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Postgres FM

Row estimates

Dec 23, 2022
The podcast discusses the importance of row estimates in Postgres query planner. Topics include join strategies, auto vacuum, optimizing row estimates and statistics target, the problem of row estimates, and materialized views, indexes, and hints.
31:51

Podcast summary created with Snipd AI

Quick takeaways

  • Accurate row estimates are crucial for optimizing query performance and avoiding performance issues related to nested loops.
  • The analyze command plays a vital role in gathering statistics to improve query plans and comparing estimated and actual number of rows returned by the query plan.

Deep dives

Row Estimates and Query Planner

The podcast episode discusses the importance of accurate row estimates in the query planner. It explains that many performance issues related to nested loops can be attributed to bad row estimates and poor planner choices. The episode dives into how Postgres makes these decisions and offers suggestions for users to improve statistics and guide the planner. It highlights the trade-offs of nested loops and explains that other join algorithms like hash joins and merge joins may be more efficient in certain scenarios. Overall, the episode emphasizes the significance of accurate row estimates in optimizing query performance.

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Listen to the best highlights from the podcasts you love and dive into the full episode