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Query Optimization

Learn how to optimize your queries for maximum performance in ReifyDB.

Understanding Query Plans​

ReifyDB's query optimizer automatically analyzes your queries and chooses the most efficient execution plan. You can view the query plan using the EXPLAIN command:

EXPLAIN SELECT * FROM users WHERE email LIKE '%@example.com';

Indexing Strategies​

Creating Indexes​

Indexes are crucial for query performance. Create indexes on columns frequently used in WHERE, JOIN, and ORDER BY clauses:

CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_posts_user_id ON posts(user_id);

Composite Indexes​

For queries filtering on multiple columns, composite indexes can be more efficient:

CREATE INDEX idx_users_name_email ON users(name, email);

Unique Indexes​

Use unique indexes to enforce uniqueness and improve lookup performance:

CREATE UNIQUE INDEX idx_users_email_unique ON users(email);

Query Optimization Tips​

1. Use Specific Column Names​

Instead of using SELECT *, specify only the columns you need:

-- Less efficient
SELECT * FROM users;

-- More efficient
SELECT id, name, email FROM users;

2. Optimize JOIN Operations​

  • Always join on indexed columns
  • Use appropriate join types (INNER, LEFT, RIGHT)
  • Filter data before joining when possible
-- Efficient join with indexed columns
SELECT u.name, COUNT(p.id) as post_count
FROM users u
INNER JOIN posts p ON u.id = p.user_id
WHERE p.published = true
GROUP BY u.id, u.name;

3. Use LIMIT for Large Result Sets​

When you don't need all results, use LIMIT to reduce data transfer:

SELECT * FROM posts
ORDER BY created_at DESC
LIMIT 10;

4. Avoid Leading Wildcards​

Leading wildcards in LIKE patterns prevent index usage:

-- Cannot use index
SELECT * FROM users WHERE email LIKE '%@example.com';

-- Can use index
SELECT * FROM users WHERE email LIKE 'john%';

5. Use EXISTS Instead of IN for Subqueries​

For large subqueries, EXISTS is often more efficient:

-- Using EXISTS (more efficient for large datasets)
SELECT * FROM users u
WHERE EXISTS (
  SELECT 1 FROM posts p 
  WHERE p.user_id = u.id AND p.published = true
);

Monitoring Performance​

Query Statistics​

ReifyDB provides statistics about query performance:

-- View query statistics
SELECT * FROM pg_stat_statements
ORDER BY total_time DESC
LIMIT 10;

Slow Query Log​

Enable slow query logging to identify problematic queries:

SET log_min_duration_statement = 1000; -- Log queries taking > 1 second

Caching Strategies​

Result Caching​

ReifyDB automatically caches frequently accessed data. You can also use materialized views for complex queries:

CREATE MATERIALIZED VIEW user_post_counts AS
SELECT u.id, u.name, COUNT(p.id) as post_count
FROM users u
LEFT JOIN posts p ON u.id = p.user_id
GROUP BY u.id, u.name;

-- Refresh the materialized view
REFRESH MATERIALIZED VIEW user_post_counts;

Best Practices​

  1. Regular Maintenance: Run ANALYZE regularly to update statistics
  2. Monitor Index Usage: Check which indexes are being used
  3. Partition Large Tables: Consider partitioning for very large tables
  4. Use Connection Pooling: Reduce connection overhead
  5. Batch Operations: Group multiple operations when possible

Conclusion​

Query optimization is an iterative process. Start with proper indexing, monitor your query performance, and adjust based on actual usage patterns.