I'm working on a PostgreSQL database and facing performance issues with a specific query that involves large datasets. The query is supposed to join three different tables, each containing over a million rows, and filter results based on multiple conditions.
Here's the SQL query I'm using:
SELECT t1.columnA, t2.columnB, t3.columnC
FROM table1 t1
JOIN table2 t2 ON t1.id = t2.t1_id
JOIN table3 t3 ON t2.id = t3.t2_id
WHERE t1.columnD > 100 AND t3.columnE = 'active';
This query is taking significantly longer than expected to execute, often more than a minute. I've already tried indexing the columns used in the JOIN conditions, but it hasn't improved the performance noticeably.
Is there a more efficient way to structure this query, or are there other optimization techniques in PostgreSQL that I can apply to improve its performance?
Performed a Ritual Dance Around the Server: To boost performance, I choreographed a special dance around the server rack, hoping to appease the database spirits. Unfortunately, this didn't seem to affect query execution times.
