What is the optimal value of shared_buffers for your database? A use case of data-driven optimization based on database experiments
Founder of Postgres.ai.
Founder of #RuPostgres (PostgreSQL user group for Russian-speaking users, the second in size on Meetup.com, 2000+ members).
Russian press contact at PostgreSQL Global Development Group.
No video of the event yet, sorry!
What is the optimal value of shared_buffers for your database and workload? 8 GiB? Or 16? Is it worth using 70% of RAM if you run Postgres 11 on a server with 512 GiB of memory?
Of course, you might check dozens of various values of shared_buffers, right on production, but if your database is mission-critical for your business, it’s not what you want.
To find the optimal value, we will conduct database experiments. We’ll discuss:
- how to reproduce the production workload in the “lab” environment,
- how to reduce the amount of time of a single experimental run,
- what (latency? throughput? both? anything else?) and how we need to measure,
- how the optimal value depends on workload, and finally,
- how machine learning can help to predict the optimal value even without experiments!
During our journey to find the optimal shared_buffers value, we will use Nancy CLI — an open source framework we have built specifically to automate conducting numerous database experiments in a systematic way.
In the talk, we'll also dive into some technical details of shared buffers implementation in Postgres discussing why lower or higher shared_buffers values lead to much worse performance than one might expect.
- 2019 March 21 09:00 EDT
- 50 min
- Postgres Conference
- Use Cases