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Database Query Optimization Table of Contents Overview When to Use Quick Start Reference Guides Best Practices Overview Slow database queries are a common performance bottleneck. Optimization through indexing, efficient queries, and caching dramatically improves application performance. When to Use Slow response times High database CPU usage Performance regression New feature deployment Regular maintenance Quick Start Minimal working example: -- Analyze query performance EXPLAIN ANALYZE SELECT users.id, users.name, COUNT(orders.id) as order_count FROM users LEFT JOIN orders ON users.id = orders.user_id WHERE users.created_at > '2024-01-01' GROUP BY users.id, users.name ORDER BY order_count DESC; -- Results show: -- - Seq Scan (slow) vs Index Scan (fast) -- - Rows: actual vs planned (high variance = bad) -- - Execution time (milliseconds) -- Key metrics: -- - Sequential Scan: Full table read (slow) -- - Index Scan: Uses index (fast) -- - Nested Loop: Joins with loops -- - Sort: In-memory or disk sort Reference Guides Detailed implementations in the references/ directory: Guide Contents Query Analysis Query Analysis Indexing Strategy Indexing Strategy Query Optimization Techniques Query Optimization Techniques Optimization Checklist Optimization Checklist Best Practices ✅ DO Follow established patterns and conventions Write clean, maintainable code Add appropriate documentation Test thoroughly before deploying ❌ DON'T Skip testing or validation Ignore error handling Hard-code configuration values 1d:[
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