Débogage des performances de base de données

VérifiéSûr

Déboguer les performances de base de données dans ettametta : requêtes lentes, pool de connexions, conflits de migration, patterns N+1 et dérive de schéma.

Spar Skills Guide Bot
DeveloppementIntermédiaire
2026/07/2026
Claude Code
#database#performance#postgresql#debugging#query-optimization

Recommandé pour

Notre avis

Ce skill fournit des commandes et des conseils pour diagnostiquer et résoudre les problèmes de performance de base de données dans le projet ettametta.

Points forts

  • Commandes concrètes pour inspecter les connexions, requêtes actives et tailles de tables
  • Couvre la configuration des connexions et les patterns de sessions (async, sync, Celery)
  • Identifie les risques N+1 et les index manquants

Limites

  • Spécifique au projet ettametta et à son schéma de base de données
  • Peut nécessiter des adaptations pour d'autres environnements
  • Ne couvre pas les optimisations avancées (requêtes complexes, index GIN/GIST)
Quand l'utiliser

Lors de l'analyse de requêtes lentes, d'épuisement du pool de connexions, de conflits de migration ou de patterns N+1.

Quand l'éviter

Pour des problèmes de performance non liés à la base de données, ou pour un réglage général de PostgreSQL sans contexte applicatif.

Analyse de sécurité

Sûr
Score qualité90/100

The skill provides read-only diagnostic SQL commands and environment inspection via docker compose, with no destructive operations or data exfiltration.

Aucun point d'attention détecté

Exemples

Diagnose slow queries
I'm experiencing slow performance in the application. Please run the database debugging commands from the db-performance skill to check active queries, connection count, and table sizes.
Check for N+1 problems
Analyze the query patterns in the routes/nexus.py file for potential N+1 issues using the db-performance skill.
Identify missing indexes
Review the database schema and suggest missing indexes based on the common issues listed in the db-performance skill.

name: db-performance description: Debug and troubleshoot database performance in ettametta. Use when investigating slow queries, connection pool issues, migration conflicts, N+1 patterns, or schema drift.

Database Performance Debugging

Quick Diagnostics

# Connection count
docker compose exec db psql -U postgres -c "SELECT count(*) FROM pg_stat_activity;"

# Active queries
docker compose exec db psql -U postgres -c "SELECT pid, now()-query_start AS duration, query FROM pg_stat_activity WHERE state='active' ORDER BY duration DESC;"

# Table sizes
docker compose exec db psql -U postgres -c "SELECT relname, n_live_tup, pg_size_pretty(pg_total_relation_size(relid)) FROM pg_stat_user_tables ORDER BY n_live_tup DESC;"

# Migration state
alembic heads
alembic current
alembic check

Connection Configuration

Async engine (FastAPI): pool_pre_ping=True, defaults pool_size=5, max_overflow=10

Sync engine (Celery): Default QueuePool, pool_size=5, max_overflow=10

Celery task-scoped: pool_size=2, max_overflow=0 (tight isolation)

NullPool for Celery workers: Fresh engine per call, disposed after use. Expensive but avoids event-loop conflicts.

Default DATABASE_URL: sqlite:///./data/db/ettametta.db. Production uses PostgreSQL.

Session Management

  • Pattern A (routes): get_db() dependency with rollback on exception
  • Pattern B (services): async_session_factory() inline
  • Pattern C (Celery): get_async_session() with NullPool

All use expire_on_commit=False, autocommit=False, autoflush=False.

Models

35 ORM models. Zero relationship() declarations — all cross-table access via explicit joins.

Key models: UserDB (7 unique indexes), ContentCandidateDB (external_id unique, niche, region), VideoJobDB, PublishedContentDB, ScheduledPostDB, SocialAccount.

Missing indexes (potential)

  • video_jobs.user_id
  • audit_logs.user_id
  • scheduled_posts.user_id
  • nexus_jobs.user_id

No composite indexes declared.

Migrations

20 migration files. Current HEAD: d410fb0d40a9. 2 merge migrations exist.

CI/CD bypasses Alembic: Deployment uses create_all() not alembic upgrade head.

Query Patterns

N+1 risks

  • Nexus stats: 4 separate COUNT(*) queries (lines 482-506 in routes/nexus.py). Fix: single GROUP BY.
  • Settings: 2 separate queries for system + user settings. Fix: join.

In-memory pagination

Discovery routes use paginate_list() — loads all then slices. Use SQL .offset().limit().

DateTime Monkeypatch

database.py lines 12-24: strips timezone info from DateTime. Workaround for SQLite/PG compat.

Common Issues

Connection pool exhaustion

docker compose exec db psql -U postgres -c "SELECT count(*) FROM pg_stat_activity;"

Stale connections

Async engine has pool_pre_ping=True. Sync engine does not.

NullPool performance

get_async_session() creates/disposes full engine per call. Expensive for high-frequency ops.

Missing composite indexes

Queries on multiple columns do sequential scans. Add Index() declarations.

expire_on_commit=False

Correct for async but means stale data if objects reused after commit without refresh.

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