I've been working on a web application for 2 months now, which has forced me to improve my knowledge of sql. It took some dedication to get more or less considerable results, so here are some tips for those who want to build more complex and efficient queries. 1. **Master the basics**: Before venturing into complex queries, make sure you have a good understanding of the basics of SQL, such as `SELECT`, `INSERT`, `UPDATE`, `DELETE`, `JOIN`, `GROUP BY`, `HAVING` and `WHERE`. 2. **Understand the Different Types of Joins**: Joins are the backbone of complex queries. Master the different types: - `INNER JOIN`: Combines common records between two tables. - `LEFT JOIN` (or `LEFT OUTER JOIN`): Returns all records from the table on the left, even if there is no match in the table on the right. - `RIGHT JOIN`: Similar to LEFT JOIN, but returns all records from the table on the right. - `FULL JOIN`: Returns records when there is a match in one of the tables. 3. **Use Subqueries and CTEs (Common Table Expressions)**: - **Subqueries**: These are queries within queries. They can be used to divide large problems into smaller parts. ```sql SELECT * FROM employees WHERE salary > (SELECT AVG(salary) FROM employees); ``` - **CTEs**: Provide a more readable and reusable way of structuring complex queries. They are defined with `WITH`. ```sql WITH HighEarners AS ( SELECT name, salary FROM employees WHERE salary > 5000 ) SELECT * FROM HighEarners; ``` 4. **Use aggregations intelligently**: Use functions such as `SUM()`, `AVG()`, `COUNT()`, `MIN()`, `MAX()` combined with `GROUP BY` to summarize data from large volumes of records. ```sql SELECT department, COUNT(employee_id), AVG(salary) FROM employees GROUP BY department; ``` 5. **Learn to Optimize Queries**: - **Use indexes**: Indexing frequently used columns in `WHERE` and `JOIN` can improve performance. - **Examine the execution plan**: Use the EXPLAIN command to see how the database processes your queries and identify bottlenecks. ```sql EXPLAIN SELECT * FROM employees WHERE salary > 5000; ``` 6. **Avoid Unnecessary Subqueries**: Whenever possible, prefer JOINs to subqueries, as JOINs tend to be more efficient in many cases. 7. **Familiarize yourself with Window Functions**: Window functions, such as `ROW_NUMBER()`, `RANK()`, `LEAD()`, and `LAG()`, allow for more advanced calculations without having to group results. This is useful in complex reports. ```sql SELECT name, salary, RANK() OVER (ORDER BY salary DESC) AS salary_rank FROM employees; ``` 8. **Divide and Conquer (Modular Query)**: When building a very complex query, split it into smaller parts using CTEs or temporary sub-queries, testing and tweaking each part separately before combining them. 9. **Know the Particularities of Your DBMS**: Different database systems (MySQL, PostgreSQL, Oracle, SQL Server) have specific syntaxes and optimizations. Study the DBMS you use to make the most of its features, such as specific functions or automatic optimizations. 10. **Test and Improve Your Queries with Real Data**: Work with large data sets to test the scalability of your queries. Practicing with real (or similar) data will allow you to identify performance bottlenecks that only appear in large volumes.