Tell me more about your experience in database optimization.

Database optimization is a set of measures aimed at improving query performance and reducing server load.

In my experience, I applied the following approaches:

• Analyzing and optimizing SQL queries: rewriting complex queries, using JOINs instead of subqueries, adding necessary indexes.
• Indexing: creating composite and covering indexes to speed up data retrieval.
• Normalization and denormalization: balancing data structure for optimal speed and convenience.
• Caching: implementing caching of frequently requested data at the application level or using Redis.
• Profiling: using tools like EXPLAIN, slow query logs to identify bottlenecks.

Example of query optimization:

// Before:
SELECT * FROM orders WHERE user_id = ? AND status = 'active';

// Added index on (user_id, status) to speed up retrieval
// And rewritten the query to select only necessary fields:
SELECT id, order_date, total FROM orders WHERE user_id = ? AND status = 'active';

This approach significantly reduced response time and database load.