1. Use Indexes Wisely 📚
Indexes speed up data retrieval but can slow down write operations. Use them on columns frequently used in WHERE, JOIN, or ORDER BY clauses.
Tip: Avoid over-indexing. For example, if a column has low selectivity (e.g., a boolean field), indexing may not be beneficial.
2. Optimize Query Execution Plans 🧭
Analyze the EXPLAIN output to understand how your query is executed. Look for full table scans or missing indexes.
Key Metrics:
rows– Number of rows scannedtype– Join type (e.g.,ref,range,all)Extra– Warnings (e.g.,Using filesort)
3. Avoid SELECT * 🚫
Specify only the columns you need. This reduces data transfer and memory usage.
Example:
SELECT id, name FROM users WHERE status = 'active';
4. Use JOINs Effectively 🔗
Join tables on indexed columns and avoid Cartesian products. Use INNER JOIN for relevant data, and LEFT JOIN when needed.
Best Practice: Keep JOIN conditions simple and use EXPLAIN to verify performance.
5. Leverage Query Caching 🧊
Enable caching for frequently executed queries. Use SELECT ... FROM cache where applicable.
Note: Caching is not suitable for queries with dynamic parameters.
🌐 Expand Your Knowledge
For more advanced techniques, check our SQL Best Practices tutorial.
Images generated for illustrative purposes. Replace keywords with actual terms as needed.