PostgreSQL performance implementing large JOINs and GROUP BY on indexed columns
I tried several approaches but none seem to work... I'm currently experiencing important performance degradation when executing a query that involves large JOINs and a GROUP BY clause in PostgreSQL 13.1. The query looks something like this: ```sql SELECT a.id, COUNT(b.id) as b_count FROM table_a a JOIN table_b b ON a.id = b.a_id WHERE a.status = 'active' GROUP BY a.id; ``` Both `table_a` and `table_b` have indexes on the columns used in the JOIN condition and the GROUP BY clause. However, when I execute the query, it takes over 30 seconds to complete, and I often see a lot of disk I/O activity. I have tried analyzing the tables and running `VACUUM ANALYZE` to refresh the statistics, but it hasn't helped. I also checked the execution plan using `EXPLAIN ANALYZE` and noted that the sequential scan on `table_b` seems to be the bottleneck. Here’s a snippet of the output: ```plaintext Seq Scan on table_b b (cost=0.00..24487.00 rows=1000000 width=8) (actual time=0.057..15024.156 rows=1000000 loops=1) Filter: (a_id = ANY ($1)) Buffers: shared hit=12 read=123456 Planning Time: 0.132 ms Execution Time: 15024.297 ms ``` I've indexed the `a_id` column in `table_b`, but it still opts for a sequential scan. Is there something I'm missing in my query or a better way to structure it for performance? Should I consider using CTEs or perhaps partitioning the tables? Any guidance or optimization strategies would be greatly appreciated! Has anyone else encountered this?