Database Indexing & Query Optimization
Strategies for optimizing database queries through proper indexing and schema design.
Index Types
B-Tree Index
- •Default for most databases (MySQL, PostgreSQL)
- •Balanced tree structure
- •Good for range queries and sorting
Hash Index
- •O(1) lookup for equality
- •Not suitable for range queries
- •Fast point lookups
Full-Text Index
- •Optimized for text search
- •Language-specific analysis
- •Used with text search queries
Spatial Index
- •R-tree, Quadtree for geographic data
- •Optimized for spatial queries
Composite Index
- •Multiple columns in one index
- •Column order matters (leftmost prefix)
Query Optimization Techniques
EXPLAIN Plans
sql
EXPLAIN ANALYZE SELECT * FROM users WHERE id = 1;
Index Selection
- •Look for WHERE clause columns
- •Consider JOIN conditions
- •Evaluate sorting/grouping columns
- •Check cardinality (selectivity)
Avoid Common Mistakes
- •Creating indexes on low-cardinality columns
- •Creating unused indexes
- •Over-indexing (write performance impact)
- •Not analyzing index usage
Performance Tuning
- •Analyze queries - Use EXPLAIN
- •Identify bottlenecks - Query profiling
- •Test thoroughly - Before/after metrics
- •Monitor regularly - Track performance changes
- •Denormalize carefully - Balance read vs write
- •Archive old data - Keep active data small
- •Partition tables - Handle large datasets
Schema Design
- •Normalization - Reduce redundancy
- •Appropriate data types - Use INT not VARCHAR for IDs
- •Foreign keys - Maintain referential integrity
- •Constraints - Enforce data quality
Tools & Commands
PostgreSQL:
sql
CREATE INDEX idx_users_email ON users(email); DROP INDEX idx_users_email; ANALYZE;
MySQL:
sql
EXPLAIN analyzer SELECT * FROM users WHERE email = 'test@example.com'; CREATE INDEX idx_email ON users(email);
References
- •PostgreSQL Index Documentation
- •MySQL Performance Tuning
- •Database Query Optimization Principles
- •Use the Index, Luke! (Free online book)