Diagnosing Database Hangs During Long-Running Loads

You're facing a common issue where long-running command line operations are causing timeouts for other database operations. Your suspicion about atomic transactions could be correct. Here are several strategies to diagnose the problem:

Database Monitoring Tools

1. Query the active transactions:

   SQLCopied
   -- For PostgreSQL
   SELECT pid, now() - xact_start AS duration, query
   FROM pg_stat_activity
   WHERE state = 'active'
   ORDER BY duration DESC;
   
   -- For MySQL
   SELECT trx_id, trx_started, trx_mysql_thread_id, trx_query
   FROM information_schema.innodb_trx
   ORDER BY trx_started;

2. Check for locks:

   SQLCopied
   -- PostgreSQL
   SELECT blocked_locks.pid AS blocked_pid,
          blocking_locks.pid AS blocking_pid,
          blocked_activity.query AS blocked_query,
          blocking_activity.query AS blocking_query
   FROM pg_catalog.pg_locks blocked_locks
   JOIN pg_catalog.pg_locks blocking_locks ON blocking_locks.locktype = blocked_locks.locktype
   JOIN pg_catalog.pg_stat_activity blocked_activity ON blocked_activity.pid = blocked_locks.pid
   JOIN pg_catalog.pg_stat_activity blocking_activity ON blocking_activity.pid = blocking_locks.pid
   WHERE NOT blocked_locks.granted AND blocking_locks.granted;

Application-Level Solutions

1. Break down large transactions: Instead of one large atomic transaction, consider breaking the load into smaller chunks.

2. Use explicit transaction management:

   PYTHONCopied
   # Example in Python
   try:
      # Process batch of 100 records
      db.commit()
   except Exception as e:
      db.rollback()
      log_error(e)

3. Implement connection timeouts: Set reasonable timeouts for your database connections.

System-Level Diagnostics

1. Database profiling: Enable query logging temporarily to see what's happening.

2. System resource monitoring: Use tools like top, htop, or iostat to check if the system is CPU or I/O bound.

3. Database connection pooling: Check if you're hitting connection limits.

Specific Recommendations

1. Review your transaction isolation level - consider using READ COMMITTED instead of SERIALIZABLE for long-running processes.

2. Implement a "maintenance mode" for large operations that might affect user-facing features.

3. Schedule intensive operations during off-peak hours.

4. Consider implementing a job queue system for long-running tasks instead of direct execution.

These approaches should help you identify what's causing the database hangs during your long-running loads.