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I’m working on a PostgreSQL database with multiple tables, each containing millions of rows. Some of my queries with multiple joins are running slower than expected, and I want to identify the root cause using the EXPLAIN and ANALYZE tools.

Specifically, I’d like to understand:

  • What should I look for in the output of EXPLAIN and ANALYZE to detect inefficiencies in join operations?
  • How can I interpret cost estimates and row counts for each step of the query plan?
  • Are there common patterns or red flags in the query plan that indicate the need for indexing or restructuring the query?

**Here’s a simplified version of one of my queries: ** SELECT a.name, b.detail FROM table_a a JOIN table_b b ON a.id = b.a_id WHERE a.status = 'active';

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I look for four things:

  • Row count mis-estimates in the EXPLAIN (ANALYZE) output. If there is a factor of ten or more between the estimated and the real row count, that is a sign of trouble. Try to improve the estimates.

  • Execution plan nodes that take a lot of time. If you speed them up, you will gain. You have to subtract the lower nodes from the higher ones to get the net time. Don't forget to multiply with the loops count!

  • The total buffers used in the EXPLAIN (ANALYZE, BUFFERS) output. Again, you have to subtract the lower nodes. I consider the buffers count the "footprint" of the query. Try to get it down, and you will win.

  • Check for excessive "rows removed by filter". A better index will usually improve the performance.

There are other things, like "heap fetches" and temporary buffers, but the above is the most important stuff.

Using a plan analysis tool like https://explain.depesz.com will make the analysis much easier.

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