How to Fix Database Deadlock in AI-Built Apps

Concurrent database operations cause deadlocks, hanging requests and eventually timing out. AI-generated transaction code often acquires locks in inconsistent order or holds transactions open too long.

Error messages you might see

ERROR: deadlock detected. Process 1234 waits for ShareLock on transaction 5678
Error: canceling statement due to lock timeout

Why this happens in AI-generated code

1

Inconsistent lock ordering

Different code paths lock tables in different orders, creating circular wait conditions.

2

Long-running transactions

AI wraps too many operations in a single transaction, holding locks while doing slow I/O like API calls.

3

Missing row-level locking strategy

AI uses table-level locks or SELECT FOR UPDATE without proper WHERE clauses, locking more rows than needed.

How to fix it

1

Always lock tables in the same order

Establish a convention for lock ordering (e.g., alphabetical by table name) and follow it in all transactions.

2

Keep transactions short

Move non-database work outside transactions. Only include the minimum SQL operations needed for data consistency.

3

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Frequently asked questions

How do I detect deadlocks?

Monitor Postgres logs for 'deadlock detected' messages. Enable `log_lock_waits` to see which queries are waiting for locks.

Will retrying the transaction fix the deadlock?

Yes, Postgres automatically aborts one deadlocked transaction. Retrying with exponential backoff is the standard recovery strategy.

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