Table Partitioning
Divide large tables into smaller, more manageable pieces..
💡 Query performance optimization is critical for applications that handle large datasets.
Key Concepts
| Concept | Description |
|---|---|
| Indexing | Speed up data retrieval with proper indexes |
| Query Plans | Understand how the database executes your query |
| Table Design | Normalize data and choose appropriate data types |
| Partitioning | Split large tables into manageable chunks |
| Caching | Reduce database load with result caching |
Example
-- Check query performance (PostgreSQL)
EXPLAIN ANALYZE
SELECT c.first_name, SUM(o.total) as total_spent
FROM customers c
INNER JOIN orders o ON c.id = o.customer_id
WHERE o.order_date >= '2024-01-01'
GROUP BY c.id, c.first_name;
✅ Key Takeaways
- Use EXPLAIN ANALYZE to understand query execution
- Create indexes on columns used in WHERE and JOIN
- Avoid SELECT * in production queries
- Monitor slow queries with database logs
- Test performance with realistic data volumes