How does SQLite's indexing mechanism affect query performance?

SQLite's indexing mechanism has a significant impact on query performance:

1. Index Types

   • B-Tree Index: Default index type, suitable for range queries and sorting
   • Hash Index: Only available in in-memory databases, suitable for equality queries
   • R-Tree Index: Used for spatial data, supports geographic information queries
   • Full-Text Index (FTS): Used for full-text search functionality

2. Index Creation

   sql
   -- Create single column index
   CREATE INDEX idx_name ON table_name(column_name);
   
   -- Create composite index
   CREATE INDEX idx_composite ON table_name(col1, col2);
   
   -- Create unique index
   CREATE UNIQUE INDEX idx_unique ON table_name(column_name);

3. Index Usage Principles

   • Create indexes on columns frequently used in WHERE clauses, JOIN conditions, ORDER BY, GROUP BY
   • Columns with high selectivity (many unique values) are more suitable for indexing
   • Avoid creating indexes on small tables
   • Composite indexes follow the leftmost prefix principle

4. Index Optimization Techniques

   • Use EXPLAIN QUERY PLAN to analyze query execution plans
   • Avoid using functions or expressions on indexed columns
   • Using LIKE 'prefix%' can utilize indexes, LIKE '%suffix' cannot
   • Reasonably use covering indexes to avoid table lookups

5. Index Maintenance

   • Indexes add overhead to INSERT, UPDATE, DELETE operations
   • Regularly use the ANALYZE command to update statistics
   • Use REINDEX to rebuild fragmented indexes
   • Delete unused indexes to save space and improve write performance

6. Primary Keys and Auto Indexes

   • Declaring PRIMARY KEY when creating a table automatically creates a unique index
   • UNIQUE constraints also automatically create indexes
   • WITHOUT ROWID tables can avoid creating hidden rowid indexes

Proper use of indexes can significantly improve query performance, but requires finding a balance between query performance and write performance.