Optimizing

1. Indexes

- Use appropriate indexes for frequently queried columns

- Be mindful of index overhead - too many indexes can slow down writes

- Consider covering indexes for queries that only need indexed columns

- Use composite indexes effectively based on query patterns

2. Query Structure

- Avoid SELECT * when you only need specific columns

- Use JOINs efficiently and minimize unnecessary joins

- Consider query execution order (FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY)

- Use EXISTS instead of IN for better performance with subqueries

- Minimize the use of DISTINCT when possible

3. WHERE Clause Optimization

- Place most restrictive conditions first

- Avoid functions on indexed columns as they prevent index usage

- Use appropriate operators (=, IN, BETWEEN rather than OR when possible)

- Consider index usage when using wildcards in LIKE conditions

4. Data Types

- Use appropriate data types for columns

- Keep consistent data types in JOIN conditions

- Consider storage and performance implications of chosen data types

5. Database Design

- Proper normalization/denormalization based on use case

- Partitioning for large tables when appropriate

- Efficient primary key design

6. Query Analysis

- Use EXPLAIN/EXPLAIN ANALYZE to understand query execution plans

- Monitor query performance metrics

- Look for table scans vs index scans

7. Caching

- Implement appropriate caching strategies

- Consider materialized views for complex queries

- Use temp tables or CTEs for complex intermediate results