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postgres-concurrent-schema-init-deadlock

Fix PostgreSQL deadlock errors caused by concurrent schema initialization in worker processes. Use when: (1) psycopg2.errors.DeadlockDetected during CREATE INDEX/TABLE IF NOT EXISTS, (2) Multiple Cloud Run jobs, Kubernetes pods, or worker processes start simultaneously, (3) Error shows "Process X waits for RowExclusiveLock... blocked by process Y", (4) init_schema() or migration code runs at worker startup. The key insight: "IF NOT EXISTS" is NOT truly concurrent-safe - PostgreSQL still acquires locks that can deadlock.

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PostgreSQL Concurrent Schema Init Deadlock

Problem

Multiple worker processes (Cloud Run jobs, K8s pods, serverless functions) starting simultaneously all try to run schema initialization code, causing PostgreSQL deadlocks even when using "IF NOT EXISTS" clauses.

Context / Trigger Conditions

  • Error: psycopg2.errors.DeadlockDetected: deadlock detected
  • Log shows: Process X waits for RowExclusiveLock on relation... blocked by process Y
  • Multiple workers/jobs starting at roughly the same time
  • Each worker calls init_schema() or runs migrations at startup
  • Using CREATE TABLE IF NOT EXISTS or CREATE INDEX IF NOT EXISTS

Why This Happens

PostgreSQL's IF NOT EXISTS is not concurrent-safe:

  1. CREATE INDEX IF NOT EXISTS still acquires locks before checking existence
  2. Multiple processes acquiring locks on different objects can deadlock
  3. Even "safe" DDL can conflict when executed concurrently

Solution

Option 1: Skip Init in Production (Recommended)

Schema already exists - don't run init_schema() in workers:

with Database() as db:
    # Schema already exists in production - skip to avoid deadlocks
    # db.init_schema()

    # ... worker code

Option 2: Use Advisory Locks

Serialize schema init with PostgreSQL advisory locks:

def init_schema_safe(self):
    cursor = self._cursor()
    # Acquire advisory lock (blocks other processes)
    cursor.execute("SELECT pg_advisory_lock(12345)")
    try:
        self.init_schema()
    finally:
        cursor.execute("SELECT pg_advisory_unlock(12345)")
        self.conn.commit()

Option 3: Separate Migration Step

Run migrations as a separate job before starting workers:

# In deployment pipeline
python -m src.migrate  # Single process, runs first
# Then start workers
gcloud run jobs execute worker-job

Option 4: Lock Timeout + Retry

Set lock timeout and retry on deadlock:

def init_schema_with_retry(self, max_retries=3):
    for attempt in range(max_retries):
        try:
            cursor = self._cursor()
            cursor.execute("SET lock_timeout = '5s'")
            self.init_schema()
            return
        except psycopg2.errors.DeadlockDetected:
            self.conn.rollback()
            if attempt == max_retries - 1:
                raise
            time.sleep(random.uniform(1, 3))

Verification

After applying fix:

  1. Start multiple workers simultaneously
  2. Check logs for absence of deadlock errors
  3. Verify all workers start successfully

Example

Before (deadlocks with 6 concurrent Cloud Run jobs):

# src/download.py
with VineDatabase() as db:
    db.init_schema()  # DEADLOCK when multiple jobs start!
    # ... download logic

After (no deadlocks):

# src/download.py
with VineDatabase() as db:
    # Schema already exists in production - skip to avoid deadlocks
    # db.init_schema()
    # ... download logic

Notes

  • This applies to any concurrent worker pattern: Cloud Run, Celery, Kubernetes, Lambda
  • The deadlock can be intermittent - depends on exact timing of worker starts
  • CREATE TABLE IF NOT EXISTS is generally safer than CREATE INDEX IF NOT EXISTS
  • Cloud Run jobs often start simultaneously when triggered, making this common
  • Consider using database migration tools (Alembic, Flyway) with proper locking

References

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