.NumRows())\n   343→\t\t}\n   344→\t\tif strings.HasPrefix(name, \"alex/\") && pf.NumRows() != 2 {\n   345→\t\t\tt.Errorf(\"alex parquet rows = %d, want 2\", pf.NumRows())\n   346→\t\t}\n   347→\t}\n   348→}\n   349→\n   350→func TestClusterAwareParquetWriterEmpty(t *testing.T) {\n   351→\ttarget := newMemTarget()\n   352→\tcw := NewClusterAwareParquetWriter(target, 512)\n   353→\n   354→\tif err := cw.Close(); err != nil {\n   355→\t\tt.Fatalf(\"close empty writer: %v\", err)\n   356→\t}\n   357→\n   358→\tif len(target.files) != 0 {\n   359→\t\tt.Errorf(\"expected no files for empty writer, got %d\", len(target.files))\n   360→\t}\n   361→}\n   362→"}]},"uuid":"865a5a9f-707f-48e4-bb93-014ea57a5d56","timestamp":"2026-03-18T04:02:45.392Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"69813891-a882-4c15-a8fa-e014769cea16","timestamp":"2026-03-18T04:02:45.750Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"d375b321-0773-492e-9b97-ebedbb6df8ed","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0151RaganG7v9p6HapDxL61S","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\"encoding/json\"\n    10→\t\"os\"\n    11→\t\"path/filepath\"\n    12→\t\"testing\"\n    13→\n    14→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    15→\tpq \"github.com/parquet-go/parquet-go\"\n    16→)\n    17→\n    18→func TestParseScopeFromName(t *testing.T) {\n    19→\ttests := []struct {\n    20→\t\tname      string\n    21→\t\twantScope string\n    22→\t\twantID    string\n    23→\t}{\n    24→\t\t{\"socket0\", \"socket\", \"0\"},\n    25→\t\t{\"socket12\", \"socket\", \"12\"},\n    26→\t\t{\"core0\", \"core\", \"0\"},\n    27→\t\t{\"core127\", \"core\", \"127\"},\n    28→\t\t{\"cpu0\", \"hwthread\", \"0\"},\n    29→\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n    30→\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n    31→\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n    32→\t\t{\"unknown\", \"unknown\", \"\"},\n    33→\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n    34→\t}\n    35→\n    36→\tfor _, tt := range tests {\n    37→\t\tt.Run(tt.name, func(t *testing.T) {\n    38→\t\t\tscope, id := parseScopeFromName(tt.name)\n    39→\t\t\tif scope != tt.wantScope || id != tt.wantID {\n    40→\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n    41→\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n    42→\t\t\t}\n    43→\t\t})\n    44→\t}\n    45→}\n    46→\n    47→func TestFlattenCheckpointFile(t *testing.T) {\n    48→\tcf := &CheckpointFile{\n    49→\t\tFrom: 1000,\n    50→\t\tTo:   1060,\n    51→\t\tMetrics: map[string]*CheckpointMetrics{\n    52→\t\t\t\"cpu_load\": {\n    53→\t\t\t\tFrequency: 60,\n    54→\t\t\t\tStart:     1000,\n    55→\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n    56→\t\t\t},\n    57→\t\t},\n    58→\t\tChildren: map[string]*CheckpointFile{\n    59→\t\t\t\"socket0\": {\n    60→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n    61→\t\t\t\t\t\"mem_bw\": {\n    62→\t\t\t\t\t\tFrequency: 60,\n    63→\t\t\t\t\t\tStart:     1000,\n    64→\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n    65→\t\t\t\t\t},\n    66→\t\t\t\t},\n    67→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n    68→\t\t\t},\n    69→\t\t},\n    70→\t}\n    71→\n    72→\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n    73→\n    74→\t// cpu_load: 2 non-NaN values at node scope\n    75→\t// mem_bw: 2 non-NaN values at socket0 scope\n    76→\tif len(rows) != 4 {\n    77→\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n    78→\t}\n    79→\n    80→\t// Verify a node-scope row\n    81→\tfound := false\n    82→\tfor _, r := range rows {\n    83→\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n    84→\t\t\tfound = true\n    85→\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n    86→\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\tif !found {\n    91→\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n    92→\t}\n    93→\n    94→\t// Verify a socket-scope row\n    95→\tfound = false\n    96→\tfor _, r := range rows {\n    97→\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n    98→\t\t\tfound = true\n    99→\t\t}\n   100→\t}"}]},"uuid":"006ccb9d-700f-450a-bf59-9cad994307be","timestamp":"2026-03-18T04:02:45.793Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"e381436a-7b60-4aae-9090-e89ce5d7ccc4","timestamp":"2026-03-18T04:02:45.794Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"e381436a-7b60-4aae-9090-e89ce5d7ccc4","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","toolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","timestamp":"2026-03-18T04:03:01.631Z","uuid":"d5eaffb2-6268-4c4c-9d3a-8c6fb5d797bc","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"dd911687-ef19-4727-bc02-483d0b5ffab8","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","type":"tool_result","content":[{"type":"text","text":"Perfect! I now have a comprehensive understanding of all parquet writing code in the codebase. Let me compile my findings:\n\n## Comprehensive Report: All Parquet Writing Usage in CC-Backend\n\nBased on my thorough search, I found **3 major parquet writing code paths** with specific accumulation patterns:\n\n### 1. **Job Retention/Archiving via ParquetWriter** \n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 20-106)\n\n**Row Accumulation Pattern**:\n- `ParquetWriter` struct (line 22) accumulates `[]ParquetJobRow` in field `rows` (line 25)\n- `AddJob()` method (line 43) appends rows to the slice\n- When `currentSize + rowSize > maxSizeBytes` (line 46), `Flush()` is called\n- `Flush()` (line 58) calls `writeParquetBytes(pw.rows)` (line 66) which creates a `pq.NewGenericWriter[ParquetJobRow]` (line 89)\n\n**GenericWriter Usage** (line 89):\n```go\nwriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"sub_cluster\"),\n        pq.Ascending(\"project\"),\n        pq.Ascending(\"start_time\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` (lines 108-149)\n- `transferJobsParquet()` creates `pqarchive.NewClusterAwareParquetWriter()` (line 109)\n- Iterates jobs, converts to ParquetJobRow via `pqarchive.JobToParquetRow()` (line 137), calls `cw.AddJob()` (line 142)\n\n---\n\n### 2. **Cluster-Aware Job Retention via ClusterAwareParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 133-186)\n\n**Row Accumulation Pattern**:\n- `ClusterAwareParquetWriter` (line 135) maintains `writers map[string]*ParquetWriter` (line 138)\n- Each cluster gets its own `ParquetWriter` instance\n- `AddJob()` (line 158) routes to the appropriate cluster's writer\n- Same row accumulation and batching as ParquetWriter above\n\n**Called from**: \n- `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` lines 109, 260, 311\n  - `RegisterRetentionCopyService()` (line 232)\n  - `RegisterRetentionMoveService()` (line 285)\n\n---\n\n### 3. **Node State Retention via NodeStateParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go` (lines 17-111)\n\n**Row Accumulation Pattern**:\n- `NodeStateParquetWriter` struct (line 19) accumulates `[]ParquetNodeStateRow` in field `rows` (line 22)\n- `AddRow()` method (line 39) appends rows with size tracking\n- When `currentSize + rowSize > maxSizeBytes` (line 42), `Flush()` is called\n- `Flush()` (line 54) calls `writeNodeStateParquetBytes(pw.rows)` (line 62)\n\n**GenericWriter Usage** (line 85):\n```go\nwriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"cluster\"),\n        pq.Ascending(\"subcluster\"),\n        pq.Ascending(\"hostname\"),\n        pq.Ascending(\"time_stamp\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go` (lines 35-120)\n- `RegisterNodeStateRetentionMoveService()` (line 35)\n- Creates `pqarchive.NewNodeStateParquetWriter()` (line 86)\n- Finds old nodestate rows via `nodeRepo.FindNodeStatesBefore()` (line 76)\n- Iterates rows, creates `ParquetNodeStateRow` structs, calls `pw.AddRow()` (line 102)\n\n---\n\n### 4. **Metric Archive via parquetArchiveWriter (Checkpoint Streaming)**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go` (lines 95-160)\n\n**Row Accumulation Pattern**:\n- `parquetArchiveWriter` struct (line 98) uses `*pq.GenericWriter[ParquetMetricRow]` directly (line 99)\n- Does **NOT** accumulate rows in memory; instead writes incrementally via `WriteHostRows()` (line 127)\n- Each host's data is sorted by (metric, timestamp) then written as a separate row group\n\n**GenericWriter Creation** (line 118):\n```go\nwriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n    pq.Compression(&pq.Zstd),\n)\n```\n\n**Data Source**: \n- `archiveCheckpointsToParquet()` (line 236) pre-allocates row slice and flattens checkpoint files\n- `flattenCheckpointFile()` (line 38) recursively converts CheckpointFile tree to `[]ParquetMetricRow`\n- Pre-allocation estimate via `estimateRowCount()` (line 223)\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go` (lines 86-300)\n- `archiveCheckpoints()` (line 173) \n- Workers pool pattern processes per-host checkpoint directories\n- Each host's rows written via `writer.WriteHostRows()` (line 260) at line 260\n- Creates streaming archive from metrics checkpoints to Parquet files in format: `<cleanupDir>/<cluster>/<timestamp>.parquet`\n\n---\n\n### Summary of Row Accumulation Patterns:\n\n| Location | Row Type | Struct Field | Batching | Trigger |\n|----------|----------|--------------|----------|---------|\n| `pkg/archive/parquet/writer.go` | `ParquetJobRow` | `rows []ParquetJobRow` | Yes | Size > maxSizeBytes |\n| `pkg/archive/parquet/nodestate_writer.go` | `ParquetNodeStateRow` | `rows []ParquetNodeStateRow` | Yes | Size > maxSizeBytes |\n| `pkg/metricstore/parquetArchive.go` | `ParquetMetricRow` | Pre-allocated slice | No | Per-host row group |\n\n### Key Implementation Details:\n\n1. **Job/NodeState Writers** use batching to avoid OOM on large datasets\n2. **Metric Archive Writer** uses streaming row groups instead of full accumulation\n3. All use `pq.NewGenericWriter` with `pq.Compression(&pq.Zstd)` for compression\n4. Job and NodeState writers use `pq.SortingWriterConfig` for column ordering\n5. Row estimation via struct field size calculation before writing\n6. All integrate with parquet-go library's generic writer API"},{"type":"text","text":"agentId: a54ce42db3d7e6a75 (for resuming to continue this agent's work if needed)\n<usage>total_tokens: 51623\ntool_uses: 17\nduration_ms: 29238</usage>"}]}]},"uuid":"dea76866-f55f-45b0-87d1-b546550a70bd","timestamp":"2026-03-18T04:03:01.630Z","toolUseResult":{"status":"completed","prompt":"Search the codebase for ALL uses of parquet writing - any place that writes parquet files, accumulates rows into slices for parquet, or uses parquet-go's GenericWriter. Look specifically for:\n\n1. Any usage of `pq.NewGenericWriter`, `pq.GenericWriter`, `SortingWriterConfig`, or `writeParquetArchive`\n2. Any function that accumulates `[]ParquetMetricRow` or similar row slices\n3. Nodestate retention or archiving code that might write parquet\n4. Any other archiving/retention code paths\n\nSearch thoroughly - check pkg/, internal/, and any other directories. Report the exact file paths, line numbers, and the accumulation patterns you find.","agentId":"a54ce42db3d7e6a75","content":[{"type":"text","text":"Perfect! I now have a comprehensive understanding of all parquet writing code in the codebase. Let me compile my findings:\n\n## Comprehensive Report: All Parquet Writing Usage in CC-Backend\n\nBased on my thorough search, I found **3 major parquet writing code paths** with specific accumulation patterns:\n\n### 1. **Job Retention/Archiving via ParquetWriter** \n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 20-106)\n\n**Row Accumulation Pattern**:\n- `ParquetWriter` struct (line 22) accumulates `[]ParquetJobRow` in field `rows` (line 25)\n- `AddJob()` method (line 43) appends rows to the slice\n- When `currentSize + rowSize > maxSizeBytes` (line 46), `Flush()` is called\n- `Flush()` (line 58) calls `writeParquetBytes(pw.rows)` (line 66) which creates a `pq.NewGenericWriter[ParquetJobRow]` (line 89)\n\n**GenericWriter Usage** (line 89):\n```go\nwriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"sub_cluster\"),\n        pq.Ascending(\"project\"),\n        pq.Ascending(\"start_time\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` (lines 108-149)\n- `transferJobsParquet()` creates `pqarchive.NewClusterAwareParquetWriter()` (line 109)\n- Iterates jobs, converts to ParquetJobRow via `pqarchive.JobToParquetRow()` (line 137), calls `cw.AddJob()` (line 142)\n\n---\n\n### 2. **Cluster-Aware Job Retention via ClusterAwareParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 133-186)\n\n**Row Accumulation Pattern**:\n- `ClusterAwareParquetWriter` (line 135) maintains `writers map[string]*ParquetWriter` (line 138)\n- Each cluster gets its own `ParquetWriter` instance\n- `AddJob()` (line 158) routes to the appropriate cluster's writer\n- Same row accumulation and batching as ParquetWriter above\n\n**Called from**: \n- `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` lines 109, 260, 311\n  - `RegisterRetentionCopyService()` (line 232)\n  - `RegisterRetentionMoveService()` (line 285)\n\n---\n\n### 3. **Node State Retention via NodeStateParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go` (lines 17-111)\n\n**Row Accumulation Pattern**:\n- `NodeStateParquetWriter` struct (line 19) accumulates `[]ParquetNodeStateRow` in field `rows` (line 22)\n- `AddRow()` method (line 39) appends rows with size tracking\n- When `currentSize + rowSize > maxSizeBytes` (line 42), `Flush()` is called\n- `Flush()` (line 54) calls `writeNodeStateParquetBytes(pw.rows)` (line 62)\n\n**GenericWriter Usage** (line 85):\n```go\nwriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"cluster\"),\n        pq.Ascending(\"subcluster\"),\n        pq.Ascending(\"hostname\"),\n        pq.Ascending(\"time_stamp\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go` (lines 35-120)\n- `RegisterNodeStateRetentionMoveService()` (line 35)\n- Creates `pqarchive.NewNodeStateParquetWriter()` (line 86)\n- Finds old nodestate rows via `nodeRepo.FindNodeStatesBefore()` (line 76)\n- Iterates rows, creates `ParquetNodeStateRow` structs, calls `pw.AddRow()` (line 102)\n\n---\n\n### 4. **Metric Archive via parquetArchiveWriter (Checkpoint Streaming)**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go` (lines 95-160)\n\n**Row Accumulation Pattern**:\n- `parquetArchiveWriter` struct (line 98) uses `*pq.GenericWriter[ParquetMetricRow]` directly (line 99)\n- Does **NOT** accumulate rows in memory; instead writes incrementally via `WriteHostRows()` (line 127)\n- Each host's data is sorted by (metric, timestamp) then written as a separate row group\n\n**GenericWriter Creation** (line 118):\n```go\nwriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n    pq.Compression(&pq.Zstd),\n)\n```\n\n**Data Source**: \n- `archiveCheckpointsToParquet()` (line 236) pre-allocates row slice and flattens checkpoint files\n- `flattenCheckpointFile()` (line 38) recursively converts CheckpointFile tree to `[]ParquetMetricRow`\n- Pre-allocation estimate via `estimateRowCount()` (line 223)\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go` (lines 86-300)\n- `archiveCheckpoints()` (line 173) \n- Workers pool pattern processes per-host checkpoint directories\n- Each host's rows written via `writer.WriteHostRows()` (line 260) at line 260\n- Creates streaming archive from metrics checkpoints to Parquet files in format: `<cleanupDir>/<cluster>/<timestamp>.parquet`\n\n---\n\n### Summary of Row Accumulation Patterns:\n\n| Location | Row Type | Struct Field | Batching | Trigger |\n|----------|----------|--------------|----------|---------|\n| `pkg/archive/parquet/writer.go` | `ParquetJobRow` | `rows []ParquetJobRow` | Yes | Size > maxSizeBytes |\n| `pkg/archive/parquet/nodestate_writer.go` | `ParquetNodeStateRow` | `rows []ParquetNodeStateRow` | Yes | Size > maxSizeBytes |\n| `pkg/metricstore/parquetArchive.go` | `ParquetMetricRow` | Pre-allocated slice | No | Per-host row group |\n\n### Key Implementation Details:\n\n1. **Job/NodeState Writers** use batching to avoid OOM on large datasets\n2. **Metric Archive Writer** uses streaming row groups instead of full accumulation\n3. All use `pq.NewGenericWriter` with `pq.Compression(&pq.Zstd)` for compression\n4. Job and NodeState writers use `pq.SortingWriterConfig` for column ordering\n5. Row estimation via struct field size calculation before writing\n6. All integrate with parquet-go library's generic writer API"}],"totalDurationMs":29238,"totalTokens":51623,"totalToolUseCount":17,"usage":{"input_tokens":6,"cache_creation_input_tokens":6652,"cache_read_input_tokens":43056,"output_tokens":1909,"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":6652},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"dd911687-ef19-4727-bc02-483d0b5ffab8","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"6ef33ff4-6796-4ef0-b60a-8faf052d22c6","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011Fh6gGsv7PiP7UZ5Fzn1HF","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\"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":"8ba2bd53-1ba2-49e6-a0fb-f32b047d809b","timestamp":"2026-03-18T04:03:08.711Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.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 parquet\n\nimport (\n\t\"bytes\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"path\"\n\t\"time\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\n// ParquetWriter batches ParquetJobRows and flushes them to a target\n// when the estimated size exceeds maxSizeBytes.\ntype ParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeBytes int64\n\trows         []ParquetJobRow\n\tcurrentSize  int64\n\tfileCounter  int\n\tdatePrefix   string\n}\n\n// NewParquetWriter creates a new writer that flushes batches to the given target.\n// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\nfunc NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n\treturn &ParquetWriter{\n\t\ttarget:       target,\n\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n\t}\n}\n\n// AddJob adds a row to the current batch. If the estimated batch size\n// exceeds the configured maximum, the batch is flushed to the target first.\nfunc (pw *ParquetWriter) AddJob(row ParquetJobRow) error {\n\trowSize := estimateRowSize(&row)\n\n\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n\t\tif err := pw.Flush(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tpw.rows = append(pw.rows, row)\n\tpw.currentSize += rowSize\n\treturn nil\n}\n\n// Flush writes the current batch to a parquet file on the target.\nfunc (pw *ParquetWriter) Flush() error {\n\tif len(pw.rows) == 0 {\n\t\treturn nil\n\t}\n\n\tpw.fileCounter++\n\tfileName := fmt.Sprintf(\"cc-archive-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n\n\tdata, err := writeParquetBytes(pw.rows)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n\t}\n\n\tif err := pw.target.WriteFile(fileName, data); err != nil {\n\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n\t}\n\n\tcclog.Infof(\"Parquet retention: wrote %s (%d jobs, %d bytes)\", fileName, len(pw.rows), len(data))\n\tpw.rows = pw.rows[:0]\n\tpw.currentSize = 0\n\treturn nil\n}\n\n// Close flushes any remaining rows and finalizes the writer.\nfunc (pw *ParquetWriter) Close() error {\n\treturn pw.Flush()\n}\n\nfunc writeParquetBytes(rows []ParquetJobRow) ([]byte, error) {\n\tvar buf bytes.Buffer\n\n\twriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n\t\tpq.Compression(&pq.Zstd),\n\t\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"sub_cluster\"),\n\t\t\tpq.Ascending(\"project\"),\n\t\t\tpq.Ascending(\"start_time\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn nil, err\n\t}\n\tif err := writer.Close(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn buf.Bytes(), nil\n}\n\nfunc estimateRowSize(row *ParquetJobRow) int64 {\n\t// Fixed fields: ~100 bytes for numeric fields + strings estimate\n\tsize := int64(200)\n\tsize += int64(len(row.Cluster) + len(row.SubCluster) + len(row.Partition) +\n\t\tlen(row.Project) + len(row.User) + len(row.State))\n\tsize += int64(len(row.ResourcesJSON))\n\tsize += int64(len(row.StatisticsJSON))\n\tsize += int64(len(row.TagsJSON))\n\tsize += int64(len(row.MetaDataJSON))\n\tsize += int64(len(row.FootprintJSON))\n\tsize += int64(len(row.EnergyFootJSON))\n\tsize += int64(len(row.MetricDataGz))\n\treturn size\n}\n\n// prefixedTarget wraps a ParquetTarget and prepends a path prefix to all file names.\ntype prefixedTarget struct {\n\tinner  ParquetTarget\n\tprefix string\n}\n\nfunc (pt *prefixedTarget) WriteFile(name string, data []byte) error {\n\treturn pt.inner.WriteFile(path.Join(pt.prefix, name), data)\n}\n\n// ClusterAwareParquetWriter organizes Parquet output by cluster.\n// Each cluster gets its own subdirectory with a cluster.json config file.\ntype ClusterAwareParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeMB    int\n\twriters      map[string]*ParquetWriter\n\tclusterCfgs  map[string]*schema.Cluster\n}\n\n// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\nfunc NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n\treturn &ClusterAwareParquetWriter{\n\t\ttarget:      target,\n\t\tmaxSizeMB:   maxSizeMB,\n\t\twriters:     make(map[string]*ParquetWriter),\n\t\tclusterCfgs: make(map[string]*schema.Cluster),\n\t}\n}\n\n// SetClusterConfig stores a cluster configuration to be written as cluster.json on Close.\nfunc (cw *ClusterAwareParquetWriter) SetClusterConfig(name string, cfg *schema.Cluster) {\n\tcw.clusterCfgs[name] = cfg\n}\n\n// AddJob routes the job row to the appropriate per-cluster writer.\nfunc (cw *ClusterAwareParquetWriter) AddJob(row ParquetJobRow) error {\n\tcluster := row.Cluster\n\tpw, ok := cw.writers[cluster]\n\tif !ok {\n\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n\t\tcw.writers[cluster] = pw\n\t}\n\treturn pw.AddJob(row)\n}\n\n// Close writes cluster.json files and flushes all per-cluster writers.\nfunc (cw *ClusterAwareParquetWriter) Close() error {\n\tfor name, cfg := range cw.clusterCfgs {\n\t\tdata, err := json.MarshalIndent(cfg, \"\", \"  \")\n\t\tif err != nil {\n\t\t\treturn fmt.Errorf(\"marshal cluster config %q: %w\", name, err)\n\t\t}\n\t\tif err := cw.target.WriteFile(path.Join(name, \"cluster.json\"), data); err != nil {\n\t\t\treturn fmt.Errorf(\"write cluster.json for %q: %w\", name, err)\n\t\t}\n\t}\n\n\tfor cluster, pw := range cw.writers {\n\t\tif err := pw.Close(); err != nil {\n\t\t\treturn fmt.Errorf(\"close writer for cluster %q: %w\", cluster, err)\n\t\t}\n\t}\n\treturn nil\n}\n","numLines":187,"startLine":1,"totalLines":187}},"sourceToolAssistantUUID":"6ef33ff4-6796-4ef0-b60a-8faf052d22c6","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"8ba2bd53-1ba2-49e6-a0fb-f32b047d809b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01Q99KAA21mZfprWFnPEyThq","toolUseID":"toolu_01Q99KAA21mZfprWFnPEyThq","timestamp":"2026-03-18T04:03:08.713Z","uuid":"8a41feef-932a-4fc3-b346-f93343dea5ec","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"7654bc76-22fd-40c9-80f1-2ca9c5f25c80","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Q99KAA21mZfprWFnPEyThq","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":"8659aa34-8044-491f-8e19-4b28746ae9dc","timestamp":"2026-03-18T04:03:08.713Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.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 parquet\n\nimport (\n\t\"bytes\"\n\t\"fmt\"\n\t\"time\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\n// NodeStateParquetWriter batches ParquetNodeStateRows and flushes them to a target\n// when the estimated size exceeds maxSizeBytes.\ntype NodeStateParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeBytes int64\n\trows         []ParquetNodeStateRow\n\tcurrentSize  int64\n\tfileCounter  int\n\tdatePrefix   string\n}\n\n// NewNodeStateParquetWriter creates a new writer for node state parquet files.\nfunc NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n\treturn &NodeStateParquetWriter{\n\t\ttarget:       target,\n\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n\t}\n}\n\n// AddRow adds a row to the current batch. If the estimated batch size\n// exceeds the configured maximum, the batch is flushed first.\nfunc (pw *NodeStateParquetWriter) AddRow(row ParquetNodeStateRow) error {\n\trowSize := estimateNodeStateRowSize(&row)\n\n\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n\t\tif err := pw.Flush(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tpw.rows = append(pw.rows, row)\n\tpw.currentSize += rowSize\n\treturn nil\n}\n\n// Flush writes the current batch to a parquet file on the target.\nfunc (pw *NodeStateParquetWriter) Flush() error {\n\tif len(pw.rows) == 0 {\n\t\treturn nil\n\t}\n\n\tpw.fileCounter++\n\tfileName := fmt.Sprintf(\"cc-nodestate-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n\n\tdata, err := writeNodeStateParquetBytes(pw.rows)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n\t}\n\n\tif err := pw.target.WriteFile(fileName, data); err != nil {\n\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n\t}\n\n\tcclog.Infof(\"NodeState retention: wrote %s (%d rows, %d bytes)\", fileName, len(pw.rows), len(data))\n\tpw.rows = pw.rows[:0]\n\tpw.currentSize = 0\n\treturn nil\n}\n\n// Close flushes any remaining rows and finalizes the writer.\nfunc (pw *NodeStateParquetWriter) Close() error {\n\treturn pw.Flush()\n}\n\nfunc writeNodeStateParquetBytes(rows []ParquetNodeStateRow) ([]byte, error) {\n\tvar buf bytes.Buffer\n\n\twriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n\t\tpq.Compression(&pq.Zstd),\n\t\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"subcluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"time_stamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn nil, err\n\t}\n\tif err := writer.Close(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn buf.Bytes(), nil\n}\n\nfunc estimateNodeStateRowSize(row *ParquetNodeStateRow) int64 {\n\tsize := int64(100) // fixed numeric fields\n\tsize += int64(len(row.NodeState) + len(row.HealthState) + len(row.HealthMetrics))\n\tsize += int64(len(row.Hostname) + len(row.Cluster) + len(row.SubCluster))\n\treturn size\n}\n","numLines":111,"startLine":1,"totalLines":111}},"sourceToolAssistantUUID":"7654bc76-22fd-40c9-80f1-2ca9c5f25c80","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"faff2a5f-39cf-41be-86c5-6881ede8648f","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_019UTA1PjoxLMwNcZgvy9yF8","type":"message","role":"assistant","content":[{"type":"text","text":"Let me check the default `maxSizeMB` values and the row schemas to assess the severity."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4503,"cache_read_input_tokens":42858,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4503},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ9t59U86JZXpoB3ce9Bp","type":"assistant","uuid":"c09f2346-0454-4886-992d-9909d6ad37cb","timestamp":"2026-03-18T04:03:22.128Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"d3ad8e22-3b2e-4bec-8879-dc19d4acfa97","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XqChKEwwhYbMpP5zPDcwMG","type":"tool_result","content":"/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-424-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-425-// convertJSONToParquet converts a JSON archive backend to parquet format.\ntools/archive-manager/main.go:426:func convertJSONToParquet(srcBackend archive.ArchiveBackend, dstCfg sourceConfig, maxSizeMB int) error {\ntools/archive-manager/main.go-427-\ttarget, err := createParquetTarget(dstCfg)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-428-\tif err != nil {\n--\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-430-\t}\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-431-\ntools/archive-manager/main.go:432:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-433-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-434-\t// Transfer cluster configs\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-30-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-31-// NewParquetWriter creates a new writer that flushes batches to the given target.\npkg/archive/parquet/writer.go:32:// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\npkg/archive/parquet/writer.go:33:func NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-34-\treturn &ParquetWriter{\npkg/archive/parquet/writer.go-35-\t\ttarget:       target,\npkg/archive/parquet/writer.go:36:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/writer.go-37-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-38-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-135-type ClusterAwareParquetWriter struct {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-136-\ttarget       ParquetTarget\npkg/archive/parquet/writer.go:137:\tmaxSizeMB    int\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-138-\twriters      map[string]*ParquetWriter\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-139-\tclusterCfgs  map[string]*schema.Cluster\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-141-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-142-// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\npkg/archive/parquet/writer.go:143:func NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-144-\treturn &ClusterAwareParquetWriter{\npkg/archive/parquet/writer.go-145-\t\ttarget:      target,\npkg/archive/parquet/writer.go:146:\t\tmaxSizeMB:   maxSizeMB,\npkg/archive/parquet/writer.go-147-\t\twriters:     make(map[string]*ParquetWriter),\npkg/archive/parquet/writer.go-148-\t\tclusterCfgs: make(map[string]*schema.Cluster),\n--\npkg/archive/parquet/writer.go-160-\tpw, ok := cw.writers[cluster]\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-161-\tif !ok {\npkg/archive/parquet/writer.go:162:\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-163-\t\tcw.writers[cluster] = pw\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-164-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-27-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-28-// NewNodeStateParquetWriter creates a new writer for node state parquet files.\npkg/archive/parquet/nodestate_writer.go:29:func NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-30-\treturn &NodeStateParquetWriter{\npkg/archive/parquet/nodestate_writer.go-31-\t\ttarget:       target,\npkg/archive/parquet/nodestate_writer.go:32:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/nodestate_writer.go-33-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-34-\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-106-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-107-// transferJobsParquet converts jobs to Parquet format, organized by cluster.\ninternal/taskmanager/retentionService.go:108:func transferJobsParquet(jobs []*schema.Job, src archive.ArchiveBackend, target pqarchive.ParquetTarget, maxSizeMB int) error {\ninternal/taskmanager/retentionService.go:109:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-110-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-111-\t// Set cluster configs for all clusters referenced by jobs"}]},"uuid":"28d33adb-22ad-4be4-bbaf-c470ef67fa84","timestamp":"2026-03-18T04:03:23.582Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-424-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-425-// convertJSONToParquet converts a JSON archive backend to parquet format.\ntools/archive-manager/main.go:426:func convertJSONToParquet(srcBackend archive.ArchiveBackend, dstCfg sourceConfig, maxSizeMB int) error {\ntools/archive-manager/main.go-427-\ttarget, err := createParquetTarget(dstCfg)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-428-\tif err != nil {\n--\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-430-\t}\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-431-\ntools/archive-manager/main.go:432:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-433-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-434-\t// Transfer cluster configs\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-30-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-31-// NewParquetWriter creates a new writer that flushes batches to the given target.\npkg/archive/parquet/writer.go:32:// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\npkg/archive/parquet/writer.go:33:func NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-34-\treturn &ParquetWriter{\npkg/archive/parquet/writer.go-35-\t\ttarget:       target,\npkg/archive/parquet/writer.go:36:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/writer.go-37-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-38-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-135-type ClusterAwareParquetWriter struct {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-136-\ttarget       ParquetTarget\npkg/archive/parquet/writer.go:137:\tmaxSizeMB    int\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-138-\twriters      map[string]*ParquetWriter\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-139-\tclusterCfgs  map[string]*schema.Cluster\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-141-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-142-// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\npkg/archive/parquet/writer.go:143:func NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-144-\treturn &ClusterAwareParquetWriter{\npkg/archive/parquet/writer.go-145-\t\ttarget:      target,\npkg/archive/parquet/writer.go:146:\t\tmaxSizeMB:   maxSizeMB,\npkg/archive/parquet/writer.go-147-\t\twriters:     make(map[string]*ParquetWriter),\npkg/archive/parquet/writer.go-148-\t\tclusterCfgs: make(map[string]*schema.Cluster),\n--\npkg/archive/parquet/writer.go-160-\tpw, ok := cw.writers[cluster]\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-161-\tif !ok {\npkg/archive/parquet/writer.go:162:\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-163-\t\tcw.writers[cluster] = pw\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-164-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-27-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-28-// NewNodeStateParquetWriter creates a new writer for node state parquet files.\npkg/archive/parquet/nodestate_writer.go:29:func NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-30-\treturn &NodeStateParquetWriter{\npkg/archive/parquet/nodestate_writer.go-31-\t\ttarget:       target,\npkg/archive/parquet/nodestate_writer.go:32:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/nodestate_writer.go-33-\t\tdatePrefix:   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`parquet:\"tags_json,optional\"`\npkg/archive/parquet/schema.go-28-\tMetaDataJSON   []byte  `parquet:\"meta_data_json,optional\"`\npkg/archive/parquet/schema.go-29-\tFootprintJSON  []byte  `parquet:\"footprint_json,optional\"`\npkg/archive/parquet/schema.go-30-\tEnergyFootJSON []byte  `parquet:\"energy_footprint_json,optional\"`\npkg/archive/parquet/schema.go-31-\tMetricDataGz   []byte  `parquet:\"metric_data_gz\"`\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/schema.go-32-}\n--\npkg/archive/parquet/nodestate_schema.go:8:type ParquetNodeStateRow struct {\npkg/archive/parquet/nodestate_schema.go-9-\tTimeStamp       int64  `parquet:\"time_stamp\"`\npkg/archive/parquet/nodestate_schema.go-10-\tNodeState       string `parquet:\"node_state\"`\npkg/archive/parquet/nodestate_schema.go-11-\tHealthState     string `parquet:\"health_state\"`\npkg/archive/parquet/nodestate_schema.go-12-\tHealthMetrics   string `parquet:\"health_metrics,optional\"`\npkg/archive/parquet/nodestate_schema.go-13-\tCpusAllocated   int32  `parquet:\"cpus_allocated\"`\npkg/archive/parquet/nodestate_schema.go-14-\tMemoryAllocated int64  `parquet:\"memory_allocated\"`\npkg/archive/parquet/nodestate_schema.go-15-\tGpusAllocated   int32  `parquet:\"gpus_allocated\"`\npkg/archive/parquet/nodestate_schema.go-16-\tJobsRunning     int32  `parquet:\"jobs_running\"`\npkg/archive/parquet/nodestate_schema.go-17-\tHostname        string `parquet:\"hostname\"`\npkg/archive/parquet/nodestate_schema.go-18-\tCluster         string `parquet:\"cluster\"`\npkg/archive/parquet/nodestate_schema.go-19-\tSubCluster      string `parquet:\"subcluster\"`\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_schema.go-20-}"}]},"uuid":"6ea7820f-c174-412f-8fa6-257028300636","timestamp":"2026-03-18T04:03:24.062Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"pkg/archive/parquet/schema.go:8:type ParquetJobRow struct {\npkg/archive/parquet/schema.go-9-\tJobID          int64   `parquet:\"job_id\"`\npkg/archive/parquet/schema.go-10-\tCluster        string  `parquet:\"cluster\"`\npkg/archive/parquet/schema.go-11-\tSubCluster     string  `parquet:\"sub_cluster\"`\npkg/archive/parquet/schema.go-12-\tPartition      string  `parquet:\"partition,optional\"`\npkg/archive/parquet/schema.go-13-\tProject        string  `parquet:\"project\"`\npkg/archive/parquet/schema.go-14-\tUser           string  `parquet:\"user\"`\npkg/archive/parquet/schema.go-15-\tState          string  `parquet:\"job_state\"`\npkg/archive/parquet/schema.go-16-\tStartTime      int64   `parquet:\"start_time\"`\npkg/archive/parquet/schema.go-17-\tDuration       int32   `parquet:\"duration\"`\npkg/archive/parquet/schema.go-18-\tWalltime       int64   `parquet:\"walltime\"`\npkg/archive/parquet/schema.go-19-\tNumNodes       int32   `parquet:\"num_nodes\"`\npkg/archive/parquet/schema.go-20-\tNumHWThreads   int32   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err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{"}]},"uuid":"e26a1aa7-04b9-40bf-ab8c-6d61bb74bd47","timestamp":"2026-03-18T04:03:28.636Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-104-\treturn nil\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-105-}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-106-\ninternal/taskmanager/retentionService.go:107:// transferJobsParquet converts jobs to Parquet format, organized by cluster.\ninternal/taskmanager/retentionService.go:108:func transferJobsParquet(jobs []*schema.Job, src archive.ArchiveBackend, target pqarchive.ParquetTarget, maxSizeMB int) error {\ninternal/taskmanager/retentionService.go:109:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-110-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-111-\t// Set cluster configs for all clusters referenced by jobs\ninternal/taskmanager/retentionService.go-112-\tclustersDone := make(map[string]bool)\n--\ninternal/taskmanager/retentionService.go-262-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-263-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-264-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:265:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{","numLines":33},"sourceToolAssistantUUID":"474b99b3-f593-4755-b27a-b8e4dd79d876","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-285-func RegisterRetentionMoveService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-286-\tcclog.Infof(\"Register retention move service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-287-\ninternal/taskmanager/retentionService.go:288:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:289:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:290:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-291-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-292-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-293-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(5, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-35-func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-36-\tcclog.Info(\"Register node state retention move service\")\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-37-\ninternal/taskmanager/nodestateRetentionService.go:38:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/nodestateRetentionService.go:39:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/nodestateRetentionService.go:40:\t\tmaxFileSizeMB = 128\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-41-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-42-\ninternal/taskmanager/nodestateRetentionService.go-43-\tageHours := cfg.Age\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{"}]},"uuid":"392fddf0-3e00-4ec8-abb9-b655845479a1","timestamp":"2026-03-18T04:03:41.650Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-232-func RegisterRetentionCopyService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-233-\tcclog.Infof(\"Register retention copy service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-234-\ninternal/taskmanager/retentionService.go:235:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:236:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:237:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-238-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-239-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-240-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(4, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-262-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-263-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-264-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:265:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-285-func RegisterRetentionMoveService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-286-\tcclog.Infof(\"Register retention move service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-287-\ninternal/taskmanager/retentionService.go:288:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:289:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:290:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-291-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-292-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-293-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(5, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-35-func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-36-\tcclog.Info(\"Register node state retention move service\")\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-37-\ninternal/taskmanager/nodestateRetentionService.go:38:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/nodestateRetentionService.go:39:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/nodestateRetentionService.go:40:\t\tmaxFileSizeMB = 128\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-41-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-42-\ninternal/taskmanager/nodestateRetentionService.go-43-\tageHours := cfg.Age\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{","numLines":53},"sourceToolAssistantUUID":"3c6b8884-7d9f-4116-803f-8edf5fb39fe7","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"0e523105-a262-4da4-8ce0-de57188c6867","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RkUewSYmhcoRrM7YPKM3gb","type":"tool_result","content":"     1→# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n     2→\n     3→## Context\n     4→\n     5→Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n     6→\n     7→## Root Cause\n     8→\n     9→Two-layer unbounded accumulation:\n    10→\n    11→1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n    12→2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n    13→3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n    14→\n    15→Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n    16→\n    17→## Fix: Stream per-host to parquet writer\n    18→\n    19→Instead of accumulating all rows, write each host's data as a separate row group.\n    20→\n    21→### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n    22→\n    23→Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n    24→\n    25→```go\n    26→type parquetArchiveWriter struct {\n    27→    writer *pq.GenericWriter[ParquetMetricRow]\n    28→    bw     *bufio.Writer\n    29→    f      *os.File\n    30→    count  int\n    31→}\n    32→\n    33→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\n    34→func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\n    35→func (w *parquetArchiveWriter) Close() error\n    36→```\n    37→\n    38→- **Remove `SortingWriterConfig`** - no global sort buffer\n    39→- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n    40→- Each `Flush()` creates a separate row group per host\n    41→\n    42→### Step 2: Add row count estimation (`parquetArchive.go`)\n    43→\n    44→```go\n    45→func estimateRowCount(cf *CheckpointFile) int\n    46→```\n    47→\n    48→Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n    49→\n    50→### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n    51→\n    52→Change from:\n    53→```\n    54→workers → channel → accumulate allRows → writeParquetArchive(allRows)\n    55→```\n    56→\n    57→To:\n    58→```\n    59→open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n    60→```\n    61→\n    62→- Only one host's rows in memory at a time\n    63→- Track `files`/`dir` for deletion separately (don't retain rows)\n    64→- Check `writer.count > 0` instead of `len(allRows) == 0`\n    65→\n    66→### Step 4: Update test (`parquetArchive_test.go`)\n    67→\n    68→- `TestParquetArchiveRoundtrip`: use new streaming writer API\n    69→- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n    70→\n    71→## Files to Modify\n    72→\n    73→- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n    74→- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n    75→- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n    76→\n    77→## Memory Impact\n    78→\n    79→- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n    80→- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n    81→\n    82→## Sorting Tradeoff\n    83→\n    84→The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n    85→\n    86→## Verification\n    87→\n    88→```bash\n    89→go test -v ./pkg/metricstore/...\n    90→```\n    91→\n    92→Also verify with `go vet ./pkg/metricstore/...` for correctness.\n    93→"}]},"uuid":"820ca3ba-c7a2-4bca-9937-7389eb28a4f0","timestamp":"2026-03-18T04:03:47.129Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n","numLines":93,"startLine":1,"totalLines":93}},"sourceToolAssistantUUID":"0e523105-a262-4da4-8ce0-de57188c6867","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"820ca3ba-c7a2-4bca-9937-7389eb28a4f0","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EwL47Q2XdLejr1ZgqEBUk4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GedVGpbmUyDDQ8S3jAgoTM","name":"Write","input":{"file_path":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1490,"cache_read_input_tokens":54617,"output_tokens":944,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1490,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ9t7yLFg4b2Cfjvg1ZDm","type":"assistant","uuid":"24b9150b-c58b-4643-90ee-51ca27affb84","timestamp":"2026-03-18T04:04:09.115Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"24b9150b-c58b-4643-90ee-51ca27affb84","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GedVGpbmUyDDQ8S3jAgoTM","type":"tool_result","content":"The file /Users/jan/.claude/plans/shimmering-wandering-flurry.md has been updated successfully."}]},"uuid":"33a3d7d3-f247-4792-bbe0-48205fa9d6b8","timestamp":"2026-03-18T04:04:09.128Z","toolUseResult":{"type":"update","filePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n","structuredPatch":[{"oldStart":1,"oldLines":92,"newStart":1,"newLines":60,"lines":["-# Fix: Memory Escalation in flattenCheckpointFile (68GB+)","+# Audit: SortingWriterConfig Memory Doubling in Parquet Writers"," "," ## Context"," ","-Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.","+After fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch."," ","-## Root Cause","+## Findings"," ","-Two-layer unbounded accumulation:","+### 1. Job Retention Writer — moderate risk","+**File**: `pkg/archive/parquet/writer.go:86-106`"," ","-1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice","-2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`","-3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling","+`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:","+- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**","+- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy"," ","-Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.","+The sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data."," ","-## Fix: Stream per-host to parquet writer","+**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy."," ","-Instead of accumulating all rows, write each host's data as a separate row group.","+### 2. NodeState Retention Writer — low risk","+**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`"," ","-### Step 1: Add streaming parquet writer (`parquetArchive.go`)","+Same pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful."," ","-Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:","+**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`."," ","-```go","-type parquetArchiveWriter struct {","-    writer *pq.GenericWriter[ParquetMetricRow]","-    bw     *bufio.Writer","-    f      *os.File","-    count  int","-}","+### 3. Metric Checkpoint Writer — already fixed","+**File**: `pkg/metricstore/parquetArchive.go`"," ","-func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)","-func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)","-func (w *parquetArchiveWriter) Close() error","-```","+Already addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`."," ","-- **Remove `SortingWriterConfig`** - no global sort buffer","-- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)","-- Each `Flush()` creates a separate row group per host","+## Recommendation"," ","-### Step 2: Add row count estimation (`parquetArchive.go`)","+Apply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change."," ","-```go","-func estimateRowCount(cf *CheckpointFile) int","-```","+### Changes"," ","-Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.","+#### `pkg/archive/parquet/writer.go`","+- Add `\"sort\"` import","+- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`","+- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options"," ","-### Step 3: Restructure `archiveCheckpoints` (`archive.go`)","+#### `pkg/archive/parquet/nodestate_writer.go`","+- Add `\"sort\"` import","+- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`","+- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options"," ","-Change from:","-```","-workers → channel → accumulate allRows → writeParquetArchive(allRows)","-```","+### Memory Impact"," ","-To:","-```","-open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer","-```","+| Writer | Before (peak per flush) | After |","+|--------|------------------------|-------|","+| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |","+| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |"," ","-- Only one host's rows in memory at a time","-- Track `files`/`dir` for deletion separately (don't retain rows)","-- Check `writer.count > 0` instead of `len(allRows) == 0`","+### Verification"," ","-### Step 4: Update test (`parquetArchive_test.go`)","-","-- `TestParquetArchiveRoundtrip`: use new streaming writer API","-- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)","-","-## Files to Modify","-","-- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import","-- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream","-- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test","-","-## Memory Impact","-","-- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+","-- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak","-","-## Sorting Tradeoff","-","-The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).","-","-## Verification","-"," ```bash","-go test -v ./pkg/metricstore/...","+go test -v ./pkg/archive/parquet/...","+go vet ./pkg/archive/parquet/..."," ```","-","-Also verify with `go vet ./pkg/metricstore/...` for correctness."]}],"originalFile":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n"},"sourceToolAssistantUUID":"24b9150b-c58b-4643-90ee-51ca27affb84","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c87cbba4-6bc3-44a3-b0f3-9a25b8f157c3","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01MB8m76U37bTSZvZgNRPPFn","content":[{"type":"tool_reference","tool_name":"ExitPlanMode"}]}]},"uuid":"e511676b-038b-47e4-add3-f205f7f18fe1","timestamp":"2026-03-18T04:04:14.429Z","toolUseResult":{"matches":["ExitPlanMode"],"query":"select:ExitPlanMode","total_deferred_tools":21},"sourceToolAssistantUUID":"c87cbba4-6bc3-44a3-b0f3-9a25b8f157c3","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"e511676b-038b-47e4-add3-f205f7f18fe1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01QxS4Nm7MmwEvvjrAR3tMPq","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nHere's what I found:\n\n**Two other writers use `SortingWriterConfig`**, which doubles memory per batch:\n\n1. **Job retention** (`pkg/archive/parquet/writer.go:89-96`) — batched at 512MB default, but `SortingWriterConfig` doubles it to ~1GB peak per flush. `ParquetJobRow` includes `MetricDataGz []byte` which makes rows heavy.\n\n2. **NodeState retention** (`pkg/archive/parquet/nodestate_writer.go:85-93`) — batched at 128MB default, doubling to ~256MB. Rows are small (~150 bytes), so this is low risk but still wasteful.\n\nNeither is catastrophic like the checkpoint case (which had NO batching at all), because `maxSizeBytes` caps each batch. But the `SortingWriterConfig` still unnecessarily copies all batch rows internally.\n\nThe fix is the same pattern we already used: **pre-sort rows in-place with `sort.Slice`, remove `SortingWriterConfig`**. This halves peak memory per flush with identical output."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1817,"cache_read_input_tokens":56107,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1817},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ9t9z9vXZht2ydikKnox","type":"assistant","uuid":"671c15f1-a9c4-4c55-80b3-6452574319f3","timestamp":"2026-03-18T04:04:25.108Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"671c15f1-a9c4-4c55-80b3-6452574319f3","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01QxS4Nm7MmwEvvjrAR3tMPq","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SKhtziAY4y9pfEEXT7v2BQ","name":"ExitPlanMode","input":{"allowedPrompts":[{"tool":"Bash","prompt":"run tests and vet for pkg/archive/parquet"}],"plan":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n","planFilePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1817,"cache_read_input_tokens":56107,"output_tokens":343,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1817,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ9t9z9vXZht2ydikKnox","type":"assistant","uuid":"268c6603-bcb3-4ff1-90c1-3b1ac1b66dba","timestamp":"2026-03-18T04:04:25.885Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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diff --git a/4a/675b8352a2/0/metadata.json b/4a/675b8352a2/0/metadata.json
new file mode 100644
index 00000000..25e1b80b
--- /dev/null
+++ b/4a/675b8352a2/0/metadata.json
@@ -0,0 +1,32 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "4a675b8352a2",
+  "session_id": "0943a044-b17e-4215-8591-c1a0c816ddf0",
+  "strategy": "manual-commit",
+  "created_at": "2026-03-18T04:08:45.361889Z",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "pkg/metricstore/archive.go",
+    "pkg/metricstore/parquetArchive.go",
+    "pkg/metricstore/parquetArchive_test.go"
+  ],
+  "agent": "Claude Code",
+  "turn_id": "90b76f55d190",
+  "token_usage": {
+    "input_tokens": 23,
+    "cache_creation_tokens": 84788,
+    "cache_read_tokens": 624841,
+    "output_tokens": 9466,
+    "api_call_count": 17
+  },
+  "initial_attribution": {
+    "calculated_at": "2026-03-18T04:08:45.27362Z",
+    "agent_lines": 139,
+    "human_added": 0,
+    "human_modified": 0,
+    "human_removed": 0,
+    "total_committed": 139,
+    "agent_percentage": 100
+  }
+}
diff --git a/4a/675b8352a2/0/prompt.txt b/4a/675b8352a2/0/prompt.txt
new file mode 100644
index 00000000..a76961c4
--- /dev/null
+++ b/4a/675b8352a2/0/prompt.txt
@@ -0,0 +1,105 @@
+Implement the following plan:
+
+# Fix: Memory Escalation in flattenCheckpointFile (68GB+)
+
+## Context
+
+Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.
+
+## Root Cause
+
+Two-layer unbounded accumulation:
+
+1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice
+2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`
+3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling
+
+Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.
+
+## Fix: Stream per-host to parquet writer
+
+Instead of accumulating all rows, write each host's data as a separate row group.
+
+### Step 1: Add streaming parquet writer (`parquetArchive.go`)
+
+Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:
+
+```go
+type parquetArchiveWriter struct {
+    writer *pq.GenericWriter[ParquetMetricRow]
+    bw     *bufio.Writer
+    f      *os.File
+    count  int
+}
+
+func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)
+func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)
+func (w *parquetArchiveWriter) Close() error
+```
+
+- **Remove `SortingWriterConfig`** - no global sort buffer
+- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)
+- Each `Flush()` creates a separate row group per host
+
+### Step 2: Add row count estimation (`parquetArchive.go`)
+
+```go
+func estimateRowCount(cf *CheckpointFile) int
+```
+
+Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.
+
+### Step 3: Restructure `archiveCheckpoints` (`archive.go`)
+
+Change from:
+```
+workers → channel → accumulate allRows → writeParquetArchive(allRows)
+```
+
+To:
+```
+open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer
+```
+
+- Only one host's rows in memory at a time
+- Track `files`/`dir` for deletion separately (don't retain rows)
+- Check `writer.count > 0` instead of `len(allRows) == 0`
+
+### Step 4: Update test (`parquetArchive_test.go`)
+
+- `TestParquetArchiveRoundtrip`: use new streaming writer API
+- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)
+
+## Files to Modify
+
+- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `"sort"` import
+- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream
+- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test
+
+## Memory Impact
+
+- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+
+- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak
+
+## Sorting Tradeoff
+
+The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).
+
+## Verification
+
+```bash
+go test -v ./pkg/metricstore/...
+```
+
+Also verify with `go vet ./pkg/metricstore/...` for correctness.
+
+
+If you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/71340843-de3d-4e83-9dcb-2fc130c50e0d.jsonl
+
+---
+
+Are the any other cases with memory spikes using the Parquet Writer, e.g. in the nodestate retention?
+
+---
+
+[Request interrupted by user for tool use]
\ No newline at end of file
diff --git a/4a/675b8352a2/metadata.json b/4a/675b8352a2/metadata.json
new file mode 100644
index 00000000..ba7e39fd
--- /dev/null
+++ b/4a/675b8352a2/metadata.json
@@ -0,0 +1,28 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "4a675b8352a2",
+  "strategy": "manual-commit",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "pkg/metricstore/archive.go",
+    "pkg/metricstore/parquetArchive.go",
+    "pkg/metricstore/parquetArchive_test.go"
+  ],
+  "sessions": [
+    {
+      "metadata": "/4a/675b8352a2/0/metadata.json",
+      "transcript": "/4a/675b8352a2/0/full.jsonl",
+      "context": "/4a/675b8352a2/0/context.md",
+      "content_hash": "/4a/675b8352a2/0/content_hash.txt",
+      "prompt": "/4a/675b8352a2/0/prompt.txt"
+    }
+  ],
+  "token_usage": {
+    "input_tokens": 23,
+    "cache_creation_tokens": 84788,
+    "cache_read_tokens": 624841,
+    "output_tokens": 9466,
+    "api_call_count": 17
+  }
+}
diff --git a/85/8b34ef56b8/0/content_hash.txt b/85/8b34ef56b8/0/content_hash.txt
new file mode 100644
index 00000000..0e6142df
--- /dev/null
+++ b/85/8b34ef56b8/0/content_hash.txt
@@ -0,0 +1 @@
+sha256:759250a16880d93d21fe76c34a6df6f66e6f077f5d0696f456150a6e10bdf5d4
\ No newline at end of file
diff --git a/85/8b34ef56b8/0/context.md b/85/8b34ef56b8/0/context.md
new file mode 100644
index 00000000..04022c84
--- /dev/null
+++ b/85/8b34ef56b8/0/context.md
@@ -0,0 +1,22 @@
+# Session Context
+
+## User Prompts
+
+### Prompt 1
+
+Implement the following plan:
+
+# Plan: Improve scanJob logging
+
+## Context
+
+`scanJob` in `internal/repository/job.go` (line 162) logs a `Warn` for every scan error, including the very common `sql.ErrNoRows` case. This produces noisy, unhelpful log lines like:
+
+```
+WARN Error while scanning rows (Job): sql: no rows in result set
+```
+
+Two problems:
+1. `sql.ErrNoRows` is a normal, expected condition (callers are documented to check for it). It should not produce a warning.
+2. When a real scan er...
+
diff --git a/85/8b34ef56b8/0/full.jsonl b/85/8b34ef56b8/0/full.jsonl
new file mode 100644
index 00000000..524bdc73
--- /dev/null
+++ b/85/8b34ef56b8/0/full.jsonl
@@ -0,0 +1,34 @@
+{"type":"file-history-snapshot","messageId":"0ee65114-d1fe-4419-b9ac-248b3919e8cd","snapshot":{"messageId":"0ee65114-d1fe-4419-b9ac-248b3919e8cd","trackedFileBackups":{},"timestamp":"2026-03-16T19:01:26.368Z"},"isSnapshotUpdate":false}
+{"parentUuid":null,"isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"eb3f389d-6f47-4c3e-bc72-48d08cbad97c","toolUseID":"eb3f389d-6f47-4c3e-bc72-48d08cbad97c","timestamp":"2026-03-16T19:01:26.327Z","uuid":"cc80828f-fa12-4dfa-9e4c-a05b3293de6c","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"cc80828f-fa12-4dfa-9e4c-a05b3293de6c","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Plan: Improve scanJob logging\n\n## Context\n\n`scanJob` in `internal/repository/job.go` (line 162) logs a `Warn` for every scan error, including the very common `sql.ErrNoRows` case. This produces noisy, unhelpful log lines like:\n\n```\nWARN Error while scanning rows (Job): sql: no rows in result set\n```\n\nTwo problems:\n1. `sql.ErrNoRows` is a normal, expected condition (callers are documented to check for it). It should not produce a warning.\n2. When a real scan error does occur, there's no call-site context — you can't tell which of the ~10 callers triggered it.\n\nThe codebase already has a precedent for using `runtime.Caller(1)` in `internal/api/rest.go:188` to include file/line in log messages.\n\n## Approach\n\nModify `scanJob` in `internal/repository/job.go`:\n\n1. **Skip logging for `sql.ErrNoRows`** — return the error silently. All callers already handle this case themselves.\n2. **Add caller context** for real scan errors using `runtime.Caller(1)` — include `file:line` in the warning message.\n\n```go\nimport (\n    \"database/sql\"\n    \"path/filepath\"\n    \"runtime\"\n    // existing imports ...\n)\n\nfunc scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n    job := &schema.Job{}\n\n    if err := row.Scan(...); err != nil {\n        if err != sql.ErrNoRows {\n            _, file, line, _ := runtime.Caller(1)\n            cclog.Warnf(\"Error while scanning rows (Job) (%s:%d): %v\", filepath.Base(file), line, err)\n        }\n        return nil, err\n    }\n    // ... rest unchanged\n}\n```\n\n## Critical File\n\n- `internal/repository/job.go` — only file to change (lines 154–184)\n\n## Imports to check\n\n`database/sql` is likely already imported (used elsewhere in the package). `runtime` and `path/filepath` — check if already present; add if not.\n\n## Verification\n\n1. `go build ./...` — must compile cleanly\n2. `go test ./internal/repository/...` — existing tests must pass\n3. Manually: trigger a lookup for a non-existent job ID; confirm no warning is logged\n4. Manually (or via test): force a real scan error; confirm warning includes `job.go:<line>`\n\n\nIf you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/b03f52bf-e58e-45a2-8b95-af846938ee2c.jsonl"},"uuid":"0ee65114-d1fe-4419-b9ac-248b3919e8cd","timestamp":"2026-03-16T19:01:26.222Z","planContent":"# Plan: Improve scanJob logging\n\n## Context\n\n`scanJob` in `internal/repository/job.go` (line 162) logs a `Warn` for every scan error, including the very common `sql.ErrNoRows` case. This produces noisy, unhelpful log lines like:\n\n```\nWARN Error while scanning rows (Job): sql: no rows in result set\n```\n\nTwo problems:\n1. `sql.ErrNoRows` is a normal, expected condition (callers are documented to check for it). It should not produce a warning.\n2. When a real scan error does occur, there's no call-site context — you can't tell which of the ~10 callers triggered it.\n\nThe codebase already has a precedent for using `runtime.Caller(1)` in `internal/api/rest.go:188` to include file/line in log messages.\n\n## Approach\n\nModify `scanJob` in `internal/repository/job.go`:\n\n1. **Skip logging for `sql.ErrNoRows`** — return the error silently. All callers already handle this case themselves.\n2. **Add caller context** for real scan errors using `runtime.Caller(1)` — include `file:line` in the warning message.\n\n```go\nimport (\n    \"database/sql\"\n    \"path/filepath\"\n    \"runtime\"\n    // existing imports ...\n)\n\nfunc scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n    job := &schema.Job{}\n\n    if err := row.Scan(...); err != nil {\n        if err != sql.ErrNoRows {\n            _, file, line, _ := runtime.Caller(1)\n            cclog.Warnf(\"Error while scanning rows (Job) (%s:%d): %v\", filepath.Base(file), line, err)\n        }\n        return nil, err\n    }\n    // ... rest unchanged\n}\n```\n\n## Critical File\n\n- `internal/repository/job.go` — only file to change (lines 154–184)\n\n## Imports to check\n\n`database/sql` is likely already imported (used elsewhere in the package). `runtime` and `path/filepath` — check if already present; add if not.\n\n## Verification\n\n1. `go build ./...` — must compile cleanly\n2. `go test ./internal/repository/...` — existing tests must pass\n3. Manually: trigger a lookup for a non-existent job ID; confirm no warning is logged\n4. Manually (or via test): force a real scan error; confirm warning includes `job.go:<line>`\n","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"f3033a28-80b1-4fc0-87d0-63077950cf6b","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012VxnUSTXy84zUjoZzr85aV","type":"tool_result","content":"     1→// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n     2→// All rights reserved. This file is part of cc-backend.\n     3→// Use of this source code is governed by a MIT-style\n     4→// license that can be found in the LICENSE file.\n     5→\n     6→// Package repository provides the data access layer for cc-backend using the repository pattern.\n     7→//\n     8→// The repository pattern abstracts database operations and provides a clean interface for\n     9→// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n    10→// operations and specialized queries.\n    11→//\n    12→// # Database Connection\n    13→//\n    14→// Initialize the database connection before using any repository:\n    15→//\n    16→//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n    17→//\n    18→// # Configuration\n    19→//\n    20→// Optional: Configure repository settings before initialization:\n    21→//\n    22→//\trepository.SetConfig(&repository.RepositoryConfig{\n    23→//\t    CacheSize: 2 * 1024 * 1024,     // 2MB cache\n    24→//\t    MaxOpenConnections: 8,           // Connection pool size\n    25→//\t    MinRunningJobDuration: 300,      // Filter threshold\n    26→//\t})\n    27→//\n    28→// If not configured, sensible defaults are used automatically.\n    29→//\n    30→// # Repositories\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"9c6618b2-e115-43d1-8e55-72802989137a","timestamp":"2026-03-16T19:01:30.039Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","content":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package repository provides the data access layer for cc-backend using the repository pattern.\n//\n// The repository pattern abstracts database operations and provides a clean interface for\n// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n// operations and specialized queries.\n//\n// # Database Connection\n//\n// Initialize the database connection before using any repository:\n//\n//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n//\n// # Configuration\n//\n// Optional: Configure repository settings before initialization:\n//\n//\trepository.SetConfig(&repository.RepositoryConfig{\n//\t    CacheSize: 2 * 1024 * 1024,     // 2MB cache\n//\t    MaxOpenConnections: 8,           // Connection pool size\n//\t    MinRunningJobDuration: 300,      // Filter threshold\n//\t})\n//\n// If not configured, sensible defaults are used automatically.\n//\n// # Repositories","numLines":30,"startLine":1,"totalLines":1137}},"sourceToolAssistantUUID":"f3033a28-80b1-4fc0-87d0-63077950cf6b","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"89bfb382-4d30-4fdb-b861-2e2f5271cdb0","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0179dJZbW863dAxmrn69ouWL","type":"tool_result","content":"    30→// # Repositories\n    31→//\n    32→//   - JobRepository: Job lifecycle management and querying\n    33→//   - UserRepository: User management and authentication\n    34→//   - NodeRepository: Cluster node state tracking\n    35→//   - Tags: Job tagging and categorization\n    36→//\n    37→// # Caching\n    38→//\n    39→// Repositories use LRU caching to improve performance. Cache keys are constructed\n    40→// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n    41→// mutations to maintain consistency.\n    42→//\n    43→// # Transaction Support\n    44→//\n    45→// For batch operations, use transactions:\n    46→//\n    47→//\tt, err := jobRepo.TransactionInit()\n    48→//\tif err != nil {\n    49→//\t    return err\n    50→//\t}\n    51→//\tdefer t.Rollback() // Rollback if not committed\n    52→//\n    53→//\t// Perform operations...\n    54→//\tjobRepo.TransactionAdd(t, query, args...)\n    55→//\n    56→//\t// Commit when done\n    57→//\tif err := t.Commit(); err != nil {\n    58→//\t    return err\n    59→//\t}\n    60→package repository\n    61→\n    62→import (\n    63→\t\"database/sql\"\n    64→\t\"encoding/json\"\n    65→\t\"errors\"\n    66→\t\"fmt\"\n    67→\t\"maps\"\n    68→\t\"math\"\n    69→\t\"sort\"\n    70→\t\"strconv\"\n    71→\t\"sync\"\n    72→\t\"time\"\n    73→\n    74→\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n    75→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    76→\t\"github.com/ClusterCockpit/cc-lib/v2/lrucache\"\n    77→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    78→\tsq \"github.com/Masterminds/squirrel\"\n    79→\t\"github.com/jmoiron/sqlx\"\n    80→)\n    81→\n    82→var (\n    83→\t// jobRepoOnce ensures singleton initialization of the JobRepository\n    84→\tjobRepoOnce sync.Once\n    85→\t// jobRepoInstance holds the single instance of JobRepository\n    86→\tjobRepoInstance *JobRepository\n    87→)\n    88→\n    89→// JobRepository provides database access for job-related operations.\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"34c2c229-cd7d-42a0-b724-de822e2d6358","timestamp":"2026-03-16T19:01:33.127Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","content":"// # Repositories\n//\n//   - JobRepository: Job lifecycle management and querying\n//   - UserRepository: User management and authentication\n//   - NodeRepository: Cluster node state tracking\n//   - Tags: Job tagging and categorization\n//\n// # Caching\n//\n// Repositories use LRU caching to improve performance. Cache keys are constructed\n// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n// mutations to maintain consistency.\n//\n// # Transaction Support\n//\n// For batch operations, use transactions:\n//\n//\tt, err := jobRepo.TransactionInit()\n//\tif err != nil {\n//\t    return err\n//\t}\n//\tdefer t.Rollback() // Rollback if not committed\n//\n//\t// Perform operations...\n//\tjobRepo.TransactionAdd(t, query, args...)\n//\n//\t// Commit when done\n//\tif err := t.Commit(); err != nil {\n//\t    return err\n//\t}\npackage repository\n\nimport (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/lrucache\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n)\n\nvar (\n\t// jobRepoOnce ensures singleton initialization of the JobRepository\n\tjobRepoOnce sync.Once\n\t// jobRepoInstance holds the single instance of JobRepository\n\tjobRepoInstance *JobRepository\n)\n\n// JobRepository provides database access for job-related operations.","numLines":60,"startLine":30,"totalLines":1137}},"sourceToolAssistantUUID":"89bfb382-4d30-4fdb-b861-2e2f5271cdb0","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"d794b7a8-bd3b-4636-a95b-9a41347d8c29","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TUQYJ3NK6LzyDKZnNQnXVt","type":"tool_result","content":"   150→// Parameters:\n   151→//   - row: Database row implementing Scan() interface (sql.Row or sql.Rows)\n   152→//\n   153→// Returns the populated Job struct or an error if scanning or unmarshaling fails.\n   154→func scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n   155→\tjob := &schema.Job{}\n   156→\n   157→\tif err := row.Scan(\n   158→\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n   159→\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n   160→\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n   161→\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n   162→\t\tcclog.Warnf(\"Error while scanning rows (Job): %v\", err)\n   163→\t\treturn nil, err\n   164→\t}\n   165→\n   166→\tif err := json.Unmarshal(job.RawResources, &job.Resources); err != nil {\n   167→\t\tcclog.Warn(\"Error while unmarshaling raw resources json\")\n   168→\t\treturn nil, err\n   169→\t}\n   170→\tjob.RawResources = nil\n   171→\n   172→\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n   173→\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json: %v\", err)\n   174→\t\treturn nil, err\n   175→\t}\n   176→\tjob.RawFootprint = nil\n   177→\n   178→\t// Always ensure accurate duration for running jobs\n   179→\tif job.State == schema.JobStateRunning {\n   180→\t\tjob.Duration = int32(time.Now().Unix() - job.StartTime)\n   181→\t}\n   182→\n   183→\treturn job, nil\n   184→}\n   185→\n   186→// Optimize performs database optimization by running VACUUM command.\n   187→// This reclaims unused space and defragments the database file.\n   188→// Should be run periodically during maintenance windows.\n   189→func (r *JobRepository) Optimize() error {\n   190→\tif _, err := r.DB.Exec(`VACUUM`); err != nil {\n   191→\t\tcclog.Errorf(\"Error while executing VACUUM: %v\", err)\n   192→\t\treturn fmt.Errorf(\"failed to optimize database: %w\", err)\n   193→\t}\n   194→\treturn nil\n   195→}\n   196→\n   197→// Flush removes all data from job-related tables (jobtag, tag, job).\n   198→// WARNING: This is a destructive operation that deletes all job data.\n   199→// Use with extreme caution, typically only for testing or complete resets.\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"1d2d9d27-9829-4e70-b0f1-8d82aeea41e4","timestamp":"2026-03-16T19:01:35.775Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","content":"// Parameters:\n//   - row: Database row implementing Scan() interface (sql.Row or sql.Rows)\n//\n// Returns the populated Job struct or an error if scanning or unmarshaling fails.\nfunc scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n\tjob := &schema.Job{}\n\n\tif err := row.Scan(\n\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n\t\tcclog.Warnf(\"Error while scanning rows (Job): %v\", err)\n\t\treturn nil, err\n\t}\n\n\tif err := json.Unmarshal(job.RawResources, &job.Resources); err != nil {\n\t\tcclog.Warn(\"Error while unmarshaling raw resources json\")\n\t\treturn nil, err\n\t}\n\tjob.RawResources = nil\n\n\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json: %v\", err)\n\t\treturn nil, err\n\t}\n\tjob.RawFootprint = nil\n\n\t// Always ensure accurate duration for running jobs\n\tif job.State == schema.JobStateRunning {\n\t\tjob.Duration = int32(time.Now().Unix() - job.StartTime)\n\t}\n\n\treturn job, nil\n}\n\n// Optimize performs database optimization by running VACUUM command.\n// This reclaims unused space and defragments the database file.\n// Should be run periodically during maintenance windows.\nfunc (r *JobRepository) Optimize() error {\n\tif _, err := r.DB.Exec(`VACUUM`); err != nil {\n\t\tcclog.Errorf(\"Error while executing VACUUM: %v\", err)\n\t\treturn fmt.Errorf(\"failed to optimize database: %w\", err)\n\t}\n\treturn nil\n}\n\n// Flush removes all data from job-related tables (jobtag, tag, job).\n// WARNING: This is a destructive operation that deletes all job data.\n// Use with extreme caution, typically only for testing or complete resets.","numLines":50,"startLine":150,"totalLines":1137}},"sourceToolAssistantUUID":"d794b7a8-bd3b-4636-a95b-9a41347d8c29","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"1d2d9d27-9829-4e70-b0f1-8d82aeea41e4","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01J7aEPCqRXeFMhyQDhRzoqR","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have all the context. The imports already include `database/sql`. I need to add `path/filepath` and `runtime`, then modify `scanJob`."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":991,"cache_read_input_tokens":20017,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":991},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ7Gy2xhWhGV9cTiNUTuh","type":"assistant","uuid":"5cce56cc-4a5b-4601-ab11-8481d1bcbd68","timestamp":"2026-03-16T19:01:39.953Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"5cce56cc-4a5b-4601-ab11-8481d1bcbd68","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01J7aEPCqRXeFMhyQDhRzoqR","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SEStTNPB564kxtccKVJNxc","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","old_string":"import (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"","new_string":"import (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"path/filepath\"\n\t\"runtime\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\""},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":991,"cache_read_input_tokens":20017,"output_tokens":271,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":991,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ7Gy2xhWhGV9cTiNUTuh","type":"assistant","uuid":"15819832-8055-4e39-bc9d-4a47ece02bd4","timestamp":"2026-03-16T19:01:41.355Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"type":"file-history-snapshot","messageId":"15819832-8055-4e39-bc9d-4a47ece02bd4","snapshot":{"messageId":"0ee65114-d1fe-4419-b9ac-248b3919e8cd","trackedFileBackups":{"internal/repository/job.go":{"backupFileName":"0742bb1d44c2b46d@v1","version":1,"backupTime":"2026-03-16T19:01:41.366Z"}},"timestamp":"2026-03-16T19:01:26.368Z"},"isSnapshotUpdate":true}
+{"parentUuid":"15819832-8055-4e39-bc9d-4a47ece02bd4","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Edit","command":"callback"},"parentToolUseID":"toolu_01SEStTNPB564kxtccKVJNxc","toolUseID":"toolu_01SEStTNPB564kxtccKVJNxc","timestamp":"2026-03-16T19:01:41.373Z","uuid":"0b91cd7b-649d-4b36-a2c8-0fbf3ea57cc6","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
+{"parentUuid":"15819832-8055-4e39-bc9d-4a47ece02bd4","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SEStTNPB564kxtccKVJNxc","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/internal/repository/job.go has been updated successfully."}]},"uuid":"a10d4b20-6803-46e1-857f-83f5e94b1ec9","timestamp":"2026-03-16T19:01:41.373Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","oldString":"import (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"","newString":"import (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"path/filepath\"\n\t\"runtime\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package repository provides the data access layer for cc-backend using the repository pattern.\n//\n// The repository pattern abstracts database operations and provides a clean interface for\n// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n// operations and specialized queries.\n//\n// # Database Connection\n//\n// Initialize the database connection before using any repository:\n//\n//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n//\n// # Configuration\n//\n// Optional: Configure repository settings before initialization:\n//\n//\trepository.SetConfig(&repository.RepositoryConfig{\n//\t    CacheSize: 2 * 1024 * 1024,     // 2MB cache\n//\t    MaxOpenConnections: 8,           // Connection pool size\n//\t    MinRunningJobDuration: 300,      // Filter threshold\n//\t})\n//\n// If not configured, sensible defaults are used automatically.\n//\n// # Repositories\n//\n//   - JobRepository: Job lifecycle management and querying\n//   - UserRepository: User management and authentication\n//   - NodeRepository: Cluster node state tracking\n//   - Tags: Job tagging and categorization\n//\n// # Caching\n//\n// Repositories use LRU caching to improve performance. Cache keys are constructed\n// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n// mutations to maintain consistency.\n//\n// # Transaction Support\n//\n// For batch operations, use transactions:\n//\n//\tt, err := jobRepo.TransactionInit()\n//\tif err != nil {\n//\t    return err\n//\t}\n//\tdefer t.Rollback() // Rollback if not committed\n//\n//\t// Perform operations...\n//\tjobRepo.TransactionAdd(t, query, args...)\n//\n//\t// Commit when done\n//\tif err := t.Commit(); err != nil {\n//\t    return err\n//\t}\npackage repository\n\nimport (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/lrucache\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n)\n\nvar (\n\t// jobRepoOnce ensures singleton initialization of the JobRepository\n\tjobRepoOnce sync.Once\n\t// jobRepoInstance holds the single instance of JobRepository\n\tjobRepoInstance *JobRepository\n)\n\n// JobRepository provides database access for job-related operations.\n// It implements the repository pattern to abstract database interactions\n// and provides caching for improved performance.\n//\n// The repository is a singleton initialized via GetJobRepository().\n// All database queries use prepared statements via stmtCache for efficiency.\n// Frequently accessed data (metadata, energy footprints) is cached in an LRU cache.\ntype JobRepository struct {\n\tDB        *sqlx.DB        // Database connection pool\n\tstmtCache *sq.StmtCache   // Prepared statement cache for query optimization\n\tcache     *lrucache.Cache // LRU cache for metadata and footprint data\n\tdriver    string          // Database driver name (e.g., \"sqlite3\")\n\tMutex     sync.Mutex      // Mutex for thread-safe operations\n}\n\n// GetJobRepository returns the singleton instance of JobRepository.\n// The repository is initialized lazily on first access with database connection,\n// prepared statement cache, and LRU cache configured from repoConfig.\n//\n// This function is thread-safe and ensures only one instance is created.\n// It must be called after Connect() has established a database connection.\nfunc GetJobRepository() *JobRepository {\n\tjobRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tjobRepoInstance = &JobRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\n\t\t\tstmtCache: sq.NewStmtCache(db.DB),\n\t\t\tcache:     lrucache.New(repoConfig.CacheSize),\n\t\t}\n\t})\n\treturn jobRepoInstance\n}\n\n// jobColumns defines the standard set of columns selected from the job table.\n// Used consistently across all job queries to ensure uniform data retrieval.\nvar jobColumns []string = []string{\n\t\"job.id\", \"job.job_id\", \"job.hpc_user\", \"job.project\", \"job.cluster\", \"job.subcluster\",\n\t\"job.start_time\", \"job.cluster_partition\", \"job.array_job_id\", \"job.num_nodes\",\n\t\"job.num_hwthreads\", \"job.num_acc\", \"job.shared\", \"job.monitoring_status\",\n\t\"job.smt\", \"job.job_state\", \"job.duration\", \"job.walltime\", \"job.resources\",\n\t\"job.footprint\", \"job.energy\",\n}\n\n// jobCacheColumns defines columns from the job_cache table, mirroring jobColumns.\n// Used for queries against cached job data for performance optimization.\nvar jobCacheColumns []string = []string{\n\t\"job_cache.id\", \"job_cache.job_id\", \"job_cache.hpc_user\", \"job_cache.project\", \"job_cache.cluster\",\n\t\"job_cache.subcluster\", \"job_cache.start_time\", \"job_cache.cluster_partition\",\n\t\"job_cache.array_job_id\", \"job_cache.num_nodes\", \"job_cache.num_hwthreads\",\n\t\"job_cache.num_acc\", \"job_cache.shared\", \"job_cache.monitoring_status\", \"job_cache.smt\",\n\t\"job_cache.job_state\", \"job_cache.duration\", \"job_cache.walltime\", \"job_cache.resources\",\n\t\"job_cache.footprint\", \"job_cache.energy\",\n}\n\n// scanJob converts a database row into a schema.Job struct.\n// It handles JSON unmarshaling of resources and footprint fields,\n// and calculates accurate duration for running jobs.\n//\n// Parameters:\n//   - row: Database row implementing Scan() interface (sql.Row or sql.Rows)\n//\n// Returns the populated Job struct or an error if scanning or unmarshaling fails.\nfunc scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n\tjob := &schema.Job{}\n\n\tif err := row.Scan(\n\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n\t\tcclog.Warnf(\"Error while scanning rows (Job): %v\", err)\n\t\treturn nil, err\n\t}\n\n\tif err := json.Unmarshal(job.RawResources, &job.Resources); err != nil {\n\t\tcclog.Warn(\"Error while unmarshaling raw resources json\")\n\t\treturn nil, err\n\t}\n\tjob.RawResources = nil\n\n\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json: %v\", err)\n\t\treturn nil, err\n\t}\n\tjob.RawFootprint = nil\n\n\t// Always ensure accurate duration for running jobs\n\tif job.State == schema.JobStateRunning {\n\t\tjob.Duration = int32(time.Now().Unix() - job.StartTime)\n\t}\n\n\treturn job, nil\n}\n\n// Optimize performs database optimization by running VACUUM command.\n// This reclaims unused space and defragments the database file.\n// Should be run periodically during maintenance windows.\nfunc (r *JobRepository) Optimize() error {\n\tif _, err := r.DB.Exec(`VACUUM`); err != nil {\n\t\tcclog.Errorf(\"Error while executing VACUUM: %v\", err)\n\t\treturn fmt.Errorf(\"failed to optimize database: %w\", err)\n\t}\n\treturn nil\n}\n\n// Flush removes all data from job-related tables (jobtag, tag, job).\n// WARNING: This is a destructive operation that deletes all job data.\n// Use with extreme caution, typically only for testing or complete resets.\nfunc (r *JobRepository) Flush() error {\n\tif _, err := r.DB.Exec(`DELETE FROM jobtag`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from jobtag table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush jobtag table: %w\", err)\n\t}\n\tif _, err := r.DB.Exec(`DELETE FROM tag`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from tag table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush tag table: %w\", err)\n\t}\n\tif _, err := r.DB.Exec(`DELETE FROM job`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from job table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush job table: %w\", err)\n\t}\n\treturn nil\n}\n\n// FetchMetadata retrieves and unmarshals the metadata JSON for a job.\n// Metadata is cached with a 24-hour TTL to improve performance.\n//\n// The metadata field stores arbitrary key-value pairs associated with a job,\n// such as tags, labels, or custom attributes added by external systems.\n//\n// Parameters:\n//   - job: Job struct with valid ID field, metadata will be populated in job.MetaData\n//\n// Returns the metadata map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchMetadata(job *schema.Job) (map[string]string, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n\t\tjob.MetaData = cached.(map[string]string)\n\t\treturn job.MetaData, nil\n\t}\n\n\tif err := sq.Select(\"job.meta_data\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawMetaData); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job metadata (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawMetaData) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawMetaData, &job.MetaData); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw metadata json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n\tcclog.Debugf(\"Timer FetchMetadata %s\", time.Since(start))\n\treturn job.MetaData, nil\n}\n\n// UpdateMetadata adds or updates a single metadata key-value pair for a job.\n// The entire metadata map is re-marshaled and stored, and the cache is invalidated.\n// Also triggers archive metadata update via archive.UpdateMetadata.\n//\n// Parameters:\n//   - job: Job struct with valid ID, existing metadata will be fetched if not present\n//   - key: Metadata key to set\n//   - val: Metadata value to set\n//\n// Returns an error if the job is nil, metadata fetch fails, or database update fails.\nfunc (r *JobRepository) UpdateMetadata(job *schema.Job, key, val string) (err error) {\n\tif job == nil {\n\t\treturn fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n\tr.cache.Del(cachekey)\n\tif job.MetaData == nil {\n\t\tif _, err = r.FetchMetadata(job); err != nil {\n\t\t\tcclog.Warnf(\"Error while fetching metadata for job, DB ID '%v'\", *job.ID)\n\t\t\treturn fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n\t\t}\n\t}\n\n\tif job.MetaData != nil {\n\t\tcpy := make(map[string]string, len(job.MetaData)+1)\n\t\tmaps.Copy(cpy, job.MetaData)\n\t\tcpy[key] = val\n\t\tjob.MetaData = cpy\n\t} else {\n\t\tjob.MetaData = map[string]string{key: val}\n\t}\n\n\tif job.RawMetaData, err = json.Marshal(job.MetaData); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling metadata for job, DB ID '%v'\", *job.ID)\n\t\treturn fmt.Errorf(\"failed to marshal metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tif _, err = sq.Update(\"job\").\n\t\tSet(\"meta_data\", job.RawMetaData).\n\t\tWhere(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Warnf(\"Error while updating metadata for job, DB ID '%v'\", *job.ID)\n\t\treturn fmt.Errorf(\"failed to update metadata in database for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n\treturn archive.UpdateMetadata(job, job.MetaData)\n}\n\n// FetchFootprint retrieves and unmarshals the performance footprint JSON for a job.\n// Unlike FetchMetadata, footprints are NOT cached as they can be large and change frequently.\n//\n// The footprint contains summary statistics (avg/min/max) for monitored metrics,\n// stored as JSON with keys like \"cpu_load_avg\", \"mem_used_max\", etc.\n//\n// Parameters:\n//   - job: Job struct with valid ID, footprint will be populated in job.Footprint\n//\n// Returns the footprint map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchFootprint(job *schema.Job) (map[string]float64, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\n\tif err := sq.Select(\"job.footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job footprint (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawFootprint) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tcclog.Debugf(\"Timer FetchFootprint %s\", time.Since(start))\n\treturn job.Footprint, nil\n}\n\n// FetchEnergyFootprint retrieves and unmarshals the energy footprint JSON for a job.\n// Energy footprints are cached with a 24-hour TTL as they are frequently accessed but rarely change.\n//\n// The energy footprint contains calculated energy consumption (in kWh) per metric,\n// stored as JSON with keys like \"power_avg\", \"acc_power_avg\", etc.\n//\n// Parameters:\n//   - job: Job struct with valid ID, energy footprint will be populated in job.EnergyFootprint\n//\n// Returns the energy footprint map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchEnergyFootprint(job *schema.Job) (map[string]float64, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\tcachekey := fmt.Sprintf(\"energyFootprint:%d\", *job.ID)\n\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n\t\tjob.EnergyFootprint = cached.(map[string]float64)\n\t\treturn job.EnergyFootprint, nil\n\t}\n\n\tif err := sq.Select(\"job.energy_footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawEnergyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job energy_footprint (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch energy footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawEnergyFootprint) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawEnergyFootprint, &job.EnergyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw energy footprint json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal energy footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.EnergyFootprint, len(job.EnergyFootprint), 24*time.Hour)\n\tcclog.Debugf(\"Timer FetchEnergyFootprint %s\", time.Since(start))\n\treturn job.EnergyFootprint, nil\n}\n\n// DeleteJobsBefore removes jobs older than the specified start time.\n// Optionally preserves tagged jobs to protect important data from deletion.\n// Cache entries for deleted jobs are automatically invalidated.\n//\n// This is typically used for data retention policies and cleanup operations.\n// WARNING: This is a destructive operation that permanently deletes job records.\n//\n// Parameters:\n//   - startTime: Unix timestamp, jobs with start_time < this value will be deleted\n//   - omitTagged: \"none\" = delete all jobs, \"all\" = skip any tagged jobs,\n//     \"user\" = skip jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n//\n// Returns the count of deleted jobs or an error if the operation fails.\nfunc (r *JobRepository) DeleteJobsBefore(startTime int64, omitTagged string) (int, error) {\n\tvar cnt int\n\tq := sq.Select(\"count(*)\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\n\tif err := q.RunWith(r.DB).QueryRow().Scan(&cnt); err != nil {\n\t\tcclog.Errorf(\"Error counting jobs before %d: %v\", startTime, err)\n\t\treturn 0, err\n\t}\n\n\t// Invalidate cache for jobs being deleted (get job IDs first)\n\tif cnt > 0 {\n\t\tvar jobIds []int64\n\t\tselectQuery := sq.Select(\"id\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\t\tswitch omitTagged {\n\t\tcase \"all\":\n\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\t\tcase \"user\":\n\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t\t}\n\n\t\trows, err := selectQuery.RunWith(r.DB).Query()\n\t\tif err == nil {\n\t\t\tdefer rows.Close()\n\t\t\tfor rows.Next() {\n\t\t\t\tvar id int64\n\t\t\t\tif err := rows.Scan(&id); err == nil {\n\t\t\t\t\tjobIds = append(jobIds, id)\n\t\t\t\t}\n\t\t\t}\n\t\t\t// Invalidate cache entries\n\t\t\tfor _, id := range jobIds {\n\t\t\t\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n\t\t\t\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n\t\t\t}\n\t\t}\n\t}\n\n\tqd := sq.Delete(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\t_, err := qd.RunWith(r.DB).Exec()\n\n\tif err != nil {\n\t\ts, _, _ := qd.ToSql()\n\t\tcclog.Errorf(\" DeleteJobsBefore(%d) with %s: error %#v\", startTime, s, err)\n\t} else {\n\t\tcclog.Debugf(\"DeleteJobsBefore(%d): Deleted %d jobs\", startTime, cnt)\n\t}\n\treturn cnt, err\n}\n\n// DeleteJobByID permanently removes a single job by its database ID.\n// Cache entries for the deleted job are automatically invalidated.\n//\n// Parameters:\n//   - id: Database ID (primary key) of the job to delete\n//\n// Returns an error if the deletion fails.\nfunc (r *JobRepository) DeleteJobByID(id int64) error {\n\t// Invalidate cache entries before deletion\n\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n\n\tqd := sq.Delete(\"job\").Where(\"job.id = ?\", id)\n\t_, err := qd.RunWith(r.DB).Exec()\n\n\tif err != nil {\n\t\ts, _, _ := qd.ToSql()\n\t\tcclog.Errorf(\"DeleteJobById(%d) with %s : error %#v\", id, s, err)\n\t} else {\n\t\tcclog.Debugf(\"DeleteJobById(%d): Success\", id)\n\t}\n\treturn err\n}\n\n// FindUserOrProjectOrJobname attempts to interpret a search term as a job ID,\n// username, project ID, or job name by querying the database.\n//\n// Search logic (in priority order):\n//  1. If searchterm is numeric, treat as job ID (returned immediately)\n//  2. Try exact match in job.hpc_user column (username)\n//  3. Try LIKE match in hpc_user.name column (real name)\n//  4. Try exact match in job.project column (project ID)\n//  5. If no matches, return searchterm as jobname for GraphQL query\n//\n// This powers the searchbar functionality for flexible job searching.\n// Requires authenticated user for database lookups (returns empty if user is nil).\n//\n// Parameters:\n//   - user: Authenticated user context, required for database access\n//   - searchterm: Search string to interpret\n//\n// Returns up to one non-empty value among (jobid, username, project, jobname).\nfunc (r *JobRepository) FindUserOrProjectOrJobname(user *schema.User, searchterm string) (jobid string, username string, project string, jobname string) {\n\tif searchterm == \"\" {\n\t\treturn \"\", \"\", \"\", \"\"\n\t}\n\n\tif _, err := strconv.Atoi(searchterm); err == nil { // Return empty on successful conversion: parent method will redirect for integer jobId\n\t\treturn searchterm, \"\", \"\", \"\"\n\t} else { // Has to have letters and logged-in user for other guesses\n\t\tif user != nil {\n\t\t\t// Find username by username in job table (match)\n\t\t\turesult, _ := r.FindColumnValue(user, searchterm, \"job\", \"hpc_user\", \"hpc_user\", false)\n\t\t\tif uresult != \"\" {\n\t\t\t\treturn \"\", uresult, \"\", \"\"\n\t\t\t}\n\t\t\t// Find username by real name in hpc_user table (like)\n\t\t\tnresult, _ := r.FindColumnValue(user, searchterm, \"hpc_user\", \"username\", \"name\", true)\n\t\t\tif nresult != \"\" {\n\t\t\t\treturn \"\", nresult, \"\", \"\"\n\t\t\t}\n\t\t\t// Find projectId by projectId in job table (match)\n\t\t\tpresult, _ := r.FindColumnValue(user, searchterm, \"job\", \"project\", \"project\", false)\n\t\t\tif presult != \"\" {\n\t\t\t\treturn \"\", \"\", presult, \"\"\n\t\t\t}\n\t\t}\n\t\t// Return searchterm if no match before: Forward as jobname query to GQL in handleSearchbar function\n\t\treturn \"\", \"\", \"\", searchterm\n\t}\n}\n\nvar (\n\tErrNotFound  = errors.New(\"no such jobname, project or user\")\n\tErrForbidden = errors.New(\"not authorized\")\n)\n\n// FindColumnValue performs a generic column lookup in a database table with role-based access control.\n// Only users with admin, support, or manager roles can execute this query.\n//\n// Parameters:\n//   - user: User context for authorization check\n//   - searchterm: Value to search for (exact match or LIKE pattern)\n//   - table: Database table name to query\n//   - selectColumn: Column name to return in results\n//   - whereColumn: Column name to filter on\n//   - isLike: If true, use LIKE with wildcards; if false, use exact equality\n//\n// Returns the first matching value, ErrForbidden if user lacks permission,\n// or ErrNotFound if no matches are found.\nfunc (r *JobRepository) FindColumnValue(user *schema.User, searchterm string, table string, selectColumn string, whereColumn string, isLike bool) (result string, err error) {\n\tif user == nil {\n\t\treturn \"\", fmt.Errorf(\"user cannot be nil\")\n\t}\n\n\tcompareStr := \" = ?\"\n\tquery := searchterm\n\tif isLike {\n\t\tcompareStr = \" LIKE ?\"\n\t\tquery = \"%\" + searchterm + \"%\"\n\t}\n\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\ttheQuery := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n\t\t\tWhere(table+\".\"+whereColumn+compareStr, query)\n\n\t\terr := theQuery.RunWith(r.stmtCache).QueryRow().Scan(&result)\n\n\t\tif err != nil && err != sql.ErrNoRows {\n\t\t\tcclog.Warnf(\"Error while querying FindColumnValue (table=%s, column=%s): %v\", table, selectColumn, err)\n\t\t\treturn \"\", fmt.Errorf(\"failed to find column value: %w\", err)\n\t\t} else if err == nil {\n\t\t\treturn result, nil\n\t\t}\n\t\treturn \"\", ErrNotFound\n\t} else {\n\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)\n\t\treturn \"\", ErrForbidden\n\t}\n}\n\n// FindColumnValues performs a generic column lookup returning multiple matches with role-based access control.\n// Similar to FindColumnValue but returns all matching values instead of just the first.\n// Only users with admin, support, or manager roles can execute this query.\n//\n// Parameters:\n//   - user: User context for authorization check\n//   - query: Search pattern (always uses LIKE with wildcards)\n//   - table: Database table name to query\n//   - selectColumn: Column name to return in results\n//   - whereColumn: Column name to filter on\n//\n// Returns a slice of matching values, ErrForbidden if user lacks permission,\n// or ErrNotFound if no matches are found.\nfunc (r *JobRepository) FindColumnValues(user *schema.User, query string, table string, selectColumn string, whereColumn string) (results []string, err error) {\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"user cannot be nil\")\n\t}\n\n\temptyResult := make([]string, 0)\n\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\trows, err := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n\t\t\tWhere(table+\".\"+whereColumn+\" LIKE ?\", fmt.Sprint(\"%\", query, \"%\")).\n\t\t\tRunWith(r.stmtCache).Query()\n\t\tif err != nil && err != sql.ErrNoRows {\n\t\t\tcclog.Errorf(\"Error while querying FindColumnValues (table=%s, column=%s): %v\", table, selectColumn, err)\n\t\t\treturn emptyResult, fmt.Errorf(\"failed to find column values: %w\", err)\n\t\t} else if err == nil {\n\t\t\tdefer rows.Close()\n\t\t\tfor rows.Next() {\n\t\t\t\tvar result string\n\t\t\t\terr := rows.Scan(&result)\n\t\t\t\tif err != nil {\n\t\t\t\t\tcclog.Warnf(\"Error while scanning rows in FindColumnValues: %v\", err)\n\t\t\t\t\treturn emptyResult, fmt.Errorf(\"failed to scan column value: %w\", err)\n\t\t\t\t}\n\t\t\t\tresults = append(results, result)\n\t\t\t}\n\t\t\treturn results, nil\n\t\t}\n\t\treturn emptyResult, ErrNotFound\n\n\t} else {\n\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)\n\t\treturn emptyResult, ErrForbidden\n\t}\n}\n\n// Partitions returns a list of distinct cluster partitions for a given cluster.\n// Results are cached with a 1-hour TTL to improve performance.\n//\n// Parameters:\n//   - cluster: Cluster name to query partitions for\n//\n// Returns a slice of partition names or an error if the database query fails.\nfunc (r *JobRepository) Partitions(cluster string) ([]string, error) {\n\tvar err error\n\tstart := time.Now()\n\tpartitions := r.cache.Get(\"partitions:\"+cluster, func() (any, time.Duration, int) {\n\t\tparts := []string{}\n\t\tif err = r.DB.Select(&parts, `SELECT DISTINCT job.cluster_partition FROM job WHERE job.cluster = ?;`, cluster); err != nil {\n\t\t\treturn nil, 0, 1000\n\t\t}\n\n\t\treturn parts, 1 * time.Hour, 1\n\t})\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tcclog.Debugf(\"Timer Partitions %s\", time.Since(start))\n\treturn partitions.([]string), nil\n}\n\n// AllocatedNodes returns a map of all subclusters to a map of hostnames to the amount of jobs running on that host.\n// Hosts with zero jobs running on them will not show up!\nfunc (r *JobRepository) AllocatedNodes(cluster string) (map[string]map[string]int, error) {\n\tstart := time.Now()\n\tsubclusters := make(map[string]map[string]int)\n\trows, err := sq.Select(\"resources\", \"subcluster\").From(\"job\").\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.cluster = ?\", cluster).\n\t\tRunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running AllocatedNodes query for cluster=%s: %v\", cluster, err)\n\t\treturn nil, fmt.Errorf(\"failed to query allocated nodes for cluster %s: %w\", cluster, err)\n\t}\n\n\tvar raw []byte\n\tdefer rows.Close()\n\tfor rows.Next() {\n\t\traw = raw[0:0]\n\t\tvar resources []*schema.Resource\n\t\tvar subcluster string\n\t\tif err := rows.Scan(&raw, &subcluster); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in AllocatedNodes: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan allocated nodes row: %w\", err)\n\t\t}\n\t\tif err := json.Unmarshal(raw, &resources); err != nil {\n\t\t\tcclog.Warnf(\"Error while unmarshaling raw resources json in AllocatedNodes: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to unmarshal resources in AllocatedNodes: %w\", err)\n\t\t}\n\n\t\thosts, ok := subclusters[subcluster]\n\t\tif !ok {\n\t\t\thosts = make(map[string]int)\n\t\t\tsubclusters[subcluster] = hosts\n\t\t}\n\n\t\tfor _, resource := range resources {\n\t\t\thosts[resource.Hostname] += 1\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AllocatedNodes %s\", time.Since(start))\n\treturn subclusters, nil\n}\n\n// StopJobsExceedingWalltimeBy marks running jobs as failed if they exceed their walltime limit.\n// This is typically called periodically to clean up stuck or orphaned jobs.\n//\n// Jobs are marked with:\n//   - monitoring_status: MonitoringStatusArchivingFailed\n//   - duration: 0\n//   - job_state: JobStateFailed\n//\n// Parameters:\n//   - seconds: Grace period beyond walltime before marking as failed\n//\n// Returns an error if the database update fails.\n// Logs the number of jobs marked as failed if any were affected.\nfunc (r *JobRepository) StopJobsExceedingWalltimeBy(seconds int) error {\n\tstart := time.Now()\n\tcurrentTime := time.Now().Unix()\n\tres, err := sq.Update(\"job\").\n\t\tSet(\"monitoring_status\", schema.MonitoringStatusArchivingFailed).\n\t\tSet(\"duration\", 0).\n\t\tSet(\"job_state\", schema.JobStateFailed).\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.walltime > 0\").\n\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\n\t\tRunWith(r.DB).Exec()\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n\t}\n\n\trowsAffected, err := res.RowsAffected()\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n\t}\n\n\tif rowsAffected > 0 {\n\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n\t}\n\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n\treturn nil\n}\n\n// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n//\n// Parameters:\n//   - tagID: Database ID of the tag to search for\n//\n// Returns a slice of job IDs or an error if the query fails.\nfunc (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n\tquery := sq.Select(\"job.id\").From(\"job\").\n\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n\t}\n\tdefer rows.Close()\n\n\tjobIds := make([]int64, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar jobID int64\n\n\t\tif err := rows.Scan(&jobID); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n\t\t}\n\n\t\tjobIds = append(jobIds, jobID)\n\t}\n\n\treturn jobIds, nil\n}\n\n// FindRunningJobs returns all currently running jobs for a specific cluster.\n// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n//\n// Parameters:\n//   - cluster: Cluster name to filter jobs\n//\n// Returns a slice of running job objects or an error if the query fails.\nfunc (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n\tquery := sq.Select(jobColumns...).From(\"job\").\n\t\tWhere(\"job.cluster = ?\", cluster).\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, 50)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n\treturn jobs, nil\n}\n\n// UpdateDuration recalculates and updates the duration field for all running jobs.\n// Called periodically to keep job durations current without querying individual jobs.\n//\n// Duration is calculated as: current_time - job.start_time\n//\n// Returns an error if the database update fails.\nfunc (r *JobRepository) UpdateDuration() error {\n\tstmnt := sq.Update(\"job\").\n\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n\t\tWhere(\"job_state = 'running'\")\n\n\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n\t}\n\n\treturn nil\n}\n\n// FindJobsBetween returns jobs within a specified time range.\n// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n// Optionally excludes tagged jobs from results.\n//\n// Parameters:\n//   - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n//   - startTimeEnd: Unix timestamp for range end\n//   - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n//     \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n//\n// Returns a slice of jobs or an error if the time range is invalid or query fails.\nfunc (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n\tvar query sq.SelectBuilder\n\n\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n\t}\n\n\tif startTimeBegin == 0 {\n\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n\t} else {\n\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n\t}\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\n\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\n\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindJobsBetween query: %v\", err)\n\t\treturn nil, fmt.Errorf(\"failed to find jobs between %d and %d: %w\", startTimeBegin, startTimeEnd, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, 50)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobsBetween: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindJobsBetween: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tcclog.Debugf(\"JobRepository.FindJobsBetween(): Return job count %d (omitTagged: %v)\", len(jobs), omitTagged)\n\treturn jobs, nil\n}\n\n// UpdateMonitoringStatus updates the monitoring status for a job and invalidates its cache entries.\n// Cache invalidation affects both metadata and energy footprint to ensure consistency.\n//\n// Parameters:\n//   - job: Database ID of the job to update\n//   - monitoringStatus: New monitoring status value (see schema.MonitoringStatus constants)\n//\n// Returns an error if the database update fails.\nfunc (r *JobRepository) UpdateMonitoringStatus(job int64, monitoringStatus int32) (err error) {\n\t// Invalidate cache entries as monitoring status affects job state\n\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", job))\n\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", job))\n\n\tstmt := sq.Update(\"job\").\n\t\tSet(\"monitoring_status\", monitoringStatus).\n\t\tWhere(\"job.id = ?\", job)\n\n\tif _, err = stmt.RunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while updating monitoring status for job %d: %v\", job, err)\n\t\treturn fmt.Errorf(\"failed to update monitoring status for job %d: %w\", job, err)\n\t}\n\treturn nil\n}\n\n// Execute runs a Squirrel UpdateBuilder statement against the database.\n// This is a generic helper for executing pre-built update queries.\n//\n// Parameters:\n//   - stmt: Squirrel UpdateBuilder with prepared update query\n//\n// Returns an error if the execution fails.\nfunc (r *JobRepository) Execute(stmt sq.UpdateBuilder) error {\n\tif _, err := stmt.RunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while executing statement: %v\", err)\n\t\treturn fmt.Errorf(\"failed to execute update statement: %w\", err)\n\t}\n\n\treturn nil\n}\n\n// MarkArchived adds monitoring status update to an existing UpdateBuilder statement.\n// This is a builder helper used when constructing multi-field update queries.\n//\n// Parameters:\n//   - stmt: Existing UpdateBuilder to modify\n//   - monitoringStatus: Monitoring status value to set\n//\n// Returns the modified UpdateBuilder for method chaining.\nfunc (r *JobRepository) MarkArchived(\n\tstmt sq.UpdateBuilder,\n\tmonitoringStatus int32,\n) sq.UpdateBuilder {\n\treturn stmt.Set(\"monitoring_status\", monitoringStatus)\n}\n\n// UpdateEnergy calculates and updates the energy consumption for a job.\n// This is called for running jobs during intermediate updates or when archiving.\n//\n// Energy calculation formula:\n//   - For \"power\" metrics: Energy (kWh) = (Power_avg * NumNodes * Duration_hours) / 1000\n//   - For \"energy\" metrics: Currently not implemented (would need sum statistics)\n//\n// The calculation accounts for:\n//   - Multi-node jobs: Multiplies by NumNodes to get total cluster energy\n//   - Shared jobs: Node average is already based on partial resources, so NumNodes=1\n//   - Unit conversion: Watts * hours / 1000 = kilowatt-hours (kWh)\n//   - Rounding: Results rounded to 2 decimal places\nfunc (r *JobRepository) UpdateEnergy(\n\tstmt sq.UpdateBuilder,\n\tjobMeta *schema.Job,\n) (sq.UpdateBuilder, error) {\n\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n\t\treturn stmt, err\n\t}\n\tenergyFootprint := make(map[string]float64)\n\n\t// Accumulate total energy across all energy-related metrics\n\ttotalEnergy := 0.0\n\tfor _, fp := range sc.EnergyFootprint {\n\t\t// Calculate energy for this specific metric\n\t\tmetricEnergy := 0.0\n\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err == nil {\n\t\t\tswitch sc.MetricConfig[i].Energy {\n\t\t\tcase \"energy\": // Metric already in energy units (Joules or Wh)\n\t\t\t\tcclog.Warnf(\"Update EnergyFootprint for Job %d and Metric %s on cluster %s: Set to 'energy' in cluster.json: Not implemented, will return 0.0\", jobMeta.JobID, jobMeta.Cluster, fp)\n\t\t\t\t// FIXME: Needs sum as stats type to accumulate energy values over time\n\t\t\tcase \"power\": // Metric in power units (Watts)\n\t\t\t\t// Energy (kWh) = Power (W) × Time (h) / 1000\n\t\t\t\t// Formula: (avg_power_per_node * num_nodes) * (duration_sec / 3600) / 1000\n\t\t\t\t//\n\t\t\t\t// Breakdown:\n\t\t\t\t//   LoadJobStat(jobMeta, fp, \"avg\") = average power per node (W)\n\t\t\t\t//   jobMeta.NumNodes = number of nodes (1 for shared jobs)\n\t\t\t\t//   jobMeta.Duration / 3600.0 = duration in hours\n\t\t\t\t//   / 1000.0 = convert Wh to kWh\n\t\t\t\trawEnergy := ((LoadJobStat(jobMeta, fp, \"avg\") * float64(jobMeta.NumNodes)) * (float64(jobMeta.Duration) / 3600.0)) / 1000.0\n\t\t\t\tmetricEnergy = math.Round(rawEnergy*100.0) / 100.0 // Round to 2 decimal places\n\t\t\t}\n\t\t} else {\n\t\t\tcclog.Warnf(\"Error while collecting energy metric %s for job, DB ID '%v', return '0.0'\", fp, jobMeta.ID)\n\t\t}\n\n\t\tenergyFootprint[fp] = metricEnergy\n\t\ttotalEnergy += metricEnergy\n\t}\n\n\tvar rawFootprint []byte\n\tif rawFootprint, err = json.Marshal(energyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling energy footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n\t\treturn stmt, err\n\t}\n\n\treturn stmt.Set(\"energy_footprint\", string(rawFootprint)).Set(\"energy\", (math.Round(totalEnergy*100.0) / 100.0)), nil\n}\n\n// UpdateFootprint calculates and updates the performance footprint for a job.\n// This is called for running jobs during intermediate updates or when archiving.\n//\n// A footprint is a summary statistic (avg/min/max) for each monitored metric.\n// The specific statistic type is defined in the cluster config's Footprint field.\n// Results are stored as JSON with keys like \"metric_avg\", \"metric_max\", etc.\n//\n// Example: For a \"cpu_load\" metric with Footprint=\"avg\", this stores\n// the average CPU load across all nodes as \"cpu_load_avg\": 85.3\nfunc (r *JobRepository) UpdateFootprint(\n\tstmt sq.UpdateBuilder,\n\tjobMeta *schema.Job,\n) (sq.UpdateBuilder, error) {\n\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n\t\treturn stmt, err\n\t}\n\tfootprint := make(map[string]float64)\n\n\t// Build footprint map with metric_stattype as keys\n\tfor _, fp := range sc.Footprint {\n\t\t// Determine which statistic to use: avg, min, or max\n\t\t// First check global metric config, then cluster-specific config\n\t\tvar statType string\n\t\tfor _, gm := range archive.GlobalMetricList {\n\t\t\tif gm.Name == fp {\n\t\t\t\tstatType = gm.Footprint\n\t\t\t}\n\t\t}\n\n\t\t// Validate statistic type\n\t\tif statType != \"avg\" && statType != \"min\" && statType != \"max\" {\n\t\t\tcclog.Warnf(\"unknown statType for footprint update: %s\", statType)\n\t\t\treturn stmt, fmt.Errorf(\"unknown statType for footprint update: %s\", statType)\n\t\t}\n\n\t\t// Override with cluster-specific config if available\n\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err != nil {\n\t\t\tstatType = sc.MetricConfig[i].Footprint\n\t\t}\n\n\t\t// Store as \"metric_stattype\": value (e.g., \"cpu_load_avg\": 85.3)\n\t\tname := fmt.Sprintf(\"%s_%s\", fp, statType)\n\t\tfootprint[name] = LoadJobStat(jobMeta, fp, statType)\n\t}\n\n\tvar rawFootprint []byte\n\tif rawFootprint, err = json.Marshal(footprint); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n\t\treturn stmt, err\n\t}\n\n\treturn stmt.Set(\"footprint\", string(rawFootprint)), nil\n}\n\n// GetUsedNodes returns a map of cluster names to sorted lists of unique hostnames\n// that are currently in use by jobs that started before the given timestamp and\n// are still in running state.\n//\n// The timestamp parameter (ts) is compared against job.start_time to find\n// relevant jobs. Returns an error if the database query fails or row iteration\n// encounters errors. Individual row parsing errors are logged but don't fail\n// the entire operation.\nfunc (r *JobRepository) GetUsedNodes(ts int64) (map[string][]string, error) {\n\t// Note: Query expects index on (job_state, start_time) for optimal performance\n\tq := sq.Select(\"job.cluster\", \"job.resources\").From(\"job\").\n\t\tWhere(\"job.start_time < ?\", ts).\n\t\tWhere(\"job.job_state = 'running'\")\n\n\trows, err := q.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tqueryString, queryVars, _ := q.ToSql()\n\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n\t}\n\tdefer rows.Close()\n\n\t// Use a map of sets for efficient deduplication\n\tnodeSet := make(map[string]map[string]struct{})\n\n\tvar (\n\t\tcluster      string\n\t\trawResources []byte\n\t\tresources    []*schema.Resource\n\t\tskippedRows  int\n\t)\n\n\tfor rows.Next() {\n\t\tif err := rows.Scan(&cluster, &rawResources); err != nil {\n\t\t\tcclog.Warnf(\"Error scanning job row in GetUsedNodes: %v\", err)\n\t\t\tskippedRows++\n\t\t\tcontinue\n\t\t}\n\n\t\tresources = resources[:0] // Clear slice, keep capacity\n\t\tif err := json.Unmarshal(rawResources, &resources); err != nil {\n\t\t\tcclog.Warnf(\"Error unmarshaling resources for cluster %s: %v\", cluster, err)\n\t\t\tskippedRows++\n\t\t\tcontinue\n\t\t}\n\n\t\tif len(resources) == 0 {\n\t\t\tcclog.Debugf(\"Job in cluster %s has no resources\", cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := nodeSet[cluster]; !ok {\n\t\t\tnodeSet[cluster] = make(map[string]struct{})\n\t\t}\n\n\t\tfor _, res := range resources {\n\t\t\tnodeSet[cluster][res.Hostname] = struct{}{}\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, fmt.Errorf(\"error iterating rows: %w\", err)\n\t}\n\n\tif skippedRows > 0 {\n\t\tcclog.Warnf(\"GetUsedNodes: Skipped %d rows due to parsing errors\", skippedRows)\n\t}\n\n\t// Convert sets to sorted slices\n\tnodeList := make(map[string][]string, len(nodeSet))\n\tfor cluster, nodes := range nodeSet {\n\t\tlist := make([]string, 0, len(nodes))\n\t\tfor node := range nodes {\n\t\t\tlist = append(list, node)\n\t\t}\n\t\tsort.Strings(list)\n\t\tnodeList[cluster] = list\n\t}\n\n\treturn nodeList, nil\n}\n","structuredPatch":[{"oldStart":66,"oldLines":6,"newStart":66,"newLines":8,"lines":["   \"fmt\"","   \"maps\"","   \"math\"","+  \"path/filepath\"","+  \"runtime\"","   \"sort\"","   \"strconv\"","   \"sync\""]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"15819832-8055-4e39-bc9d-4a47ece02bd4","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"d4c9cee3-04a0-4ae5-b7f8-7bfdca3a92b4","isSidechain":false,"promptId":"652c48e5-2f9a-4604-a66a-0690cd2d0027","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SZPEX5512qv3fM85xahS4n","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/internal/repository/job.go has been updated successfully."}]},"uuid":"50bcd5bd-22b4-4919-a37d-015b9f4b77cf","timestamp":"2026-03-16T19:01:47.323Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/internal/repository/job.go","oldString":"\tif err := row.Scan(\n\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n\t\tcclog.Warnf(\"Error while scanning rows (Job): %v\", err)\n\t\treturn nil, err\n\t}","newString":"\tif err := row.Scan(\n\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n\t\tif err != sql.ErrNoRows {\n\t\t\t_, file, line, _ := runtime.Caller(1)\n\t\t\tcclog.Warnf(\"Error while scanning rows (Job) (%s:%d): %v\", filepath.Base(file), line, err)\n\t\t}\n\t\treturn nil, err\n\t}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\n// Package repository provides the data access layer for cc-backend using the repository pattern.\n//\n// The repository pattern abstracts database operations and provides a clean interface for\n// data access. Each major entity (Job, User, Node, Tag) has its own repository with CRUD\n// operations and specialized queries.\n//\n// # Database Connection\n//\n// Initialize the database connection before using any repository:\n//\n//\trepository.Connect(\"sqlite3\", \"./var/job.db\")\n//\n// # Configuration\n//\n// Optional: Configure repository settings before initialization:\n//\n//\trepository.SetConfig(&repository.RepositoryConfig{\n//\t    CacheSize: 2 * 1024 * 1024,     // 2MB cache\n//\t    MaxOpenConnections: 8,           // Connection pool size\n//\t    MinRunningJobDuration: 300,      // Filter threshold\n//\t})\n//\n// If not configured, sensible defaults are used automatically.\n//\n// # Repositories\n//\n//   - JobRepository: Job lifecycle management and querying\n//   - UserRepository: User management and authentication\n//   - NodeRepository: Cluster node state tracking\n//   - Tags: Job tagging and categorization\n//\n// # Caching\n//\n// Repositories use LRU caching to improve performance. Cache keys are constructed\n// as \"type:id\" (e.g., \"metadata:123\"). Cache is automatically invalidated on\n// mutations to maintain consistency.\n//\n// # Transaction Support\n//\n// For batch operations, use transactions:\n//\n//\tt, err := jobRepo.TransactionInit()\n//\tif err != nil {\n//\t    return err\n//\t}\n//\tdefer t.Rollback() // Rollback if not committed\n//\n//\t// Perform operations...\n//\tjobRepo.TransactionAdd(t, query, args...)\n//\n//\t// Commit when done\n//\tif err := t.Commit(); err != nil {\n//\t    return err\n//\t}\npackage repository\n\nimport (\n\t\"database/sql\"\n\t\"encoding/json\"\n\t\"errors\"\n\t\"fmt\"\n\t\"maps\"\n\t\"math\"\n\t\"path/filepath\"\n\t\"runtime\"\n\t\"sort\"\n\t\"strconv\"\n\t\"sync\"\n\t\"time\"\n\n\t\"github.com/ClusterCockpit/cc-backend/pkg/archive\"\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/lrucache\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tsq \"github.com/Masterminds/squirrel\"\n\t\"github.com/jmoiron/sqlx\"\n)\n\nvar (\n\t// jobRepoOnce ensures singleton initialization of the JobRepository\n\tjobRepoOnce sync.Once\n\t// jobRepoInstance holds the single instance of JobRepository\n\tjobRepoInstance *JobRepository\n)\n\n// JobRepository provides database access for job-related operations.\n// It implements the repository pattern to abstract database interactions\n// and provides caching for improved performance.\n//\n// The repository is a singleton initialized via GetJobRepository().\n// All database queries use prepared statements via stmtCache for efficiency.\n// Frequently accessed data (metadata, energy footprints) is cached in an LRU cache.\ntype JobRepository struct {\n\tDB        *sqlx.DB        // Database connection pool\n\tstmtCache *sq.StmtCache   // Prepared statement cache for query optimization\n\tcache     *lrucache.Cache // LRU cache for metadata and footprint data\n\tdriver    string          // Database driver name (e.g., \"sqlite3\")\n\tMutex     sync.Mutex      // Mutex for thread-safe operations\n}\n\n// GetJobRepository returns the singleton instance of JobRepository.\n// The repository is initialized lazily on first access with database connection,\n// prepared statement cache, and LRU cache configured from repoConfig.\n//\n// This function is thread-safe and ensures only one instance is created.\n// It must be called after Connect() has established a database connection.\nfunc GetJobRepository() *JobRepository {\n\tjobRepoOnce.Do(func() {\n\t\tdb := GetConnection()\n\n\t\tjobRepoInstance = &JobRepository{\n\t\t\tDB:     db.DB,\n\t\t\tdriver: db.Driver,\n\n\t\t\tstmtCache: sq.NewStmtCache(db.DB),\n\t\t\tcache:     lrucache.New(repoConfig.CacheSize),\n\t\t}\n\t})\n\treturn jobRepoInstance\n}\n\n// jobColumns defines the standard set of columns selected from the job table.\n// Used consistently across all job queries to ensure uniform data retrieval.\nvar jobColumns []string = []string{\n\t\"job.id\", \"job.job_id\", \"job.hpc_user\", \"job.project\", \"job.cluster\", \"job.subcluster\",\n\t\"job.start_time\", \"job.cluster_partition\", \"job.array_job_id\", \"job.num_nodes\",\n\t\"job.num_hwthreads\", \"job.num_acc\", \"job.shared\", \"job.monitoring_status\",\n\t\"job.smt\", \"job.job_state\", \"job.duration\", \"job.walltime\", \"job.resources\",\n\t\"job.footprint\", \"job.energy\",\n}\n\n// jobCacheColumns defines columns from the job_cache table, mirroring jobColumns.\n// Used for queries against cached job data for performance optimization.\nvar jobCacheColumns []string = []string{\n\t\"job_cache.id\", \"job_cache.job_id\", \"job_cache.hpc_user\", \"job_cache.project\", \"job_cache.cluster\",\n\t\"job_cache.subcluster\", \"job_cache.start_time\", \"job_cache.cluster_partition\",\n\t\"job_cache.array_job_id\", \"job_cache.num_nodes\", \"job_cache.num_hwthreads\",\n\t\"job_cache.num_acc\", \"job_cache.shared\", \"job_cache.monitoring_status\", \"job_cache.smt\",\n\t\"job_cache.job_state\", \"job_cache.duration\", \"job_cache.walltime\", \"job_cache.resources\",\n\t\"job_cache.footprint\", \"job_cache.energy\",\n}\n\n// scanJob converts a database row into a schema.Job struct.\n// It handles JSON unmarshaling of resources and footprint fields,\n// and calculates accurate duration for running jobs.\n//\n// Parameters:\n//   - row: Database row implementing Scan() interface (sql.Row or sql.Rows)\n//\n// Returns the populated Job struct or an error if scanning or unmarshaling fails.\nfunc scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {\n\tjob := &schema.Job{}\n\n\tif err := row.Scan(\n\t\t&job.ID, &job.JobID, &job.User, &job.Project, &job.Cluster, &job.SubCluster,\n\t\t&job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,\n\t\t&job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,\n\t\t&job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {\n\t\tcclog.Warnf(\"Error while scanning rows (Job): %v\", err)\n\t\treturn nil, err\n\t}\n\n\tif err := json.Unmarshal(job.RawResources, &job.Resources); err != nil {\n\t\tcclog.Warn(\"Error while unmarshaling raw resources json\")\n\t\treturn nil, err\n\t}\n\tjob.RawResources = nil\n\n\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json: %v\", err)\n\t\treturn nil, err\n\t}\n\tjob.RawFootprint = nil\n\n\t// Always ensure accurate duration for running jobs\n\tif job.State == schema.JobStateRunning {\n\t\tjob.Duration = int32(time.Now().Unix() - job.StartTime)\n\t}\n\n\treturn job, nil\n}\n\n// Optimize performs database optimization by running VACUUM command.\n// This reclaims unused space and defragments the database file.\n// Should be run periodically during maintenance windows.\nfunc (r *JobRepository) Optimize() error {\n\tif _, err := r.DB.Exec(`VACUUM`); err != nil {\n\t\tcclog.Errorf(\"Error while executing VACUUM: %v\", err)\n\t\treturn fmt.Errorf(\"failed to optimize database: %w\", err)\n\t}\n\treturn nil\n}\n\n// Flush removes all data from job-related tables (jobtag, tag, job).\n// WARNING: This is a destructive operation that deletes all job data.\n// Use with extreme caution, typically only for testing or complete resets.\nfunc (r *JobRepository) Flush() error {\n\tif _, err := r.DB.Exec(`DELETE FROM jobtag`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from jobtag table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush jobtag table: %w\", err)\n\t}\n\tif _, err := r.DB.Exec(`DELETE FROM tag`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from tag table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush tag table: %w\", err)\n\t}\n\tif _, err := r.DB.Exec(`DELETE FROM job`); err != nil {\n\t\tcclog.Errorf(\"Error while deleting from job table: %v\", err)\n\t\treturn fmt.Errorf(\"failed to flush job table: %w\", err)\n\t}\n\treturn nil\n}\n\n// FetchMetadata retrieves and unmarshals the metadata JSON for a job.\n// Metadata is cached with a 24-hour TTL to improve performance.\n//\n// The metadata field stores arbitrary key-value pairs associated with a job,\n// such as tags, labels, or custom attributes added by external systems.\n//\n// Parameters:\n//   - job: Job struct with valid ID field, metadata will be populated in job.MetaData\n//\n// Returns the metadata map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchMetadata(job *schema.Job) (map[string]string, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n\t\tjob.MetaData = cached.(map[string]string)\n\t\treturn job.MetaData, nil\n\t}\n\n\tif err := sq.Select(\"job.meta_data\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawMetaData); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job metadata (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawMetaData) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawMetaData, &job.MetaData); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw metadata json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n\tcclog.Debugf(\"Timer FetchMetadata %s\", time.Since(start))\n\treturn job.MetaData, nil\n}\n\n// UpdateMetadata adds or updates a single metadata key-value pair for a job.\n// The entire metadata map is re-marshaled and stored, and the cache is invalidated.\n// Also triggers archive metadata update via archive.UpdateMetadata.\n//\n// Parameters:\n//   - job: Job struct with valid ID, existing metadata will be fetched if not present\n//   - key: Metadata key to set\n//   - val: Metadata value to set\n//\n// Returns an error if the job is nil, metadata fetch fails, or database update fails.\nfunc (r *JobRepository) UpdateMetadata(job *schema.Job, key, val string) (err error) {\n\tif job == nil {\n\t\treturn fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tcachekey := fmt.Sprintf(\"metadata:%d\", *job.ID)\n\tr.cache.Del(cachekey)\n\tif job.MetaData == nil {\n\t\tif _, err = r.FetchMetadata(job); err != nil {\n\t\t\tcclog.Warnf(\"Error while fetching metadata for job, DB ID '%v'\", *job.ID)\n\t\t\treturn fmt.Errorf(\"failed to fetch metadata for job %d: %w\", *job.ID, err)\n\t\t}\n\t}\n\n\tif job.MetaData != nil {\n\t\tcpy := make(map[string]string, len(job.MetaData)+1)\n\t\tmaps.Copy(cpy, job.MetaData)\n\t\tcpy[key] = val\n\t\tjob.MetaData = cpy\n\t} else {\n\t\tjob.MetaData = map[string]string{key: val}\n\t}\n\n\tif job.RawMetaData, err = json.Marshal(job.MetaData); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling metadata for job, DB ID '%v'\", *job.ID)\n\t\treturn fmt.Errorf(\"failed to marshal metadata for job %d: %w\", *job.ID, err)\n\t}\n\n\tif _, err = sq.Update(\"job\").\n\t\tSet(\"meta_data\", job.RawMetaData).\n\t\tWhere(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Warnf(\"Error while updating metadata for job, DB ID '%v'\", *job.ID)\n\t\treturn fmt.Errorf(\"failed to update metadata in database for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.MetaData, len(job.RawMetaData), 24*time.Hour)\n\treturn archive.UpdateMetadata(job, job.MetaData)\n}\n\n// FetchFootprint retrieves and unmarshals the performance footprint JSON for a job.\n// Unlike FetchMetadata, footprints are NOT cached as they can be large and change frequently.\n//\n// The footprint contains summary statistics (avg/min/max) for monitored metrics,\n// stored as JSON with keys like \"cpu_load_avg\", \"mem_used_max\", etc.\n//\n// Parameters:\n//   - job: Job struct with valid ID, footprint will be populated in job.Footprint\n//\n// Returns the footprint map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchFootprint(job *schema.Job) (map[string]float64, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\n\tif err := sq.Select(\"job.footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job footprint (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawFootprint) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawFootprint, &job.Footprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw footprint json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tcclog.Debugf(\"Timer FetchFootprint %s\", time.Since(start))\n\treturn job.Footprint, nil\n}\n\n// FetchEnergyFootprint retrieves and unmarshals the energy footprint JSON for a job.\n// Energy footprints are cached with a 24-hour TTL as they are frequently accessed but rarely change.\n//\n// The energy footprint contains calculated energy consumption (in kWh) per metric,\n// stored as JSON with keys like \"power_avg\", \"acc_power_avg\", etc.\n//\n// Parameters:\n//   - job: Job struct with valid ID, energy footprint will be populated in job.EnergyFootprint\n//\n// Returns the energy footprint map or an error if the job is nil or database query fails.\nfunc (r *JobRepository) FetchEnergyFootprint(job *schema.Job) (map[string]float64, error) {\n\tif job == nil {\n\t\treturn nil, fmt.Errorf(\"job cannot be nil\")\n\t}\n\n\tstart := time.Now()\n\tcachekey := fmt.Sprintf(\"energyFootprint:%d\", *job.ID)\n\tif cached := r.cache.Get(cachekey, nil); cached != nil {\n\t\tjob.EnergyFootprint = cached.(map[string]float64)\n\t\treturn job.EnergyFootprint, nil\n\t}\n\n\tif err := sq.Select(\"job.energy_footprint\").From(\"job\").Where(\"job.id = ?\", job.ID).\n\t\tRunWith(r.stmtCache).QueryRow().Scan(&job.RawEnergyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while scanning for job energy_footprint (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to fetch energy footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tif len(job.RawEnergyFootprint) == 0 {\n\t\treturn nil, nil\n\t}\n\n\tif err := json.Unmarshal(job.RawEnergyFootprint, &job.EnergyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while unmarshaling raw energy footprint json (ID=%d): %v\", *job.ID, err)\n\t\treturn nil, fmt.Errorf(\"failed to unmarshal energy footprint for job %d: %w\", *job.ID, err)\n\t}\n\n\tr.cache.Put(cachekey, job.EnergyFootprint, len(job.EnergyFootprint), 24*time.Hour)\n\tcclog.Debugf(\"Timer FetchEnergyFootprint %s\", time.Since(start))\n\treturn job.EnergyFootprint, nil\n}\n\n// DeleteJobsBefore removes jobs older than the specified start time.\n// Optionally preserves tagged jobs to protect important data from deletion.\n// Cache entries for deleted jobs are automatically invalidated.\n//\n// This is typically used for data retention policies and cleanup operations.\n// WARNING: This is a destructive operation that permanently deletes job records.\n//\n// Parameters:\n//   - startTime: Unix timestamp, jobs with start_time < this value will be deleted\n//   - omitTagged: \"none\" = delete all jobs, \"all\" = skip any tagged jobs,\n//     \"user\" = skip jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n//\n// Returns the count of deleted jobs or an error if the operation fails.\nfunc (r *JobRepository) DeleteJobsBefore(startTime int64, omitTagged string) (int, error) {\n\tvar cnt int\n\tq := sq.Select(\"count(*)\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tq = q.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\n\tif err := q.RunWith(r.DB).QueryRow().Scan(&cnt); err != nil {\n\t\tcclog.Errorf(\"Error counting jobs before %d: %v\", startTime, err)\n\t\treturn 0, err\n\t}\n\n\t// Invalidate cache for jobs being deleted (get job IDs first)\n\tif cnt > 0 {\n\t\tvar jobIds []int64\n\t\tselectQuery := sq.Select(\"id\").From(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\t\tswitch omitTagged {\n\t\tcase \"all\":\n\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\t\tcase \"user\":\n\t\t\tselectQuery = selectQuery.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t\t}\n\n\t\trows, err := selectQuery.RunWith(r.DB).Query()\n\t\tif err == nil {\n\t\t\tdefer rows.Close()\n\t\t\tfor rows.Next() {\n\t\t\t\tvar id int64\n\t\t\t\tif err := rows.Scan(&id); err == nil {\n\t\t\t\t\tjobIds = append(jobIds, id)\n\t\t\t\t}\n\t\t\t}\n\t\t\t// Invalidate cache entries\n\t\t\tfor _, id := range jobIds {\n\t\t\t\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n\t\t\t\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n\t\t\t}\n\t\t}\n\t}\n\n\tqd := sq.Delete(\"job\").Where(\"job.start_time < ?\", startTime)\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tqd = qd.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\t_, err := qd.RunWith(r.DB).Exec()\n\n\tif err != nil {\n\t\ts, _, _ := qd.ToSql()\n\t\tcclog.Errorf(\" DeleteJobsBefore(%d) with %s: error %#v\", startTime, s, err)\n\t} else {\n\t\tcclog.Debugf(\"DeleteJobsBefore(%d): Deleted %d jobs\", startTime, cnt)\n\t}\n\treturn cnt, err\n}\n\n// DeleteJobByID permanently removes a single job by its database ID.\n// Cache entries for the deleted job are automatically invalidated.\n//\n// Parameters:\n//   - id: Database ID (primary key) of the job to delete\n//\n// Returns an error if the deletion fails.\nfunc (r *JobRepository) DeleteJobByID(id int64) error {\n\t// Invalidate cache entries before deletion\n\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", id))\n\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", id))\n\n\tqd := sq.Delete(\"job\").Where(\"job.id = ?\", id)\n\t_, err := qd.RunWith(r.DB).Exec()\n\n\tif err != nil {\n\t\ts, _, _ := qd.ToSql()\n\t\tcclog.Errorf(\"DeleteJobById(%d) with %s : error %#v\", id, s, err)\n\t} else {\n\t\tcclog.Debugf(\"DeleteJobById(%d): Success\", id)\n\t}\n\treturn err\n}\n\n// FindUserOrProjectOrJobname attempts to interpret a search term as a job ID,\n// username, project ID, or job name by querying the database.\n//\n// Search logic (in priority order):\n//  1. If searchterm is numeric, treat as job ID (returned immediately)\n//  2. Try exact match in job.hpc_user column (username)\n//  3. Try LIKE match in hpc_user.name column (real name)\n//  4. Try exact match in job.project column (project ID)\n//  5. If no matches, return searchterm as jobname for GraphQL query\n//\n// This powers the searchbar functionality for flexible job searching.\n// Requires authenticated user for database lookups (returns empty if user is nil).\n//\n// Parameters:\n//   - user: Authenticated user context, required for database access\n//   - searchterm: Search string to interpret\n//\n// Returns up to one non-empty value among (jobid, username, project, jobname).\nfunc (r *JobRepository) FindUserOrProjectOrJobname(user *schema.User, searchterm string) (jobid string, username string, project string, jobname string) {\n\tif searchterm == \"\" {\n\t\treturn \"\", \"\", \"\", \"\"\n\t}\n\n\tif _, err := strconv.Atoi(searchterm); err == nil { // Return empty on successful conversion: parent method will redirect for integer jobId\n\t\treturn searchterm, \"\", \"\", \"\"\n\t} else { // Has to have letters and logged-in user for other guesses\n\t\tif user != nil {\n\t\t\t// Find username by username in job table (match)\n\t\t\turesult, _ := r.FindColumnValue(user, searchterm, \"job\", \"hpc_user\", \"hpc_user\", false)\n\t\t\tif uresult != \"\" {\n\t\t\t\treturn \"\", uresult, \"\", \"\"\n\t\t\t}\n\t\t\t// Find username by real name in hpc_user table (like)\n\t\t\tnresult, _ := r.FindColumnValue(user, searchterm, \"hpc_user\", \"username\", \"name\", true)\n\t\t\tif nresult != \"\" {\n\t\t\t\treturn \"\", nresult, \"\", \"\"\n\t\t\t}\n\t\t\t// Find projectId by projectId in job table (match)\n\t\t\tpresult, _ := r.FindColumnValue(user, searchterm, \"job\", \"project\", \"project\", false)\n\t\t\tif presult != \"\" {\n\t\t\t\treturn \"\", \"\", presult, \"\"\n\t\t\t}\n\t\t}\n\t\t// Return searchterm if no match before: Forward as jobname query to GQL in handleSearchbar function\n\t\treturn \"\", \"\", \"\", searchterm\n\t}\n}\n\nvar (\n\tErrNotFound  = errors.New(\"no such jobname, project or user\")\n\tErrForbidden = errors.New(\"not authorized\")\n)\n\n// FindColumnValue performs a generic column lookup in a database table with role-based access control.\n// Only users with admin, support, or manager roles can execute this query.\n//\n// Parameters:\n//   - user: User context for authorization check\n//   - searchterm: Value to search for (exact match or LIKE pattern)\n//   - table: Database table name to query\n//   - selectColumn: Column name to return in results\n//   - whereColumn: Column name to filter on\n//   - isLike: If true, use LIKE with wildcards; if false, use exact equality\n//\n// Returns the first matching value, ErrForbidden if user lacks permission,\n// or ErrNotFound if no matches are found.\nfunc (r *JobRepository) FindColumnValue(user *schema.User, searchterm string, table string, selectColumn string, whereColumn string, isLike bool) (result string, err error) {\n\tif user == nil {\n\t\treturn \"\", fmt.Errorf(\"user cannot be nil\")\n\t}\n\n\tcompareStr := \" = ?\"\n\tquery := searchterm\n\tif isLike {\n\t\tcompareStr = \" LIKE ?\"\n\t\tquery = \"%\" + searchterm + \"%\"\n\t}\n\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\ttheQuery := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n\t\t\tWhere(table+\".\"+whereColumn+compareStr, query)\n\n\t\terr := theQuery.RunWith(r.stmtCache).QueryRow().Scan(&result)\n\n\t\tif err != nil && err != sql.ErrNoRows {\n\t\t\tcclog.Warnf(\"Error while querying FindColumnValue (table=%s, column=%s): %v\", table, selectColumn, err)\n\t\t\treturn \"\", fmt.Errorf(\"failed to find column value: %w\", err)\n\t\t} else if err == nil {\n\t\t\treturn result, nil\n\t\t}\n\t\treturn \"\", ErrNotFound\n\t} else {\n\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)\n\t\treturn \"\", ErrForbidden\n\t}\n}\n\n// FindColumnValues performs a generic column lookup returning multiple matches with role-based access control.\n// Similar to FindColumnValue but returns all matching values instead of just the first.\n// Only users with admin, support, or manager roles can execute this query.\n//\n// Parameters:\n//   - user: User context for authorization check\n//   - query: Search pattern (always uses LIKE with wildcards)\n//   - table: Database table name to query\n//   - selectColumn: Column name to return in results\n//   - whereColumn: Column name to filter on\n//\n// Returns a slice of matching values, ErrForbidden if user lacks permission,\n// or ErrNotFound if no matches are found.\nfunc (r *JobRepository) FindColumnValues(user *schema.User, query string, table string, selectColumn string, whereColumn string) (results []string, err error) {\n\tif user == nil {\n\t\treturn nil, fmt.Errorf(\"user cannot be nil\")\n\t}\n\n\temptyResult := make([]string, 0)\n\tif user.HasAnyRole([]schema.Role{schema.RoleAdmin, schema.RoleSupport, schema.RoleManager}) {\n\t\trows, err := sq.Select(table+\".\"+selectColumn).Distinct().From(table).\n\t\t\tWhere(table+\".\"+whereColumn+\" LIKE ?\", fmt.Sprint(\"%\", query, \"%\")).\n\t\t\tRunWith(r.stmtCache).Query()\n\t\tif err != nil && err != sql.ErrNoRows {\n\t\t\tcclog.Errorf(\"Error while querying FindColumnValues (table=%s, column=%s): %v\", table, selectColumn, err)\n\t\t\treturn emptyResult, fmt.Errorf(\"failed to find column values: %w\", err)\n\t\t} else if err == nil {\n\t\t\tdefer rows.Close()\n\t\t\tfor rows.Next() {\n\t\t\t\tvar result string\n\t\t\t\terr := rows.Scan(&result)\n\t\t\t\tif err != nil {\n\t\t\t\t\tcclog.Warnf(\"Error while scanning rows in FindColumnValues: %v\", err)\n\t\t\t\t\treturn emptyResult, fmt.Errorf(\"failed to scan column value: %w\", err)\n\t\t\t\t}\n\t\t\t\tresults = append(results, result)\n\t\t\t}\n\t\t\treturn results, nil\n\t\t}\n\t\treturn emptyResult, ErrNotFound\n\n\t} else {\n\t\tcclog.Infof(\"Non-Admin User %s : Requested Query '%s' on table '%s' : Forbidden\", user.Name, query, table)\n\t\treturn emptyResult, ErrForbidden\n\t}\n}\n\n// Partitions returns a list of distinct cluster partitions for a given cluster.\n// Results are cached with a 1-hour TTL to improve performance.\n//\n// Parameters:\n//   - cluster: Cluster name to query partitions for\n//\n// Returns a slice of partition names or an error if the database query fails.\nfunc (r *JobRepository) Partitions(cluster string) ([]string, error) {\n\tvar err error\n\tstart := time.Now()\n\tpartitions := r.cache.Get(\"partitions:\"+cluster, func() (any, time.Duration, int) {\n\t\tparts := []string{}\n\t\tif err = r.DB.Select(&parts, `SELECT DISTINCT job.cluster_partition FROM job WHERE job.cluster = ?;`, cluster); err != nil {\n\t\t\treturn nil, 0, 1000\n\t\t}\n\n\t\treturn parts, 1 * time.Hour, 1\n\t})\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tcclog.Debugf(\"Timer Partitions %s\", time.Since(start))\n\treturn partitions.([]string), nil\n}\n\n// AllocatedNodes returns a map of all subclusters to a map of hostnames to the amount of jobs running on that host.\n// Hosts with zero jobs running on them will not show up!\nfunc (r *JobRepository) AllocatedNodes(cluster string) (map[string]map[string]int, error) {\n\tstart := time.Now()\n\tsubclusters := make(map[string]map[string]int)\n\trows, err := sq.Select(\"resources\", \"subcluster\").From(\"job\").\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.cluster = ?\", cluster).\n\t\tRunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running AllocatedNodes query for cluster=%s: %v\", cluster, err)\n\t\treturn nil, fmt.Errorf(\"failed to query allocated nodes for cluster %s: %w\", cluster, err)\n\t}\n\n\tvar raw []byte\n\tdefer rows.Close()\n\tfor rows.Next() {\n\t\traw = raw[0:0]\n\t\tvar resources []*schema.Resource\n\t\tvar subcluster string\n\t\tif err := rows.Scan(&raw, &subcluster); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in AllocatedNodes: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan allocated nodes row: %w\", err)\n\t\t}\n\t\tif err := json.Unmarshal(raw, &resources); err != nil {\n\t\t\tcclog.Warnf(\"Error while unmarshaling raw resources json in AllocatedNodes: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to unmarshal resources in AllocatedNodes: %w\", err)\n\t\t}\n\n\t\thosts, ok := subclusters[subcluster]\n\t\tif !ok {\n\t\t\thosts = make(map[string]int)\n\t\t\tsubclusters[subcluster] = hosts\n\t\t}\n\n\t\tfor _, resource := range resources {\n\t\t\thosts[resource.Hostname] += 1\n\t\t}\n\t}\n\n\tcclog.Debugf(\"Timer AllocatedNodes %s\", time.Since(start))\n\treturn subclusters, nil\n}\n\n// StopJobsExceedingWalltimeBy marks running jobs as failed if they exceed their walltime limit.\n// This is typically called periodically to clean up stuck or orphaned jobs.\n//\n// Jobs are marked with:\n//   - monitoring_status: MonitoringStatusArchivingFailed\n//   - duration: 0\n//   - job_state: JobStateFailed\n//\n// Parameters:\n//   - seconds: Grace period beyond walltime before marking as failed\n//\n// Returns an error if the database update fails.\n// Logs the number of jobs marked as failed if any were affected.\nfunc (r *JobRepository) StopJobsExceedingWalltimeBy(seconds int) error {\n\tstart := time.Now()\n\tcurrentTime := time.Now().Unix()\n\tres, err := sq.Update(\"job\").\n\t\tSet(\"monitoring_status\", schema.MonitoringStatusArchivingFailed).\n\t\tSet(\"duration\", 0).\n\t\tSet(\"job_state\", schema.JobStateFailed).\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.walltime > 0\").\n\t\tWhere(\"job.start_time < (? - job.walltime)\", currentTime-int64(seconds)).\n\t\tRunWith(r.DB).Exec()\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while stopping jobs exceeding walltime: %v\", err)\n\t\treturn fmt.Errorf(\"failed to stop jobs exceeding walltime: %w\", err)\n\t}\n\n\trowsAffected, err := res.RowsAffected()\n\tif err != nil {\n\t\tcclog.Warnf(\"Error while fetching affected rows after stopping due to exceeded walltime: %v\", err)\n\t\treturn fmt.Errorf(\"failed to get rows affected count: %w\", err)\n\t}\n\n\tif rowsAffected > 0 {\n\t\tcclog.Infof(\"%d jobs have been marked as failed due to running too long\", rowsAffected)\n\t}\n\tcclog.Debugf(\"Timer StopJobsExceedingWalltimeBy %s\", time.Since(start))\n\treturn nil\n}\n\n// FindJobIdsByTag returns all job database IDs associated with a specific tag.\n//\n// Parameters:\n//   - tagID: Database ID of the tag to search for\n//\n// Returns a slice of job IDs or an error if the query fails.\nfunc (r *JobRepository) FindJobIdsByTag(tagID int64) ([]int64, error) {\n\tquery := sq.Select(\"job.id\").From(\"job\").\n\t\tJoin(\"jobtag ON jobtag.job_id = job.id\").\n\t\tWhere(sq.Eq{\"jobtag.tag_id\": tagID}).Distinct()\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindJobIdsByTag query for tagID=%d: %v\", tagID, err)\n\t\treturn nil, fmt.Errorf(\"failed to find job IDs by tag %d: %w\", tagID, err)\n\t}\n\tdefer rows.Close()\n\n\tjobIds := make([]int64, 0, 100)\n\n\tfor rows.Next() {\n\t\tvar jobID int64\n\n\t\tif err := rows.Scan(&jobID); err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobIdsByTag: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job ID in FindJobIdsByTag: %w\", err)\n\t\t}\n\n\t\tjobIds = append(jobIds, jobID)\n\t}\n\n\treturn jobIds, nil\n}\n\n// FindRunningJobs returns all currently running jobs for a specific cluster.\n// Filters out short-running jobs based on repoConfig.MinRunningJobDuration threshold.\n//\n// Parameters:\n//   - cluster: Cluster name to filter jobs\n//\n// Returns a slice of running job objects or an error if the query fails.\nfunc (r *JobRepository) FindRunningJobs(cluster string) ([]*schema.Job, error) {\n\tquery := sq.Select(jobColumns...).From(\"job\").\n\t\tWhere(\"job.cluster = ?\", cluster).\n\t\tWhere(\"job.job_state = 'running'\").\n\t\tWhere(\"job.duration > ?\", repoConfig.MinRunningJobDuration)\n\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindRunningJobs query for cluster=%s: %v\", cluster, err)\n\t\treturn nil, fmt.Errorf(\"failed to find running jobs for cluster %s: %w\", cluster, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, 50)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindRunningJobs: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindRunningJobs: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tcclog.Debugf(\"JobRepository.FindRunningJobs(): Return job count %d (cluster: %s)\", len(jobs), cluster)\n\treturn jobs, nil\n}\n\n// UpdateDuration recalculates and updates the duration field for all running jobs.\n// Called periodically to keep job durations current without querying individual jobs.\n//\n// Duration is calculated as: current_time - job.start_time\n//\n// Returns an error if the database update fails.\nfunc (r *JobRepository) UpdateDuration() error {\n\tstmnt := sq.Update(\"job\").\n\t\tSet(\"duration\", sq.Expr(\"? - job.start_time\", time.Now().Unix())).\n\t\tWhere(\"job_state = 'running'\")\n\n\t_, err := stmnt.RunWith(r.stmtCache).Exec()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while updating duration for running jobs: %v\", err)\n\t\treturn fmt.Errorf(\"failed to update duration for running jobs: %w\", err)\n\t}\n\n\treturn nil\n}\n\n// FindJobsBetween returns jobs within a specified time range.\n// If startTimeBegin is 0, returns all jobs before startTimeEnd.\n// Optionally excludes tagged jobs from results.\n//\n// Parameters:\n//   - startTimeBegin: Unix timestamp for range start (use 0 for unbounded start)\n//   - startTimeEnd: Unix timestamp for range end\n//   - omitTagged: \"none\" = include all jobs, \"all\" = exclude any tagged jobs,\n//     \"user\" = exclude jobs with user-created tags (not auto-tagger types \"app\"/\"jobClass\")\n//\n// Returns a slice of jobs or an error if the time range is invalid or query fails.\nfunc (r *JobRepository) FindJobsBetween(startTimeBegin int64, startTimeEnd int64, omitTagged string) ([]*schema.Job, error) {\n\tvar query sq.SelectBuilder\n\n\tif startTimeBegin == startTimeEnd || startTimeBegin > startTimeEnd {\n\t\treturn nil, errors.New(\"startTimeBegin is equal or larger startTimeEnd\")\n\t}\n\n\tif startTimeBegin == 0 {\n\t\tcclog.Infof(\"Find jobs before %d\", startTimeEnd)\n\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time < ?\", startTimeEnd)\n\t} else {\n\t\tcclog.Infof(\"Find jobs between %d and %d\", startTimeBegin, startTimeEnd)\n\t\tquery = sq.Select(jobColumns...).From(\"job\").Where(\"job.start_time BETWEEN ? AND ?\", startTimeBegin, startTimeEnd)\n\t}\n\n\tswitch omitTagged {\n\tcase \"all\":\n\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag WHERE jobtag.job_id = job.id)\")\n\tcase \"user\":\n\t\tquery = query.Where(\"NOT EXISTS (SELECT 1 FROM jobtag JOIN tag ON tag.id = jobtag.tag_id WHERE jobtag.job_id = job.id AND tag.tag_type NOT IN ('app', 'jobClass'))\")\n\t}\n\n\tquery = query.OrderBy(\"job.cluster ASC\", \"job.subcluster ASC\", \"job.project ASC\", \"job.start_time ASC\")\n\n\trows, err := query.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tcclog.Errorf(\"Error while running FindJobsBetween query: %v\", err)\n\t\treturn nil, fmt.Errorf(\"failed to find jobs between %d and %d: %w\", startTimeBegin, startTimeEnd, err)\n\t}\n\tdefer rows.Close()\n\n\tjobs := make([]*schema.Job, 0, 50)\n\tfor rows.Next() {\n\t\tjob, err := scanJob(rows)\n\t\tif err != nil {\n\t\t\tcclog.Warnf(\"Error while scanning rows in FindJobsBetween: %v\", err)\n\t\t\treturn nil, fmt.Errorf(\"failed to scan job in FindJobsBetween: %w\", err)\n\t\t}\n\t\tjobs = append(jobs, job)\n\t}\n\n\tcclog.Debugf(\"JobRepository.FindJobsBetween(): Return job count %d (omitTagged: %v)\", len(jobs), omitTagged)\n\treturn jobs, nil\n}\n\n// UpdateMonitoringStatus updates the monitoring status for a job and invalidates its cache entries.\n// Cache invalidation affects both metadata and energy footprint to ensure consistency.\n//\n// Parameters:\n//   - job: Database ID of the job to update\n//   - monitoringStatus: New monitoring status value (see schema.MonitoringStatus constants)\n//\n// Returns an error if the database update fails.\nfunc (r *JobRepository) UpdateMonitoringStatus(job int64, monitoringStatus int32) (err error) {\n\t// Invalidate cache entries as monitoring status affects job state\n\tr.cache.Del(fmt.Sprintf(\"metadata:%d\", job))\n\tr.cache.Del(fmt.Sprintf(\"energyFootprint:%d\", job))\n\n\tstmt := sq.Update(\"job\").\n\t\tSet(\"monitoring_status\", monitoringStatus).\n\t\tWhere(\"job.id = ?\", job)\n\n\tif _, err = stmt.RunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while updating monitoring status for job %d: %v\", job, err)\n\t\treturn fmt.Errorf(\"failed to update monitoring status for job %d: %w\", job, err)\n\t}\n\treturn nil\n}\n\n// Execute runs a Squirrel UpdateBuilder statement against the database.\n// This is a generic helper for executing pre-built update queries.\n//\n// Parameters:\n//   - stmt: Squirrel UpdateBuilder with prepared update query\n//\n// Returns an error if the execution fails.\nfunc (r *JobRepository) Execute(stmt sq.UpdateBuilder) error {\n\tif _, err := stmt.RunWith(r.stmtCache).Exec(); err != nil {\n\t\tcclog.Errorf(\"Error while executing statement: %v\", err)\n\t\treturn fmt.Errorf(\"failed to execute update statement: %w\", err)\n\t}\n\n\treturn nil\n}\n\n// MarkArchived adds monitoring status update to an existing UpdateBuilder statement.\n// This is a builder helper used when constructing multi-field update queries.\n//\n// Parameters:\n//   - stmt: Existing UpdateBuilder to modify\n//   - monitoringStatus: Monitoring status value to set\n//\n// Returns the modified UpdateBuilder for method chaining.\nfunc (r *JobRepository) MarkArchived(\n\tstmt sq.UpdateBuilder,\n\tmonitoringStatus int32,\n) sq.UpdateBuilder {\n\treturn stmt.Set(\"monitoring_status\", monitoringStatus)\n}\n\n// UpdateEnergy calculates and updates the energy consumption for a job.\n// This is called for running jobs during intermediate updates or when archiving.\n//\n// Energy calculation formula:\n//   - For \"power\" metrics: Energy (kWh) = (Power_avg * NumNodes * Duration_hours) / 1000\n//   - For \"energy\" metrics: Currently not implemented (would need sum statistics)\n//\n// The calculation accounts for:\n//   - Multi-node jobs: Multiplies by NumNodes to get total cluster energy\n//   - Shared jobs: Node average is already based on partial resources, so NumNodes=1\n//   - Unit conversion: Watts * hours / 1000 = kilowatt-hours (kWh)\n//   - Rounding: Results rounded to 2 decimal places\nfunc (r *JobRepository) UpdateEnergy(\n\tstmt sq.UpdateBuilder,\n\tjobMeta *schema.Job,\n) (sq.UpdateBuilder, error) {\n\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n\t\treturn stmt, err\n\t}\n\tenergyFootprint := make(map[string]float64)\n\n\t// Accumulate total energy across all energy-related metrics\n\ttotalEnergy := 0.0\n\tfor _, fp := range sc.EnergyFootprint {\n\t\t// Calculate energy for this specific metric\n\t\tmetricEnergy := 0.0\n\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err == nil {\n\t\t\tswitch sc.MetricConfig[i].Energy {\n\t\t\tcase \"energy\": // Metric already in energy units (Joules or Wh)\n\t\t\t\tcclog.Warnf(\"Update EnergyFootprint for Job %d and Metric %s on cluster %s: Set to 'energy' in cluster.json: Not implemented, will return 0.0\", jobMeta.JobID, jobMeta.Cluster, fp)\n\t\t\t\t// FIXME: Needs sum as stats type to accumulate energy values over time\n\t\t\tcase \"power\": // Metric in power units (Watts)\n\t\t\t\t// Energy (kWh) = Power (W) × Time (h) / 1000\n\t\t\t\t// Formula: (avg_power_per_node * num_nodes) * (duration_sec / 3600) / 1000\n\t\t\t\t//\n\t\t\t\t// Breakdown:\n\t\t\t\t//   LoadJobStat(jobMeta, fp, \"avg\") = average power per node (W)\n\t\t\t\t//   jobMeta.NumNodes = number of nodes (1 for shared jobs)\n\t\t\t\t//   jobMeta.Duration / 3600.0 = duration in hours\n\t\t\t\t//   / 1000.0 = convert Wh to kWh\n\t\t\t\trawEnergy := ((LoadJobStat(jobMeta, fp, \"avg\") * float64(jobMeta.NumNodes)) * (float64(jobMeta.Duration) / 3600.0)) / 1000.0\n\t\t\t\tmetricEnergy = math.Round(rawEnergy*100.0) / 100.0 // Round to 2 decimal places\n\t\t\t}\n\t\t} else {\n\t\t\tcclog.Warnf(\"Error while collecting energy metric %s for job, DB ID '%v', return '0.0'\", fp, jobMeta.ID)\n\t\t}\n\n\t\tenergyFootprint[fp] = metricEnergy\n\t\ttotalEnergy += metricEnergy\n\t}\n\n\tvar rawFootprint []byte\n\tif rawFootprint, err = json.Marshal(energyFootprint); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling energy footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n\t\treturn stmt, err\n\t}\n\n\treturn stmt.Set(\"energy_footprint\", string(rawFootprint)).Set(\"energy\", (math.Round(totalEnergy*100.0) / 100.0)), nil\n}\n\n// UpdateFootprint calculates and updates the performance footprint for a job.\n// This is called for running jobs during intermediate updates or when archiving.\n//\n// A footprint is a summary statistic (avg/min/max) for each monitored metric.\n// The specific statistic type is defined in the cluster config's Footprint field.\n// Results are stored as JSON with keys like \"metric_avg\", \"metric_max\", etc.\n//\n// Example: For a \"cpu_load\" metric with Footprint=\"avg\", this stores\n// the average CPU load across all nodes as \"cpu_load_avg\": 85.3\nfunc (r *JobRepository) UpdateFootprint(\n\tstmt sq.UpdateBuilder,\n\tjobMeta *schema.Job,\n) (sq.UpdateBuilder, error) {\n\tsc, err := archive.GetSubCluster(jobMeta.Cluster, jobMeta.SubCluster)\n\tif err != nil {\n\t\tcclog.Errorf(\"cannot get subcluster: %s\", err.Error())\n\t\treturn stmt, err\n\t}\n\tfootprint := make(map[string]float64)\n\n\t// Build footprint map with metric_stattype as keys\n\tfor _, fp := range sc.Footprint {\n\t\t// Determine which statistic to use: avg, min, or max\n\t\t// First check global metric config, then cluster-specific config\n\t\tvar statType string\n\t\tfor _, gm := range archive.GlobalMetricList {\n\t\t\tif gm.Name == fp {\n\t\t\t\tstatType = gm.Footprint\n\t\t\t}\n\t\t}\n\n\t\t// Validate statistic type\n\t\tif statType != \"avg\" && statType != \"min\" && statType != \"max\" {\n\t\t\tcclog.Warnf(\"unknown statType for footprint update: %s\", statType)\n\t\t\treturn stmt, fmt.Errorf(\"unknown statType for footprint update: %s\", statType)\n\t\t}\n\n\t\t// Override with cluster-specific config if available\n\t\tif i, err := archive.MetricIndex(sc.MetricConfig, fp); err != nil {\n\t\t\tstatType = sc.MetricConfig[i].Footprint\n\t\t}\n\n\t\t// Store as \"metric_stattype\": value (e.g., \"cpu_load_avg\": 85.3)\n\t\tname := fmt.Sprintf(\"%s_%s\", fp, statType)\n\t\tfootprint[name] = LoadJobStat(jobMeta, fp, statType)\n\t}\n\n\tvar rawFootprint []byte\n\tif rawFootprint, err = json.Marshal(footprint); err != nil {\n\t\tcclog.Warnf(\"Error while marshaling footprint for job INTO BYTES, DB ID '%v'\", jobMeta.ID)\n\t\treturn stmt, err\n\t}\n\n\treturn stmt.Set(\"footprint\", string(rawFootprint)), nil\n}\n\n// GetUsedNodes returns a map of cluster names to sorted lists of unique hostnames\n// that are currently in use by jobs that started before the given timestamp and\n// are still in running state.\n//\n// The timestamp parameter (ts) is compared against job.start_time to find\n// relevant jobs. Returns an error if the database query fails or row iteration\n// encounters errors. Individual row parsing errors are logged but don't fail\n// the entire operation.\nfunc (r *JobRepository) GetUsedNodes(ts int64) (map[string][]string, error) {\n\t// Note: Query expects index on (job_state, start_time) for optimal performance\n\tq := sq.Select(\"job.cluster\", \"job.resources\").From(\"job\").\n\t\tWhere(\"job.start_time < ?\", ts).\n\t\tWhere(\"job.job_state = 'running'\")\n\n\trows, err := q.RunWith(r.stmtCache).Query()\n\tif err != nil {\n\t\tqueryString, queryVars, _ := q.ToSql()\n\t\treturn nil, fmt.Errorf(\"query failed [%s] %v: %w\", queryString, queryVars, err)\n\t}\n\tdefer rows.Close()\n\n\t// Use a map of sets for efficient deduplication\n\tnodeSet := make(map[string]map[string]struct{})\n\n\tvar (\n\t\tcluster      string\n\t\trawResources []byte\n\t\tresources    []*schema.Resource\n\t\tskippedRows  int\n\t)\n\n\tfor rows.Next() {\n\t\tif err := rows.Scan(&cluster, &rawResources); err != nil {\n\t\t\tcclog.Warnf(\"Error scanning job row in GetUsedNodes: %v\", err)\n\t\t\tskippedRows++\n\t\t\tcontinue\n\t\t}\n\n\t\tresources = resources[:0] // Clear slice, keep capacity\n\t\tif err := json.Unmarshal(rawResources, &resources); err != nil {\n\t\t\tcclog.Warnf(\"Error unmarshaling resources for cluster %s: %v\", cluster, err)\n\t\t\tskippedRows++\n\t\t\tcontinue\n\t\t}\n\n\t\tif len(resources) == 0 {\n\t\t\tcclog.Debugf(\"Job in cluster %s has no resources\", cluster)\n\t\t\tcontinue\n\t\t}\n\n\t\tif _, ok := nodeSet[cluster]; !ok {\n\t\t\tnodeSet[cluster] = make(map[string]struct{})\n\t\t}\n\n\t\tfor _, res := range resources {\n\t\t\tnodeSet[cluster][res.Hostname] = struct{}{}\n\t\t}\n\t}\n\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, fmt.Errorf(\"error iterating rows: %w\", err)\n\t}\n\n\tif skippedRows > 0 {\n\t\tcclog.Warnf(\"GetUsedNodes: Skipped %d rows due to parsing errors\", skippedRows)\n\t}\n\n\t// Convert sets to sorted slices\n\tnodeList := make(map[string][]string, len(nodeSet))\n\tfor cluster, nodes := range nodeSet {\n\t\tlist := make([]string, 0, len(nodes))\n\t\tfor node := range nodes {\n\t\t\tlist = append(list, node)\n\t\t}\n\t\tsort.Strings(list)\n\t\tnodeList[cluster] = list\n\t}\n\n\treturn nodeList, nil\n}\n","structuredPatch":[{"oldStart":161,"oldLines":7,"newStart":161,"newLines":10,"lines":["     &job.StartTime, &job.Partition, &job.ArrayJobID, &job.NumNodes, &job.NumHWThreads,","     &job.NumAcc, &job.Shared, &job.MonitoringStatus, &job.SMT, &job.State,","     &job.Duration, &job.Walltime, &job.RawResources, &job.RawFootprint, &job.Energy); err != nil {","-    cclog.Warnf(\"Error while scanning rows (Job): %v\", err)","+    if err != sql.ErrNoRows {","+      _, file, line, _ := runtime.Caller(1)","+      cclog.Warnf(\"Error while scanning rows (Job) (%s:%d): %v\", filepath.Base(file), line, err)","+    }","     return nil, err","   }"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"d4c9cee3-04a0-4ae5-b7f8-7bfdca3a92b4","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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+{"parentUuid":"ada75e01-2dcc-4e8d-86df-c0f1b9d67040","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_01SWU5onx1QX5RjWwfezkdU7","type":"message","role":"assistant","content":[{"type":"text","text":"All tests pass. The changes are complete:\n\n- `sql.ErrNoRows` is now returned silently (no warning log)\n- Real scan errors include the caller's `file:line` in the warning, e.g. `Error while scanning rows (Job) (jobQuery.go:87): ...`"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":131,"cache_read_input_tokens":22859,"output_tokens":72,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":131,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ7H1Z12WheJuQxsdwymL","type":"assistant","uuid":"691d7efd-d4d0-421c-a09f-8f5287679115","timestamp":"2026-03-16T19:02:14.051Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd","version":"2.1.76","gitBranch":"hotfix","slug":"lexical-finding-hartmanis"}
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diff --git a/85/8b34ef56b8/0/metadata.json b/85/8b34ef56b8/0/metadata.json
new file mode 100644
index 00000000..8a5de5da
--- /dev/null
+++ b/85/8b34ef56b8/0/metadata.json
@@ -0,0 +1,30 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "858b34ef56b8",
+  "session_id": "7916ffa0-cf9e-4cb7-a75f-8a1db33c75bd",
+  "strategy": "manual-commit",
+  "created_at": "2026-03-16T19:03:32.318189Z",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "internal/repository/job.go"
+  ],
+  "agent": "Claude Code",
+  "turn_id": "9fa519255684",
+  "token_usage": {
+    "input_tokens": 11,
+    "cache_creation_tokens": 9711,
+    "cache_read_tokens": 180508,
+    "output_tokens": 1631,
+    "api_call_count": 9
+  },
+  "initial_attribution": {
+    "calculated_at": "2026-03-16T19:03:32.265756Z",
+    "agent_lines": 6,
+    "human_added": 0,
+    "human_modified": 0,
+    "human_removed": 0,
+    "total_committed": 6,
+    "agent_percentage": 100
+  }
+}
diff --git a/85/8b34ef56b8/0/prompt.txt b/85/8b34ef56b8/0/prompt.txt
new file mode 100644
index 00000000..1b34fb2e
--- /dev/null
+++ b/85/8b34ef56b8/0/prompt.txt
@@ -0,0 +1,64 @@
+Implement the following plan:
+
+# Plan: Improve scanJob logging
+
+## Context
+
+`scanJob` in `internal/repository/job.go` (line 162) logs a `Warn` for every scan error, including the very common `sql.ErrNoRows` case. This produces noisy, unhelpful log lines like:
+
+```
+WARN Error while scanning rows (Job): sql: no rows in result set
+```
+
+Two problems:
+1. `sql.ErrNoRows` is a normal, expected condition (callers are documented to check for it). It should not produce a warning.
+2. When a real scan error does occur, there's no call-site context — you can't tell which of the ~10 callers triggered it.
+
+The codebase already has a precedent for using `runtime.Caller(1)` in `internal/api/rest.go:188` to include file/line in log messages.
+
+## Approach
+
+Modify `scanJob` in `internal/repository/job.go`:
+
+1. **Skip logging for `sql.ErrNoRows`** — return the error silently. All callers already handle this case themselves.
+2. **Add caller context** for real scan errors using `runtime.Caller(1)` — include `file:line` in the warning message.
+
+```go
+import (
+    "database/sql"
+    "path/filepath"
+    "runtime"
+    // existing imports ...
+)
+
+func scanJob(row interface{ Scan(...any) error }) (*schema.Job, error) {
+    job := &schema.Job{}
+
+    if err := row.Scan(...); err != nil {
+        if err != sql.ErrNoRows {
+            _, file, line, _ := runtime.Caller(1)
+            cclog.Warnf("Error while scanning rows (Job) (%s:%d): %v", filepath.Base(file), line, err)
+        }
+        return nil, err
+    }
+    // ... rest unchanged
+}
+```
+
+## Critical File
+
+- `internal/repository/job.go` — only file to change (lines 154–184)
+
+## Imports to check
+
+`database/sql` is likely already imported (used elsewhere in the package). `runtime` and `path/filepath` — check if already present; add if not.
+
+## Verification
+
+1. `go build ./...` — must compile cleanly
+2. `go test ./internal/repository/...` — existing tests must pass
+3. Manually: trigger a lookup for a non-existent job ID; confirm no warning is logged
+4. Manually (or via test): force a real scan error; confirm warning includes `job.go:<line>`
+
+
+If you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/b03f52bf-e58e-45a2-8b95-af846938ee2c.jsonl
\ No newline at end of file
diff --git a/85/8b34ef56b8/metadata.json b/85/8b34ef56b8/metadata.json
new file mode 100644
index 00000000..52981f89
--- /dev/null
+++ b/85/8b34ef56b8/metadata.json
@@ -0,0 +1,26 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "858b34ef56b8",
+  "strategy": "manual-commit",
+  "branch": "hotfix",
+  "checkpoints_count": 1,
+  "files_touched": [
+    "internal/repository/job.go"
+  ],
+  "sessions": [
+    {
+      "metadata": "/85/8b34ef56b8/0/metadata.json",
+      "transcript": "/85/8b34ef56b8/0/full.jsonl",
+      "context": "/85/8b34ef56b8/0/context.md",
+      "content_hash": "/85/8b34ef56b8/0/content_hash.txt",
+      "prompt": "/85/8b34ef56b8/0/prompt.txt"
+    }
+  ],
+  "token_usage": {
+    "input_tokens": 11,
+    "cache_creation_tokens": 9711,
+    "cache_read_tokens": 180508,
+    "output_tokens": 1631,
+    "api_call_count": 9
+  }
+}
diff --git a/bf/29af79b268/0/content_hash.txt b/bf/29af79b268/0/content_hash.txt
new file mode 100644
index 00000000..375e560c
--- /dev/null
+++ b/bf/29af79b268/0/content_hash.txt
@@ -0,0 +1 @@
+sha256:b184f713fed8a0efc8240d19849de07ab8e1009e71da3ce0891e3f282cf69adb
\ No newline at end of file
diff --git a/bf/29af79b268/0/context.md b/bf/29af79b268/0/context.md
new file mode 100644
index 00000000..fab3958e
--- /dev/null
+++ b/bf/29af79b268/0/context.md
@@ -0,0 +1,34 @@
+# Session Context
+
+## User Prompts
+
+### Prompt 1
+
+Implement the following plan:
+
+# Fix: Memory Escalation in flattenCheckpointFile (68GB+)
+
+## Context
+
+Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.
+
+## Root Cause
+
+Two-layer unbounde...
+
+### Prompt 2
+
+Are the any other cases with memory spikes using the Parquet Writer, e.g. in the nodestate retention?
+
+### Prompt 3
+
+[Request interrupted by user for tool use]
+
+### Prompt 4
+
+Compare the archive writer implementation with @~/tmp/cc-backend/pkg/metricstore/parquetArchive.go . Compare and explain differences.
+
+### Prompt 5
+
+Add an Info logmessage in archiveCheckpoints that archving started and provide timing information how long it took.
+
diff --git a/bf/29af79b268/0/full.jsonl b/bf/29af79b268/0/full.jsonl
new file mode 100644
index 00000000..7bc88608
--- /dev/null
+++ b/bf/29af79b268/0/full.jsonl
@@ -0,0 +1,168 @@
+{"type":"file-history-snapshot","messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","snapshot":{"messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","trackedFileBackups":{},"timestamp":"2026-03-17T18:14:06.692Z"},"isSnapshotUpdate":false}
+{"parentUuid":null,"isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"SessionStart","hookName":"SessionStart:clear","command":"entire hooks claude-code session-start"},"parentToolUseID":"d78d8e9c-5382-4185-9219-683f79dd3065","toolUseID":"d78d8e9c-5382-4185-9219-683f79dd3065","timestamp":"2026-03-17T18:14:06.646Z","uuid":"1ccea021-492e-4f7f-8ce8-eb5cd2377954","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"1ccea021-492e-4f7f-8ce8-eb5cd2377954","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":"Implement the following plan:\n\n# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n\n\nIf you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/71340843-de3d-4e83-9dcb-2fc130c50e0d.jsonl"},"uuid":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","timestamp":"2026-03-17T18:14:06.473Z","planContent":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AyF6Jg771Hu8xTwZKEMzV6","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nLet me start by reading the relevant files to understand the current implementation."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":12307,"cache_read_input_tokens":6489,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":12307},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ979w6ddKngVT3C7ef14","type":"assistant","uuid":"a1ffff0a-75c8-4ed4-affd-9f599af2f79f","timestamp":"2026-03-17T18:14:09.794Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"8c2533e3-d964-4a82-9cba-cec560086bc5","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JW7rVTjQ4z7YAw3jsNrSDY","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→\n    16→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n    35→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    36→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    37→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n    38→\tfor metricName, cm := range cf.Metrics {\n    39→\t\tts := cm.Start\n    40→\t\tfor _, v := range cm.Data {\n    41→\t\t\tif !v.IsNaN() {\n    42→\t\t\t\trows = append(rows, ParquetMetricRow{\n    43→\t\t\t\t\tCluster:   cluster,\n    44→\t\t\t\t\tHostname:  hostname,\n    45→\t\t\t\t\tMetric:    metricName,\n    46→\t\t\t\t\tScope:     scope,\n    47→\t\t\t\t\tScopeID:   scopeID,\n    48→\t\t\t\t\tTimestamp: ts,\n    49→\t\t\t\t\tFrequency: cm.Frequency,\n    50→\t\t\t\t\tValue:     float32(v),\n    51→\t\t\t\t})\n    52→\t\t\t}\n    53→\t\t\tts += cm.Frequency\n    54→\t\t}\n    55→\t}\n    56→\n    57→\tfor childName, childCf := range cf.Children {\n    58→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    59→\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n    60→\t}\n    61→\n    62→\treturn rows\n    63→}\n    64→\n    65→// parseScopeFromName infers scope and scope_id from a child level name.\n    66→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    67→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    68→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    69→func parseScopeFromName(name string) (string, string) {\n    70→\tprefixes := []struct {\n    71→\t\tprefix string\n    72→\t\tscope  string\n    73→\t}{\n    74→\t\t{\"socket\", \"socket\"},\n    75→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    76→\t\t{\"core\", \"core\"},\n    77→\t\t{\"hwthread\", \"hwthread\"},\n    78→\t\t{\"cpu\", \"hwthread\"},\n    79→\t\t{\"accelerator\", \"accelerator\"},\n    80→\t}\n    81→\n    82→\tfor _, p := range prefixes {\n    83→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    84→\t\t\tid := name[len(p.prefix):]\n    85→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    86→\t\t\t\treturn p.scope, id\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\n    91→\treturn name, \"\"\n    92→}\n    93→\n    94→// writeParquetArchive writes rows to a Parquet file with Zstd compression.\n    95→func writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n    96→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n    97→\t\treturn fmt.Errorf(\"creating archive directory: %w\", err)\n    98→\t}\n    99→\n   100→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   101→\tif err != nil {\n   102→\t\treturn fmt.Errorf(\"creating parquet file: %w\", err)\n   103→\t}\n   104→\tdefer f.Close()\n   105→\n   106→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   107→\n   108→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   109→\t\tpq.Compression(&pq.Zstd),\n   110→\t\tpq.SortingWriterConfig(pq.SortingColumns(\n   111→\t\t\tpq.Ascending(\"cluster\"),\n   112→\t\t\tpq.Ascending(\"hostname\"),\n   113→\t\t\tpq.Ascending(\"metric\"),\n   114→\t\t\tpq.Ascending(\"timestamp\"),\n   115→\t\t)),\n   116→\t)\n   117→\n   118→\tif _, err := writer.Write(rows); err != nil {\n   119→\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n   120→\t}\n   121→\n   122→\tif err := writer.Close(); err != nil {\n   123→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n   124→\t}\n   125→\n   126→\tif err := bw.Flush(); err != nil {\n   127→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n   128→\t}\n   129→\n   130→\treturn nil\n   131→}\n   132→\n   133→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   134→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   135→// before converting it to Parquet format.\n   136→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   137→\tf, err := os.Open(filename)\n   138→\tif err != nil {\n   139→\t\treturn nil, err\n   140→\t}\n   141→\tdefer f.Close()\n   142→\n   143→\text := filepath.Ext(filename)\n   144→\tswitch ext {\n   145→\tcase \".json\":\n   146→\t\tcf := &CheckpointFile{}\n   147→\t\tbr := bufio.NewReader(f)\n   148→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   149→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   150→\t\t}\n   151→\t\treturn cf, nil\n   152→\n   153→\tcase \".bin\":\n   154→\t\tbr := bufio.NewReader(f)\n   155→\t\tvar magic uint32\n   156→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   157→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   158→\t\t}\n   159→\t\tif magic != snapFileMagic {\n   160→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   161→\t\t}\n   162→\t\tvar fileFrom, fileTo int64\n   163→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   164→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   165→\t\t}\n   166→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   167→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   168→\t\t}\n   169→\t\tcf, err := readBinaryLevel(br)\n   170→\t\tif err != nil {\n   171→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   172→\t\t}\n   173→\t\tcf.From = fileFrom\n   174→\t\tcf.To = fileTo\n   175→\t\treturn cf, nil\n   176→\n   177→\tdefault:\n   178→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   179→\t}\n   180→}\n   181→\n   182→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   183→// converts them to Parquet rows. Returns the rows and filenames that were processed.\n   184→func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {\n   185→\tentries, err := os.ReadDir(dir)\n   186→\tif err != nil {\n   187→\t\treturn nil, nil, err\n   188→\t}\n   189→\n   190→\tfiles, err := findFiles(entries, from, false)\n   191→\tif err != nil {\n   192→\t\treturn nil, nil, err\n   193→\t}\n   194→\n   195→\tif len(files) == 0 {\n   196→\t\treturn nil, nil, nil\n   197→\t}\n   198→\n   199→\tvar rows []ParquetMetricRow\n   200→\n   201→\tfor _, checkpoint := range files {\n   202→\t\tfilename := filepath.Join(dir, checkpoint)\n   203→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   204→\t\tif err != nil {\n   205→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   206→\t\t\tcontinue\n   207→\t\t}\n   208→\n   209→\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n   210→\t}\n   211→\n   212→\treturn rows, files, nil\n   213→}\n   214→"}]},"uuid":"7b2d9ff8-b786-4c43-aceb-98f92f903d5c","timestamp":"2026-03-17T18:14:10.793Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/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\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","numLines":214,"startLine":1,"totalLines":214}},"sourceToolAssistantUUID":"8c2533e3-d964-4a82-9cba-cec560086bc5","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"7b2d9ff8-b786-4c43-aceb-98f92f903d5c","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01TTkqqEZu8i9v4aSq57ZyF8","toolUseID":"toolu_01TTkqqEZu8i9v4aSq57ZyF8","timestamp":"2026-03-17T18:14:10.792Z","uuid":"237be391-9ce8-4868-88ec-2ffeaa23653f","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"4704a1bc-5253-41ee-b057-59f5c34430a8","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TTkqqEZu8i9v4aSq57ZyF8","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\t// Run as Archiver\n    26→\t\tcleanUpWorker(wg, ctx,\n    27→\t\t\tKeys.RetentionInMemory,\n    28→\t\t\t\"archiving\",\n    29→\t\t\tKeys.Cleanup.RootDir,\n    30→\t\t\tfalse,\n    31→\t\t)\n    32→\t} else {\n    33→\t\t// Run as Deleter\n    34→\t\tcleanUpWorker(wg, ctx,\n    35→\t\t\tKeys.RetentionInMemory,\n    36→\t\t\t\"deleting\",\n    37→\t\t\t\"\",\n    38→\t\t\ttrue,\n    39→\t\t)\n    40→\t}\n    41→}\n    42→\n    43→// cleanUpWorker takes simple values to configure what it does\n    44→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n    45→\twg.Go(func() {\n    46→\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→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n   172→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n   173→\tif err != nil {\n   174→\t\treturn 0, err\n   175→\t}\n   176→\n   177→\ttotalFiles := 0\n   178→\n   179→\tfor _, clusterEntry := range clusterEntries {\n   180→\t\tif !clusterEntry.IsDir() {\n   181→\t\t\tcontinue\n   182→\t\t}\n   183→\n   184→\t\tcluster := clusterEntry.Name()\n   185→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n   186→\t\tif err != nil {\n   187→\t\t\treturn totalFiles, err\n   188→\t\t}\n   189→\n   190→\t\t// Collect rows from all hosts in this cluster using worker pool\n   191→\t\ttype hostResult struct {\n   192→\t\t\trows  []ParquetMetricRow\n   193→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n   194→\t\t\tdir   string   // checkpoint directory for this host\n   195→\t\t}\n   196→\n   197→\t\tresults := make(chan hostResult, len(hostEntries))\n   198→\t\twork := make(chan struct {\n   199→\t\t\tdir, host string\n   200→\t\t}, Keys.NumWorkers)\n   201→\n   202→\t\tvar wg sync.WaitGroup\n   203→\t\terrs := int32(0)\n   204→\n   205→\t\twg.Add(Keys.NumWorkers)\n   206→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n   207→\t\t\tgo func() {\n   208→\t\t\t\tdefer wg.Done()\n   209→\t\t\t\tfor item := range work {\n   210→\t\t\t\t\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, from)\n   211→\t\t\t\t\tif err != nil {\n   212→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n   213→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n   214→\t\t\t\t\t\tcontinue\n   215→\t\t\t\t\t}\n   216→\t\t\t\t\tif len(rows) > 0 {\n   217→\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\n   218→\t\t\t\t\t}\n   219→\t\t\t\t}\n   220→\t\t\t}()\n   221→\t\t}\n   222→\n   223→\t\tgo func() {\n   224→\t\t\tfor _, hostEntry := range hostEntries {\n   225→\t\t\t\tif !hostEntry.IsDir() {\n   226→\t\t\t\t\tcontinue\n   227→\t\t\t\t}\n   228→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n   229→\t\t\t\twork <- struct {\n   230→\t\t\t\t\tdir, host string\n   231→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n   232→\t\t\t}\n   233→\t\t\tclose(work)\n   234→\t\t\twg.Wait()\n   235→\t\t\tclose(results)\n   236→\t\t}()\n   237→\n   238→\t\t// Collect all rows and file info\n   239→\t\tvar allRows []ParquetMetricRow\n   240→\t\tvar allResults []hostResult\n   241→\t\tfor r := range results {\n   242→\t\t\tallRows = append(allRows, r.rows...)\n   243→\t\t\tallResults = append(allResults, r)\n   244→\t\t}\n   245→\n   246→\t\tif errs > 0 {\n   247→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n   248→\t\t}\n   249→\n   250→\t\tif len(allRows) == 0 {\n   251→\t\t\tcontinue\n   252→\t\t}\n   253→\n   254→\t\t// Write one Parquet file per cluster\n   255→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n   256→\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n   257→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n   258→\t\t}\n   259→\n   260→\t\t// Delete archived checkpoint files\n   261→\t\tfor _, result := range allResults {\n   262→\t\t\tfor _, file := range result.files {\n   263→\t\t\t\tfilename := filepath.Join(result.dir, file)\n   264→\t\t\t\tif err := os.Remove(filename); err != nil {\n   265→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n   266→\t\t\t\t} else {\n   267→\t\t\t\t\ttotalFiles++\n   268→\t\t\t\t}\n   269→\t\t\t}\n   270→\t\t}\n   271→\n   272→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n   273→\t\t\tlen(allRows), totalFiles, cluster, parquetFile)\n   274→\t}\n   275→\n   276→\treturn totalFiles, nil\n   277→}\n   278→"}]},"uuid":"5c641ce2-75b5-4d5f-8b5c-fd0a8d05eefe","timestamp":"2026-03-17T18:14:10.792Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/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\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\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\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}\n","numLines":278,"startLine":1,"totalLines":278}},"sourceToolAssistantUUID":"4704a1bc-5253-41ee-b057-59f5c34430a8","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"530dbdcc-8f1e-4870-a1c5-88215ce6a729","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AdHt5nZpLoZxxyDJ4BAorq","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\"encoding/json\"\n    10→\t\"os\"\n    11→\t\"path/filepath\"\n    12→\t\"testing\"\n    13→\n    14→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    15→\tpq \"github.com/parquet-go/parquet-go\"\n    16→)\n    17→\n    18→func TestParseScopeFromName(t *testing.T) {\n    19→\ttests := []struct {\n    20→\t\tname      string\n    21→\t\twantScope string\n    22→\t\twantID    string\n    23→\t}{\n    24→\t\t{\"socket0\", \"socket\", \"0\"},\n    25→\t\t{\"socket12\", \"socket\", \"12\"},\n    26→\t\t{\"core0\", \"core\", \"0\"},\n    27→\t\t{\"core127\", \"core\", \"127\"},\n    28→\t\t{\"cpu0\", \"hwthread\", \"0\"},\n    29→\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n    30→\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n    31→\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n    32→\t\t{\"unknown\", \"unknown\", \"\"},\n    33→\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n    34→\t}\n    35→\n    36→\tfor _, tt := range tests {\n    37→\t\tt.Run(tt.name, func(t *testing.T) {\n    38→\t\t\tscope, id := parseScopeFromName(tt.name)\n    39→\t\t\tif scope != tt.wantScope || id != tt.wantID {\n    40→\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n    41→\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n    42→\t\t\t}\n    43→\t\t})\n    44→\t}\n    45→}\n    46→\n    47→func TestFlattenCheckpointFile(t *testing.T) {\n    48→\tcf := &CheckpointFile{\n    49→\t\tFrom: 1000,\n    50→\t\tTo:   1060,\n    51→\t\tMetrics: map[string]*CheckpointMetrics{\n    52→\t\t\t\"cpu_load\": {\n    53→\t\t\t\tFrequency: 60,\n    54→\t\t\t\tStart:     1000,\n    55→\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n    56→\t\t\t},\n    57→\t\t},\n    58→\t\tChildren: map[string]*CheckpointFile{\n    59→\t\t\t\"socket0\": {\n    60→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n    61→\t\t\t\t\t\"mem_bw\": {\n    62→\t\t\t\t\t\tFrequency: 60,\n    63→\t\t\t\t\t\tStart:     1000,\n    64→\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n    65→\t\t\t\t\t},\n    66→\t\t\t\t},\n    67→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n    68→\t\t\t},\n    69→\t\t},\n    70→\t}\n    71→\n    72→\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n    73→\n    74→\t// cpu_load: 2 non-NaN values at node scope\n    75→\t// mem_bw: 2 non-NaN values at socket0 scope\n    76→\tif len(rows) != 4 {\n    77→\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n    78→\t}\n    79→\n    80→\t// Verify a node-scope row\n    81→\tfound := false\n    82→\tfor _, r := range rows {\n    83→\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n    84→\t\t\tfound = true\n    85→\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n    86→\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\tif !found {\n    91→\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n    92→\t}\n    93→\n    94→\t// Verify a socket-scope row\n    95→\tfound = false\n    96→\tfor _, r := range rows {\n    97→\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n    98→\t\t\tfound = true\n    99→\t\t}\n   100→\t}\n   101→\tif !found {\n   102→\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n   103→\t}\n   104→}\n   105→\n   106→func TestParquetArchiveRoundtrip(t *testing.T) {\n   107→\ttmpDir := t.TempDir()\n   108→\n   109→\t// Create checkpoint files on disk (JSON format)\n   110→\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n   111→\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n   112→\t\tt.Fatal(err)\n   113→\t}\n   114→\n   115→\tcf := &CheckpointFile{\n   116→\t\tFrom: 1000,\n   117→\t\tTo:   1180,\n   118→\t\tMetrics: map[string]*CheckpointMetrics{\n   119→\t\t\t\"cpu_load\": {\n   120→\t\t\t\tFrequency: 60,\n   121→\t\t\t\tStart:     1000,\n   122→\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n   123→\t\t\t},\n   124→\t\t\t\"mem_used\": {\n   125→\t\t\t\tFrequency: 60,\n   126→\t\t\t\tStart:     1000,\n   127→\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n   128→\t\t\t},\n   129→\t\t},\n   130→\t\tChildren: map[string]*CheckpointFile{\n   131→\t\t\t\"socket0\": {\n   132→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n   133→\t\t\t\t\t\"mem_bw\": {\n   134→\t\t\t\t\t\tFrequency: 60,\n   135→\t\t\t\t\t\tStart:     1000,\n   136→\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n   137→\t\t\t\t\t},\n   138→\t\t\t\t},\n   139→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n   140→\t\t\t},\n   141→\t\t},\n   142→\t}\n   143→\n   144→\t// Write JSON checkpoint\n   145→\tcpFile := filepath.Join(cpDir, \"1000.json\")\n   146→\tdata, err := json.Marshal(cf)\n   147→\tif err != nil {\n   148→\t\tt.Fatal(err)\n   149→\t}\n   150→\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n   151→\t\tt.Fatal(err)\n   152→\t}\n   153→\n   154→\t// Archive to Parquet\n   155→\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n   156→\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n   157→\tif err != nil {\n   158→\t\tt.Fatal(err)\n   159→\t}\n   160→\tif len(files) != 1 || files[0] != \"1000.json\" {\n   161→\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n   162→\t}\n   163→\n   164→\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n   165→\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n   166→\t\tt.Fatal(err)\n   167→\t}\n   168→\n   169→\t// Read back and verify\n   170→\tf, err := os.Open(parquetFile)\n   171→\tif err != nil {\n   172→\t\tt.Fatal(err)\n   173→\t}\n   174→\tdefer f.Close()\n   175→\n   176→\tstat, _ := f.Stat()\n   177→\tpf, err := pq.OpenFile(f, stat.Size())\n   178→\tif err != nil {\n   179→\t\tt.Fatal(err)\n   180→\t}\n   181→\n   182→\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n   183→\treadRows := make([]ParquetMetricRow, 100)\n   184→\tn, err := reader.Read(readRows)\n   185→\tif err != nil && n == 0 {\n   186→\t\tt.Fatal(err)\n   187→\t}\n   188→\treadRows = readRows[:n]\n   189→\treader.Close()\n   190→\n   191→\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n   192→\tif n != 9 {\n   193→\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n   194→\t}\n   195→\n   196→\t// Verify cluster and hostname are set correctly\n   197→\tfor _, r := range readRows {\n   198→\t\tif r.Cluster != \"testcluster\" {\n   199→\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n   200→\t\t}\n   201→\t\tif r.Hostname != \"node001\" {\n   202→\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n   203→\t\t}\n   204→\t}\n   205→\n   206→\t// Verify parquet file is smaller than JSON (compression working)\n   207→\tif stat.Size() == 0 {\n   208→\t\tt.Error(\"parquet file is empty\")\n   209→\t}\n   210→\n   211→\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n   212→}\n   213→\n   214→func TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n   215→\ttmpDir := t.TempDir()\n   216→\n   217→\tcf := &CheckpointFile{\n   218→\t\tFrom: 1000,\n   219→\t\tTo:   1060,\n   220→\t\tMetrics: map[string]*CheckpointMetrics{\n   221→\t\t\t\"test_metric\": {\n   222→\t\t\t\tFrequency: 60,\n   223→\t\t\t\tStart:     1000,\n   224→\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n   225→\t\t\t},\n   226→\t\t},\n   227→\t\tChildren: make(map[string]*CheckpointFile),\n   228→\t}\n   229→\n   230→\tfilename := filepath.Join(tmpDir, \"1000.json\")\n   231→\tdata, err := json.Marshal(cf)\n   232→\tif err != nil {\n   233→\t\tt.Fatal(err)\n   234→\t}\n   235→\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n   236→\t\tt.Fatal(err)\n   237→\t}\n   238→\n   239→\tloaded, err := loadCheckpointFileFromDisk(filename)\n   240→\tif err != nil {\n   241→\t\tt.Fatal(err)\n   242→\t}\n   243→\n   244→\tif loaded.From != 1000 || loaded.To != 1060 {\n   245→\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n   246→\t}\n   247→\n   248→\tm, ok := loaded.Metrics[\"test_metric\"]\n   249→\tif !ok {\n   250→\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n   251→\t}\n   252→\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n   253→\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n   254→\t}\n   255→}\n   256→"}]},"uuid":"4a0aef1c-e87c-4f66-9d2e-f9bec302737c","timestamp":"2026-03-17T18:14:11.268Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive_test.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\"encoding/json\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\nfunc TestParseScopeFromName(t *testing.T) {\n\ttests := []struct {\n\t\tname      string\n\t\twantScope string\n\t\twantID    string\n\t}{\n\t\t{\"socket0\", \"socket\", \"0\"},\n\t\t{\"socket12\", \"socket\", \"12\"},\n\t\t{\"core0\", \"core\", \"0\"},\n\t\t{\"core127\", \"core\", \"127\"},\n\t\t{\"cpu0\", \"hwthread\", \"0\"},\n\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n\t\t{\"unknown\", \"unknown\", \"\"},\n\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tscope, id := parseScopeFromName(tt.name)\n\t\t\tif scope != tt.wantScope || id != tt.wantID {\n\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestFlattenCheckpointFile(t *testing.T) {\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n\n\t// cpu_load: 2 non-NaN values at node scope\n\t// mem_bw: 2 non-NaN values at socket0 scope\n\tif len(rows) != 4 {\n\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n\t}\n\n\t// Verify a node-scope row\n\tfound := false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n\t\t\tfound = true\n\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n\t\t\t}\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n\t}\n\n\t// Verify a socket-scope row\n\tfound = false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n\t\t\tfound = true\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n\t}\n}\n\nfunc TestParquetArchiveRoundtrip(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\t// Create checkpoint files on disk (JSON format)\n\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1180,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n\t\t\t},\n\t\t\t\"mem_used\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\t// Write JSON checkpoint\n\tcpFile := filepath.Join(cpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Archive to Parquet\n\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif len(files) != 1 || files[0] != \"1000.json\" {\n\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n\t}\n\n\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Read back and verify\n\tf, err := os.Open(parquetFile)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tdefer f.Close()\n\n\tstat, _ := f.Stat()\n\tpf, err := pq.OpenFile(f, stat.Size())\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n\treadRows := make([]ParquetMetricRow, 100)\n\tn, err := reader.Read(readRows)\n\tif err != nil && n == 0 {\n\t\tt.Fatal(err)\n\t}\n\treadRows = readRows[:n]\n\treader.Close()\n\n\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n\tif n != 9 {\n\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n\t}\n\n\t// Verify cluster and hostname are set correctly\n\tfor _, r := range readRows {\n\t\tif r.Cluster != \"testcluster\" {\n\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n\t\t}\n\t\tif r.Hostname != \"node001\" {\n\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n\t\t}\n\t}\n\n\t// Verify parquet file is smaller than JSON (compression working)\n\tif stat.Size() == 0 {\n\t\tt.Error(\"parquet file is empty\")\n\t}\n\n\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n}\n\nfunc TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"test_metric\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n\t\t\t},\n\t\t},\n\t\tChildren: make(map[string]*CheckpointFile),\n\t}\n\n\tfilename := filepath.Join(tmpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tloaded, err := loadCheckpointFileFromDisk(filename)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tif loaded.From != 1000 || loaded.To != 1060 {\n\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n\t}\n\n\tm, ok := loaded.Metrics[\"test_metric\"]\n\tif !ok {\n\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n\t}\n\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n\t}\n}\n","numLines":256,"startLine":1,"totalLines":256}},"sourceToolAssistantUUID":"530dbdcc-8f1e-4870-a1c5-88215ce6a729","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c275b193-e533-456b-9230-e0ee1ea0fa1c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01RMdmF6xH1mm2DpsrqgJrgu","type":"message","role":"assistant","content":[{"type":"text","text":"Now I have a clear picture. Let me implement the changes.\n\n**Step 1: Update `parquetArchive.go`** - Add streaming writer, remove old `writeParquetArchive`"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":10208,"cache_read_input_tokens":18796,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":10208},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ97AGSxvMsprpByJkyy2","type":"assistant","uuid":"98760d2a-e3cc-42e4-8777-b0c8be9375ea","timestamp":"2026-03-17T18:14:18.228Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"type":"file-history-snapshot","messageId":"66271b96-1bbf-4446-bc30-dc4fe8513046","snapshot":{"messageId":"b533e922-ca3a-46ea-b62d-b0ee4ca0d906","trackedFileBackups":{"pkg/metricstore/parquetArchive.go":{"backupFileName":"d23fbf0a668003f6@v1","version":1,"backupTime":"2026-03-17T18:14:21.260Z"}},"timestamp":"2026-03-17T18:14:06.692Z"},"isSnapshotUpdate":true}
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+{"parentUuid":"66271b96-1bbf-4446-bc30-dc4fe8513046","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KEEBSH5oTDBJaFVzJj24Fp","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go has been updated successfully."}]},"uuid":"8ea10542-c017-448f-9afb-91498f3807c8","timestamp":"2026-03-17T18:14:21.265Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","oldString":"import (\n\t\"bufio\"\n\t\"encoding/binary\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"os\"\n\t\"path/filepath\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)","newString":"import (\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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":12,"oldLines":6,"newStart":12,"newLines":7,"lines":["   \"fmt\"","   \"os\"","   \"path/filepath\"","+  \"sort\""," ","   cclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"","   pq \"github.com/parquet-go/parquet-go\""]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"66271b96-1bbf-4446-bc30-dc4fe8513046","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"8ea10542-c017-448f-9afb-91498f3807c8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01DPuC6qZGeRor7sj16J9WjX","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01LEFj1LSgwARFjJfDqJypBn","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","old_string":"// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\n}","new_string":"// parquetArchiveWriter supports incremental writes to a Parquet file.\n// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":513,"cache_read_input_tokens":29004,"output_tokens":1391,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":513,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97B37JmQrRhr5sZtBP6","type":"assistant","uuid":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","timestamp":"2026-03-17T18:14:38.960Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LEFj1LSgwARFjJfDqJypBn","type":"tool_result","content":"The file /Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go has been updated successfully."}]},"uuid":"36701fa4-3179-4da4-89fa-9bfce3b3f37d","timestamp":"2026-03-17T18:14:38.984Z","toolUseResult":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","oldString":"// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\n}","newString":"// parquetArchiveWriter supports incremental writes to a Parquet file.\n// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// writeParquetArchive writes rows to a Parquet file with Zstd compression.\nfunc writeParquetArchive(filename string, rows []ParquetMetricRow) error {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\treturn 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 fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":92,"oldLines":45,"newStart":92,"newLines":83,"lines":["   return name, \"\""," }"," ","-// writeParquetArchive writes rows to a Parquet file with Zstd compression.","-func writeParquetArchive(filename string, rows []ParquetMetricRow) error {","+// parquetArchiveWriter supports incremental writes to a Parquet file.","+// Each call to WriteHostRows writes one row group (typically one host's data),","+// avoiding accumulation of all rows in memory.","+type parquetArchiveWriter struct {","+  writer *pq.GenericWriter[ParquetMetricRow]","+  bw     *bufio.Writer","+  f      *os.File","+  count  int","+}","+","+// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.","+func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {","   if err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {","-    return fmt.Errorf(\"creating archive directory: %w\", err)","+    return nil, fmt.Errorf(\"creating archive directory: %w\", err)","   }"," ","   f, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)","   if err != nil {","-    return fmt.Errorf(\"creating parquet file: %w\", err)","+    return nil, fmt.Errorf(\"creating parquet file: %w\", err)","   }","-  defer f.Close()"," ","   bw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer"," ","   writer := pq.NewGenericWriter[ParquetMetricRow](bw,","     pq.Compression(&pq.Zstd),","-    pq.SortingWriterConfig(pq.SortingColumns(","-      pq.Ascending(\"cluster\"),","-      pq.Ascending(\"hostname\"),","-      pq.Ascending(\"metric\"),","-      pq.Ascending(\"timestamp\"),","-    )),","   )"," ","-  if _, err := writer.Write(rows); err != nil {","+  return &parquetArchiveWriter{writer: writer, bw: bw, f: f}, nil","+}","+","+// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,","+// and flushes to create a separate row group.","+func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {","+  sort.Slice(rows, func(i, j int) bool {","+    if rows[i].Metric != rows[j].Metric {","+      return rows[i].Metric < rows[j].Metric","+    }","+    return rows[i].Timestamp < rows[j].Timestamp","+  })","+","+  if _, err := w.writer.Write(rows); err != nil {","     return fmt.Errorf(\"writing parquet rows: %w\", err)","   }"," ","-  if err := writer.Close(); err != nil {","+  if err := w.writer.Flush(); err != nil {","+    return fmt.Errorf(\"flushing parquet row group: %w\", err)","+  }","+","+  w.count += len(rows)","+  return nil","+}","+","+// Close finalises the Parquet file (footer, buffered I/O, file handle).","+func (w *parquetArchiveWriter) Close() error {","+  if err := w.writer.Close(); err != nil {","+    w.f.Close()","     return fmt.Errorf(\"closing parquet writer: %w\", err)","   }"," ","-  if err := bw.Flush(); err != nil {","+  if err := w.bw.Flush(); err != nil {","+    w.f.Close()","     return fmt.Errorf(\"flushing parquet file: %w\", err)","   }"," ","-  return nil","+  return w.f.Close()"," }"," ","+// sortParquetRows sorts rows by (metric, timestamp) in-place.","+func sortParquetRows(rows []ParquetMetricRow) {","+  sort.Slice(rows, func(i, j int) bool {","+    if rows[i].Metric != rows[j].Metric {","+      return rows[i].Metric < rows[j].Metric","+    }","+    return rows[i].Timestamp < rows[j].Timestamp","+  })","+}","+"," // loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns"," // a CheckpointFile. Used by the Parquet archiver to read checkpoint data"," // before converting it to Parquet format."]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"c7d57baf-2b11-4363-bd22-b6f5ae4cf140","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"b1545362-e02b-4a3e-a599-0260932338f4","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01VfefjavQzgZsqg8hHTVosW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01L18aviRMvE979p3KoRTiow","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go","old_string":"// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}","new_string":"// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n// Used for pre-allocating the rows slice to avoid repeated append doubling.\nfunc estimateRowCount(cf *CheckpointFile) int {\n\tn := 0\n\tfor _, cm := range cf.Metrics {\n\t\tn += len(cm.Data)\n\t}\n\tfor _, child := range cf.Children {\n\t\tn += estimateRowCount(child)\n\t}\n\treturn n\n}\n\n// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n\ttype loaded struct {\n\t\tcf       *CheckpointFile\n\t\tfilename string\n\t}\n\tvar checkpoints []loaded\n\ttotalEstimate := 0\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\t\ttotalEstimate += estimateRowCount(cf)\n\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n\t}\n\n\tif len(checkpoints) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\trows := make([]ParquetMetricRow, 0, totalEstimate)\n\tprocessedFiles := make([]string, 0, len(checkpoints))\n\n\tfor _, cp := range checkpoints {\n\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n\t\tprocessedFiles = append(processedFiles, cp.filename)\n\t}\n\n\treturn rows, processedFiles, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1526,"cache_read_input_tokens":29517,"output_tokens":1038,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1526,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97CJzZck3MZdNy2tP5h","type":"assistant","uuid":"4f5d24ca-a19c-4d0c-821d-792a973286f3","timestamp":"2026-03-17T18:14:53.263Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}","newString":"// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n// Used for pre-allocating the rows slice to avoid repeated append doubling.\nfunc estimateRowCount(cf *CheckpointFile) int {\n\tn := 0\n\tfor _, cm := range cf.Metrics {\n\t\tn += len(cm.Data)\n\t}\n\tfor _, child := range cf.Children {\n\t\tn += estimateRowCount(child)\n\t}\n\treturn n\n}\n\n// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n\ttype loaded struct {\n\t\tcf       *CheckpointFile\n\t\tfilename string\n\t}\n\tvar checkpoints []loaded\n\ttotalEstimate := 0\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\t\ttotalEstimate += estimateRowCount(cf)\n\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n\t}\n\n\tif len(checkpoints) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\trows := make([]ParquetMetricRow, 0, totalEstimate)\n\tprocessedFiles := make([]string, 0, len(checkpoints))\n\n\tfor _, cp := range checkpoints {\n\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n\t\tprocessedFiles = append(processedFiles, cp.filename)\n\t}\n\n\treturn rows, processedFiles, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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 rows []ParquetMetricRow\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\trows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)\n\t}\n\n\treturn rows, files, nil\n}\n","structuredPatch":[{"oldStart":218,"oldLines":6,"newStart":218,"newLines":19,"lines":["   }"," }"," ","+// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.","+// Used for pre-allocating the rows slice to avoid repeated append doubling.","+func estimateRowCount(cf *CheckpointFile) int {","+  n := 0","+  for _, cm := range cf.Metrics {","+    n += len(cm.Data)","+  }","+  for _, child := range cf.Children {","+    n += estimateRowCount(child)","+  }","+  return n","+}","+"," // archiveCheckpointsToParquet reads checkpoint files for a host directory,"," // converts them to Parquet rows. Returns the rows and filenames that were processed."," func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {"]},{"oldStart":235,"oldLines":7,"newStart":248,"newLines":13,"lines":["     return nil, nil, nil","   }"," ","-  var rows []ParquetMetricRow","+  // First pass: load checkpoints and estimate total rows for pre-allocation.","+  type loaded struct {","+    cf       *CheckpointFile","+    filename string","+  }","+  var checkpoints []loaded","+  totalEstimate := 0"," ","   for _, checkpoint := range files {","     filename := filepath.Join(dir, checkpoint)"]},{"oldStart":244,"oldLines":9,"newStart":263,"newLines":21,"lines":["       cclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)","       continue","     }","+    totalEstimate += estimateRowCount(cf)","+    checkpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})","+  }"," ","-    rows = flattenCheckpointFile(cf, cluster, host, \"node\", \"\", rows)","+  if len(checkpoints) == 0 {","+    return nil, nil, nil","   }"," ","-  return rows, files, nil","+  rows := make([]ParquetMetricRow, 0, totalEstimate)","+  processedFiles := make([]string, 0, len(checkpoints))","+","+  for _, cp := range checkpoints {","+    rows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)","+    processedFiles = append(processedFiles, cp.filename)","+  }","+","+  return rows, processedFiles, nil"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"4f5d24ca-a19c-4d0c-821d-792a973286f3","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"2c2d7e52-c2d4-4eb8-95df-c41b6b08c910","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_012Lax8yyV7unZDoBkvqzsAQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01F2NUeSmUXJ526j3VVko9pD","name":"Edit","input":{"replace_all":false,"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go","old_string":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}","new_string":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1193,"cache_read_input_tokens":31043,"output_tokens":2500,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1193,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ97DNEoZArSeP2DNLgPJ","type":"assistant","uuid":"9d120e45-e7dc-43fe-9300-b76eeb8d8ff4","timestamp":"2026-03-17T18:15:23.085Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}","newString":"// archiveCheckpoints archives checkpoint files to Parquet format.\n// Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet\n// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}","originalFile":"// Copyright (C) NHR@FAU, University Erlangen-Nuremberg.\n// All rights reserved. This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\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\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\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Collect rows from all hosts in this cluster using worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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// Collect all rows and file info\n\t\tvar allRows []ParquetMetricRow\n\t\tvar allResults []hostResult\n\t\tfor r := range results {\n\t\t\tallRows = append(allRows, r.rows...)\n\t\t\tallResults = append(allResults, r)\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 len(allRows) == 0 {\n\t\t\tcontinue\n\t\t}\n\n\t\t// Write one Parquet file per cluster\n\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n\t\tif err := writeParquetArchive(parquetFile, allRows); err != nil {\n\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)\n\t\t}\n\n\t\t// Delete archived checkpoint files\n\t\tfor _, result := range allResults {\n\t\t\tfor _, file := range result.files {\n\t\t\t\tfilename := filepath.Join(result.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\tlen(allRows), totalFiles, cluster, parquetFile)\n\t}\n\n\treturn totalFiles, nil\n}\n","structuredPatch":[{"oldStart":168,"oldLines":6,"newStart":168,"newLines":8,"lines":[" "," // archiveCheckpoints archives checkpoint files to Parquet format."," // Produces one Parquet file per cluster: <cleanupDir>/<cluster>/<timestamp>.parquet","+// Each host's rows are written as a separate row group to avoid accumulating","+// all data in memory at once."," func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {","   clusterEntries, err := os.ReadDir(checkpointsDir)","   if err != nil {"]},{"oldStart":187,"oldLines":7,"newStart":189,"newLines":7,"lines":["       return totalFiles, err","     }"," ","-    // Collect rows from all hosts in this cluster using worker pool","+    // Stream per-host rows to parquet writer via worker pool","     type hostResult struct {","       rows  []ParquetMetricRow","       files []string // checkpoint filenames to delete after successful write"]},{"oldStart":235,"oldLines":32,"newStart":237,"newLines":57,"lines":["       close(results)","     }()"," ","-    // Collect all rows and file info","-    var allRows []ParquetMetricRow","-    var allResults []hostResult","+    // Open streaming writer and write each host's rows as a row group","+    parquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))","+    writer, err := newParquetArchiveWriter(parquetFile)","+    if err != nil {","+      // Drain results channel to unblock workers","+      for range results {","+      }","+      return totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)","+    }","+","+    type deleteItem struct {","+      dir   string","+      files []string","+    }","+    var toDelete []deleteItem","+    writeErr := error(nil)","+","     for r := range results {","-      allRows = append(allRows, r.rows...)","-      allResults = append(allResults, r)","+      if writeErr == nil {","+        sortParquetRows(r.rows)","+        if err := writer.WriteHostRows(r.rows); err != nil {","+          writeErr = err","+        }","+      }","+      // Always track files for deletion (even if write failed, we still drain)","+      toDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})","     }"," ","+    if err := writer.Close(); err != nil && writeErr == nil {","+      writeErr = err","+    }","+","     if errs > 0 {","       return totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)","     }"," ","-    if len(allRows) == 0 {","+    if writer.count == 0 {","+      // No data written — remove empty file","+      os.Remove(parquetFile)","       continue","     }"," ","-    // Write one Parquet file per cluster","-    parquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))","-    if err := writeParquetArchive(parquetFile, allRows); err != nil {","-      return totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, err)","+    if writeErr != nil {","+      os.Remove(parquetFile)","+      return totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)","     }"," ","     // Delete archived checkpoint files","-    for _, result := range allResults {","-      for _, file := range result.files {","-        filename := filepath.Join(result.dir, file)","+    for _, item := range toDelete {","+      for _, file := range item.files {","+        filename := filepath.Join(item.dir, file)","         if err := os.Remove(filename); err != nil {","           cclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)","         } else {"]},{"oldStart":270,"oldLines":7,"newStart":297,"newLines":7,"lines":["     }"," ","     cclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",","-      len(allRows), totalFiles, cluster, parquetFile)","+      writer.count, totalFiles, cluster, parquetFile)","   }"," ","   return totalFiles, nil"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"9d120e45-e7dc-43fe-9300-b76eeb8d8ff4","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage metricstore\n\nimport (\n\t\"encoding/json\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"testing\"\n\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\nfunc TestParseScopeFromName(t *testing.T) {\n\ttests := []struct {\n\t\tname      string\n\t\twantScope string\n\t\twantID    string\n\t}{\n\t\t{\"socket0\", \"socket\", \"0\"},\n\t\t{\"socket12\", \"socket\", \"12\"},\n\t\t{\"core0\", \"core\", \"0\"},\n\t\t{\"core127\", \"core\", \"127\"},\n\t\t{\"cpu0\", \"hwthread\", \"0\"},\n\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n\t\t{\"unknown\", \"unknown\", \"\"},\n\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n\t}\n\n\tfor _, tt := range tests {\n\t\tt.Run(tt.name, func(t *testing.T) {\n\t\t\tscope, id := parseScopeFromName(tt.name)\n\t\t\tif scope != tt.wantScope || id != tt.wantID {\n\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n\t\t\t}\n\t\t})\n\t}\n}\n\nfunc TestFlattenCheckpointFile(t *testing.T) {\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n\n\t// cpu_load: 2 non-NaN values at node scope\n\t// mem_bw: 2 non-NaN values at socket0 scope\n\tif len(rows) != 4 {\n\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n\t}\n\n\t// Verify a node-scope row\n\tfound := false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n\t\t\tfound = true\n\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n\t\t\t}\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n\t}\n\n\t// Verify a socket-scope row\n\tfound = false\n\tfor _, r := range rows {\n\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n\t\t\tfound = true\n\t\t}\n\t}\n\tif !found {\n\t\tt.Error(\"expected mem_bw row with scope=socket, scope_id=0\")\n\t}\n}\n\nfunc TestParquetArchiveRoundtrip(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\t// Create checkpoint files on disk (JSON format)\n\tcpDir := filepath.Join(tmpDir, \"checkpoints\", \"testcluster\", \"node001\")\n\tif err := os.MkdirAll(cpDir, 0o755); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1180,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"cpu_load\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{0.5, 0.7, 0.9},\n\t\t\t},\n\t\t\t\"mem_used\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{45.0, 46.0, 47.0},\n\t\t\t},\n\t\t},\n\t\tChildren: map[string]*CheckpointFile{\n\t\t\t\"socket0\": {\n\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\t\t\"mem_bw\": {\n\t\t\t\t\t\tFrequency: 60,\n\t\t\t\t\t\tStart:     1000,\n\t\t\t\t\t\tData:      []schema.Float{100.0, 110.0, 120.0},\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t\tChildren: make(map[string]*CheckpointFile),\n\t\t\t},\n\t\t},\n\t}\n\n\t// Write JSON checkpoint\n\tcpFile := filepath.Join(cpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(cpFile, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Archive to Parquet\n\tarchiveDir := filepath.Join(tmpDir, \"archive\")\n\trows, files, err := archiveCheckpointsToParquet(cpDir, \"testcluster\", \"node001\", 2000)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif len(files) != 1 || files[0] != \"1000.json\" {\n\t\tt.Fatalf(\"expected 1 file, got %v\", files)\n\t}\n\n\tparquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")\n\tif err := writeParquetArchive(parquetFile, rows); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\t// Read back and verify\n\tf, err := os.Open(parquetFile)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tdefer f.Close()\n\n\tstat, _ := f.Stat()\n\tpf, err := pq.OpenFile(f, stat.Size())\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\treader := pq.NewGenericReader[ParquetMetricRow](pf)\n\treadRows := make([]ParquetMetricRow, 100)\n\tn, err := reader.Read(readRows)\n\tif err != nil && n == 0 {\n\t\tt.Fatal(err)\n\t}\n\treadRows = readRows[:n]\n\treader.Close()\n\n\t// We expect: cpu_load(3) + mem_used(3) + mem_bw(3) = 9 rows\n\tif n != 9 {\n\t\tt.Fatalf(\"expected 9 rows in parquet file, got %d\", n)\n\t}\n\n\t// Verify cluster and hostname are set correctly\n\tfor _, r := range readRows {\n\t\tif r.Cluster != \"testcluster\" {\n\t\t\tt.Errorf(\"expected cluster=testcluster, got %s\", r.Cluster)\n\t\t}\n\t\tif r.Hostname != \"node001\" {\n\t\t\tt.Errorf(\"expected hostname=node001, got %s\", r.Hostname)\n\t\t}\n\t}\n\n\t// Verify parquet file is smaller than JSON (compression working)\n\tif stat.Size() == 0 {\n\t\tt.Error(\"parquet file is empty\")\n\t}\n\n\tt.Logf(\"Parquet file size: %d bytes for %d rows\", stat.Size(), n)\n}\n\nfunc TestLoadCheckpointFileFromDisk_JSON(t *testing.T) {\n\ttmpDir := t.TempDir()\n\n\tcf := &CheckpointFile{\n\t\tFrom: 1000,\n\t\tTo:   1060,\n\t\tMetrics: map[string]*CheckpointMetrics{\n\t\t\t\"test_metric\": {\n\t\t\t\tFrequency: 60,\n\t\t\t\tStart:     1000,\n\t\t\t\tData:      []schema.Float{1.0, 2.0, 3.0},\n\t\t\t},\n\t\t},\n\t\tChildren: make(map[string]*CheckpointFile),\n\t}\n\n\tfilename := filepath.Join(tmpDir, \"1000.json\")\n\tdata, err := json.Marshal(cf)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\tif err := os.WriteFile(filename, data, 0o644); err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tloaded, err := loadCheckpointFileFromDisk(filename)\n\tif err != nil {\n\t\tt.Fatal(err)\n\t}\n\n\tif loaded.From != 1000 || loaded.To != 1060 {\n\t\tt.Errorf(\"expected From=1000, To=1060, got From=%d, To=%d\", loaded.From, loaded.To)\n\t}\n\n\tm, ok := loaded.Metrics[\"test_metric\"]\n\tif !ok {\n\t\tt.Fatal(\"expected test_metric in loaded checkpoint\")\n\t}\n\tif m.Frequency != 60 || m.Start != 1000 || len(m.Data) != 3 {\n\t\tt.Errorf(\"unexpected metric data: %+v\", m)\n\t}\n}\n","structuredPatch":[{"oldStart":162,"oldLines":9,"newStart":162,"newLines":17,"lines":["   }"," ","   parquetFile := filepath.Join(archiveDir, \"testcluster\", \"1000.parquet\")","-  if err := writeParquetArchive(parquetFile, rows); err != nil {","+  writer, err := newParquetArchiveWriter(parquetFile)","+  if err != nil {","     t.Fatal(err)","   }","+  sortParquetRows(rows)","+  if err := writer.WriteHostRows(rows); err != nil {","+    t.Fatal(err)","+  }","+  if err := writer.Close(); err != nil {","+    t.Fatal(err)","+  }"," ","   // Read back and verify","   f, err := os.Open(parquetFile)"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"53cbcd29-7347-43e9-909c-86cbb06de2ee","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"442aef62-2c74-45f6-8858-79e6b9da2e9f","isSidechain":false,"promptId":"9e69bd94-834f-43c2-9173-add782b0f1d4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Y1VTXV4w6gCfFBDTJRRJiU","type":"tool_result","content":"=== RUN   TestBufferPoolGetReuse\n--- PASS: TestBufferPoolGetReuse (0.00s)\n=== RUN   TestBufferPoolClear\n--- PASS: TestBufferPoolClear (0.00s)\n=== RUN   TestBufferEndFirstWrite\n--- PASS: TestBufferEndFirstWrite (0.00s)\n=== RUN   TestBufferWriteNaNFill\n--- PASS: TestBufferWriteNaNFill (0.00s)\n=== RUN   TestBufferWriteCapacityOverflow\n--- PASS: TestBufferWriteCapacityOverflow (0.00s)\n=== RUN   TestBufferWriteOverwrite\n--- PASS: TestBufferWriteOverwrite (0.00s)\n=== RUN   TestBufferReadBeforeFirstWrite\n--- PASS: TestBufferReadBeforeFirstWrite (0.00s)\n=== RUN   TestBufferReadChain\n--- PASS: TestBufferReadChain (0.00s)\n=== RUN   TestBufferReadIdxAfterSwitch\n--- PASS: TestBufferReadIdxAfterSwitch (0.00s)\n=== RUN   TestBufferReadNaNValues\n--- PASS: TestBufferReadNaNValues (0.00s)\n=== RUN   TestBufferReadAccumulation\n--- PASS: TestBufferReadAccumulation (0.00s)\n=== RUN   TestBufferFreeRetention\n--- PASS: TestBufferFreeRetention (0.00s)\n=== RUN   TestBufferFreeAll\n--- PASS: TestBufferFreeAll (0.00s)\n=== RUN   TestForceFreeOldestPoolReturn\n--- PASS: TestForceFreeOldestPoolReturn (0.00s)\n=== RUN   TestForceFreeOldestSingleBuffer\n--- PASS: TestForceFreeOldestSingleBuffer (0.00s)\n=== RUN   TestBufferIterFromToOrder\n--- PASS: TestBufferIterFromToOrder (0.00s)\n=== RUN   TestBufferIterFromToFiltered\n--- PASS: TestBufferIterFromToFiltered (0.00s)\n=== RUN   TestBufferIterFromToNilBuffer\n--- PASS: TestBufferIterFromToNilBuffer (0.00s)\n=== RUN   TestBufferCount\n--- PASS: TestBufferCount (0.00s)\n=== RUN   TestAssignAggregationStrategy\n=== RUN   TestAssignAggregationStrategy/empty_string\n=== RUN   TestAssignAggregationStrategy/sum\n=== RUN   TestAssignAggregationStrategy/avg\n=== RUN   TestAssignAggregationStrategy/invalid\n--- PASS: TestAssignAggregationStrategy (0.00s)\n    --- PASS: TestAssignAggregationStrategy/empty_string (0.00s)\n    --- PASS: TestAssignAggregationStrategy/sum (0.00s)\n    --- PASS: TestAssignAggregationStrategy/avg (0.00s)\n    --- PASS: TestAssignAggregationStrategy/invalid (0.00s)\n=== RUN   TestBufferWrite\n--- PASS: TestBufferWrite (0.00s)\n=== RUN   TestBufferRead\n--- PASS: TestBufferRead (0.00s)\n=== RUN   TestHealthCheck\n=== RUN   TestHealthCheck/all_metrics_healthy\n=== RUN   TestHealthCheck/some_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node002degraded metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/some_metrics_missing\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node003missing metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/node_not_found\n=== RUN   TestHealthCheck/all_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used cpu_user cpu_system]\n=== RUN   TestHealthCheck/multiple_nodes_mixed_states\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used]\n--- PASS: TestHealthCheck (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_healthy (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_missing (0.00s)\n    --- PASS: TestHealthCheck/node_not_found (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/multiple_nodes_mixed_states (0.00s)\n=== RUN   TestGetHealthyMetrics\n=== RUN   TestGetHealthyMetrics/mixed_health_states\n=== RUN   TestGetHealthyMetrics/node_not_found\n=== RUN   TestGetHealthyMetrics/check_only_healthy_metric\n--- PASS: TestGetHealthyMetrics (0.00s)\n    --- PASS: TestGetHealthyMetrics/mixed_health_states (0.00s)\n    --- PASS: TestGetHealthyMetrics/node_not_found (0.00s)\n    --- PASS: TestGetHealthyMetrics/check_only_healthy_metric (0.00s)\n=== RUN   TestBufferHealthChecks\n=== RUN   TestBufferHealthChecks/nil_buffer\n=== RUN   TestBufferHealthChecks/empty_buffer\n=== RUN   TestBufferHealthChecks/healthy_buffer_with_recent_data\n=== RUN   TestBufferHealthChecks/stale_buffer_beyond_threshold\n=== RUN   TestBufferHealthChecks/buffer_at_threshold_boundary\n--- PASS: TestBufferHealthChecks (0.00s)\n    --- PASS: TestBufferHealthChecks/nil_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/empty_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/healthy_buffer_with_recent_data (0.00s)\n    --- PASS: TestBufferHealthChecks/stale_buffer_beyond_threshold (0.00s)\n    --- PASS: TestBufferHealthChecks/buffer_at_threshold_boundary (0.00s)\n=== RUN   TestBufferPoolClean\n--- PASS: TestBufferPoolClean (0.00s)\n=== RUN   TestParseScopeFromName\n=== RUN   TestParseScopeFromName/socket0\n=== RUN   TestParseScopeFromName/socket12\n=== RUN   TestParseScopeFromName/core0\n=== RUN   TestParseScopeFromName/core127\n=== RUN   TestParseScopeFromName/cpu0\n=== RUN   TestParseScopeFromName/hwthread5\n=== RUN   TestParseScopeFromName/memoryDomain0\n=== RUN   TestParseScopeFromName/accelerator0\n=== RUN   TestParseScopeFromName/unknown\n=== RUN   TestParseScopeFromName/socketX\n--- PASS: TestParseScopeFromName (0.00s)\n    --- PASS: TestParseScopeFromName/socket0 (0.00s)\n    --- PASS: TestParseScopeFromName/socket12 (0.00s)\n    --- PASS: TestParseScopeFromName/core0 (0.00s)\n    --- PASS: TestParseScopeFromName/core127 (0.00s)\n    --- PASS: TestParseScopeFromName/cpu0 (0.00s)\n    --- PASS: TestParseScopeFromName/hwthread5 (0.00s)\n    --- PASS: TestParseScopeFromName/memoryDomain0 (0.00s)\n    --- PASS: TestParseScopeFromName/accelerator0 (0.00s)\n    --- PASS: TestParseScopeFromName/unknown (0.00s)\n    --- PASS: TestParseScopeFromName/socketX (0.00s)\n=== RUN   TestFlattenCheckpointFile\n--- PASS: TestFlattenCheckpointFile (0.00s)\n=== RUN   TestParquetArchiveRoundtrip\n    parquetArchive_test.go:219: Parquet file size: 2060 bytes for 9 rows\n--- PASS: TestParquetArchiveRoundtrip (0.01s)\n=== RUN   TestLoadCheckpointFileFromDisk_JSON\n--- PASS: TestLoadCheckpointFileFromDisk_JSON (0.00s)\n=== RUN   TestBuildScopeQueries\n=== RUN   TestBuildScopeQueries/HWThread->HWThread\n=== RUN   TestBuildScopeQueries/Core->Core\n=== RUN   TestBuildScopeQueries/Socket->Socket\n=== RUN   TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN   TestBuildScopeQueries/Node->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN   TestBuildScopeQueries/HWThread->Core\n=== RUN   TestBuildScopeQueries/HWThread->Socket\n=== RUN   TestBuildScopeQueries/HWThread->Node\n=== RUN   TestBuildScopeQueries/Core->Socket\n=== RUN   TestBuildScopeQueries/Core->Node\n=== RUN   TestBuildScopeQueries/Socket->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN   TestBuildScopeQueries/Accelerator->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n    --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN   TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN   TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN   TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN   TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok  \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.496s","is_error":false}]},"uuid":"0793b054-000b-44b7-98f9-e872d7349770","timestamp":"2026-03-17T18:15:40.202Z","toolUseResult":{"stdout":"=== RUN   TestBufferPoolGetReuse\n--- PASS: TestBufferPoolGetReuse (0.00s)\n=== RUN   TestBufferPoolClear\n--- PASS: TestBufferPoolClear (0.00s)\n=== RUN   TestBufferEndFirstWrite\n--- PASS: TestBufferEndFirstWrite (0.00s)\n=== RUN   TestBufferWriteNaNFill\n--- PASS: TestBufferWriteNaNFill (0.00s)\n=== RUN   TestBufferWriteCapacityOverflow\n--- PASS: TestBufferWriteCapacityOverflow (0.00s)\n=== RUN   TestBufferWriteOverwrite\n--- PASS: TestBufferWriteOverwrite (0.00s)\n=== RUN   TestBufferReadBeforeFirstWrite\n--- PASS: TestBufferReadBeforeFirstWrite (0.00s)\n=== RUN   TestBufferReadChain\n--- PASS: TestBufferReadChain (0.00s)\n=== RUN   TestBufferReadIdxAfterSwitch\n--- PASS: TestBufferReadIdxAfterSwitch (0.00s)\n=== RUN   TestBufferReadNaNValues\n--- PASS: TestBufferReadNaNValues (0.00s)\n=== RUN   TestBufferReadAccumulation\n--- PASS: TestBufferReadAccumulation (0.00s)\n=== RUN   TestBufferFreeRetention\n--- PASS: TestBufferFreeRetention (0.00s)\n=== RUN   TestBufferFreeAll\n--- PASS: TestBufferFreeAll (0.00s)\n=== RUN   TestForceFreeOldestPoolReturn\n--- PASS: TestForceFreeOldestPoolReturn (0.00s)\n=== RUN   TestForceFreeOldestSingleBuffer\n--- PASS: TestForceFreeOldestSingleBuffer (0.00s)\n=== RUN   TestBufferIterFromToOrder\n--- PASS: TestBufferIterFromToOrder (0.00s)\n=== RUN   TestBufferIterFromToFiltered\n--- PASS: TestBufferIterFromToFiltered (0.00s)\n=== RUN   TestBufferIterFromToNilBuffer\n--- PASS: TestBufferIterFromToNilBuffer (0.00s)\n=== RUN   TestBufferCount\n--- PASS: TestBufferCount (0.00s)\n=== RUN   TestAssignAggregationStrategy\n=== RUN   TestAssignAggregationStrategy/empty_string\n=== RUN   TestAssignAggregationStrategy/sum\n=== RUN   TestAssignAggregationStrategy/avg\n=== RUN   TestAssignAggregationStrategy/invalid\n--- PASS: TestAssignAggregationStrategy (0.00s)\n    --- PASS: TestAssignAggregationStrategy/empty_string (0.00s)\n    --- PASS: TestAssignAggregationStrategy/sum (0.00s)\n    --- PASS: TestAssignAggregationStrategy/avg (0.00s)\n    --- PASS: TestAssignAggregationStrategy/invalid (0.00s)\n=== RUN   TestBufferWrite\n--- PASS: TestBufferWrite (0.00s)\n=== RUN   TestBufferRead\n--- PASS: TestBufferRead (0.00s)\n=== RUN   TestHealthCheck\n=== RUN   TestHealthCheck/all_metrics_healthy\n=== RUN   TestHealthCheck/some_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node002degraded metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/some_metrics_missing\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node003missing metrics:[cpu_user cpu_system]\n=== RUN   TestHealthCheck/node_not_found\n=== RUN   TestHealthCheck/all_metrics_stale\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used cpu_user cpu_system]\n=== RUN   TestHealthCheck/multiple_nodes_mixed_states\n<7>[DEBUG]    2026/03/17 19:15:40 [metricstore] HealthCheck: node node005degraded metrics:[load mem_used]\n--- PASS: TestHealthCheck (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_healthy (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/some_metrics_missing (0.00s)\n    --- PASS: TestHealthCheck/node_not_found (0.00s)\n    --- PASS: TestHealthCheck/all_metrics_stale (0.00s)\n    --- PASS: TestHealthCheck/multiple_nodes_mixed_states (0.00s)\n=== RUN   TestGetHealthyMetrics\n=== RUN   TestGetHealthyMetrics/mixed_health_states\n=== RUN   TestGetHealthyMetrics/node_not_found\n=== RUN   TestGetHealthyMetrics/check_only_healthy_metric\n--- PASS: TestGetHealthyMetrics (0.00s)\n    --- PASS: TestGetHealthyMetrics/mixed_health_states (0.00s)\n    --- PASS: TestGetHealthyMetrics/node_not_found (0.00s)\n    --- PASS: TestGetHealthyMetrics/check_only_healthy_metric (0.00s)\n=== RUN   TestBufferHealthChecks\n=== RUN   TestBufferHealthChecks/nil_buffer\n=== RUN   TestBufferHealthChecks/empty_buffer\n=== RUN   TestBufferHealthChecks/healthy_buffer_with_recent_data\n=== RUN   TestBufferHealthChecks/stale_buffer_beyond_threshold\n=== RUN   TestBufferHealthChecks/buffer_at_threshold_boundary\n--- PASS: TestBufferHealthChecks (0.00s)\n    --- PASS: TestBufferHealthChecks/nil_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/empty_buffer (0.00s)\n    --- PASS: TestBufferHealthChecks/healthy_buffer_with_recent_data (0.00s)\n    --- PASS: TestBufferHealthChecks/stale_buffer_beyond_threshold (0.00s)\n    --- PASS: TestBufferHealthChecks/buffer_at_threshold_boundary (0.00s)\n=== RUN   TestBufferPoolClean\n--- PASS: TestBufferPoolClean (0.00s)\n=== RUN   TestParseScopeFromName\n=== RUN   TestParseScopeFromName/socket0\n=== RUN   TestParseScopeFromName/socket12\n=== RUN   TestParseScopeFromName/core0\n=== RUN   TestParseScopeFromName/core127\n=== RUN   TestParseScopeFromName/cpu0\n=== RUN   TestParseScopeFromName/hwthread5\n=== RUN   TestParseScopeFromName/memoryDomain0\n=== RUN   TestParseScopeFromName/accelerator0\n=== RUN   TestParseScopeFromName/unknown\n=== RUN   TestParseScopeFromName/socketX\n--- PASS: TestParseScopeFromName (0.00s)\n    --- PASS: TestParseScopeFromName/socket0 (0.00s)\n    --- PASS: TestParseScopeFromName/socket12 (0.00s)\n    --- PASS: TestParseScopeFromName/core0 (0.00s)\n    --- PASS: TestParseScopeFromName/core127 (0.00s)\n    --- PASS: TestParseScopeFromName/cpu0 (0.00s)\n    --- PASS: TestParseScopeFromName/hwthread5 (0.00s)\n    --- PASS: TestParseScopeFromName/memoryDomain0 (0.00s)\n    --- PASS: TestParseScopeFromName/accelerator0 (0.00s)\n    --- PASS: TestParseScopeFromName/unknown (0.00s)\n    --- PASS: TestParseScopeFromName/socketX (0.00s)\n=== RUN   TestFlattenCheckpointFile\n--- PASS: TestFlattenCheckpointFile (0.00s)\n=== RUN   TestParquetArchiveRoundtrip\n    parquetArchive_test.go:219: Parquet file size: 2060 bytes for 9 rows\n--- PASS: TestParquetArchiveRoundtrip (0.01s)\n=== RUN   TestLoadCheckpointFileFromDisk_JSON\n--- PASS: TestLoadCheckpointFileFromDisk_JSON (0.00s)\n=== RUN   TestBuildScopeQueries\n=== RUN   TestBuildScopeQueries/HWThread->HWThread\n=== RUN   TestBuildScopeQueries/Core->Core\n=== RUN   TestBuildScopeQueries/Socket->Socket\n=== RUN   TestBuildScopeQueries/MemoryDomain->MemoryDomain\n=== RUN   TestBuildScopeQueries/Node->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Accelerator\n=== RUN   TestBuildScopeQueries/HWThread->Core\n=== RUN   TestBuildScopeQueries/HWThread->Socket\n=== RUN   TestBuildScopeQueries/HWThread->Node\n=== RUN   TestBuildScopeQueries/Core->Socket\n=== RUN   TestBuildScopeQueries/Core->Node\n=== RUN   TestBuildScopeQueries/Socket->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Node\n=== RUN   TestBuildScopeQueries/MemoryDomain->Socket\n=== RUN   TestBuildScopeQueries/Accelerator->Node\n=== RUN   TestBuildScopeQueries/Accelerator->Core_(exception)\n--- PASS: TestBuildScopeQueries (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->HWThread (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->MemoryDomain (0.00s)\n    --- PASS: TestBuildScopeQueries/Node->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Accelerator (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Core (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/HWThread->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Core->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Socket->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/MemoryDomain->Socket (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Node (0.00s)\n    --- PASS: TestBuildScopeQueries/Accelerator->Core_(exception) (0.00s)\n=== RUN   TestBuildScopeQueries_UnhandledCase\n--- PASS: TestBuildScopeQueries_UnhandledCase (0.00s)\n=== RUN   TestIntToStringSlice\n--- PASS: TestIntToStringSlice (0.00s)\n=== RUN   TestSanitizeStats\n--- PASS: TestSanitizeStats (0.00s)\n=== RUN   TestNodeToNodeQuery\n--- PASS: TestNodeToNodeQuery (0.00s)\nPASS\nok  \tgithub.com/ClusterCockpit/cc-backend/pkg/metricstore\t0.496s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"442aef62-2c74-45f6-8858-79e6b9da2e9f","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"0793b054-000b-44b7-98f9-e872d7349770","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0141zKHqUaRE5ZzPG2dBZwmN","type":"message","role":"assistant","content":[{"type":"text","text":"All tests pass and `go vet` is clean. Here's a summary of the changes:\n\n### Changes Made\n\n**`pkg/metricstore/parquetArchive.go`**:\n- Added `parquetArchiveWriter` struct with `newParquetArchiveWriter()`, `WriteHostRows()`, and `Close()` methods — streams rows incrementally instead of buffering everything\n- Removed `writeParquetArchive()` which buffered all rows + used `SortingWriterConfig` (the double-buffering culprit)\n- Each `WriteHostRows()` call sorts in-place and flushes, creating one row group per host\n- Added `estimateRowCount()` to pre-allocate the per-host rows slice\n- Added `sortParquetRows()` helper\n- `archiveCheckpointsToParquet()` now pre-allocates rows using `estimateRowCount()`\n\n**`pkg/metricstore/archive.go`**:\n- `archiveCheckpoints()` now opens a `parquetArchiveWriter` before consuming results\n- Each host's rows are written and flushed immediately via `WriteHostRows()`, then the rows are GC'd\n- Only one host's data lives in memory at a time instead of all hosts\n- Empty file cleanup if no data was written\n\n**`pkg/metricstore/parquetArchive_test.go`**:\n- Updated `TestParquetArchiveRoundtrip` to use the new streaming writer API\n\n### Memory Impact\n- **Before**: ~3x raw data (all rows + sorting writer copy + append overhead) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3493,"cache_read_input_tokens":35270,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3493},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ97Gpd8w1yQHh3JNoHUn","type":"assistant","uuid":"cb8ce8a5-8c94-457e-92f2-d57e5590614f","timestamp":"2026-03-17T18:15:51.621Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"2430868c-673d-479b-8db3-af90c85f7921","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015JSipUSkSXoxHkMsaNbZTP","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→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    18→\tpq \"github.com/parquet-go/parquet-go\"\n    19→)\n    20→\n    21→// ParquetMetricRow is the long-format schema for archived metric data.\n    22→// One row per (host, metric, scope, scope_id, timestamp) data point.\n    23→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n    24→type ParquetMetricRow struct {\n    25→\tCluster   string  `parquet:\"cluster\"`\n    26→\tHostname  string  `parquet:\"hostname\"`\n    27→\tMetric    string  `parquet:\"metric\"`\n    28→\tScope     string  `parquet:\"scope\"`\n    29→\tScopeID   string  `parquet:\"scope_id\"`\n    30→\tTimestamp int64   `parquet:\"timestamp\"`\n    31→\tFrequency int64   `parquet:\"frequency\"`\n    32→\tValue     float32 `parquet:\"value\"`\n    33→}\n    34→\n    35→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n    36→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    37→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    38→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n    39→\tfor metricName, cm := range cf.Metrics {\n    40→\t\tts := cm.Start\n    41→\t\tfor _, v := range cm.Data {\n    42→\t\t\tif !v.IsNaN() {\n    43→\t\t\t\trows = append(rows, ParquetMetricRow{\n    44→\t\t\t\t\tCluster:   cluster,\n    45→\t\t\t\t\tHostname:  hostname,\n    46→\t\t\t\t\tMetric:    metricName,\n    47→\t\t\t\t\tScope:     scope,\n    48→\t\t\t\t\tScopeID:   scopeID,\n    49→\t\t\t\t\tTimestamp: ts,\n    50→\t\t\t\t\tFrequency: cm.Frequency,\n    51→\t\t\t\t\tValue:     float32(v),\n    52→\t\t\t\t})\n    53→\t\t\t}\n    54→\t\t\tts += cm.Frequency\n    55→\t\t}\n    56→\t}\n    57→\n    58→\tfor childName, childCf := range cf.Children {\n    59→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    60→\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n    61→\t}\n    62→\n    63→\treturn rows\n    64→}\n    65→\n    66→// parseScopeFromName infers scope and scope_id from a child level name.\n    67→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    68→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    69→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    70→func parseScopeFromName(name string) (string, string) {\n    71→\tprefixes := []struct {\n    72→\t\tprefix string\n    73→\t\tscope  string\n    74→\t}{\n    75→\t\t{\"socket\", \"socket\"},\n    76→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    77→\t\t{\"core\", \"core\"},\n    78→\t\t{\"hwthread\", \"hwthread\"},\n    79→\t\t{\"cpu\", \"hwthread\"},\n    80→\t\t{\"accelerator\", \"accelerator\"},\n    81→\t}\n    82→\n    83→\tfor _, p := range prefixes {\n    84→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    85→\t\t\tid := name[len(p.prefix):]\n    86→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    87→\t\t\t\treturn p.scope, id\n    88→\t\t\t}\n    89→\t\t}\n    90→\t}\n    91→\n    92→\treturn name, \"\"\n    93→}\n    94→\n    95→// parquetArchiveWriter supports incremental writes to a Parquet file.\n    96→// Each call to WriteHostRows writes one row group (typically one host's data),\n    97→// avoiding accumulation of all rows in memory.\n    98→type parquetArchiveWriter struct {\n    99→\twriter *pq.GenericWriter[ParquetMetricRow]\n   100→\tbw     *bufio.Writer\n   101→\tf      *os.File\n   102→\tcount  int\n   103→}\n   104→\n   105→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n   106→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n   107→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n   108→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n   109→\t}\n   110→\n   111→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   112→\tif err != nil {\n   113→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n   114→\t}\n   115→\n   116→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   117→\n   118→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   119→\t\tpq.Compression(&pq.Zstd),\n   120→\t)\n   121→\n   122→\treturn &parquetArchiveWriter{writer: writer, bw: bw, f: f}, nil\n   123→}\n   124→\n   125→// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n   126→// and flushes to create a separate row group.\n   127→func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n   128→\tsort.Slice(rows, func(i, j int) bool {\n   129→\t\tif rows[i].Metric != rows[j].Metric {\n   130→\t\t\treturn rows[i].Metric < rows[j].Metric\n   131→\t\t}\n   132→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   133→\t})\n   134→\n   135→\tif _, err := w.writer.Write(rows); err != nil {\n   136→\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n   137→\t}\n   138→\n   139→\tif err := w.writer.Flush(); err != nil {\n   140→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n   141→\t}\n   142→\n   143→\tw.count += len(rows)\n   144→\treturn nil\n   145→}\n   146→\n   147→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n   148→func (w *parquetArchiveWriter) Close() error {\n   149→\tif err := w.writer.Close(); err != nil {\n   150→\t\tw.f.Close()\n   151→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n   152→\t}\n   153→\n   154→\tif err := w.bw.Flush(); err != nil {\n   155→\t\tw.f.Close()\n   156→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n   157→\t}\n   158→\n   159→\treturn w.f.Close()\n   160→}\n   161→\n   162→// sortParquetRows sorts rows by (metric, timestamp) in-place.\n   163→func sortParquetRows(rows []ParquetMetricRow) {\n   164→\tsort.Slice(rows, func(i, j int) bool {\n   165→\t\tif rows[i].Metric != rows[j].Metric {\n   166→\t\t\treturn rows[i].Metric < rows[j].Metric\n   167→\t\t}\n   168→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   169→\t})\n   170→}\n   171→\n   172→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   173→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   174→// before converting it to Parquet format.\n   175→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   176→\tf, err := os.Open(filename)\n   177→\tif err != nil {\n   178→\t\treturn nil, err\n   179→\t}\n   180→\tdefer f.Close()\n   181→\n   182→\text := filepath.Ext(filename)\n   183→\tswitch ext {\n   184→\tcase \".json\":\n   185→\t\tcf := &CheckpointFile{}\n   186→\t\tbr := bufio.NewReader(f)\n   187→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   188→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   189→\t\t}\n   190→\t\treturn cf, nil\n   191→\n   192→\tcase \".bin\":\n   193→\t\tbr := bufio.NewReader(f)\n   194→\t\tvar magic uint32\n   195→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   196→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   197→\t\t}\n   198→\t\tif magic != snapFileMagic {\n   199→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   200→\t\t}\n   201→\t\tvar fileFrom, fileTo int64\n   202→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   203→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   204→\t\t}\n   205→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   206→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   207→\t\t}\n   208→\t\tcf, err := readBinaryLevel(br)\n   209→\t\tif err != nil {\n   210→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   211→\t\t}\n   212→\t\tcf.From = fileFrom\n   213→\t\tcf.To = fileTo\n   214→\t\treturn cf, nil\n   215→\n   216→\tdefault:\n   217→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   218→\t}\n   219→}\n   220→\n   221→// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n   222→// Used for pre-allocating the rows slice to avoid repeated append doubling.\n   223→func estimateRowCount(cf *CheckpointFile) int {\n   224→\tn := 0\n   225→\tfor _, cm := range cf.Metrics {\n   226→\t\tn += len(cm.Data)\n   227→\t}\n   228→\tfor _, child := range cf.Children {\n   229→\t\tn += estimateRowCount(child)\n   230→\t}\n   231→\treturn n\n   232→}\n   233→\n   234→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   235→// converts them to Parquet rows. Returns the rows and filenames that were processed.\n   236→func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {\n   237→\tentries, err := os.ReadDir(dir)\n   238→\tif err != nil {\n   239→\t\treturn nil, nil, err\n   240→\t}\n   241→\n   242→\tfiles, err := findFiles(entries, from, false)\n   243→\tif err != nil {\n   244→\t\treturn nil, nil, err\n   245→\t}\n   246→\n   247→\tif len(files) == 0 {\n   248→\t\treturn nil, nil, nil\n   249→\t}\n   250→\n   251→\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n   252→\ttype loaded struct {\n   253→\t\tcf       *CheckpointFile\n   254→\t\tfilename string\n   255→\t}\n   256→\tvar checkpoints []loaded\n   257→\ttotalEstimate := 0\n   258→\n   259→\tfor _, checkpoint := range files {\n   260→\t\tfilename := filepath.Join(dir, checkpoint)\n   261→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   262→\t\tif err != nil {\n   263→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   264→\t\t\tcontinue\n   265→\t\t}\n   266→\t\ttotalEstimate += estimateRowCount(cf)\n   267→\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n   268→\t}\n   269→\n   270→\tif len(checkpoints) == 0 {\n   271→\t\treturn nil, nil, nil\n   272→\t}\n   273→\n   274→\trows := make([]ParquetMetricRow, 0, totalEstimate)\n   275→\tprocessedFiles := make([]string, 0, len(checkpoints))\n   276→\n   277→\tfor _, cp := range checkpoints {\n   278→\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n   279→\t\tprocessedFiles = append(processedFiles, cp.filename)\n   280→\t}\n   281→\n   282→\treturn rows, processedFiles, nil\n   283→}\n   284→"}]},"uuid":"0b8f00ca-48da-4b9c-a3e9-265029b39781","timestamp":"2026-03-18T04:02:36.395Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"3fbe0910-10c9-48c1-9b6b-7929c4eba811","timestamp":"2026-03-18T04:02:36.577Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"912f12d8-7474-41e1-8f48-739a31adb3d8","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LEnHcZQkV5PNC7XPaU6Pgb","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\"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":"1112516e-76fc-42b2-9709-8c6466b84dd7","timestamp":"2026-03-18T04:02:36.604Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"dbd83243-3f80-41dd-a55a-79a9516936db","timestamp":"2026-03-18T04:02:36.837Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"5143d6be-379b-4abf-a157-a66bd9488b93","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GNs92J7Re4V1XiEhUdVFzR","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":"5139460a-6d14-44e6-83e4-ce582368071b","timestamp":"2026-03-18T04:02:36.857Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"f80b2e80-bf73-4f8f-bf82-05cad2523928","timestamp":"2026-03-18T04:02:37.006Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"e994be56-621a-458a-9404-8649dd75d275","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019UUYjj6J4QJS6RmAgcJTSo","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":"9c55ee61-e630-466b-8ade-4bc796ede8ec","timestamp":"2026-03-18T04:02:39.550Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"5fcacfb4-089a-4e6c-aa2c-47de7b6497db","timestamp":"2026-03-18T04:02:39.550Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"021c6590-b1e0-4880-a2ac-ed0a85ce8b0b","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01N4KBTu1ntjU3HDvgueA7nE","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\"time\"\n    10→\n    11→\t\"github.com/ClusterCockpit/cc-backend/internal/config\"\n    12→\t\"github.com/ClusterCockpit/cc-backend/internal/repository\"\n    13→\tpqarchive \"github.com/ClusterCockpit/cc-backend/pkg/archive/parquet\"\n    14→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    15→\t\"github.com/go-co-op/gocron/v2\"\n    16→)\n    17→\n    18→func RegisterNodeStateRetentionDeleteService(ageHours int) {\n    19→\tcclog.Info(\"Register node state retention delete service\")\n    20→\n    21→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(2, 0, 0))),\n    22→\t\tgocron.NewTask(\n    23→\t\t\tfunc() {\n    24→\t\t\t\tcutoff := time.Now().Unix() - int64(ageHours*3600)\n    25→\t\t\t\tnodeRepo := repository.GetNodeRepository()\n    26→\t\t\t\tcnt, err := nodeRepo.DeleteNodeStatesBefore(cutoff)\n    27→\t\t\t\tif err != nil {\n    28→\t\t\t\t\tcclog.Errorf(\"NodeState retention: error deleting old rows: %v\", err)\n    29→\t\t\t\t} else if cnt > 0 {\n    30→\t\t\t\t\tcclog.Infof(\"NodeState retention: deleted %d old rows\", cnt)\n    31→\t\t\t\t}\n    32→\t\t\t}))\n    33→}\n    34→\n    35→func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n    36→\tcclog.Info(\"Register node state retention move service\")\n    37→\n    38→\tmaxFileSizeMB := cfg.MaxFileSizeMB\n    39→\tif maxFileSizeMB <= 0 {\n    40→\t\tmaxFileSizeMB = 128\n    41→\t}\n    42→\n    43→\tageHours := cfg.Age\n    44→\tif ageHours <= 0 {\n    45→\t\tageHours = 24\n    46→\t}\n    47→\n    48→\tvar target pqarchive.ParquetTarget\n    49→\tvar err error\n    50→\n    51→\tswitch cfg.TargetKind {\n    52→\tcase \"s3\":\n    53→\t\ttarget, err = pqarchive.NewS3Target(pqarchive.S3TargetConfig{\n    54→\t\t\tEndpoint:     cfg.TargetEndpoint,\n    55→\t\t\tBucket:       cfg.TargetBucket,\n    56→\t\t\tAccessKey:    cfg.TargetAccessKey,\n    57→\t\t\tSecretKey:    cfg.TargetSecretKey,\n    58→\t\t\tRegion:       cfg.TargetRegion,\n    59→\t\t\tUsePathStyle: cfg.TargetUsePathStyle,\n    60→\t\t})\n    61→\tdefault:\n    62→\t\ttarget, err = pqarchive.NewFileTarget(cfg.TargetPath)\n    63→\t}\n    64→\n    65→\tif err != nil {\n    66→\t\tcclog.Errorf(\"NodeState move retention: failed to create target: %v\", err)\n    67→\t\treturn\n    68→\t}\n    69→\n    70→\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(2, 30, 0))),\n    71→\t\tgocron.NewTask(\n    72→\t\t\tfunc() {\n    73→\t\t\t\tcutoff := time.Now().Unix() - int64(ageHours*3600)\n    74→\t\t\t\tnodeRepo := repository.GetNodeRepository()\n    75→\n    76→\t\t\t\trows, err := nodeRepo.FindNodeStatesBefore(cutoff)\n    77→\t\t\t\tif err != nil {\n    78→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: error finding rows: %v\", err)\n    79→\t\t\t\t\treturn\n    80→\t\t\t\t}\n    81→\t\t\t\tif len(rows) == 0 {\n    82→\t\t\t\t\treturn\n    83→\t\t\t\t}\n    84→\n    85→\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\n    86→\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n    87→\n    88→\t\t\t\tfor _, ns := range rows {\n    89→\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{\n    90→\t\t\t\t\t\tTimeStamp:       ns.TimeStamp,\n    91→\t\t\t\t\t\tNodeState:       ns.NodeState,\n    92→\t\t\t\t\t\tHealthState:     ns.HealthState,\n    93→\t\t\t\t\t\tHealthMetrics:   ns.HealthMetrics,\n    94→\t\t\t\t\t\tCpusAllocated:   int32(ns.CpusAllocated),\n    95→\t\t\t\t\t\tMemoryAllocated: ns.MemoryAllocated,\n    96→\t\t\t\t\t\tGpusAllocated:   int32(ns.GpusAllocated),\n    97→\t\t\t\t\t\tJobsRunning:     int32(ns.JobsRunning),\n    98→\t\t\t\t\t\tHostname:        ns.Hostname,\n    99→\t\t\t\t\t\tCluster:         ns.Cluster,\n   100→\t\t\t\t\t\tSubCluster:      ns.SubCluster,\n   101→\t\t\t\t\t}\n   102→\t\t\t\t\tif err := pw.AddRow(row); err != nil {\n   103→\t\t\t\t\t\tcclog.Errorf(\"NodeState move retention: add row: %v\", err)\n   104→\t\t\t\t\t\tcontinue\n   105→\t\t\t\t\t}\n   106→\t\t\t\t}\n   107→\n   108→\t\t\t\tif err := pw.Close(); err != nil {\n   109→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: close writer: %v\", err)\n   110→\t\t\t\t\treturn\n   111→\t\t\t\t}\n   112→\n   113→\t\t\t\tcnt, err := nodeRepo.DeleteNodeStatesBefore(cutoff)\n   114→\t\t\t\tif err != nil {\n   115→\t\t\t\t\tcclog.Errorf(\"NodeState move retention: error deleting rows: %v\", err)\n   116→\t\t\t\t} else {\n   117→\t\t\t\t\tcclog.Infof(\"NodeState move retention: deleted %d rows from db\", cnt)\n   118→\t\t\t\t}\n   119→\t\t\t}))\n   120→}\n   121→"}]},"uuid":"ef5b2bb2-c6c2-4ad6-8de9-f17ad72570d6","timestamp":"2026-03-18T04:02:39.609Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"16ae8feb-f59c-44fd-b541-6d2b7553859c","timestamp":"2026-03-18T04:02:39.610Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"16ae8feb-f59c-44fd-b541-6d2b7553859c","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-18T04:02:39.755Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01AGhRwzpLPizPqmLZJmbUqk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01B3qau1at87zKUnxbhjYBLe","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go","limit":300},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":8899,"cache_read_input_tokens":20542,"cache_creation":{"ephemeral_5m_input_tokens":8899,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ9t2qQ8AnpMjGLdf6L1a","uuid":"a785207e-c3ee-4e7b-884e-ac18e3bc423e"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"4371f6de-6875-46f4-9168-dc00b1848578","timestamp":"2026-03-18T04:02:39.755Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"4371f6de-6875-46f4-9168-dc00b1848578","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B3qau1at87zKUnxbhjYBLe","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\t// Run as Archiver\n    26→\t\tcleanUpWorker(wg, ctx,\n    27→\t\t\tKeys.RetentionInMemory,\n    28→\t\t\t\"archiving\",\n    29→\t\t\tKeys.Cleanup.RootDir,\n    30→\t\t\tfalse,\n    31→\t\t)\n    32→\t} else {\n    33→\t\t// Run as Deleter\n    34→\t\tcleanUpWorker(wg, ctx,\n    35→\t\t\tKeys.RetentionInMemory,\n    36→\t\t\t\"deleting\",\n    37→\t\t\t\"\",\n    38→\t\t\ttrue,\n    39→\t\t)\n    40→\t}\n    41→}\n    42→\n    43→// cleanUpWorker takes simple values to configure what it does\n    44→func cleanUpWorker(wg *sync.WaitGroup, ctx context.Context, interval string, mode string, cleanupDir string, delete bool) {\n    45→\twg.Go(func() {\n    46→\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→// Each host's rows are written as a separate row group to avoid accumulating\n   172→// all data in memory at once.\n   173→func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\n   174→\tclusterEntries, err := os.ReadDir(checkpointsDir)\n   175→\tif err != nil {\n   176→\t\treturn 0, err\n   177→\t}\n   178→\n   179→\ttotalFiles := 0\n   180→\n   181→\tfor _, clusterEntry := range clusterEntries {\n   182→\t\tif !clusterEntry.IsDir() {\n   183→\t\t\tcontinue\n   184→\t\t}\n   185→\n   186→\t\tcluster := clusterEntry.Name()\n   187→\t\thostEntries, err := os.ReadDir(filepath.Join(checkpointsDir, cluster))\n   188→\t\tif err != nil {\n   189→\t\t\treturn totalFiles, err\n   190→\t\t}\n   191→\n   192→\t\t// Stream per-host rows to parquet writer via worker pool\n   193→\t\ttype hostResult struct {\n   194→\t\t\trows  []ParquetMetricRow\n   195→\t\t\tfiles []string // checkpoint filenames to delete after successful write\n   196→\t\t\tdir   string   // checkpoint directory for this host\n   197→\t\t}\n   198→\n   199→\t\tresults := make(chan hostResult, len(hostEntries))\n   200→\t\twork := make(chan struct {\n   201→\t\t\tdir, host string\n   202→\t\t}, Keys.NumWorkers)\n   203→\n   204→\t\tvar wg sync.WaitGroup\n   205→\t\terrs := int32(0)\n   206→\n   207→\t\twg.Add(Keys.NumWorkers)\n   208→\t\tfor w := 0; w < Keys.NumWorkers; w++ {\n   209→\t\t\tgo func() {\n   210→\t\t\t\tdefer wg.Done()\n   211→\t\t\t\tfor item := range work {\n   212→\t\t\t\t\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, from)\n   213→\t\t\t\t\tif err != nil {\n   214→\t\t\t\t\t\tcclog.Errorf(\"[METRICSTORE]> error reading checkpoints for %s/%s: %s\", cluster, item.host, err.Error())\n   215→\t\t\t\t\t\tatomic.AddInt32(&errs, 1)\n   216→\t\t\t\t\t\tcontinue\n   217→\t\t\t\t\t}\n   218→\t\t\t\t\tif len(rows) > 0 {\n   219→\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\n   220→\t\t\t\t\t}\n   221→\t\t\t\t}\n   222→\t\t\t}()\n   223→\t\t}\n   224→\n   225→\t\tgo func() {\n   226→\t\t\tfor _, hostEntry := range hostEntries {\n   227→\t\t\t\tif !hostEntry.IsDir() {\n   228→\t\t\t\t\tcontinue\n   229→\t\t\t\t}\n   230→\t\t\t\tdir := filepath.Join(checkpointsDir, cluster, hostEntry.Name())\n   231→\t\t\t\twork <- struct {\n   232→\t\t\t\t\tdir, host string\n   233→\t\t\t\t}{dir: dir, host: hostEntry.Name()}\n   234→\t\t\t}\n   235→\t\t\tclose(work)\n   236→\t\t\twg.Wait()\n   237→\t\t\tclose(results)\n   238→\t\t}()\n   239→\n   240→\t\t// Open streaming writer and write each host's rows as a row group\n   241→\t\tparquetFile := filepath.Join(cleanupDir, cluster, fmt.Sprintf(\"%d.parquet\", from))\n   242→\t\twriter, err := newParquetArchiveWriter(parquetFile)\n   243→\t\tif err != nil {\n   244→\t\t\t// Drain results channel to unblock workers\n   245→\t\t\tfor range results {\n   246→\t\t\t}\n   247→\t\t\treturn totalFiles, fmt.Errorf(\"creating parquet writer for cluster %s: %w\", cluster, err)\n   248→\t\t}\n   249→\n   250→\t\ttype deleteItem struct {\n   251→\t\t\tdir   string\n   252→\t\t\tfiles []string\n   253→\t\t}\n   254→\t\tvar toDelete []deleteItem\n   255→\t\twriteErr := error(nil)\n   256→\n   257→\t\tfor r := range results {\n   258→\t\t\tif writeErr == nil {\n   259→\t\t\t\tsortParquetRows(r.rows)\n   260→\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n   261→\t\t\t\t\twriteErr = err\n   262→\t\t\t\t}\n   263→\t\t\t}\n   264→\t\t\t// Always track files for deletion (even if write failed, we still drain)\n   265→\t\t\ttoDelete = append(toDelete, deleteItem{dir: r.dir, files: r.files})\n   266→\t\t}\n   267→\n   268→\t\tif err := writer.Close(); err != nil && writeErr == nil {\n   269→\t\t\twriteErr = err\n   270→\t\t}\n   271→\n   272→\t\tif errs > 0 {\n   273→\t\t\treturn totalFiles, fmt.Errorf(\"%d errors reading checkpoints for cluster %s\", errs, cluster)\n   274→\t\t}\n   275→\n   276→\t\tif writer.count == 0 {\n   277→\t\t\t// No data written — remove empty file\n   278→\t\t\tos.Remove(parquetFile)\n   279→\t\t\tcontinue\n   280→\t\t}\n   281→\n   282→\t\tif writeErr != nil {\n   283→\t\t\tos.Remove(parquetFile)\n   284→\t\t\treturn totalFiles, fmt.Errorf(\"writing parquet archive for cluster %s: %w\", cluster, writeErr)\n   285→\t\t}\n   286→\n   287→\t\t// Delete archived checkpoint files\n   288→\t\tfor _, item := range toDelete {\n   289→\t\t\tfor _, file := range item.files {\n   290→\t\t\t\tfilename := filepath.Join(item.dir, file)\n   291→\t\t\t\tif err := os.Remove(filename); err != nil {\n   292→\t\t\t\t\tcclog.Warnf(\"[METRICSTORE]> could not remove archived checkpoint %s: %v\", filename, err)\n   293→\t\t\t\t} else {\n   294→\t\t\t\t\ttotalFiles++\n   295→\t\t\t\t}\n   296→\t\t\t}\n   297→\t\t}\n   298→\n   299→\t\tcclog.Infof(\"[METRICSTORE]> archived %d rows from %d files for cluster %s to %s\",\n   300→\t\t\twriter.count, totalFiles, cluster, parquetFile)"}]},"uuid":"9ba823f7-f70b-408c-85a5-d24ed2584aea","timestamp":"2026-03-18T04:02:39.767Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"c60873cc-1254-4214-8fd0-17084b70fe7c","timestamp":"2026-03-18T04:02:39.768Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"91d42c01-6b72-4d41-9852-696f364e6edb","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013LMkXWdTD9Mrr8mFng5HZw","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\"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,"}]},"uuid":"7b6a47be-a2c0-488e-ba31-b52aea20f0ea","timestamp":"2026-03-18T04:02:43.724Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"1c7c8ba0-45fa-4dcf-a87d-03f5d8f26168","timestamp":"2026-03-18T04:02:43.726Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"1c7c8ba0-45fa-4dcf-a87d-03f5d8f26168","isSidechain":false,"type":"progress","data":{"message":{"type":"assistant","timestamp":"2026-03-18T04:02:45.376Z","message":{"model":"claude-haiku-4-5-20251001","id":"msg_01AeDDgdidv1BEeCrQFmdBTc","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RR1p1p9GmJcZsKdnHvrmY8","name":"Read","input":{"file_path":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer_test.go"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":1586,"cache_read_input_tokens":41470,"cache_creation":{"ephemeral_5m_input_tokens":1586,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"requestId":"req_011CZ9t3JEAaXHwUp2qQFHHG","uuid":"be8ab130-3d8c-4c5e-be06-5c6e300b2aa4"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"b86b4a2f-0e5a-4339-aa72-47e83065dde7","timestamp":"2026-03-18T04:02:45.376Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"b86b4a2f-0e5a-4339-aa72-47e83065dde7","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RR1p1p9GmJcZsKdnHvrmY8","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\"compress/gzip\"\n    11→\t\"encoding/json\"\n    12→\t\"io\"\n    13→\t\"os\"\n    14→\t\"path/filepath\"\n    15→\t\"strings\"\n    16→\t\"sync\"\n    17→\t\"testing\"\n    18→\n    19→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    20→\tpq \"github.com/parquet-go/parquet-go\"\n    21→)\n    22→\n    23→// memTarget collects written files in memory for testing.\n    24→type memTarget struct {\n    25→\tmu    sync.Mutex\n    26→\tfiles map[string][]byte\n    27→}\n    28→\n    29→func newMemTarget() *memTarget {\n    30→\treturn &memTarget{files: make(map[string][]byte)}\n    31→}\n    32→\n    33→func (m *memTarget) WriteFile(name string, data []byte) error {\n    34→\tm.mu.Lock()\n    35→\tdefer m.mu.Unlock()\n    36→\tm.files[name] = append([]byte(nil), data...)\n    37→\treturn nil\n    38→}\n    39→\n    40→func makeTestJob(jobID int64) (*schema.Job, *schema.JobData) {\n    41→\tmeta := &schema.Job{\n    42→\t\tJobID:        jobID,\n    43→\t\tCluster:      \"testcluster\",\n    44→\t\tSubCluster:   \"sc0\",\n    45→\t\tProject:      \"testproject\",\n    46→\t\tUser:         \"testuser\",\n    47→\t\tState:        schema.JobStateCompleted,\n    48→\t\tStartTime:    1700000000,\n    49→\t\tDuration:     3600,\n    50→\t\tWalltime:     7200,\n    51→\t\tNumNodes:     2,\n    52→\t\tNumHWThreads: 16,\n    53→\t\tSMT:          1,\n    54→\t\tResources: []*schema.Resource{\n    55→\t\t\t{Hostname: \"node001\"},\n    56→\t\t\t{Hostname: \"node002\"},\n    57→\t\t},\n    58→\t}\n    59→\n    60→\tdata := schema.JobData{\n    61→\t\t\"cpu_load\": {\n    62→\t\t\tschema.MetricScopeNode: &schema.JobMetric{\n    63→\t\t\t\tUnit:     schema.Unit{Base: \"\"},\n    64→\t\t\t\tTimestep: 60,\n    65→\t\t\t\tSeries: []schema.Series{\n    66→\t\t\t\t\t{\n    67→\t\t\t\t\t\tHostname: \"node001\",\n    68→\t\t\t\t\t\tData:     []schema.Float{1.0, 2.0, 3.0},\n    69→\t\t\t\t\t},\n    70→\t\t\t\t},\n    71→\t\t\t},\n    72→\t\t},\n    73→\t}\n    74→\n    75→\treturn meta, &data\n    76→}\n    77→\n    78→func TestJobToParquetRowConversion(t *testing.T) {\n    79→\tmeta, data := makeTestJob(1001)\n    80→\tmeta.Tags = []*schema.Tag{{Type: \"test\", Name: \"tag1\"}}\n    81→\tmeta.MetaData = map[string]string{\"key\": \"value\"}\n    82→\n    83→\trow, err := JobToParquetRow(meta, data)\n    84→\tif err != nil {\n    85→\t\tt.Fatalf(\"JobToParquetRow: %v\", err)\n    86→\t}\n    87→\n    88→\tif row.JobID != 1001 {\n    89→\t\tt.Errorf(\"JobID = %d, want 1001\", row.JobID)\n    90→\t}\n    91→\tif row.Cluster != \"testcluster\" {\n    92→\t\tt.Errorf(\"Cluster = %q, want %q\", row.Cluster, \"testcluster\")\n    93→\t}\n    94→\tif row.User != \"testuser\" {\n    95→\t\tt.Errorf(\"User = %q, want %q\", row.User, \"testuser\")\n    96→\t}\n    97→\tif row.State != \"completed\" {\n    98→\t\tt.Errorf(\"State = %q, want %q\", row.State, \"completed\")\n    99→\t}\n   100→\tif row.NumNodes != 2 {\n   101→\t\tt.Errorf(\"NumNodes = %d, want 2\", row.NumNodes)\n   102→\t}\n   103→\n   104→\t// Verify resources JSON\n   105→\tvar resources []*schema.Resource\n   106→\tif err := json.Unmarshal(row.ResourcesJSON, &resources); err != nil {\n   107→\t\tt.Fatalf(\"unmarshal resources: %v\", err)\n   108→\t}\n   109→\tif len(resources) != 2 {\n   110→\t\tt.Errorf(\"resources len = %d, want 2\", len(resources))\n   111→\t}\n   112→\n   113→\t// Verify tags JSON\n   114→\tvar tags []*schema.Tag\n   115→\tif err := json.Unmarshal(row.TagsJSON, &tags); err != nil {\n   116→\t\tt.Fatalf(\"unmarshal tags: %v\", err)\n   117→\t}\n   118→\tif len(tags) != 1 || tags[0].Name != \"tag1\" {\n   119→\t\tt.Errorf(\"tags = %v, want [{test tag1}]\", tags)\n   120→\t}\n   121→\n   122→\t// Verify metric data is gzip-compressed valid JSON\n   123→\tgz, err := gzip.NewReader(bytes.NewReader(row.MetricDataGz))\n   124→\tif err != nil {\n   125→\t\tt.Fatalf(\"gzip reader: %v\", err)\n   126→\t}\n   127→\tdecompressed, err := io.ReadAll(gz)\n   128→\tif err != nil {\n   129→\t\tt.Fatalf(\"gzip read: %v\", err)\n   130→\t}\n   131→\tvar jobData schema.JobData\n   132→\tif err := json.Unmarshal(decompressed, &jobData); err != nil {\n   133→\t\tt.Fatalf(\"unmarshal metric data: %v\", err)\n   134→\t}\n   135→\tif _, ok := jobData[\"cpu_load\"]; !ok {\n   136→\t\tt.Error(\"metric data missing cpu_load key\")\n   137→\t}\n   138→}\n   139→\n   140→func TestParquetWriterSingleBatch(t *testing.T) {\n   141→\ttarget := newMemTarget()\n   142→\tpw := NewParquetWriter(target, 512)\n   143→\n   144→\tfor i := range int64(5) {\n   145→\t\tmeta, data := makeTestJob(i)\n   146→\t\trow, err := JobToParquetRow(meta, data)\n   147→\t\tif err != nil {\n   148→\t\t\tt.Fatalf(\"convert job %d: %v\", i, err)\n   149→\t\t}\n   150→\t\tif err := pw.AddJob(*row); err != nil {\n   151→\t\t\tt.Fatalf(\"add job %d: %v\", i, err)\n   152→\t\t}\n   153→\t}\n   154→\n   155→\tif err := pw.Close(); err != nil {\n   156→\t\tt.Fatalf(\"close: %v\", err)\n   157→\t}\n   158→\n   159→\tif len(target.files) != 1 {\n   160→\t\tt.Fatalf(\"expected 1 file, got %d\", len(target.files))\n   161→\t}\n   162→\n   163→\t// Verify the parquet file is readable\n   164→\tfor name, data := range target.files {\n   165→\t\tfile := bytes.NewReader(data)\n   166→\t\tpf, err := pq.OpenFile(file, int64(len(data)))\n   167→\t\tif err != nil {\n   168→\t\t\tt.Fatalf(\"open parquet %s: %v\", name, err)\n   169→\t\t}\n   170→\t\tif pf.NumRows() != 5 {\n   171→\t\t\tt.Errorf(\"parquet rows = %d, want 5\", pf.NumRows())\n   172→\t\t}\n   173→\t}\n   174→}\n   175→\n   176→func TestParquetWriterBatching(t *testing.T) {\n   177→\ttarget := newMemTarget()\n   178→\t// Use a very small max size to force multiple files\n   179→\tpw := NewParquetWriter(target, 0) // 0 MB means every job triggers a flush\n   180→\tpw.maxSizeBytes = 1               // Force flush after every row\n   181→\n   182→\tfor i := range int64(3) {\n   183→\t\tmeta, data := makeTestJob(i)\n   184→\t\trow, err := JobToParquetRow(meta, data)\n   185→\t\tif err != nil {\n   186→\t\t\tt.Fatalf(\"convert job %d: %v\", i, err)\n   187→\t\t}\n   188→\t\tif err := pw.AddJob(*row); err != nil {\n   189→\t\t\tt.Fatalf(\"add job %d: %v\", i, err)\n   190→\t\t}\n   191→\t}\n   192→\n   193→\tif err := pw.Close(); err != nil {\n   194→\t\tt.Fatalf(\"close: %v\", err)\n   195→\t}\n   196→\n   197→\t// With maxSizeBytes=1, each AddJob should flush the previous batch,\n   198→\t// resulting in multiple files\n   199→\tif len(target.files) < 2 {\n   200→\t\tt.Errorf(\"expected multiple files due to batching, got %d\", len(target.files))\n   201→\t}\n   202→\n   203→\t// Verify all files are valid parquet\n   204→\tfor name, data := range target.files {\n   205→\t\tfile := bytes.NewReader(data)\n   206→\t\t_, err := pq.OpenFile(file, int64(len(data)))\n   207→\t\tif err != nil {\n   208→\t\t\tt.Errorf(\"invalid parquet file %s: %v\", name, err)\n   209→\t\t}\n   210→\t}\n   211→}\n   212→\n   213→func TestFileTarget(t *testing.T) {\n   214→\tdir := t.TempDir()\n   215→\tft, err := NewFileTarget(dir)\n   216→\tif err != nil {\n   217→\t\tt.Fatalf(\"NewFileTarget: %v\", err)\n   218→\t}\n   219→\n   220→\ttestData := []byte(\"test parquet data\")\n   221→\tif err := ft.WriteFile(\"test.parquet\", testData); err != nil {\n   222→\t\tt.Fatalf(\"WriteFile: %v\", err)\n   223→\t}\n   224→\n   225→\t// Verify file exists and has correct content\n   226→\t// (using the target itself is sufficient; we just check no error)\n   227→}\n   228→\n   229→func TestFileTargetSubdirectories(t *testing.T) {\n   230→\tdir := t.TempDir()\n   231→\tft, err := NewFileTarget(dir)\n   232→\tif err != nil {\n   233→\t\tt.Fatalf(\"NewFileTarget: %v\", err)\n   234→\t}\n   235→\n   236→\ttestData := []byte(\"test data in subdir\")\n   237→\tif err := ft.WriteFile(\"fritz/cc-archive-2025-01-20-001.parquet\", testData); err != nil {\n   238→\t\tt.Fatalf(\"WriteFile with subdir: %v\", err)\n   239→\t}\n   240→\n   241→\t// Verify file was created in subdirectory\n   242→\tcontent, err := os.ReadFile(filepath.Join(dir, \"fritz\", \"cc-archive-2025-01-20-001.parquet\"))\n   243→\tif err != nil {\n   244→\t\tt.Fatalf(\"read file in subdir: %v\", err)\n   245→\t}\n   246→\tif !bytes.Equal(content, testData) {\n   247→\t\tt.Error(\"file content mismatch\")\n   248→\t}\n   249→}\n   250→\n   251→func makeTestJobForCluster(jobID int64, cluster string) (*schema.Job, *schema.JobData) {\n   252→\tmeta, data := makeTestJob(jobID)\n   253→\tmeta.Cluster = cluster\n   254→\treturn meta, data\n   255→}\n   256→\n   257→func TestClusterAwareParquetWriter(t *testing.T) {\n   258→\ttarget := newMemTarget()\n   259→\tcw := NewClusterAwareParquetWriter(target, 512)\n   260→\n   261→\t// Set cluster configs\n   262→\tcw.SetClusterConfig(\"fritz\", &schema.Cluster{Name: \"fritz\"})\n   263→\tcw.SetClusterConfig(\"alex\", &schema.Cluster{Name: \"alex\"})\n   264→\n   265→\t// Add jobs from different clusters\n   266→\tfor i := range int64(3) {\n   267→\t\tmeta, data := makeTestJobForCluster(i, \"fritz\")\n   268→\t\trow, err := JobToParquetRow(meta, data)\n   269→\t\tif err != nil {\n   270→\t\t\tt.Fatalf(\"convert fritz job %d: %v\", i, err)\n   271→\t\t}\n   272→\t\tif err := cw.AddJob(*row); err != nil {\n   273→\t\t\tt.Fatalf(\"add fritz job %d: %v\", i, err)\n   274→\t\t}\n   275→\t}\n   276→\n   277→\tfor i := int64(10); i < 12; i++ {\n   278→\t\tmeta, data := makeTestJobForCluster(i, \"alex\")\n   279→\t\trow, err := JobToParquetRow(meta, data)\n   280→\t\tif err != nil {\n   281→\t\t\tt.Fatalf(\"convert alex job %d: %v\", i, err)\n   282→\t\t}\n   283→\t\tif err := cw.AddJob(*row); err != nil {\n   284→\t\t\tt.Fatalf(\"add alex job %d: %v\", i, err)\n   285→\t\t}\n   286→\t}\n   287→\n   288→\tif err := cw.Close(); err != nil {\n   289→\t\tt.Fatalf(\"close: %v\", err)\n   290→\t}\n   291→\n   292→\ttarget.mu.Lock()\n   293→\tdefer target.mu.Unlock()\n   294→\n   295→\t// Check cluster.json files were written\n   296→\tif _, ok := target.files[\"fritz/cluster.json\"]; !ok {\n   297→\t\tt.Error(\"missing fritz/cluster.json\")\n   298→\t}\n   299→\tif _, ok := target.files[\"alex/cluster.json\"]; !ok {\n   300→\t\tt.Error(\"missing alex/cluster.json\")\n   301→\t}\n   302→\n   303→\t// Verify cluster.json content\n   304→\tvar clusterCfg schema.Cluster\n   305→\tif err := json.Unmarshal(target.files[\"fritz/cluster.json\"], &clusterCfg); err != nil {\n   306→\t\tt.Fatalf(\"unmarshal fritz cluster.json: %v\", err)\n   307→\t}\n   308→\tif clusterCfg.Name != \"fritz\" {\n   309→\t\tt.Errorf(\"fritz cluster name = %q, want %q\", clusterCfg.Name, \"fritz\")\n   310→\t}\n   311→\n   312→\t// Check parquet files are in cluster subdirectories\n   313→\tfritzParquets := 0\n   314→\talexParquets := 0\n   315→\tfor name := range target.files {\n   316→\t\tif strings.HasPrefix(name, \"fritz/\") && strings.HasSuffix(name, \".parquet\") {\n   317→\t\t\tfritzParquets++\n   318→\t\t}\n   319→\t\tif strings.HasPrefix(name, \"alex/\") && strings.HasSuffix(name, \".parquet\") {\n   320→\t\t\talexParquets++\n   321→\t\t}\n   322→\t}\n   323→\tif fritzParquets == 0 {\n   324→\t\tt.Error(\"no parquet files in fritz/\")\n   325→\t}\n   326→\tif alexParquets == 0 {\n   327→\t\tt.Error(\"no parquet files in alex/\")\n   328→\t}\n   329→\n   330→\t// Verify parquet files are readable and have correct row counts\n   331→\tfor name, data := range target.files {\n   332→\t\tif !strings.HasSuffix(name, \".parquet\") {\n   333→\t\t\tcontinue\n   334→\t\t}\n   335→\t\tfile := bytes.NewReader(data)\n   336→\t\tpf, err := pq.OpenFile(file, int64(len(data)))\n   337→\t\tif err != nil {\n   338→\t\t\tt.Errorf(\"open parquet %s: %v\", name, err)\n   339→\t\t\tcontinue\n   340→\t\t}\n   341→\t\tif strings.HasPrefix(name, \"fritz/\") && pf.NumRows() != 3 {\n   342→\t\t\tt.Errorf(\"fritz parquet rows = %d, want 3\", pf.NumRows())\n   343→\t\t}\n   344→\t\tif strings.HasPrefix(name, \"alex/\") && pf.NumRows() != 2 {\n   345→\t\t\tt.Errorf(\"alex parquet rows = %d, want 2\", pf.NumRows())\n   346→\t\t}\n   347→\t}\n   348→}\n   349→\n   350→func TestClusterAwareParquetWriterEmpty(t *testing.T) {\n   351→\ttarget := newMemTarget()\n   352→\tcw := NewClusterAwareParquetWriter(target, 512)\n   353→\n   354→\tif err := cw.Close(); err != nil {\n   355→\t\tt.Fatalf(\"close empty writer: %v\", err)\n   356→\t}\n   357→\n   358→\tif len(target.files) != 0 {\n   359→\t\tt.Errorf(\"expected no files for empty writer, got %d\", len(target.files))\n   360→\t}\n   361→}\n   362→"}]},"uuid":"865a5a9f-707f-48e4-bb93-014ea57a5d56","timestamp":"2026-03-18T04:02:45.392Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"69813891-a882-4c15-a8fa-e014769cea16","timestamp":"2026-03-18T04:02:45.750Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"d375b321-0773-492e-9b97-ebedbb6df8ed","isSidechain":false,"type":"progress","data":{"message":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0151RaganG7v9p6HapDxL61S","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\"encoding/json\"\n    10→\t\"os\"\n    11→\t\"path/filepath\"\n    12→\t\"testing\"\n    13→\n    14→\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n    15→\tpq \"github.com/parquet-go/parquet-go\"\n    16→)\n    17→\n    18→func TestParseScopeFromName(t *testing.T) {\n    19→\ttests := []struct {\n    20→\t\tname      string\n    21→\t\twantScope string\n    22→\t\twantID    string\n    23→\t}{\n    24→\t\t{\"socket0\", \"socket\", \"0\"},\n    25→\t\t{\"socket12\", \"socket\", \"12\"},\n    26→\t\t{\"core0\", \"core\", \"0\"},\n    27→\t\t{\"core127\", \"core\", \"127\"},\n    28→\t\t{\"cpu0\", \"hwthread\", \"0\"},\n    29→\t\t{\"hwthread5\", \"hwthread\", \"5\"},\n    30→\t\t{\"memoryDomain0\", \"memoryDomain\", \"0\"},\n    31→\t\t{\"accelerator0\", \"accelerator\", \"0\"},\n    32→\t\t{\"unknown\", \"unknown\", \"\"},\n    33→\t\t{\"socketX\", \"socketX\", \"\"}, // not numeric suffix\n    34→\t}\n    35→\n    36→\tfor _, tt := range tests {\n    37→\t\tt.Run(tt.name, func(t *testing.T) {\n    38→\t\t\tscope, id := parseScopeFromName(tt.name)\n    39→\t\t\tif scope != tt.wantScope || id != tt.wantID {\n    40→\t\t\t\tt.Errorf(\"parseScopeFromName(%q) = (%q, %q), want (%q, %q)\",\n    41→\t\t\t\t\ttt.name, scope, id, tt.wantScope, tt.wantID)\n    42→\t\t\t}\n    43→\t\t})\n    44→\t}\n    45→}\n    46→\n    47→func TestFlattenCheckpointFile(t *testing.T) {\n    48→\tcf := &CheckpointFile{\n    49→\t\tFrom: 1000,\n    50→\t\tTo:   1060,\n    51→\t\tMetrics: map[string]*CheckpointMetrics{\n    52→\t\t\t\"cpu_load\": {\n    53→\t\t\t\tFrequency: 60,\n    54→\t\t\t\tStart:     1000,\n    55→\t\t\t\tData:      []schema.Float{0.5, 0.7, schema.NaN},\n    56→\t\t\t},\n    57→\t\t},\n    58→\t\tChildren: map[string]*CheckpointFile{\n    59→\t\t\t\"socket0\": {\n    60→\t\t\t\tMetrics: map[string]*CheckpointMetrics{\n    61→\t\t\t\t\t\"mem_bw\": {\n    62→\t\t\t\t\t\tFrequency: 60,\n    63→\t\t\t\t\t\tStart:     1000,\n    64→\t\t\t\t\t\tData:      []schema.Float{100.0, schema.NaN, 200.0},\n    65→\t\t\t\t\t},\n    66→\t\t\t\t},\n    67→\t\t\t\tChildren: make(map[string]*CheckpointFile),\n    68→\t\t\t},\n    69→\t\t},\n    70→\t}\n    71→\n    72→\trows := flattenCheckpointFile(cf, \"fritz\", \"node001\", \"node\", \"\", nil)\n    73→\n    74→\t// cpu_load: 2 non-NaN values at node scope\n    75→\t// mem_bw: 2 non-NaN values at socket0 scope\n    76→\tif len(rows) != 4 {\n    77→\t\tt.Fatalf(\"expected 4 rows, got %d\", len(rows))\n    78→\t}\n    79→\n    80→\t// Verify a node-scope row\n    81→\tfound := false\n    82→\tfor _, r := range rows {\n    83→\t\tif r.Metric == \"cpu_load\" && r.Timestamp == 1000 {\n    84→\t\t\tfound = true\n    85→\t\t\tif r.Cluster != \"fritz\" || r.Hostname != \"node001\" || r.Scope != \"node\" || r.Value != 0.5 {\n    86→\t\t\t\tt.Errorf(\"unexpected row: %+v\", r)\n    87→\t\t\t}\n    88→\t\t}\n    89→\t}\n    90→\tif !found {\n    91→\t\tt.Error(\"expected cpu_load row at timestamp 1000\")\n    92→\t}\n    93→\n    94→\t// Verify a socket-scope row\n    95→\tfound = false\n    96→\tfor _, r := range rows {\n    97→\t\tif r.Metric == \"mem_bw\" && r.Scope == \"socket\" && r.ScopeID == \"0\" {\n    98→\t\t\tfound = true\n    99→\t\t}\n   100→\t}"}]},"uuid":"006ccb9d-700f-450a-bf59-9cad994307be","timestamp":"2026-03-18T04:02:45.793Z"},"type":"agent_progress","prompt":"","agentId":"a54ce42db3d7e6a75"},"toolUseID":"agent_msg_017PFZLZcJVrCweDKN2Pv1ax","parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","uuid":"e381436a-7b60-4aae-9090-e89ce5d7ccc4","timestamp":"2026-03-18T04:02:45.794Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"e381436a-7b60-4aae-9090-e89ce5d7ccc4","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Agent","command":"entire hooks claude-code post-task"},"parentToolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","toolUseID":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","timestamp":"2026-03-18T04:03:01.631Z","uuid":"d5eaffb2-6268-4c4c-9d3a-8c6fb5d797bc","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"dd911687-ef19-4727-bc02-483d0b5ffab8","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0115GTb7Gkjjtf2iDpNmgN9u","type":"tool_result","content":[{"type":"text","text":"Perfect! I now have a comprehensive understanding of all parquet writing code in the codebase. Let me compile my findings:\n\n## Comprehensive Report: All Parquet Writing Usage in CC-Backend\n\nBased on my thorough search, I found **3 major parquet writing code paths** with specific accumulation patterns:\n\n### 1. **Job Retention/Archiving via ParquetWriter** \n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 20-106)\n\n**Row Accumulation Pattern**:\n- `ParquetWriter` struct (line 22) accumulates `[]ParquetJobRow` in field `rows` (line 25)\n- `AddJob()` method (line 43) appends rows to the slice\n- When `currentSize + rowSize > maxSizeBytes` (line 46), `Flush()` is called\n- `Flush()` (line 58) calls `writeParquetBytes(pw.rows)` (line 66) which creates a `pq.NewGenericWriter[ParquetJobRow]` (line 89)\n\n**GenericWriter Usage** (line 89):\n```go\nwriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"sub_cluster\"),\n        pq.Ascending(\"project\"),\n        pq.Ascending(\"start_time\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` (lines 108-149)\n- `transferJobsParquet()` creates `pqarchive.NewClusterAwareParquetWriter()` (line 109)\n- Iterates jobs, converts to ParquetJobRow via `pqarchive.JobToParquetRow()` (line 137), calls `cw.AddJob()` (line 142)\n\n---\n\n### 2. **Cluster-Aware Job Retention via ClusterAwareParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 133-186)\n\n**Row Accumulation Pattern**:\n- `ClusterAwareParquetWriter` (line 135) maintains `writers map[string]*ParquetWriter` (line 138)\n- Each cluster gets its own `ParquetWriter` instance\n- `AddJob()` (line 158) routes to the appropriate cluster's writer\n- Same row accumulation and batching as ParquetWriter above\n\n**Called from**: \n- `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` lines 109, 260, 311\n  - `RegisterRetentionCopyService()` (line 232)\n  - `RegisterRetentionMoveService()` (line 285)\n\n---\n\n### 3. **Node State Retention via NodeStateParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go` (lines 17-111)\n\n**Row Accumulation Pattern**:\n- `NodeStateParquetWriter` struct (line 19) accumulates `[]ParquetNodeStateRow` in field `rows` (line 22)\n- `AddRow()` method (line 39) appends rows with size tracking\n- When `currentSize + rowSize > maxSizeBytes` (line 42), `Flush()` is called\n- `Flush()` (line 54) calls `writeNodeStateParquetBytes(pw.rows)` (line 62)\n\n**GenericWriter Usage** (line 85):\n```go\nwriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"cluster\"),\n        pq.Ascending(\"subcluster\"),\n        pq.Ascending(\"hostname\"),\n        pq.Ascending(\"time_stamp\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go` (lines 35-120)\n- `RegisterNodeStateRetentionMoveService()` (line 35)\n- Creates `pqarchive.NewNodeStateParquetWriter()` (line 86)\n- Finds old nodestate rows via `nodeRepo.FindNodeStatesBefore()` (line 76)\n- Iterates rows, creates `ParquetNodeStateRow` structs, calls `pw.AddRow()` (line 102)\n\n---\n\n### 4. **Metric Archive via parquetArchiveWriter (Checkpoint Streaming)**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go` (lines 95-160)\n\n**Row Accumulation Pattern**:\n- `parquetArchiveWriter` struct (line 98) uses `*pq.GenericWriter[ParquetMetricRow]` directly (line 99)\n- Does **NOT** accumulate rows in memory; instead writes incrementally via `WriteHostRows()` (line 127)\n- Each host's data is sorted by (metric, timestamp) then written as a separate row group\n\n**GenericWriter Creation** (line 118):\n```go\nwriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n    pq.Compression(&pq.Zstd),\n)\n```\n\n**Data Source**: \n- `archiveCheckpointsToParquet()` (line 236) pre-allocates row slice and flattens checkpoint files\n- `flattenCheckpointFile()` (line 38) recursively converts CheckpointFile tree to `[]ParquetMetricRow`\n- Pre-allocation estimate via `estimateRowCount()` (line 223)\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go` (lines 86-300)\n- `archiveCheckpoints()` (line 173) \n- Workers pool pattern processes per-host checkpoint directories\n- Each host's rows written via `writer.WriteHostRows()` (line 260) at line 260\n- Creates streaming archive from metrics checkpoints to Parquet files in format: `<cleanupDir>/<cluster>/<timestamp>.parquet`\n\n---\n\n### Summary of Row Accumulation Patterns:\n\n| Location | Row Type | Struct Field | Batching | Trigger |\n|----------|----------|--------------|----------|---------|\n| `pkg/archive/parquet/writer.go` | `ParquetJobRow` | `rows []ParquetJobRow` | Yes | Size > maxSizeBytes |\n| `pkg/archive/parquet/nodestate_writer.go` | `ParquetNodeStateRow` | `rows []ParquetNodeStateRow` | Yes | Size > maxSizeBytes |\n| `pkg/metricstore/parquetArchive.go` | `ParquetMetricRow` | Pre-allocated slice | No | Per-host row group |\n\n### Key Implementation Details:\n\n1. **Job/NodeState Writers** use batching to avoid OOM on large datasets\n2. **Metric Archive Writer** uses streaming row groups instead of full accumulation\n3. All use `pq.NewGenericWriter` with `pq.Compression(&pq.Zstd)` for compression\n4. Job and NodeState writers use `pq.SortingWriterConfig` for column ordering\n5. Row estimation via struct field size calculation before writing\n6. All integrate with parquet-go library's generic writer API"},{"type":"text","text":"agentId: a54ce42db3d7e6a75 (for resuming to continue this agent's work if needed)\n<usage>total_tokens: 51623\ntool_uses: 17\nduration_ms: 29238</usage>"}]}]},"uuid":"dea76866-f55f-45b0-87d1-b546550a70bd","timestamp":"2026-03-18T04:03:01.630Z","toolUseResult":{"status":"completed","prompt":"Search the codebase for ALL uses of parquet writing - any place that writes parquet files, accumulates rows into slices for parquet, or uses parquet-go's GenericWriter. Look specifically for:\n\n1. Any usage of `pq.NewGenericWriter`, `pq.GenericWriter`, `SortingWriterConfig`, or `writeParquetArchive`\n2. Any function that accumulates `[]ParquetMetricRow` or similar row slices\n3. Nodestate retention or archiving code that might write parquet\n4. Any other archiving/retention code paths\n\nSearch thoroughly - check pkg/, internal/, and any other directories. Report the exact file paths, line numbers, and the accumulation patterns you find.","agentId":"a54ce42db3d7e6a75","content":[{"type":"text","text":"Perfect! I now have a comprehensive understanding of all parquet writing code in the codebase. Let me compile my findings:\n\n## Comprehensive Report: All Parquet Writing Usage in CC-Backend\n\nBased on my thorough search, I found **3 major parquet writing code paths** with specific accumulation patterns:\n\n### 1. **Job Retention/Archiving via ParquetWriter** \n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 20-106)\n\n**Row Accumulation Pattern**:\n- `ParquetWriter` struct (line 22) accumulates `[]ParquetJobRow` in field `rows` (line 25)\n- `AddJob()` method (line 43) appends rows to the slice\n- When `currentSize + rowSize > maxSizeBytes` (line 46), `Flush()` is called\n- `Flush()` (line 58) calls `writeParquetBytes(pw.rows)` (line 66) which creates a `pq.NewGenericWriter[ParquetJobRow]` (line 89)\n\n**GenericWriter Usage** (line 89):\n```go\nwriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"sub_cluster\"),\n        pq.Ascending(\"project\"),\n        pq.Ascending(\"start_time\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` (lines 108-149)\n- `transferJobsParquet()` creates `pqarchive.NewClusterAwareParquetWriter()` (line 109)\n- Iterates jobs, converts to ParquetJobRow via `pqarchive.JobToParquetRow()` (line 137), calls `cw.AddJob()` (line 142)\n\n---\n\n### 2. **Cluster-Aware Job Retention via ClusterAwareParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go` (lines 133-186)\n\n**Row Accumulation Pattern**:\n- `ClusterAwareParquetWriter` (line 135) maintains `writers map[string]*ParquetWriter` (line 138)\n- Each cluster gets its own `ParquetWriter` instance\n- `AddJob()` (line 158) routes to the appropriate cluster's writer\n- Same row accumulation and batching as ParquetWriter above\n\n**Called from**: \n- `/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go` lines 109, 260, 311\n  - `RegisterRetentionCopyService()` (line 232)\n  - `RegisterRetentionMoveService()` (line 285)\n\n---\n\n### 3. **Node State Retention via NodeStateParquetWriter**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go` (lines 17-111)\n\n**Row Accumulation Pattern**:\n- `NodeStateParquetWriter` struct (line 19) accumulates `[]ParquetNodeStateRow` in field `rows` (line 22)\n- `AddRow()` method (line 39) appends rows with size tracking\n- When `currentSize + rowSize > maxSizeBytes` (line 42), `Flush()` is called\n- `Flush()` (line 54) calls `writeNodeStateParquetBytes(pw.rows)` (line 62)\n\n**GenericWriter Usage** (line 85):\n```go\nwriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n    pq.Compression(&pq.Zstd),\n    pq.SortingWriterConfig(pq.SortingColumns(\n        pq.Ascending(\"cluster\"),\n        pq.Ascending(\"subcluster\"),\n        pq.Ascending(\"hostname\"),\n        pq.Ascending(\"time_stamp\"),\n    )),\n)\n```\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go` (lines 35-120)\n- `RegisterNodeStateRetentionMoveService()` (line 35)\n- Creates `pqarchive.NewNodeStateParquetWriter()` (line 86)\n- Finds old nodestate rows via `nodeRepo.FindNodeStatesBefore()` (line 76)\n- Iterates rows, creates `ParquetNodeStateRow` structs, calls `pw.AddRow()` (line 102)\n\n---\n\n### 4. **Metric Archive via parquetArchiveWriter (Checkpoint Streaming)**\n**File**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/parquetArchive.go` (lines 95-160)\n\n**Row Accumulation Pattern**:\n- `parquetArchiveWriter` struct (line 98) uses `*pq.GenericWriter[ParquetMetricRow]` directly (line 99)\n- Does **NOT** accumulate rows in memory; instead writes incrementally via `WriteHostRows()` (line 127)\n- Each host's data is sorted by (metric, timestamp) then written as a separate row group\n\n**GenericWriter Creation** (line 118):\n```go\nwriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n    pq.Compression(&pq.Zstd),\n)\n```\n\n**Data Source**: \n- `archiveCheckpointsToParquet()` (line 236) pre-allocates row slice and flattens checkpoint files\n- `flattenCheckpointFile()` (line 38) recursively converts CheckpointFile tree to `[]ParquetMetricRow`\n- Pre-allocation estimate via `estimateRowCount()` (line 223)\n\n**Called from**: `/Users/jan/prg/CC/cc-backend/pkg/metricstore/archive.go` (lines 86-300)\n- `archiveCheckpoints()` (line 173) \n- Workers pool pattern processes per-host checkpoint directories\n- Each host's rows written via `writer.WriteHostRows()` (line 260) at line 260\n- Creates streaming archive from metrics checkpoints to Parquet files in format: `<cleanupDir>/<cluster>/<timestamp>.parquet`\n\n---\n\n### Summary of Row Accumulation Patterns:\n\n| Location | Row Type | Struct Field | Batching | Trigger |\n|----------|----------|--------------|----------|---------|\n| `pkg/archive/parquet/writer.go` | `ParquetJobRow` | `rows []ParquetJobRow` | Yes | Size > maxSizeBytes |\n| `pkg/archive/parquet/nodestate_writer.go` | `ParquetNodeStateRow` | `rows []ParquetNodeStateRow` | Yes | Size > maxSizeBytes |\n| `pkg/metricstore/parquetArchive.go` | `ParquetMetricRow` | Pre-allocated slice | No | Per-host row group |\n\n### Key Implementation Details:\n\n1. **Job/NodeState Writers** use batching to avoid OOM on large datasets\n2. **Metric Archive Writer** uses streaming row groups instead of full accumulation\n3. All use `pq.NewGenericWriter` with `pq.Compression(&pq.Zstd)` for compression\n4. Job and NodeState writers use `pq.SortingWriterConfig` for column ordering\n5. Row estimation via struct field size calculation before writing\n6. All integrate with parquet-go library's generic writer API"}],"totalDurationMs":29238,"totalTokens":51623,"totalToolUseCount":17,"usage":{"input_tokens":6,"cache_creation_input_tokens":6652,"cache_read_input_tokens":43056,"output_tokens":1909,"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":6652},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"dd911687-ef19-4727-bc02-483d0b5ffab8","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"6ef33ff4-6796-4ef0-b60a-8faf052d22c6","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011Fh6gGsv7PiP7UZ5Fzn1HF","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\"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":"8ba2bd53-1ba2-49e6-a0fb-f32b047d809b","timestamp":"2026-03-18T04:03:08.711Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.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 parquet\n\nimport (\n\t\"bytes\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"path\"\n\t\"time\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\t\"github.com/ClusterCockpit/cc-lib/v2/schema\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\n// ParquetWriter batches ParquetJobRows and flushes them to a target\n// when the estimated size exceeds maxSizeBytes.\ntype ParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeBytes int64\n\trows         []ParquetJobRow\n\tcurrentSize  int64\n\tfileCounter  int\n\tdatePrefix   string\n}\n\n// NewParquetWriter creates a new writer that flushes batches to the given target.\n// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\nfunc NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n\treturn &ParquetWriter{\n\t\ttarget:       target,\n\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n\t}\n}\n\n// AddJob adds a row to the current batch. If the estimated batch size\n// exceeds the configured maximum, the batch is flushed to the target first.\nfunc (pw *ParquetWriter) AddJob(row ParquetJobRow) error {\n\trowSize := estimateRowSize(&row)\n\n\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n\t\tif err := pw.Flush(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tpw.rows = append(pw.rows, row)\n\tpw.currentSize += rowSize\n\treturn nil\n}\n\n// Flush writes the current batch to a parquet file on the target.\nfunc (pw *ParquetWriter) Flush() error {\n\tif len(pw.rows) == 0 {\n\t\treturn nil\n\t}\n\n\tpw.fileCounter++\n\tfileName := fmt.Sprintf(\"cc-archive-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n\n\tdata, err := writeParquetBytes(pw.rows)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n\t}\n\n\tif err := pw.target.WriteFile(fileName, data); err != nil {\n\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n\t}\n\n\tcclog.Infof(\"Parquet retention: wrote %s (%d jobs, %d bytes)\", fileName, len(pw.rows), len(data))\n\tpw.rows = pw.rows[:0]\n\tpw.currentSize = 0\n\treturn nil\n}\n\n// Close flushes any remaining rows and finalizes the writer.\nfunc (pw *ParquetWriter) Close() error {\n\treturn pw.Flush()\n}\n\nfunc writeParquetBytes(rows []ParquetJobRow) ([]byte, error) {\n\tvar buf bytes.Buffer\n\n\twriter := pq.NewGenericWriter[ParquetJobRow](&buf,\n\t\tpq.Compression(&pq.Zstd),\n\t\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"sub_cluster\"),\n\t\t\tpq.Ascending(\"project\"),\n\t\t\tpq.Ascending(\"start_time\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn nil, err\n\t}\n\tif err := writer.Close(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn buf.Bytes(), nil\n}\n\nfunc estimateRowSize(row *ParquetJobRow) int64 {\n\t// Fixed fields: ~100 bytes for numeric fields + strings estimate\n\tsize := int64(200)\n\tsize += int64(len(row.Cluster) + len(row.SubCluster) + len(row.Partition) +\n\t\tlen(row.Project) + len(row.User) + len(row.State))\n\tsize += int64(len(row.ResourcesJSON))\n\tsize += int64(len(row.StatisticsJSON))\n\tsize += int64(len(row.TagsJSON))\n\tsize += int64(len(row.MetaDataJSON))\n\tsize += int64(len(row.FootprintJSON))\n\tsize += int64(len(row.EnergyFootJSON))\n\tsize += int64(len(row.MetricDataGz))\n\treturn size\n}\n\n// prefixedTarget wraps a ParquetTarget and prepends a path prefix to all file names.\ntype prefixedTarget struct {\n\tinner  ParquetTarget\n\tprefix string\n}\n\nfunc (pt *prefixedTarget) WriteFile(name string, data []byte) error {\n\treturn pt.inner.WriteFile(path.Join(pt.prefix, name), data)\n}\n\n// ClusterAwareParquetWriter organizes Parquet output by cluster.\n// Each cluster gets its own subdirectory with a cluster.json config file.\ntype ClusterAwareParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeMB    int\n\twriters      map[string]*ParquetWriter\n\tclusterCfgs  map[string]*schema.Cluster\n}\n\n// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\nfunc NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n\treturn &ClusterAwareParquetWriter{\n\t\ttarget:      target,\n\t\tmaxSizeMB:   maxSizeMB,\n\t\twriters:     make(map[string]*ParquetWriter),\n\t\tclusterCfgs: make(map[string]*schema.Cluster),\n\t}\n}\n\n// SetClusterConfig stores a cluster configuration to be written as cluster.json on Close.\nfunc (cw *ClusterAwareParquetWriter) SetClusterConfig(name string, cfg *schema.Cluster) {\n\tcw.clusterCfgs[name] = cfg\n}\n\n// AddJob routes the job row to the appropriate per-cluster writer.\nfunc (cw *ClusterAwareParquetWriter) AddJob(row ParquetJobRow) error {\n\tcluster := row.Cluster\n\tpw, ok := cw.writers[cluster]\n\tif !ok {\n\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n\t\tcw.writers[cluster] = pw\n\t}\n\treturn pw.AddJob(row)\n}\n\n// Close writes cluster.json files and flushes all per-cluster writers.\nfunc (cw *ClusterAwareParquetWriter) Close() error {\n\tfor name, cfg := range cw.clusterCfgs {\n\t\tdata, err := json.MarshalIndent(cfg, \"\", \"  \")\n\t\tif err != nil {\n\t\t\treturn fmt.Errorf(\"marshal cluster config %q: %w\", name, err)\n\t\t}\n\t\tif err := cw.target.WriteFile(path.Join(name, \"cluster.json\"), data); err != nil {\n\t\t\treturn fmt.Errorf(\"write cluster.json for %q: %w\", name, err)\n\t\t}\n\t}\n\n\tfor cluster, pw := range cw.writers {\n\t\tif err := pw.Close(); err != nil {\n\t\t\treturn fmt.Errorf(\"close writer for cluster %q: %w\", cluster, err)\n\t\t}\n\t}\n\treturn nil\n}\n","numLines":187,"startLine":1,"totalLines":187}},"sourceToolAssistantUUID":"6ef33ff4-6796-4ef0-b60a-8faf052d22c6","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"8ba2bd53-1ba2-49e6-a0fb-f32b047d809b","isSidechain":false,"type":"progress","data":{"type":"hook_progress","hookEvent":"PostToolUse","hookName":"PostToolUse:Read","command":"callback"},"parentToolUseID":"toolu_01Q99KAA21mZfprWFnPEyThq","toolUseID":"toolu_01Q99KAA21mZfprWFnPEyThq","timestamp":"2026-03-18T04:03:08.713Z","uuid":"8a41feef-932a-4fc3-b346-f93343dea5ec","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"7654bc76-22fd-40c9-80f1-2ca9c5f25c80","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Q99KAA21mZfprWFnPEyThq","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":"8659aa34-8044-491f-8e19-4b28746ae9dc","timestamp":"2026-03-18T04:03:08.713Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.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 parquet\n\nimport (\n\t\"bytes\"\n\t\"fmt\"\n\t\"time\"\n\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n\tpq \"github.com/parquet-go/parquet-go\"\n)\n\n// NodeStateParquetWriter batches ParquetNodeStateRows and flushes them to a target\n// when the estimated size exceeds maxSizeBytes.\ntype NodeStateParquetWriter struct {\n\ttarget       ParquetTarget\n\tmaxSizeBytes int64\n\trows         []ParquetNodeStateRow\n\tcurrentSize  int64\n\tfileCounter  int\n\tdatePrefix   string\n}\n\n// NewNodeStateParquetWriter creates a new writer for node state parquet files.\nfunc NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n\treturn &NodeStateParquetWriter{\n\t\ttarget:       target,\n\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\n\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n\t}\n}\n\n// AddRow adds a row to the current batch. If the estimated batch size\n// exceeds the configured maximum, the batch is flushed first.\nfunc (pw *NodeStateParquetWriter) AddRow(row ParquetNodeStateRow) error {\n\trowSize := estimateNodeStateRowSize(&row)\n\n\tif pw.currentSize+rowSize > pw.maxSizeBytes && len(pw.rows) > 0 {\n\t\tif err := pw.Flush(); err != nil {\n\t\t\treturn err\n\t\t}\n\t}\n\n\tpw.rows = append(pw.rows, row)\n\tpw.currentSize += rowSize\n\treturn nil\n}\n\n// Flush writes the current batch to a parquet file on the target.\nfunc (pw *NodeStateParquetWriter) Flush() error {\n\tif len(pw.rows) == 0 {\n\t\treturn nil\n\t}\n\n\tpw.fileCounter++\n\tfileName := fmt.Sprintf(\"cc-nodestate-%s-%03d.parquet\", pw.datePrefix, pw.fileCounter)\n\n\tdata, err := writeNodeStateParquetBytes(pw.rows)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"write parquet buffer: %w\", err)\n\t}\n\n\tif err := pw.target.WriteFile(fileName, data); err != nil {\n\t\treturn fmt.Errorf(\"write parquet file %q: %w\", fileName, err)\n\t}\n\n\tcclog.Infof(\"NodeState retention: wrote %s (%d rows, %d bytes)\", fileName, len(pw.rows), len(data))\n\tpw.rows = pw.rows[:0]\n\tpw.currentSize = 0\n\treturn nil\n}\n\n// Close flushes any remaining rows and finalizes the writer.\nfunc (pw *NodeStateParquetWriter) Close() error {\n\treturn pw.Flush()\n}\n\nfunc writeNodeStateParquetBytes(rows []ParquetNodeStateRow) ([]byte, error) {\n\tvar buf bytes.Buffer\n\n\twriter := pq.NewGenericWriter[ParquetNodeStateRow](&buf,\n\t\tpq.Compression(&pq.Zstd),\n\t\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"subcluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"time_stamp\"),\n\t\t)),\n\t)\n\n\tif _, err := writer.Write(rows); err != nil {\n\t\treturn nil, err\n\t}\n\tif err := writer.Close(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn buf.Bytes(), nil\n}\n\nfunc estimateNodeStateRowSize(row *ParquetNodeStateRow) int64 {\n\tsize := int64(100) // fixed numeric fields\n\tsize += int64(len(row.NodeState) + len(row.HealthState) + len(row.HealthMetrics))\n\tsize += int64(len(row.Hostname) + len(row.Cluster) + len(row.SubCluster))\n\treturn size\n}\n","numLines":111,"startLine":1,"totalLines":111}},"sourceToolAssistantUUID":"7654bc76-22fd-40c9-80f1-2ca9c5f25c80","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"faff2a5f-39cf-41be-86c5-6881ede8648f","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_019UTA1PjoxLMwNcZgvy9yF8","type":"message","role":"assistant","content":[{"type":"text","text":"Let me check the default `maxSizeMB` values and the row schemas to assess the severity."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4503,"cache_read_input_tokens":42858,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4503},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ9t59U86JZXpoB3ce9Bp","type":"assistant","uuid":"c09f2346-0454-4886-992d-9909d6ad37cb","timestamp":"2026-03-18T04:03:22.128Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"d3ad8e22-3b2e-4bec-8879-dc19d4acfa97","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XqChKEwwhYbMpP5zPDcwMG","type":"tool_result","content":"/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-424-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-425-// convertJSONToParquet converts a JSON archive backend to parquet format.\ntools/archive-manager/main.go:426:func convertJSONToParquet(srcBackend archive.ArchiveBackend, dstCfg sourceConfig, maxSizeMB int) error {\ntools/archive-manager/main.go-427-\ttarget, err := createParquetTarget(dstCfg)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-428-\tif err != nil {\n--\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-430-\t}\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-431-\ntools/archive-manager/main.go:432:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-433-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-434-\t// Transfer cluster configs\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-30-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-31-// NewParquetWriter creates a new writer that flushes batches to the given target.\npkg/archive/parquet/writer.go:32:// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\npkg/archive/parquet/writer.go:33:func NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-34-\treturn &ParquetWriter{\npkg/archive/parquet/writer.go-35-\t\ttarget:       target,\npkg/archive/parquet/writer.go:36:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/writer.go-37-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-38-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-135-type ClusterAwareParquetWriter struct {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-136-\ttarget       ParquetTarget\npkg/archive/parquet/writer.go:137:\tmaxSizeMB    int\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-138-\twriters      map[string]*ParquetWriter\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-139-\tclusterCfgs  map[string]*schema.Cluster\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-141-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-142-// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\npkg/archive/parquet/writer.go:143:func NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-144-\treturn &ClusterAwareParquetWriter{\npkg/archive/parquet/writer.go-145-\t\ttarget:      target,\npkg/archive/parquet/writer.go:146:\t\tmaxSizeMB:   maxSizeMB,\npkg/archive/parquet/writer.go-147-\t\twriters:     make(map[string]*ParquetWriter),\npkg/archive/parquet/writer.go-148-\t\tclusterCfgs: make(map[string]*schema.Cluster),\n--\npkg/archive/parquet/writer.go-160-\tpw, ok := cw.writers[cluster]\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-161-\tif !ok {\npkg/archive/parquet/writer.go:162:\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-163-\t\tcw.writers[cluster] = pw\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-164-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-27-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-28-// NewNodeStateParquetWriter creates a new writer for node state parquet files.\npkg/archive/parquet/nodestate_writer.go:29:func NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-30-\treturn &NodeStateParquetWriter{\npkg/archive/parquet/nodestate_writer.go-31-\t\ttarget:       target,\npkg/archive/parquet/nodestate_writer.go:32:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/nodestate_writer.go-33-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-34-\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-106-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-107-// transferJobsParquet converts jobs to Parquet format, organized by cluster.\ninternal/taskmanager/retentionService.go:108:func transferJobsParquet(jobs []*schema.Job, src archive.ArchiveBackend, target pqarchive.ParquetTarget, maxSizeMB int) error {\ninternal/taskmanager/retentionService.go:109:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-110-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-111-\t// Set cluster configs for all clusters referenced by jobs"}]},"uuid":"28d33adb-22ad-4be4-bbaf-c470ef67fa84","timestamp":"2026-03-18T04:03:23.582Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-424-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-425-// convertJSONToParquet converts a JSON archive backend to parquet format.\ntools/archive-manager/main.go:426:func convertJSONToParquet(srcBackend archive.ArchiveBackend, dstCfg sourceConfig, maxSizeMB int) error {\ntools/archive-manager/main.go-427-\ttarget, err := createParquetTarget(dstCfg)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-428-\tif err != nil {\n--\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-430-\t}\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-431-\ntools/archive-manager/main.go:432:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-433-\n/Users/jan/prg/CC/cc-backend/tools/archive-manager/main.go-434-\t// Transfer cluster configs\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-30-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-31-// NewParquetWriter creates a new writer that flushes batches to the given target.\npkg/archive/parquet/writer.go:32:// maxSizeMB sets the approximate maximum size per parquet file in megabytes.\npkg/archive/parquet/writer.go:33:func NewParquetWriter(target ParquetTarget, maxSizeMB int) *ParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-34-\treturn &ParquetWriter{\npkg/archive/parquet/writer.go-35-\t\ttarget:       target,\npkg/archive/parquet/writer.go:36:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/writer.go-37-\t\tdatePrefix:   time.Now().Format(\"2006-01-02\"),\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-38-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-135-type ClusterAwareParquetWriter struct {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-136-\ttarget       ParquetTarget\npkg/archive/parquet/writer.go:137:\tmaxSizeMB    int\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-138-\twriters      map[string]*ParquetWriter\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-139-\tclusterCfgs  map[string]*schema.Cluster\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-141-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-142-// NewClusterAwareParquetWriter creates a writer that routes jobs to per-cluster ParquetWriters.\npkg/archive/parquet/writer.go:143:func NewClusterAwareParquetWriter(target ParquetTarget, maxSizeMB int) *ClusterAwareParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-144-\treturn &ClusterAwareParquetWriter{\npkg/archive/parquet/writer.go-145-\t\ttarget:      target,\npkg/archive/parquet/writer.go:146:\t\tmaxSizeMB:   maxSizeMB,\npkg/archive/parquet/writer.go-147-\t\twriters:     make(map[string]*ParquetWriter),\npkg/archive/parquet/writer.go-148-\t\tclusterCfgs: make(map[string]*schema.Cluster),\n--\npkg/archive/parquet/writer.go-160-\tpw, ok := cw.writers[cluster]\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-161-\tif !ok {\npkg/archive/parquet/writer.go:162:\t\tpw = NewParquetWriter(&prefixedTarget{inner: cw.target, prefix: cluster}, cw.maxSizeMB)\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-163-\t\tcw.writers[cluster] = pw\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/writer.go-164-\t}\n--\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-27-\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-28-// NewNodeStateParquetWriter creates a new writer for node state parquet files.\npkg/archive/parquet/nodestate_writer.go:29:func NewNodeStateParquetWriter(target ParquetTarget, maxSizeMB int) *NodeStateParquetWriter {\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_writer.go-30-\treturn &NodeStateParquetWriter{\npkg/archive/parquet/nodestate_writer.go-31-\t\ttarget:       target,\npkg/archive/parquet/nodestate_writer.go:32:\t\tmaxSizeBytes: int64(maxSizeMB) * 1024 * 1024,\npkg/archive/parquet/nodestate_writer.go-33-\t\tdatePrefix:   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`parquet:\"tags_json,optional\"`\npkg/archive/parquet/schema.go-28-\tMetaDataJSON   []byte  `parquet:\"meta_data_json,optional\"`\npkg/archive/parquet/schema.go-29-\tFootprintJSON  []byte  `parquet:\"footprint_json,optional\"`\npkg/archive/parquet/schema.go-30-\tEnergyFootJSON []byte  `parquet:\"energy_footprint_json,optional\"`\npkg/archive/parquet/schema.go-31-\tMetricDataGz   []byte  `parquet:\"metric_data_gz\"`\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/schema.go-32-}\n--\npkg/archive/parquet/nodestate_schema.go:8:type ParquetNodeStateRow struct {\npkg/archive/parquet/nodestate_schema.go-9-\tTimeStamp       int64  `parquet:\"time_stamp\"`\npkg/archive/parquet/nodestate_schema.go-10-\tNodeState       string `parquet:\"node_state\"`\npkg/archive/parquet/nodestate_schema.go-11-\tHealthState     string `parquet:\"health_state\"`\npkg/archive/parquet/nodestate_schema.go-12-\tHealthMetrics   string `parquet:\"health_metrics,optional\"`\npkg/archive/parquet/nodestate_schema.go-13-\tCpusAllocated   int32  `parquet:\"cpus_allocated\"`\npkg/archive/parquet/nodestate_schema.go-14-\tMemoryAllocated int64  `parquet:\"memory_allocated\"`\npkg/archive/parquet/nodestate_schema.go-15-\tGpusAllocated   int32  `parquet:\"gpus_allocated\"`\npkg/archive/parquet/nodestate_schema.go-16-\tJobsRunning     int32  `parquet:\"jobs_running\"`\npkg/archive/parquet/nodestate_schema.go-17-\tHostname        string `parquet:\"hostname\"`\npkg/archive/parquet/nodestate_schema.go-18-\tCluster         string `parquet:\"cluster\"`\npkg/archive/parquet/nodestate_schema.go-19-\tSubCluster      string `parquet:\"subcluster\"`\n/Users/jan/prg/CC/cc-backend/pkg/archive/parquet/nodestate_schema.go-20-}"}]},"uuid":"6ea7820f-c174-412f-8fa6-257028300636","timestamp":"2026-03-18T04:03:24.062Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"pkg/archive/parquet/schema.go:8:type ParquetJobRow struct {\npkg/archive/parquet/schema.go-9-\tJobID          int64   `parquet:\"job_id\"`\npkg/archive/parquet/schema.go-10-\tCluster        string  `parquet:\"cluster\"`\npkg/archive/parquet/schema.go-11-\tSubCluster     string  `parquet:\"sub_cluster\"`\npkg/archive/parquet/schema.go-12-\tPartition      string  `parquet:\"partition,optional\"`\npkg/archive/parquet/schema.go-13-\tProject        string  `parquet:\"project\"`\npkg/archive/parquet/schema.go-14-\tUser           string  `parquet:\"user\"`\npkg/archive/parquet/schema.go-15-\tState          string  `parquet:\"job_state\"`\npkg/archive/parquet/schema.go-16-\tStartTime      int64   `parquet:\"start_time\"`\npkg/archive/parquet/schema.go-17-\tDuration       int32   `parquet:\"duration\"`\npkg/archive/parquet/schema.go-18-\tWalltime       int64   `parquet:\"walltime\"`\npkg/archive/parquet/schema.go-19-\tNumNodes       int32   `parquet:\"num_nodes\"`\npkg/archive/parquet/schema.go-20-\tNumHWThreads   int32   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err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{"}]},"uuid":"e26a1aa7-04b9-40bf-ab8c-6d61bb74bd47","timestamp":"2026-03-18T04:03:28.636Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-104-\treturn nil\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-105-}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-106-\ninternal/taskmanager/retentionService.go:107:// transferJobsParquet converts jobs to Parquet format, organized by cluster.\ninternal/taskmanager/retentionService.go:108:func transferJobsParquet(jobs []*schema.Job, src archive.ArchiveBackend, target pqarchive.ParquetTarget, maxSizeMB int) error {\ninternal/taskmanager/retentionService.go:109:\tcw := pqarchive.NewClusterAwareParquetWriter(target, maxSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-110-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-111-\t// Set cluster configs for all clusters referenced by jobs\ninternal/taskmanager/retentionService.go-112-\tclustersDone := make(map[string]bool)\n--\ninternal/taskmanager/retentionService.go-262-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-263-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-264-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:265:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{","numLines":33},"sourceToolAssistantUUID":"474b99b3-f593-4755-b27a-b8e4dd79d876","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-285-func RegisterRetentionMoveService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-286-\tcclog.Infof(\"Register retention move service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-287-\ninternal/taskmanager/retentionService.go:288:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:289:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:290:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-291-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-292-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-293-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(5, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-35-func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-36-\tcclog.Info(\"Register node state retention move service\")\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-37-\ninternal/taskmanager/nodestateRetentionService.go:38:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/nodestateRetentionService.go:39:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/nodestateRetentionService.go:40:\t\tmaxFileSizeMB = 128\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-41-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-42-\ninternal/taskmanager/nodestateRetentionService.go-43-\tageHours := cfg.Age\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{"}]},"uuid":"392fddf0-3e00-4ec8-abb9-b655845479a1","timestamp":"2026-03-18T04:03:41.650Z","toolUseResult":{"mode":"content","numFiles":0,"filenames":[],"content":"/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-232-func RegisterRetentionCopyService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-233-\tcclog.Infof(\"Register retention copy service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-234-\ninternal/taskmanager/retentionService.go:235:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:236:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:237:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-238-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-239-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-240-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(4, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-262-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-263-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-264-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:265:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-266-\t\t\t\t\t\tcclog.Errorf(\"Retention copy: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-267-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-268-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-285-func RegisterRetentionMoveService(cfg Retention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-286-\tcclog.Infof(\"Register retention move service (format=%s, target=%s)\", cfg.Format, cfg.TargetKind)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-287-\ninternal/taskmanager/retentionService.go:288:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/retentionService.go:289:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/retentionService.go:290:\t\tmaxFileSizeMB = 512\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-291-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-292-\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-293-\ts.NewJob(gocron.DailyJob(1, gocron.NewAtTimes(gocron.NewAtTime(5, 0, 0))),\n--\ninternal/taskmanager/retentionService.go-313-\t\t\t\t\t\tcclog.Errorf(\"Retention move: create parquet target: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-314-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-315-\t\t\t\t\t}\ninternal/taskmanager/retentionService.go:316:\t\t\t\t\tif err := transferJobsParquet(jobs, ar, target, maxFileSizeMB); err != nil {\ninternal/taskmanager/retentionService.go-317-\t\t\t\t\t\tcclog.Errorf(\"Retention move: parquet transfer: %v\", err)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-318-\t\t\t\t\t\treturn\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/retentionService.go-319-\t\t\t\t\t}\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-35-func RegisterNodeStateRetentionMoveService(cfg *config.NodeStateRetention) {\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-36-\tcclog.Info(\"Register node state retention move service\")\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-37-\ninternal/taskmanager/nodestateRetentionService.go:38:\tmaxFileSizeMB := cfg.MaxFileSizeMB\ninternal/taskmanager/nodestateRetentionService.go:39:\tif maxFileSizeMB <= 0 {\ninternal/taskmanager/nodestateRetentionService.go:40:\t\tmaxFileSizeMB = 128\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-41-\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-42-\ninternal/taskmanager/nodestateRetentionService.go-43-\tageHours := cfg.Age\n--\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-83-\t\t\t\t}\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-84-\ninternal/taskmanager/nodestateRetentionService.go-85-\t\t\t\tcclog.Infof(\"NodeState move retention: archiving %d rows\", len(rows))\ninternal/taskmanager/nodestateRetentionService.go:86:\t\t\t\tpw := pqarchive.NewNodeStateParquetWriter(target, maxFileSizeMB)\n/Users/jan/prg/CC/cc-backend/internal/taskmanager/nodestateRetentionService.go-87-\ninternal/taskmanager/nodestateRetentionService.go-88-\t\t\t\tfor _, ns := range rows {\ninternal/taskmanager/nodestateRetentionService.go-89-\t\t\t\t\trow := pqarchive.ParquetNodeStateRow{","numLines":53},"sourceToolAssistantUUID":"3c6b8884-7d9f-4116-803f-8edf5fb39fe7","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"0e523105-a262-4da4-8ce0-de57188c6867","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RkUewSYmhcoRrM7YPKM3gb","type":"tool_result","content":"     1→# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n     2→\n     3→## Context\n     4→\n     5→Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n     6→\n     7→## Root Cause\n     8→\n     9→Two-layer unbounded accumulation:\n    10→\n    11→1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n    12→2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n    13→3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n    14→\n    15→Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n    16→\n    17→## Fix: Stream per-host to parquet writer\n    18→\n    19→Instead of accumulating all rows, write each host's data as a separate row group.\n    20→\n    21→### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n    22→\n    23→Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n    24→\n    25→```go\n    26→type parquetArchiveWriter struct {\n    27→    writer *pq.GenericWriter[ParquetMetricRow]\n    28→    bw     *bufio.Writer\n    29→    f      *os.File\n    30→    count  int\n    31→}\n    32→\n    33→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\n    34→func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\n    35→func (w *parquetArchiveWriter) Close() error\n    36→```\n    37→\n    38→- **Remove `SortingWriterConfig`** - no global sort buffer\n    39→- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n    40→- Each `Flush()` creates a separate row group per host\n    41→\n    42→### Step 2: Add row count estimation (`parquetArchive.go`)\n    43→\n    44→```go\n    45→func estimateRowCount(cf *CheckpointFile) int\n    46→```\n    47→\n    48→Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n    49→\n    50→### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n    51→\n    52→Change from:\n    53→```\n    54→workers → channel → accumulate allRows → writeParquetArchive(allRows)\n    55→```\n    56→\n    57→To:\n    58→```\n    59→open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n    60→```\n    61→\n    62→- Only one host's rows in memory at a time\n    63→- Track `files`/`dir` for deletion separately (don't retain rows)\n    64→- Check `writer.count > 0` instead of `len(allRows) == 0`\n    65→\n    66→### Step 4: Update test (`parquetArchive_test.go`)\n    67→\n    68→- `TestParquetArchiveRoundtrip`: use new streaming writer API\n    69→- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n    70→\n    71→## Files to Modify\n    72→\n    73→- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n    74→- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n    75→- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n    76→\n    77→## Memory Impact\n    78→\n    79→- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n    80→- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n    81→\n    82→## Sorting Tradeoff\n    83→\n    84→The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n    85→\n    86→## Verification\n    87→\n    88→```bash\n    89→go test -v ./pkg/metricstore/...\n    90→```\n    91→\n    92→Also verify with `go vet ./pkg/metricstore/...` for correctness.\n    93→"}]},"uuid":"820ca3ba-c7a2-4bca-9937-7389eb28a4f0","timestamp":"2026-03-18T04:03:47.129Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n","numLines":93,"startLine":1,"totalLines":93}},"sourceToolAssistantUUID":"0e523105-a262-4da4-8ce0-de57188c6867","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"820ca3ba-c7a2-4bca-9937-7389eb28a4f0","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EwL47Q2XdLejr1ZgqEBUk4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GedVGpbmUyDDQ8S3jAgoTM","name":"Write","input":{"file_path":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1490,"cache_read_input_tokens":54617,"output_tokens":944,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1490,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ9t7yLFg4b2Cfjvg1ZDm","type":"assistant","uuid":"24b9150b-c58b-4643-90ee-51ca27affb84","timestamp":"2026-03-18T04:04:09.115Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"24b9150b-c58b-4643-90ee-51ca27affb84","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GedVGpbmUyDDQ8S3jAgoTM","type":"tool_result","content":"The file /Users/jan/.claude/plans/shimmering-wandering-flurry.md has been updated successfully."}]},"uuid":"33a3d7d3-f247-4792-bbe0-48205fa9d6b8","timestamp":"2026-03-18T04:04:09.128Z","toolUseResult":{"type":"update","filePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md","content":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n","structuredPatch":[{"oldStart":1,"oldLines":92,"newStart":1,"newLines":60,"lines":["-# Fix: Memory Escalation in flattenCheckpointFile (68GB+)","+# Audit: SortingWriterConfig Memory Doubling in Parquet Writers"," "," ## Context"," ","-Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.","+After fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch."," ","-## Root Cause","+## Findings"," ","-Two-layer unbounded accumulation:","+### 1. Job Retention Writer — moderate risk","+**File**: `pkg/archive/parquet/writer.go:86-106`"," ","-1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice","-2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`","-3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling","+`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:","+- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**","+- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy"," ","-Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.","+The sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data."," ","-## Fix: Stream per-host to parquet writer","+**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy."," ","-Instead of accumulating all rows, write each host's data as a separate row group.","+### 2. NodeState Retention Writer — low risk","+**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`"," ","-### Step 1: Add streaming parquet writer (`parquetArchive.go`)","+Same pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful."," ","-Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:","+**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`."," ","-```go","-type parquetArchiveWriter struct {","-    writer *pq.GenericWriter[ParquetMetricRow]","-    bw     *bufio.Writer","-    f      *os.File","-    count  int","-}","+### 3. Metric Checkpoint Writer — already fixed","+**File**: `pkg/metricstore/parquetArchive.go`"," ","-func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)","-func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)","-func (w *parquetArchiveWriter) Close() error","-```","+Already addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`."," ","-- **Remove `SortingWriterConfig`** - no global sort buffer","-- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)","-- Each `Flush()` creates a separate row group per host","+## Recommendation"," ","-### Step 2: Add row count estimation (`parquetArchive.go`)","+Apply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change."," ","-```go","-func estimateRowCount(cf *CheckpointFile) int","-```","+### Changes"," ","-Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.","+#### `pkg/archive/parquet/writer.go`","+- Add `\"sort\"` import","+- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`","+- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options"," ","-### Step 3: Restructure `archiveCheckpoints` (`archive.go`)","+#### `pkg/archive/parquet/nodestate_writer.go`","+- Add `\"sort\"` import","+- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`","+- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options"," ","-Change from:","-```","-workers → channel → accumulate allRows → writeParquetArchive(allRows)","-```","+### Memory Impact"," ","-To:","-```","-open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer","-```","+| Writer | Before (peak per flush) | After |","+|--------|------------------------|-------|","+| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |","+| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |"," ","-- Only one host's rows in memory at a time","-- Track `files`/`dir` for deletion separately (don't retain rows)","-- Check `writer.count > 0` instead of `len(allRows) == 0`","+### Verification"," ","-### Step 4: Update test (`parquetArchive_test.go`)","-","-- `TestParquetArchiveRoundtrip`: use new streaming writer API","-- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)","-","-## Files to Modify","-","-- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import","-- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream","-- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test","-","-## Memory Impact","-","-- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+","-- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak","-","-## Sorting Tradeoff","-","-The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).","-","-## Verification","-"," ```bash","-go test -v ./pkg/metricstore/...","+go test -v ./pkg/archive/parquet/...","+go vet ./pkg/archive/parquet/..."," ```","-","-Also verify with `go vet ./pkg/metricstore/...` for correctness."]}],"originalFile":"# Fix: Memory Escalation in flattenCheckpointFile (68GB+)\n\n## Context\n\nProduction gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.\n\n## Root Cause\n\nTwo-layer unbounded accumulation:\n\n1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice\n2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`\n3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling\n\nPeak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.\n\n## Fix: Stream per-host to parquet writer\n\nInstead of accumulating all rows, write each host's data as a separate row group.\n\n### Step 1: Add streaming parquet writer (`parquetArchive.go`)\n\nReplace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:\n\n```go\ntype parquetArchiveWriter struct {\n    writer *pq.GenericWriter[ParquetMetricRow]\n    bw     *bufio.Writer\n    f      *os.File\n    count  int\n}\n\nfunc newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)\nfunc (w *parquetArchiveWriter) Close() error\n```\n\n- **Remove `SortingWriterConfig`** - no global sort buffer\n- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)\n- Each `Flush()` creates a separate row group per host\n\n### Step 2: Add row count estimation (`parquetArchive.go`)\n\n```go\nfunc estimateRowCount(cf *CheckpointFile) int\n```\n\nPre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.\n\n### Step 3: Restructure `archiveCheckpoints` (`archive.go`)\n\nChange from:\n```\nworkers → channel → accumulate allRows → writeParquetArchive(allRows)\n```\n\nTo:\n```\nopen writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer\n```\n\n- Only one host's rows in memory at a time\n- Track `files`/`dir` for deletion separately (don't retain rows)\n- Check `writer.count > 0` instead of `len(allRows) == 0`\n\n### Step 4: Update test (`parquetArchive_test.go`)\n\n- `TestParquetArchiveRoundtrip`: use new streaming writer API\n- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)\n\n## Files to Modify\n\n- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `\"sort\"` import\n- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream\n- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test\n\n## Memory Impact\n\n- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+\n- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak\n\n## Sorting Tradeoff\n\nThe output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).\n\n## Verification\n\n```bash\ngo test -v ./pkg/metricstore/...\n```\n\nAlso verify with `go vet ./pkg/metricstore/...` for correctness.\n"},"sourceToolAssistantUUID":"24b9150b-c58b-4643-90ee-51ca27affb84","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"c87cbba4-6bc3-44a3-b0f3-9a25b8f157c3","isSidechain":false,"promptId":"ba68d540-ba70-4f66-94e7-2c9d72fab3f4","type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01MB8m76U37bTSZvZgNRPPFn","content":[{"type":"tool_reference","tool_name":"ExitPlanMode"}]}]},"uuid":"e511676b-038b-47e4-add3-f205f7f18fe1","timestamp":"2026-03-18T04:04:14.429Z","toolUseResult":{"matches":["ExitPlanMode"],"query":"select:ExitPlanMode","total_deferred_tools":21},"sourceToolAssistantUUID":"c87cbba4-6bc3-44a3-b0f3-9a25b8f157c3","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"e511676b-038b-47e4-add3-f205f7f18fe1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01QxS4Nm7MmwEvvjrAR3tMPq","type":"message","role":"assistant","content":[{"type":"text","text":"\n\nHere's what I found:\n\n**Two other writers use `SortingWriterConfig`**, which doubles memory per batch:\n\n1. **Job retention** (`pkg/archive/parquet/writer.go:89-96`) — batched at 512MB default, but `SortingWriterConfig` doubles it to ~1GB peak per flush. `ParquetJobRow` includes `MetricDataGz []byte` which makes rows heavy.\n\n2. **NodeState retention** (`pkg/archive/parquet/nodestate_writer.go:85-93`) — batched at 128MB default, doubling to ~256MB. Rows are small (~150 bytes), so this is low risk but still wasteful.\n\nNeither is catastrophic like the checkpoint case (which had NO batching at all), because `maxSizeBytes` caps each batch. But the `SortingWriterConfig` still unnecessarily copies all batch rows internally.\n\nThe fix is the same pattern we already used: **pre-sort rows in-place with `sort.Slice`, remove `SortingWriterConfig`**. This halves peak memory per flush with identical output."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1817,"cache_read_input_tokens":56107,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1817},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CZ9t9z9vXZht2ydikKnox","type":"assistant","uuid":"671c15f1-a9c4-4c55-80b3-6452574319f3","timestamp":"2026-03-18T04:04:25.108Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"671c15f1-a9c4-4c55-80b3-6452574319f3","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01QxS4Nm7MmwEvvjrAR3tMPq","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SKhtziAY4y9pfEEXT7v2BQ","name":"ExitPlanMode","input":{"allowedPrompts":[{"tool":"Bash","prompt":"run tests and vet for pkg/archive/parquet"}],"plan":"# Audit: SortingWriterConfig Memory Doubling in Parquet Writers\n\n## Context\n\nAfter fixing the 68GB+ memory spike in `flattenCheckpointFile` (already implemented on this branch), the user asks whether other parquet writers in the codebase have similar memory issues. Specifically, `SortingWriterConfig` buffers ALL rows internally until `Close()`, effectively doubling memory usage per batch.\n\n## Findings\n\n### 1. Job Retention Writer — moderate risk\n**File**: `pkg/archive/parquet/writer.go:86-106`\n\n`writeParquetBytes()` uses `SortingWriterConfig` with `bytes.Buffer`. The batching via `maxSizeBytes` (default 512MB) caps the damage, but `SortingWriterConfig` still doubles memory within each batch:\n- Peak per-flush = batch rows (~512MB) + sorting writer copy (~512MB) = **~1GB**\n- `ParquetJobRow.MetricDataGz` (compressed metric data blob) can be large, making rows heavy\n\nThe sorting columns are `(sub_cluster, project, start_time)` — this provides marginal compression benefit for already-batched data.\n\n**Mitigation**: Remove `SortingWriterConfig`. Pre-sort `pw.rows` in-place with `sort.Slice` before calling `writer.Write()`. Same output order, no internal copy.\n\n### 2. NodeState Retention Writer — low risk\n**File**: `pkg/archive/parquet/nodestate_writer.go:82-103`\n\nSame pattern: `SortingWriterConfig` in `writeNodeStateParquetBytes()`. Default batch cap is 128MB. `ParquetNodeStateRow` is small (~150 bytes per row), so the doubling yields ~256MB peak at worst. Not catastrophic, but still wasteful.\n\n**Mitigation**: Same fix — pre-sort, remove `SortingWriterConfig`.\n\n### 3. Metric Checkpoint Writer — already fixed\n**File**: `pkg/metricstore/parquetArchive.go`\n\nAlready addressed in the current branch changes. Uses streaming row groups, no `SortingWriterConfig`.\n\n## Recommendation\n\nApply the same pattern used in the checkpoint fix: **pre-sort rows in-place, remove `SortingWriterConfig`**. This halves peak memory per flush in both writers with zero output change.\n\n### Changes\n\n#### `pkg/archive/parquet/writer.go`\n- Add `\"sort\"` import\n- In `writeParquetBytes()`: sort `rows` by `(sub_cluster, project, start_time)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n#### `pkg/archive/parquet/nodestate_writer.go`\n- Add `\"sort\"` import\n- In `writeNodeStateParquetBytes()`: sort `rows` by `(cluster, subcluster, hostname, time_stamp)` before `writer.Write()`\n- Remove `SortingWriterConfig(...)` from `pq.NewGenericWriter` options\n\n### Memory Impact\n\n| Writer | Before (peak per flush) | After |\n|--------|------------------------|-------|\n| Job retention | ~2x batch (~1GB at 512MB default) | ~1x batch (~512MB) |\n| NodeState retention | ~2x batch (~256MB at 128MB default) | ~1x batch (~128MB) |\n\n### Verification\n\n```bash\ngo test -v ./pkg/archive/parquet/...\ngo vet ./pkg/archive/parquet/...\n```\n","planFilePath":"/Users/jan/.claude/plans/shimmering-wandering-flurry.md"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1817,"cache_read_input_tokens":56107,"output_tokens":343,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1817,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ9t9z9vXZht2ydikKnox","type":"assistant","uuid":"268c6603-bcb3-4ff1-90c1-3b1ac1b66dba","timestamp":"2026-03-18T04:04:25.885Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"0dd0c6cf-303c-4716-923f-8f885fda22dc","isSidechain":false,"promptId":"818611a2-b158-437a-8bb3-d87143ab3074","type":"user","message":{"role":"user","content":"Compare the archive writer implementation with @~/tmp/cc-backend/pkg/metricstore/parquetArchive.go . Compare and explain differences."},"uuid":"005e5240-d272-4d5d-8788-91359f385c60","timestamp":"2026-03-18T04:15:40.358Z","permissionMode":"plan","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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+{"parentUuid":"7c5c5a50-d691-4409-a21b-afad18cfc15d","isSidechain":false,"promptId":"818611a2-b158-437a-8bb3-d87143ab3074","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Bd4jXeKitPbMrorCxFEA2Z","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→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\n    18→\tpq \"github.com/parquet-go/parquet-go\"\n    19→)\n    20→\n    21→// ParquetMetricRow is the long-format schema for archived metric data.\n    22→// One row per (host, metric, scope, scope_id, timestamp) data point.\n    23→// Sorted by (cluster, hostname, metric, timestamp) for optimal compression.\n    24→type ParquetMetricRow struct {\n    25→\tCluster   string  `parquet:\"cluster\"`\n    26→\tHostname  string  `parquet:\"hostname\"`\n    27→\tMetric    string  `parquet:\"metric\"`\n    28→\tScope     string  `parquet:\"scope\"`\n    29→\tScopeID   string  `parquet:\"scope_id\"`\n    30→\tTimestamp int64   `parquet:\"timestamp\"`\n    31→\tFrequency int64   `parquet:\"frequency\"`\n    32→\tValue     float32 `parquet:\"value\"`\n    33→}\n    34→\n    35→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n    36→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    37→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    38→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n    39→\tfor metricName, cm := range cf.Metrics {\n    40→\t\tts := cm.Start\n    41→\t\tfor _, v := range cm.Data {\n    42→\t\t\tif !v.IsNaN() {\n    43→\t\t\t\trows = append(rows, ParquetMetricRow{\n    44→\t\t\t\t\tCluster:   cluster,\n    45→\t\t\t\t\tHostname:  hostname,\n    46→\t\t\t\t\tMetric:    metricName,\n    47→\t\t\t\t\tScope:     scope,\n    48→\t\t\t\t\tScopeID:   scopeID,\n    49→\t\t\t\t\tTimestamp: ts,\n    50→\t\t\t\t\tFrequency: cm.Frequency,\n    51→\t\t\t\t\tValue:     float32(v),\n    52→\t\t\t\t})\n    53→\t\t\t}\n    54→\t\t\tts += cm.Frequency\n    55→\t\t}\n    56→\t}\n    57→\n    58→\tfor childName, childCf := range cf.Children {\n    59→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    60→\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n    61→\t}\n    62→\n    63→\treturn rows\n    64→}\n    65→\n    66→// parseScopeFromName infers scope and scope_id from a child level name.\n    67→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    68→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    69→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    70→func parseScopeFromName(name string) (string, string) {\n    71→\tprefixes := []struct {\n    72→\t\tprefix string\n    73→\t\tscope  string\n    74→\t}{\n    75→\t\t{\"socket\", \"socket\"},\n    76→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    77→\t\t{\"core\", \"core\"},\n    78→\t\t{\"hwthread\", \"hwthread\"},\n    79→\t\t{\"cpu\", \"hwthread\"},\n    80→\t\t{\"accelerator\", \"accelerator\"},\n    81→\t}\n    82→\n    83→\tfor _, p := range prefixes {\n    84→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    85→\t\t\tid := name[len(p.prefix):]\n    86→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    87→\t\t\t\treturn p.scope, id\n    88→\t\t\t}\n    89→\t\t}\n    90→\t}\n    91→\n    92→\treturn name, \"\"\n    93→}\n    94→\n    95→// parquetArchiveWriter supports incremental writes to a Parquet file.\n    96→// Each call to WriteHostRows writes one row group (typically one host's data),\n    97→// avoiding accumulation of all rows in memory.\n    98→type parquetArchiveWriter struct {\n    99→\twriter *pq.GenericWriter[ParquetMetricRow]\n   100→\tbw     *bufio.Writer\n   101→\tf      *os.File\n   102→\tcount  int\n   103→}\n   104→\n   105→// newParquetArchiveWriter creates a streaming Parquet writer with Zstd compression.\n   106→func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error) {\n   107→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n   108→\t\treturn nil, fmt.Errorf(\"creating archive directory: %w\", err)\n   109→\t}\n   110→\n   111→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   112→\tif err != nil {\n   113→\t\treturn nil, fmt.Errorf(\"creating parquet file: %w\", err)\n   114→\t}\n   115→\n   116→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   117→\n   118→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   119→\t\tpq.Compression(&pq.Zstd),\n   120→\t)\n   121→\n   122→\treturn &parquetArchiveWriter{writer: writer, bw: bw, f: f}, nil\n   123→}\n   124→\n   125→// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n   126→// and flushes to create a separate row group.\n   127→func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n   128→\tsort.Slice(rows, func(i, j int) bool {\n   129→\t\tif rows[i].Metric != rows[j].Metric {\n   130→\t\t\treturn rows[i].Metric < rows[j].Metric\n   131→\t\t}\n   132→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   133→\t})\n   134→\n   135→\tif _, err := w.writer.Write(rows); err != nil {\n   136→\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\n   137→\t}\n   138→\n   139→\tif err := w.writer.Flush(); err != nil {\n   140→\t\treturn fmt.Errorf(\"flushing parquet row group: %w\", err)\n   141→\t}\n   142→\n   143→\tw.count += len(rows)\n   144→\treturn nil\n   145→}\n   146→\n   147→// Close finalises the Parquet file (footer, buffered I/O, file handle).\n   148→func (w *parquetArchiveWriter) Close() error {\n   149→\tif err := w.writer.Close(); err != nil {\n   150→\t\tw.f.Close()\n   151→\t\treturn fmt.Errorf(\"closing parquet writer: %w\", err)\n   152→\t}\n   153→\n   154→\tif err := w.bw.Flush(); err != nil {\n   155→\t\tw.f.Close()\n   156→\t\treturn fmt.Errorf(\"flushing parquet file: %w\", err)\n   157→\t}\n   158→\n   159→\treturn w.f.Close()\n   160→}\n   161→\n   162→// sortParquetRows sorts rows by (metric, timestamp) in-place.\n   163→func sortParquetRows(rows []ParquetMetricRow) {\n   164→\tsort.Slice(rows, func(i, j int) bool {\n   165→\t\tif rows[i].Metric != rows[j].Metric {\n   166→\t\t\treturn rows[i].Metric < rows[j].Metric\n   167→\t\t}\n   168→\t\treturn rows[i].Timestamp < rows[j].Timestamp\n   169→\t})\n   170→}\n   171→\n   172→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   173→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   174→// before converting it to Parquet format.\n   175→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   176→\tf, err := os.Open(filename)\n   177→\tif err != nil {\n   178→\t\treturn nil, err\n   179→\t}\n   180→\tdefer f.Close()\n   181→\n   182→\text := filepath.Ext(filename)\n   183→\tswitch ext {\n   184→\tcase \".json\":\n   185→\t\tcf := &CheckpointFile{}\n   186→\t\tbr := bufio.NewReader(f)\n   187→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   188→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   189→\t\t}\n   190→\t\treturn cf, nil\n   191→\n   192→\tcase \".bin\":\n   193→\t\tbr := bufio.NewReader(f)\n   194→\t\tvar magic uint32\n   195→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   196→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   197→\t\t}\n   198→\t\tif magic != snapFileMagic {\n   199→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   200→\t\t}\n   201→\t\tvar fileFrom, fileTo int64\n   202→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   203→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   204→\t\t}\n   205→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   206→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   207→\t\t}\n   208→\t\tcf, err := readBinaryLevel(br)\n   209→\t\tif err != nil {\n   210→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   211→\t\t}\n   212→\t\tcf.From = fileFrom\n   213→\t\tcf.To = fileTo\n   214→\t\treturn cf, nil\n   215→\n   216→\tdefault:\n   217→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   218→\t}\n   219→}\n   220→\n   221→// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n   222→// Used for pre-allocating the rows slice to avoid repeated append doubling.\n   223→func estimateRowCount(cf *CheckpointFile) int {\n   224→\tn := 0\n   225→\tfor _, cm := range cf.Metrics {\n   226→\t\tn += len(cm.Data)\n   227→\t}\n   228→\tfor _, child := range cf.Children {\n   229→\t\tn += estimateRowCount(child)\n   230→\t}\n   231→\treturn n\n   232→}\n   233→\n   234→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   235→// converts them to Parquet rows. Returns the rows and filenames that were processed.\n   236→func archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []string, error) {\n   237→\tentries, err := os.ReadDir(dir)\n   238→\tif err != nil {\n   239→\t\treturn nil, nil, err\n   240→\t}\n   241→\n   242→\tfiles, err := findFiles(entries, from, false)\n   243→\tif err != nil {\n   244→\t\treturn nil, nil, err\n   245→\t}\n   246→\n   247→\tif len(files) == 0 {\n   248→\t\treturn nil, nil, nil\n   249→\t}\n   250→\n   251→\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n   252→\ttype loaded struct {\n   253→\t\tcf       *CheckpointFile\n   254→\t\tfilename string\n   255→\t}\n   256→\tvar checkpoints []loaded\n   257→\ttotalEstimate := 0\n   258→\n   259→\tfor _, checkpoint := range files {\n   260→\t\tfilename := filepath.Join(dir, checkpoint)\n   261→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   262→\t\tif err != nil {\n   263→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   264→\t\t\tcontinue\n   265→\t\t}\n   266→\t\ttotalEstimate += estimateRowCount(cf)\n   267→\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n   268→\t}\n   269→\n   270→\tif len(checkpoints) == 0 {\n   271→\t\treturn nil, nil, nil\n   272→\t}\n   273→\n   274→\trows := make([]ParquetMetricRow, 0, totalEstimate)\n   275→\tprocessedFiles := make([]string, 0, len(checkpoints))\n   276→\n   277→\tfor _, cp := range checkpoints {\n   278→\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n   279→\t\tprocessedFiles = append(processedFiles, cp.filename)\n   280→\t}\n   281→\n   282→\treturn rows, processedFiles, nil\n   283→}\n   284→"}]},"uuid":"a8ad17a0-acb9-494a-bb7f-a355ea45a0c6","timestamp":"2026-03-18T04:15:45.457Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/prg/CC/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\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rows []ParquetMetricRow) []ParquetMetricRow {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trows = append(rows, 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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\trows = flattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rows)\n\t}\n\n\treturn rows\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// Each call to WriteHostRows writes one row group (typically one host's data),\n// avoiding accumulation of all rows in memory.\ntype parquetArchiveWriter struct {\n\twriter *pq.GenericWriter[ParquetMetricRow]\n\tbw     *bufio.Writer\n\tf      *os.File\n\tcount  int\n}\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{writer: writer, bw: bw, f: f}, nil\n}\n\n// WriteHostRows sorts rows by (metric, timestamp) in-place, writes them,\n// and flushes to create a separate row group.\nfunc (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\n\n\tif _, err := w.writer.Write(rows); err != nil {\n\t\treturn fmt.Errorf(\"writing parquet rows: %w\", err)\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\tw.count += len(rows)\n\treturn nil\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// sortParquetRows sorts rows by (metric, timestamp) in-place.\nfunc sortParquetRows(rows []ParquetMetricRow) {\n\tsort.Slice(rows, func(i, j int) bool {\n\t\tif rows[i].Metric != rows[j].Metric {\n\t\t\treturn rows[i].Metric < rows[j].Metric\n\t\t}\n\t\treturn rows[i].Timestamp < rows[j].Timestamp\n\t})\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// estimateRowCount estimates the number of Parquet rows a CheckpointFile will produce.\n// Used for pre-allocating the rows slice to avoid repeated append doubling.\nfunc estimateRowCount(cf *CheckpointFile) int {\n\tn := 0\n\tfor _, cm := range cf.Metrics {\n\t\tn += len(cm.Data)\n\t}\n\tfor _, child := range cf.Children {\n\t\tn += estimateRowCount(child)\n\t}\n\treturn n\n}\n\n// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the rows and filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64) ([]ParquetMetricRow, []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\t// First pass: load checkpoints and estimate total rows for pre-allocation.\n\ttype loaded struct {\n\t\tcf       *CheckpointFile\n\t\tfilename string\n\t}\n\tvar checkpoints []loaded\n\ttotalEstimate := 0\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\t\ttotalEstimate += estimateRowCount(cf)\n\t\tcheckpoints = append(checkpoints, loaded{cf: cf, filename: checkpoint})\n\t}\n\n\tif len(checkpoints) == 0 {\n\t\treturn nil, nil, nil\n\t}\n\n\trows := make([]ParquetMetricRow, 0, totalEstimate)\n\tprocessedFiles := make([]string, 0, len(checkpoints))\n\n\tfor _, cp := range checkpoints {\n\t\trows = flattenCheckpointFile(cp.cf, cluster, host, \"node\", \"\", rows)\n\t\tprocessedFiles = append(processedFiles, cp.filename)\n\t}\n\n\treturn rows, processedFiles, nil\n}\n","numLines":284,"startLine":1,"totalLines":284}},"sourceToolAssistantUUID":"7c5c5a50-d691-4409-a21b-afad18cfc15d","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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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 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→\n    16→\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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→// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows via a channel.\n    35→// The scope path is built from the hierarchy: host level is \"node\", then child names\n    36→// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\n    37→func flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rowChan chan<- *ParquetMetricRow) {\n    38→\tfor metricName, cm := range cf.Metrics {\n    39→\t\tts := cm.Start\n    40→\t\tfor _, v := range cm.Data {\n    41→\t\t\tif !v.IsNaN() {\n    42→\t\t\t\trowChan <- &ParquetMetricRow{\n    43→\t\t\t\t\tCluster:   cluster,\n    44→\t\t\t\t\tHostname:  hostname,\n    45→\t\t\t\t\tMetric:    metricName,\n    46→\t\t\t\t\tScope:     scope,\n    47→\t\t\t\t\tScopeID:   scopeID,\n    48→\t\t\t\t\tTimestamp: ts,\n    49→\t\t\t\t\tFrequency: cm.Frequency,\n    50→\t\t\t\t\tValue:     float32(v),\n    51→\t\t\t\t}\n    52→\t\t\t}\n    53→\t\t\tts += cm.Frequency\n    54→\t\t}\n    55→\t}\n    56→\n    57→\tfor childName, childCf := range cf.Children {\n    58→\t\tchildScope, childScopeID := parseScopeFromName(childName)\n    59→\t\tflattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rowChan)\n    60→\t}\n    61→}\n    62→\n    63→// parseScopeFromName infers scope and scope_id from a child level name.\n    64→// Examples: \"socket0\" → (\"socket\", \"0\"), \"core12\" → (\"core\", \"12\"),\n    65→// \"a0\" (accelerator) → (\"accelerator\", \"0\").\n    66→// If the name doesn't match known patterns, it's used as-is for scope with empty scope_id.\n    67→func parseScopeFromName(name string) (string, string) {\n    68→\tprefixes := []struct {\n    69→\t\tprefix string\n    70→\t\tscope  string\n    71→\t}{\n    72→\t\t{\"socket\", \"socket\"},\n    73→\t\t{\"memoryDomain\", \"memoryDomain\"},\n    74→\t\t{\"core\", \"core\"},\n    75→\t\t{\"hwthread\", \"hwthread\"},\n    76→\t\t{\"cpu\", \"hwthread\"},\n    77→\t\t{\"accelerator\", \"accelerator\"},\n    78→\t}\n    79→\n    80→\tfor _, p := range prefixes {\n    81→\t\tif len(name) > len(p.prefix) && name[:len(p.prefix)] == p.prefix {\n    82→\t\t\tid := name[len(p.prefix):]\n    83→\t\t\tif len(id) > 0 && id[0] >= '0' && id[0] <= '9' {\n    84→\t\t\t\treturn p.scope, id\n    85→\t\t\t}\n    86→\t\t}\n    87→\t}\n    88→\n    89→\treturn name, \"\"\n    90→}\n    91→\n    92→// writeParquetArchiveStream writes rows from a channel to a Parquet file with Zstd compression in batches.\n    93→func writeParquetArchiveStream(filename string, rowChan <-chan *ParquetMetricRow) (int, error) {\n    94→\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n    95→\t\tgo func() {\n    96→\t\t\tfor range rowChan {\n    97→\t\t\t}\n    98→\t\t}()\n    99→\t\treturn 0, fmt.Errorf(\"creating archive directory: %w\", err)\n   100→\t}\n   101→\n   102→\tf, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY|os.O_TRUNC, CheckpointFilePerms)\n   103→\tif err != nil {\n   104→\t\tgo func() {\n   105→\t\t\tfor range rowChan {\n   106→\t\t\t}\n   107→\t\t}()\n   108→\t\treturn 0, fmt.Errorf(\"creating parquet file: %w\", err)\n   109→\t}\n   110→\tdefer f.Close()\n   111→\n   112→\tbw := bufio.NewWriterSize(f, 1<<20) // 1MB write buffer\n   113→\n   114→\twriter := pq.NewGenericWriter[ParquetMetricRow](bw,\n   115→\t\tpq.Compression(&pq.Zstd),\n   116→\t\tpq.SortingWriterConfig(pq.SortingColumns(\n   117→\t\t\tpq.Ascending(\"cluster\"),\n   118→\t\t\tpq.Ascending(\"hostname\"),\n   119→\t\t\tpq.Ascending(\"metric\"),\n   120→\t\t\tpq.Ascending(\"timestamp\"),\n   121→\t\t)),\n   122→\t)\n   123→\n   124→\tbatchSize := 4096\n   125→\tbatch := make([]ParquetMetricRow, 0, batchSize)\n   126→\trowCount := 0\n   127→\tvar writeErr error\n   128→\n   129→\tfor rowPtr := range rowChan {\n   130→\t\tif writeErr != nil {\n   131→\t\t\tcontinue // Drain the channel to prevent worker deadlock\n   132→\t\t}\n   133→\t\tbatch = append(batch, *rowPtr)\n   134→\t\tif len(batch) >= batchSize {\n   135→\t\t\tif _, err := writer.Write(batch); err != nil {\n   136→\t\t\t\twriteErr = fmt.Errorf(\"writing parquet batch: %w\", err)\n   137→\t\t\t}\n   138→\t\t\trowCount += len(batch)\n   139→\t\t\tbatch = batch[:0]\n   140→\t\t}\n   141→\t}\n   142→\n   143→\tif writeErr != nil {\n   144→\t\treturn rowCount, writeErr\n   145→\t}\n   146→\n   147→\tif len(batch) > 0 {\n   148→\t\tif _, err := writer.Write(batch); err != nil {\n   149→\t\t\treturn rowCount, fmt.Errorf(\"writing remaining parquet batch: %w\", err)\n   150→\t\t}\n   151→\t\trowCount += len(batch)\n   152→\t}\n   153→\n   154→\tif err := writer.Close(); err != nil {\n   155→\t\treturn rowCount, fmt.Errorf(\"closing parquet writer: %w\", err)\n   156→\t}\n   157→\n   158→\tif err := bw.Flush(); err != nil {\n   159→\t\treturn rowCount, fmt.Errorf(\"flushing parquet file: %w\", err)\n   160→\t}\n   161→\n   162→\treturn rowCount, nil\n   163→}\n   164→\n   165→// loadCheckpointFileFromDisk reads a JSON or binary checkpoint file and returns\n   166→// a CheckpointFile. Used by the Parquet archiver to read checkpoint data\n   167→// before converting it to Parquet format.\n   168→func loadCheckpointFileFromDisk(filename string) (*CheckpointFile, error) {\n   169→\tf, err := os.Open(filename)\n   170→\tif err != nil {\n   171→\t\treturn nil, err\n   172→\t}\n   173→\tdefer f.Close()\n   174→\n   175→\text := filepath.Ext(filename)\n   176→\tswitch ext {\n   177→\tcase \".json\":\n   178→\t\tcf := &CheckpointFile{}\n   179→\t\tbr := bufio.NewReader(f)\n   180→\t\tif err := json.NewDecoder(br).Decode(cf); err != nil {\n   181→\t\t\treturn nil, fmt.Errorf(\"decoding JSON checkpoint %s: %w\", filename, err)\n   182→\t\t}\n   183→\t\treturn cf, nil\n   184→\n   185→\tcase \".bin\":\n   186→\t\tbr := bufio.NewReader(f)\n   187→\t\tvar magic uint32\n   188→\t\tif err := binary.Read(br, binary.LittleEndian, &magic); err != nil {\n   189→\t\t\treturn nil, fmt.Errorf(\"reading magic from %s: %w\", filename, err)\n   190→\t\t}\n   191→\t\tif magic != snapFileMagic {\n   192→\t\t\treturn nil, fmt.Errorf(\"invalid snapshot magic in %s: 0x%08X\", filename, magic)\n   193→\t\t}\n   194→\t\tvar fileFrom, fileTo int64\n   195→\t\tif err := binary.Read(br, binary.LittleEndian, &fileFrom); err != nil {\n   196→\t\t\treturn nil, fmt.Errorf(\"reading from-timestamp from %s: %w\", filename, err)\n   197→\t\t}\n   198→\t\tif err := binary.Read(br, binary.LittleEndian, &fileTo); err != nil {\n   199→\t\t\treturn nil, fmt.Errorf(\"reading to-timestamp from %s: %w\", filename, err)\n   200→\t\t}\n   201→\t\tcf, err := readBinaryLevel(br)\n   202→\t\tif err != nil {\n   203→\t\t\treturn nil, fmt.Errorf(\"reading binary level from %s: %w\", filename, err)\n   204→\t\t}\n   205→\t\tcf.From = fileFrom\n   206→\t\tcf.To = fileTo\n   207→\t\treturn cf, nil\n   208→\n   209→\tdefault:\n   210→\t\treturn nil, fmt.Errorf(\"unsupported checkpoint extension: %s\", ext)\n   211→\t}\n   212→}\n   213→\n   214→// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n   215→// converts them to Parquet rows. Returns the filenames that were processed.\n   216→func archiveCheckpointsToParquet(dir, cluster, host string, from int64, rowChan chan<- *ParquetMetricRow) ([]string, error) {\n   217→\tentries, err := os.ReadDir(dir)\n   218→\tif err != nil {\n   219→\t\treturn nil, err\n   220→\t}\n   221→\n   222→\tfiles, err := findFiles(entries, from, false)\n   223→\tif err != nil {\n   224→\t\treturn nil, err\n   225→\t}\n   226→\n   227→\tif len(files) == 0 {\n   228→\t\treturn nil, nil\n   229→\t}\n   230→\n   231→\tfor _, checkpoint := range files {\n   232→\t\tfilename := filepath.Join(dir, checkpoint)\n   233→\t\tcf, err := loadCheckpointFileFromDisk(filename)\n   234→\t\tif err != nil {\n   235→\t\t\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n   236→\t\t\tcontinue\n   237→\t\t}\n   238→\n   239→\t\tflattenCheckpointFile(cf, cluster, host, \"node\", \"\", rowChan)\n   240→\t}\n   241→\n   242→\treturn files, nil\n   243→}\n   244→"}]},"uuid":"70268700-0562-475c-9bb1-8ac1d78195a4","timestamp":"2026-03-18T04:15:47.811Z","toolUseResult":{"type":"text","file":{"filePath":"/Users/jan/tmp/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\n\tcclog \"github.com/ClusterCockpit/cc-lib/v2/ccLogger\"\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// flattenCheckpointFile recursively converts a CheckpointFile tree into Parquet rows via a channel.\n// The scope path is built from the hierarchy: host level is \"node\", then child names\n// map to scope/scope_id (e.g., \"socket0\" → scope=\"socket\", scope_id=\"0\").\nfunc flattenCheckpointFile(cf *CheckpointFile, cluster, hostname, scope, scopeID string, rowChan chan<- *ParquetMetricRow) {\n\tfor metricName, cm := range cf.Metrics {\n\t\tts := cm.Start\n\t\tfor _, v := range cm.Data {\n\t\t\tif !v.IsNaN() {\n\t\t\t\trowChan <- &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\t\t\t}\n\t\t\tts += cm.Frequency\n\t\t}\n\t}\n\n\tfor childName, childCf := range cf.Children {\n\t\tchildScope, childScopeID := parseScopeFromName(childName)\n\t\tflattenCheckpointFile(childCf, cluster, hostname, childScope, childScopeID, rowChan)\n\t}\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// writeParquetArchiveStream writes rows from a channel to a Parquet file with Zstd compression in batches.\nfunc writeParquetArchiveStream(filename string, rowChan <-chan *ParquetMetricRow) (int, error) {\n\tif err := os.MkdirAll(filepath.Dir(filename), CheckpointDirPerms); err != nil {\n\t\tgo func() {\n\t\t\tfor range rowChan {\n\t\t\t}\n\t\t}()\n\t\treturn 0, 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\tgo func() {\n\t\t\tfor range rowChan {\n\t\t\t}\n\t\t}()\n\t\treturn 0, fmt.Errorf(\"creating parquet file: %w\", err)\n\t}\n\tdefer f.Close()\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\tpq.SortingWriterConfig(pq.SortingColumns(\n\t\t\tpq.Ascending(\"cluster\"),\n\t\t\tpq.Ascending(\"hostname\"),\n\t\t\tpq.Ascending(\"metric\"),\n\t\t\tpq.Ascending(\"timestamp\"),\n\t\t)),\n\t)\n\n\tbatchSize := 4096\n\tbatch := make([]ParquetMetricRow, 0, batchSize)\n\trowCount := 0\n\tvar writeErr error\n\n\tfor rowPtr := range rowChan {\n\t\tif writeErr != nil {\n\t\t\tcontinue // Drain the channel to prevent worker deadlock\n\t\t}\n\t\tbatch = append(batch, *rowPtr)\n\t\tif len(batch) >= batchSize {\n\t\t\tif _, err := writer.Write(batch); err != nil {\n\t\t\t\twriteErr = fmt.Errorf(\"writing parquet batch: %w\", err)\n\t\t\t}\n\t\t\trowCount += len(batch)\n\t\t\tbatch = batch[:0]\n\t\t}\n\t}\n\n\tif writeErr != nil {\n\t\treturn rowCount, writeErr\n\t}\n\n\tif len(batch) > 0 {\n\t\tif _, err := writer.Write(batch); err != nil {\n\t\t\treturn rowCount, fmt.Errorf(\"writing remaining parquet batch: %w\", err)\n\t\t}\n\t\trowCount += len(batch)\n\t}\n\n\tif err := writer.Close(); err != nil {\n\t\treturn rowCount, fmt.Errorf(\"closing parquet writer: %w\", err)\n\t}\n\n\tif err := bw.Flush(); err != nil {\n\t\treturn rowCount, fmt.Errorf(\"flushing parquet file: %w\", err)\n\t}\n\n\treturn rowCount, nil\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// archiveCheckpointsToParquet reads checkpoint files for a host directory,\n// converts them to Parquet rows. Returns the filenames that were processed.\nfunc archiveCheckpointsToParquet(dir, cluster, host string, from int64, rowChan chan<- *ParquetMetricRow) ([]string, error) {\n\tentries, err := os.ReadDir(dir)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tfiles, err := findFiles(entries, from, false)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif len(files) == 0 {\n\t\treturn nil, nil\n\t}\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\tcclog.Warnf(\"[METRICSTORE]> skipping unreadable checkpoint %s: %v\", filename, err)\n\t\t\tcontinue\n\t\t}\n\n\t\tflattenCheckpointFile(cf, cluster, host, \"node\", \"\", rowChan)\n\t}\n\n\treturn files, nil\n}\n","numLines":244,"startLine":1,"totalLines":244}},"sourceToolAssistantUUID":"98c39255-0c74-4b80-bb95-b89ce1fcdb14","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
+{"parentUuid":"70268700-0562-475c-9bb1-8ac1d78195a4","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01XwUMDjqMRQDnzKopuDkkZb","type":"message","role":"assistant","content":[{"type":"text","text":"Two different approaches to the same problem. Here's how they compare:\n\n## Architecture: Batch-per-host (ours) vs Channel-streaming (tmp)\n\n### `flattenCheckpointFile`\n\n| | Ours (hotfix) | tmp |\n|---|---|---|\n| **Signature** | `(..., rows []ParquetMetricRow) []ParquetMetricRow` | `(..., rowChan chan<- *ParquetMetricRow)` |\n| **Mechanism** | Appends to a slice, returns it | Sends `*ParquetMetricRow` pointers to a channel |\n| **Allocation** | Struct values in a contiguous slice | One heap-allocated pointer per row |\n\n### Writer\n\n| | Ours (`parquetArchiveWriter`) | tmp (`writeParquetArchiveStream`) |\n|---|---|---|\n| **API** | Struct with `WriteHostRows()` + `Close()` | Single function consuming `<-chan *ParquetMetricRow` |\n| **SortingWriterConfig** | Removed | **Still present** (lines 116-121) |\n| **Row groups** | One per host (explicit `Flush()`) | One big row group (only `Close()` at end) |\n| **Sorting** | Pre-sorted in-place per host via `sort.Slice` | Delegated to `SortingWriterConfig` internally |\n| **Batching** | Entire host's rows at once | Fixed 4096-row batches from channel |\n\n### `archiveCheckpointsToParquet`\n\n| | Ours | tmp |\n|---|---|---|\n| **Returns** | `([]ParquetMetricRow, []string, error)` — rows + files | `([]string, error)` — files only |\n| **Pre-allocation** | `estimateRowCount()` → `make([]ParquetMetricRow, 0, n)` | No pre-allocation (rows go through channel) |\n| **Two-pass loading** | Yes: load all checkpoints, estimate, then flatten | No: single pass, streams directly to channel |\n\n## Key Differences\n\n**1. The tmp version still has the `SortingWriterConfig` problem.** It batches 4096 rows at a time into `writer.Write()`, but `SortingWriterConfig` buffers ALL written rows internally until `writer.Close()`. So despite the channel streaming, the sorting writer still accumulates every row in memory — the memory fix is incomplete.\n\n**2. Per-row heap allocation in tmp.** Each row is `&ParquetMetricRow{...}` sent as a pointer through the channel. For millions of rows this creates significant GC pressure vs our approach of contiguous slice values.\n\n**3. Our version creates proper row groups.** Each `WriteHostRows()` + `Flush()` creates a separate Parquet row group per host, enabling row-group skipping on read. The tmp version produces one monolithic row group.\n\n**4. Error handling on early failure.** The tmp version spawns goroutines to drain the channel if `MkdirAll` or `OpenFile` fails (lines 95-98, 104-107). Our version avoids this by opening the writer before starting workers (in `archive.go`).\n\n**5. Our version has `estimateRowCount` + pre-allocation** to avoid append doubling. The tmp version doesn't need this (no slice accumulation) but trades it for per-row channel send overhead.\n\n## Bottom line\n\nThe tmp version streams row-by-row through a channel (good for decoupling producer/consumer) but **defeats its own purpose** by keeping `SortingWriterConfig`, which buffers everything internally anyway. Our version removes `SortingWriterConfig`, pre-sorts per host, and writes proper row groups — actually solving the memory problem."}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7494,"cache_read_input_tokens":62663,"output_tokens":902,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":7494,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CZ9u36c2znfXfmD5yRam8","type":"assistant","uuid":"d8ffe716-42f7-4544-a617-bf35bbbd6a16","timestamp":"2026-03-18T04:16:14.406Z","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\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\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// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\nfunc archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}\n","structuredPatch":[{"oldStart":171,"oldLines":6,"newStart":171,"newLines":9,"lines":[" // Each host's rows are written as a separate row group to avoid accumulating"," // all data in memory at once."," func archiveCheckpoints(checkpointsDir, cleanupDir string, from int64) (int, error) {","+  cclog.Info(\"[METRICSTORE]> start archiving checkpoints to parquet\")","+  startTime := time.Now()","+","   clusterEntries, err := os.ReadDir(checkpointsDir)","   if err != nil {","     return 0, err"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"732b7b7e-93bb-4c15-821c-6f3e1731e33a","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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This file is part of cc-backend.\n// Use of this source code is governed by a MIT-style\n// license that can be found in the LICENSE file.\n\npackage 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\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\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// Each host's rows are written as a separate row group to avoid accumulating\n// all data in memory at once.\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// Stream per-host rows to parquet writer via worker pool\n\t\ttype hostResult struct {\n\t\t\trows  []ParquetMetricRow\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\tresults := make(chan hostResult, len(hostEntries))\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\trows, files, err := archiveCheckpointsToParquet(item.dir, cluster, item.host, 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(rows) > 0 {\n\t\t\t\t\t\tresults <- hostResult{rows: rows, files: files, dir: item.dir}\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 rows 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\tsortParquetRows(r.rows)\n\t\t\t\tif err := writer.WriteHostRows(r.rows); err != nil {\n\t\t\t\t\twriteErr = err\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\treturn totalFiles, nil\n}\n","structuredPatch":[{"oldStart":303,"oldLines":5,"newStart":303,"newLines":6,"lines":["       writer.count, totalFiles, cluster, parquetFile)","   }"," ","+  cclog.Infof(\"[METRICSTORE]> archiving checkpoints completed in %s (%d files)\", time.Since(startTime).Round(time.Millisecond), totalFiles)","   return totalFiles, nil"," }"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"34c20240-d48b-430e-946a-88831b45c4f0","userType":"external","cwd":"/Users/jan/prg/CC/cc-backend","sessionId":"0943a044-b17e-4215-8591-c1a0c816ddf0","version":"2.1.76","gitBranch":"hotfix","slug":"shimmering-wandering-flurry"}
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diff --git a/bf/29af79b268/0/metadata.json b/bf/29af79b268/0/metadata.json
new file mode 100644
index 00000000..f99016d3
--- /dev/null
+++ b/bf/29af79b268/0/metadata.json
@@ -0,0 +1,30 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "bf29af79b268",
+  "session_id": "0943a044-b17e-4215-8591-c1a0c816ddf0",
+  "strategy": "manual-commit",
+  "created_at": "2026-03-18T04:22:41.042241Z",
+  "branch": "hotfix",
+  "checkpoints_count": 2,
+  "files_touched": [
+    "pkg/metricstore/archive.go"
+  ],
+  "agent": "Claude Code",
+  "turn_id": "4178691e07bd",
+  "token_usage": {
+    "input_tokens": 38,
+    "cache_creation_tokens": 101668,
+    "cache_read_tokens": 1392819,
+    "output_tokens": 11761,
+    "api_call_count": 28
+  },
+  "initial_attribution": {
+    "calculated_at": "2026-03-18T04:22:40.9438Z",
+    "agent_lines": 4,
+    "human_added": 0,
+    "human_modified": 0,
+    "human_removed": 0,
+    "total_committed": 4,
+    "agent_percentage": 100
+  }
+}
diff --git a/bf/29af79b268/0/prompt.txt b/bf/29af79b268/0/prompt.txt
new file mode 100644
index 00000000..b0970f13
--- /dev/null
+++ b/bf/29af79b268/0/prompt.txt
@@ -0,0 +1,113 @@
+Implement the following plan:
+
+# Fix: Memory Escalation in flattenCheckpointFile (68GB+)
+
+## Context
+
+Production gops shows `flattenCheckpointFile` allocating 68GB+ (74.89% of memory). The archiving pipeline accumulates ALL metric data from ALL hosts into a single `[]ParquetMetricRow` slice before writing to Parquet. For large HPC clusters this is catastrophic. Additionally, the `SortingWriterConfig` in the parquet writer buffers everything again internally.
+
+## Root Cause
+
+Two-layer unbounded accumulation:
+
+1. **`archive.go:239-242`**: `allRows = append(allRows, r.rows...)` merges every host's rows into one giant slice
+2. **`parquetArchive.go:108-116`**: `SortingWriterConfig` creates a sorting writer that buffers ALL rows until `Close()`
+3. **`parquetArchive.go:199`**: `var rows []ParquetMetricRow` starts at zero capacity, grows via append doubling
+
+Peak memory = (all hosts' rows) + (sorting writer copy) + (append overhead) = ~3x raw data size.
+
+## Fix: Stream per-host to parquet writer
+
+Instead of accumulating all rows, write each host's data as a separate row group.
+
+### Step 1: Add streaming parquet writer (`parquetArchive.go`)
+
+Replace `writeParquetArchive(filename, rows)` with a struct that supports incremental writes:
+
+```go
+type parquetArchiveWriter struct {
+    writer *pq.GenericWriter[ParquetMetricRow]
+    bw     *bufio.Writer
+    f      *os.File
+    count  int
+}
+
+func newParquetArchiveWriter(filename string) (*parquetArchiveWriter, error)
+func (w *parquetArchiveWriter) WriteHostRows(rows []ParquetMetricRow) error  // Write + Flush (creates row group)
+func (w *parquetArchiveWriter) Close() error
+```
+
+- **Remove `SortingWriterConfig`** - no global sort buffer
+- Sort each host's rows in-place with `sort.Slice` before writing (cheap: single host data)
+- Each `Flush()` creates a separate row group per host
+
+### Step 2: Add row count estimation (`parquetArchive.go`)
+
+```go
+func estimateRowCount(cf *CheckpointFile) int
+```
+
+Pre-allocate `rows` slice in `archiveCheckpointsToParquet` to avoid append doubling per host.
+
+### Step 3: Restructure `archiveCheckpoints` (`archive.go`)
+
+Change from:
+```
+workers → channel → accumulate allRows → writeParquetArchive(allRows)
+```
+
+To:
+```
+open writer → workers → channel → for each host: sort rows, writer.WriteHostRows(rows) → close writer
+```
+
+- Only one host's rows in memory at a time
+- Track `files`/`dir` for deletion separately (don't retain rows)
+- Check `writer.count > 0` instead of `len(allRows) == 0`
+
+### Step 4: Update test (`parquetArchive_test.go`)
+
+- `TestParquetArchiveRoundtrip`: use new streaming writer API
+- Keep `archiveCheckpointsToParquet` returning rows (it's per-host, manageable size)
+
+## Files to Modify
+
+- **`pkg/metricstore/parquetArchive.go`**: Add `parquetArchiveWriter`, `estimateRowCount`; remove `writeParquetArchive`; add `"sort"` import
+- **`pkg/metricstore/archive.go`**: Restructure `archiveCheckpoints` to stream
+- **`pkg/metricstore/parquetArchive_test.go`**: Update roundtrip test
+
+## Memory Impact
+
+- **Before**: All hosts in memory (~40GB for 256 nodes) + sorting buffer (~40GB) = 68GB+
+- **After**: One host at a time (~16MB) + parquet page buffer (~1MB) = ~17MB peak
+
+## Sorting Tradeoff
+
+The output changes from one globally-sorted row group to N row groups (one per host), each internally sorted by (metric, timestamp). This is actually better for ClusterCockpit's per-host query patterns (enables row group skipping).
+
+## Verification
+
+```bash
+go test -v ./pkg/metricstore/...
+```
+
+Also verify with `go vet ./pkg/metricstore/...` for correctness.
+
+
+If you need specific details from before exiting plan mode (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/jan/.claude/projects/-Users-jan-prg-CC-cc-backend/71340843-de3d-4e83-9dcb-2fc130c50e0d.jsonl
+
+---
+
+Are the any other cases with memory spikes using the Parquet Writer, e.g. in the nodestate retention?
+
+---
+
+[Request interrupted by user for tool use]
+
+---
+
+Compare the archive writer implementation with @~/tmp/cc-backend/pkg/metricstore/parquetArchive.go . Compare and explain differences.
+
+---
+
+Add an Info logmessage in archiveCheckpoints that archving started and provide timing information how long it took.
\ No newline at end of file
diff --git a/bf/29af79b268/metadata.json b/bf/29af79b268/metadata.json
new file mode 100644
index 00000000..70520f78
--- /dev/null
+++ b/bf/29af79b268/metadata.json
@@ -0,0 +1,26 @@
+{
+  "cli_version": "0.4.8",
+  "checkpoint_id": "bf29af79b268",
+  "strategy": "manual-commit",
+  "branch": "hotfix",
+  "checkpoints_count": 2,
+  "files_touched": [
+    "pkg/metricstore/archive.go"
+  ],
+  "sessions": [
+    {
+      "metadata": "/bf/29af79b268/0/metadata.json",
+      "transcript": "/bf/29af79b268/0/full.jsonl",
+      "context": "/bf/29af79b268/0/context.md",
+      "content_hash": "/bf/29af79b268/0/content_hash.txt",
+      "prompt": "/bf/29af79b268/0/prompt.txt"
+    }
+  ],
+  "token_usage": {
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+    "output_tokens": 11761,
+    "api_call_count": 28
+  }
+}