Database Deadlock Detector
Overview
Detect, analyze, and prevent database deadlocks in PostgreSQL, MySQL, and MongoDB by examining lock wait graphs, parsing deadlock log entries, identifying the application code paths that cause lock ordering conflicts, and implementing preventive patterns.
Prerequisites
- Database credentials with access to lock monitoring views (
pglocks, INNODBLOCK_WAITS)
psql or mysql CLI for executing diagnostic queries- PostgreSQL:
loglockwaits = on and deadlock_timeout = 1s configured
- MySQL:
innodbprintall_deadlocks = ON for deadlock logging to error log
- Access to database error logs for deadlock event parsing
- Application source code access for identifying lock-inducing code paths
Instructions
- Check for currently blocked transactions and their blockers:
- PostgreSQL:
SELECT blocked.pid AS blockedpid, blocked.query AS blockedquery, blocking.pid AS blockingpid, blocking.query AS blockingquery FROM pgstatactivity blocked JOIN pglocks bl ON bl.pid = blocked.pid JOIN pglocks bl2 ON bl2.locktype = bl.locktype AND bl2.relation = bl.relation AND bl2.pid != bl.pid JOIN pgstatactivity blocking ON blocking.pid = bl2.pid WHERE NOT bl.granted
- MySQL:
SELECT * FROM informationschema.INNODBLOCK_WAITS
- Parse recent deadlock events from database logs:
- PostgreSQL: Search logs for
ERROR: deadlock detected entries, which include the two conflicting queries and the lock types
- MySQL: Run
SHOW ENGINE INNODB STATUS\G and examine the LATEST DETECTED DEADLOCK section
- Extract: transaction IDs, queries involved, tables and rows locked, and which transaction was rolled back
- Construct the lock wait graph from the deadlock log. Map which transaction held which lock and which lock each transaction was waiting for. The circular dependency reveals the deadlock cycle. Identify the specific rows or index ranges involved.
- Trace the deadlocking queries back to application code. Use Grep to find the SQL statements in the codebase and identify the transaction boundaries (
BEGIN/COMMIT blocks or ORM transaction decorators). Map the full sequence of operations within each transaction.
- Identify the root cause pattern:
- Opposite lock ordering: Transaction A locks row 1 then row 2; Transaction B locks row 2 then row 1. Fix by ensuring consistent lock ordering.
- Index gap locks (MySQL): UPDATE/DELETE on non-existent rows creates gap locks that conflict. Fix by adding the target row first or using
