How to use SQLite's Full-Text Search (FTS) functionality?

SQLite's Full-Text Search (FTS) functionality provides efficient text search capabilities:

1. FTS Extension Modules

   • SQLite provides three versions: FTS3, FTS4, FTS5
   • FTS5 is the latest version with the most powerful features
   • Need to enable corresponding extensions during compilation

2. Creating FTS Tables

   sql
   -- Create full-text search table using FTS5
   CREATE VIRTUAL TABLE articles_fts USING fts5(title, content);
   
   -- Create full-text search table using FTS4
   CREATE VIRTUAL TABLE articles_fts USING fts4(title, content);

3. Inserting Data

   sql
   -- Insert data into FTS table
   INSERT INTO articles_fts (title, content) 
   VALUES ('SQLite Tutorial', 'SQLite is a lightweight database...');

4. Full-Text Search Queries

   sql
   -- Simple search
   SELECT * FROM articles_fts WHERE articles_fts MATCH 'SQLite';
   
   -- Phrase search
   SELECT * FROM articles_fts WHERE articles_fts MATCH '"lightweight database"';
   
   -- Boolean search
   SELECT * FROM articles_fts WHERE articles_fts MATCH 'SQLite AND database';
   
   -- Prefix search
   SELECT * FROM articles_fts WHERE articles_fts MATCH 'data*';

5. FTS5 Advanced Features

   • External Content Table: Associate FTS table with regular table

   sql
   CREATE TABLE articles(id, title, content);
   CREATE VIRTUAL TABLE articles_fts USING fts5(title, content, content='articles', content_rowid='id');

   • Trigger Auto-Sync: Use triggers to keep FTS table synchronized with source table
   • Ranking Function: Use bm25() function for result ranking

6. Performance Optimization

   • Create FTS indexes for large documents
   • Use batch inserts to improve performance
   • Regularly optimize FTS tables

   sql
   INSERT INTO articles_fts(articles_fts) VALUES('optimize');

7. Use Cases

   • Document search systems
   • Log analysis
   • Product search
   • Content management systems
   • Code search

FTS functionality enables SQLite to handle complex text search requirements and is an important tool for building search features.