sql-optimization-patternslisted

# SQL Optimization Patterns Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis. ## When to Use This Skill - Debugging slow-running queries - Designing performant database schemas - Optimizing application response times - Reducing database load and costs - Improving scalability for growing datasets - Analyzing EXPLAIN query plans - Implementing efficient indexes - Resolving N+1 query problems ## Core Concepts ### 1. Query Execution Plans (EXPLAIN) Understanding EXPLAIN output is fundamental to optimization. **PostgreSQL EXPLAIN:** ```sql -- Basic explain EXPLAIN SELECT * FROM users WHERE email = 'user@example.com'; -- With actual execution stats EXPLAIN ANALYZE SELECT * FROM users WHERE email = 'user@example.com'; -- Verbose output with more details EXPLAIN (ANALYZE, BUFFERS, VERBOSE) SELECT u.*, o.order_total FROM users u JOIN orders o ON u.id = o.user_id WHERE u.created_at > NOW() - INTERVAL '30 days'; ``` **Key Metrics to Watch:** - **Seq Scan**: Full table scan (usually slow for large tables) - **Index Scan**: Using index (good) - **Index Only Scan**: Using index without touching table (best) - **Nested Loop**: Join method (okay for small datasets) - **Hash Join**: Join method (good for larger datasets) - **Merge Join**: Join method (good for sorted data) - **Cost**: Estimated query cost (lower is better) - **Rows**: Estimated rows returned - **Actual Time**: Real execution time