PostgreSQL: How to Optimize Window Functions for Large Datasets in Version 14
Could someone explain I'm writing unit tests and Hey everyone, I'm running into an issue that's driving me crazy... I'm working with a large dataset in PostgreSQL 14 and running into performance issues when using window functions. My current query looks like this: ```sql SELECT id, amount, SUM(amount) OVER (PARTITION BY category ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total FROM sales WHERE date >= '2023-01-01'; ``` The `sales` table has over 1 million records, and the query takes several seconds to run. I have created an index on the `category` and `date` columns, but it doesn't seem to help much. I'm receiving a notice that the planner is considering a sequential scan, which I suspect is contributing to the slow performance. Additionally, I tried using `EXPLAIN ANALYZE` to understand the execution plan: ```sql EXPLAIN ANALYZE SELECT id, amount, SUM(amount) OVER (PARTITION BY category ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total FROM sales WHERE date >= '2023-01-01'; ``` The output shows that the sequential scan is indeed being used, and it mentions "Too many rows" in the cost estimates. Iām unsure how to rewrite this query or what additional indexes might improve performance. Any advice on optimizing this window function for large datasets would be greatly appreciated. I'm working on a service that needs to handle this. I'm using Sql 3.10 in this project. Thanks for your help in advance! I'm coming from a different tech stack and learning Sql. I'd be grateful for any help.