👀 Views: 61 💬 Answers: 1 📅 Created: 2025-09-13

mysql performance indexing SQL

Currently developing a portfolio application that aggregates user profiles from multiple sources, and I’ve hit a roadblock with MySQL performance..... As user traffic grows, the queries for fetching and displaying user profiles are becoming increasingly slow. I've set up a basic schema with tables for `users`, `profiles`, and `user_activities`, and the initial setup works fine with a small dataset, but as I simulate more users, the lag becomes prominent. The query I’m using to retrieve user profiles looks something like this: ```sql SELECT u.id, u.name, p.bio, ua.activity_type FROM users u JOIN profiles p ON u.id = p.user_id LEFT JOIN user_activities ua ON u.id = ua.user_id WHERE u.status = 'active' ORDER BY u.created_at DESC LIMIT 10; ``` While this works, adding indexes has proven tricky. I tried indexing `user_id` in both `profiles` and `user_activities`, but execution times still seem off. I’ve considered using a caching layer with Redis to store frequently accessed profiles, but I’m unsure if that’s the best approach or if there are more effective indexing strategies I should explore. I've also read about the impact of `JOIN` queries on performance and wonder if denormalizing some of my data might be a path forward. Would love insights on how to best structure my queries and tables for scalability or if caching could significantly boost performance in this scenario. Perhaps a different indexing strategy could help as well? Any advice or resources would be greatly appreciated! Any help would be greatly appreciated!