PostgresSQL Fine-Tuning

PostgreSQL is a powerful relational database management system, but it requires careful configuration to perform optimally, especially when dealing with high workloads and tables with frequent row deletions. In this guide, we’ll discuss some best practices and recommended settings to ensure PostgreSQL can efficiently manage your data and prevent unexpected downtime.

Fine-Tuning Recommendations

1. Adjust Vacuuming Parameters

PostgreSQL uses a process called “vacuuming” to reclaim space and improve performance. Use the following settings for high-update and -delete-rate tables:

  • fillfactor = 0.5: This setting reserves space within pages for future updates, reducing index bloat.
  • autovacuum_vacuum_threshold = 250000: Lower this threshold to trigger vacuum more frequently.
  • autovacuum_vacuum_scale_factor = 0: Disable scale factor-based vacuum scheduling.

These settings encourage “HOT” updates, keeping index updates in check and controlling index bloat. However, remember that modifying these parameters may require additional autovacuum workers.

2. Increase Autovacuum Workers

When you modify storage parameters for specific tables, PostgreSQL may need more autovacuum workers to keep up with the increased workload. Increase autovacuum_max_workers by the number of tables you’ve modified with new storage parameters. For example, if you modified three tables, add three workers to the current value. Ensure that maintenance_work_mem is set to an appropriate value, ideally no more than 1GB.

3. Regularly Monitor Bloat

To prevent issues, it’s crucial to monitor table and index bloat in PostgreSQL. Implement a monitoring system that can use Nagios-compatible plugins, such as This tool allows you to regularly check for bloat and take corrective actions when necessary.

4. Set a Schedule for pg_repack

For large tables and busy systems, consider scheduling the use of pg_repack weekly during your lowest traffic periods. pg_repack helps you reclaim space by reorganizing tables without causing downtime.