Server is under high load from multiple concurrent queries. Temporary files or WAL logs consuming all available disk space. Memory exhaustion from large sort or hash operations

Step 1: Check server disk, memory, and CPU: `df -h`, `free -m`, `top`.. Step 2: Review PostgreSQL logs for more specific resource errors.. Step 3: Cancel long-running queries: `SELECT pg_cancel_backend(pid) FROM pg_stat_activity WHERE state='active' AND duration > interval '10 minutes';`. Step 4: Increase `work_mem` or `max_wal_size` if the issue is memory or WAL-related.

Critical severitycapacity

Power BI Refresh Error:
53000

What does this error mean?

PostgreSQL could not complete the operation due to insufficient server resources (generic resource exhaustion error).

Common causes

1Server is under high load from multiple concurrent queries
2Temporary files or WAL logs consuming all available disk space
3Memory exhaustion from large sort or hash operations

How to fix it

1Step 1: Check server disk, memory, and CPU: `df -h`, `free -m`, `top`.
2Step 2: Review PostgreSQL logs for more specific resource errors.
3Step 3: Cancel long-running queries: `SELECT pg_cancel_backend(pid) FROM pg_stat_activity WHERE state='active' AND duration > interval '10 minutes';`
4Step 4: Increase `work_mem` or `max_wal_size` if the issue is memory or WAL-related.

Frequently asked questions

How do I prevent 53000 errors in automated pipelines?

Add retry logic with exponential backoff, validate data quality before loading, and monitor pipeline failures in MetricSign to catch this error early.

Official documentation: https://www.postgresql.org/docs/current/errcodes-appendix.html