How to reduce WAL by increasing checkpoint distance in PostgreSQL?

In PostgreSQL, the WAL (Write-Ahead Logging) is a critical component of the database system that ensures durability and consistency of data. However, frequent WAL writes can impact the performance of the database, especially if the checkpoint distance is set to a low value. Here are some steps to reduce WAL by increasing the checkpoint distance:

  1. Check the current checkpoint distance: You can check the current checkpoint distance by running the following command in the PostgreSQL command-line interface (psql):

This will display the current checkpoint distance as a percentage of the total time between checkpoints. The default value is usually 0.5, which means that the checkpoint will occur when half of the time between checkpoints has elapsed.

  1. Increase the checkpoint distance: You can increase the checkpoint distance by setting the checkpoint_completion_target parameter in the postgresql.conf file. For example, to set the checkpoint distance to 0.9, you can add the following line to the file:

This will increase the time between checkpoints, which will reduce the frequency of WAL writes.

  1. Monitor the impact: After changing the checkpoint distance, you should monitor the impact on the database performance and adjust the value as necessary. If the checkpoint distance is set too high, it could cause the database to become unresponsive or crash in the event of a system failure.
  2. Tune other parameters: In addition to the checkpoint_completion_target parameter, there are other parameters that can be tuned to reduce WAL writes and improve database performance. For example, you can increase the shared_buffers parameter to reduce disk I/O, or adjust the autovacuum settings to reduce the number of unnecessary writes.

By following these steps, you can reduce the frequency of WAL writes and improve the performance of your PostgreSQL database.

About Shiv Iyer 443 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.