MySQL: implementing Indexing and Query Performance on Large Tables with Multiple Joins
I'm experiencing important performance degradation when running a query that involves multiple joins on a large table (over 1 million records) in MySQL 8.0. I've indexed the foreign keys and the columns that I'm filtering on, but the query still takes several seconds to execute. Here's the query I'm trying to run: ```sql SELECT a.id, a.name, b.details, c.status FROM table_a a JOIN table_b b ON a.b_id = b.id JOIN table_c c ON a.c_id = c.id WHERE a.active = 1 AND b.type = 'example' AND c.updated_at > NOW() - INTERVAL 30 DAY; ``` I've created indexes on `b.id`, `c.id`, `a.b_id`, and `a.c_id`, but when I check the execution plan using `EXPLAIN`, it still shows that it's performing a full table scan on `table_a`. I also tried using `ANALYZE TABLE` on `table_a` to update statistics, but that didn't seem to help either. The cardinality of the indexed columns is quite low, which I suspect could be contributing to the scenario. Additionally, I’ve checked the server configuration and ensured that the `innodb_buffer_pool_size` is set appropriately for my server's available RAM (it's around 2GB for my test environment). I don't have any foreign key constraints between these tables, which I thought could help with enforcing relationships but also might slow down inserts. Does anyone have suggestions on how to optimize this query further? Should I reconsider my indexing strategy or explore other query optimizations? Any insights would be greatly appreciated!