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Postgres Performance: From Slow to Pro with Elizabeth Christensen
Improve Postgres performance from slow to pro with expert tips on indexing, query analysis, connection pooling, and more.
- Indexing is crucial for query performance. You should consider creating indexes on frequently used fields.
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Understand how to analyze query performance using
EXPLAINplans. - Postgres 17 is coming soon and will offer improved performance.
- Pay attention to IOPS, as disk writes can be a major bottleneck.
- Shared buffers are important for query performance. Allocate a significant portion of your machine’s memory to shared buffers.
- Use a connection pooler like PgBouncer to manage connections and reduce overhead.
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Set a timeout for long-running queries using
SETstatements. - Consider creating hypothetical indexes for frequently used queries.
- Regularly vacuum and analyze your database to remove dead rows and improve performance.
- Maximize your database’s RAM usage to reduce IOPS.
- Consider using a tool like Django Silk to analyze and improve query performance.
- Database performance tuning can make a significant impact on application performance.
- Set aside time to deepen your understanding of Postgres performance tuning.
- Monitor your database’s performance regularly using tools like pgstat statements.
- Understand how to determine the correct amount of shared buffers for your machine.
- Always log queries and analyze their performance to identify bottlenecks.
- Use indexes to reduce the number of queries to your database.
- Ensure that your database has sufficient memory and CPU power.
- Consider using a third-party tool to monitor and analyze your database’s performance.
- Regularly update your database schema to ensure optimal query performance.
- Set a budget for database performance tuning and prioritize tasks accordingly.
- Postgres has a console that can help you debug and improve query performance.
- Keep an eye on your database’s disk space and adjust your auto-vacuum settings accordingly.