A SELECT statement retrieves data from a database and consists of several core components. The most basic structure includes the SELECT clause, which specifies the columns to return, and the FROM clause, which identifies the table or tables to query. For example, SELECT name, age FROM users; retrieves the name and age columns from the users table. Optional clauses like WHERE add conditions to filter rows: SELECT * FROM users WHERE age > 30; returns all columns for users over 30. These foundational components allow developers to define what data to fetch and where to find it.
Beyond the basics, the GROUP BY and HAVING clauses organize and filter aggregated data. GROUP BY groups rows by one or more columns, often used with aggregate functions like COUNT() or SUM(). For instance, SELECT department, COUNT(*) FROM employees GROUP BY department; counts employees per department. The HAVING clause filters grouped results, similar to WHERE but applied after aggregation: SELECT department, COUNT(*) FROM employees GROUP BY department HAVING COUNT(*) > 5; shows departments with more than five employees. Additionally, ORDER BY sorts results (SELECT name FROM users ORDER BY age DESC;), and LIMIT restricts the number of rows returned (SELECT * FROM products LIMIT 10;). These clauses refine how data is processed and presented.
Advanced features include JOIN operations to combine tables, aliases with AS, and modifiers like DISTINCT. A JOIN clause links tables based on related columns: SELECT users.name, orders.total FROM users JOIN orders ON users.id = orders.user_id; pairs users with their orders. Aliases simplify complex queries: SELECT COUNT(*) AS total_users FROM users; renames the result column. DISTINCT removes duplicates: SELECT DISTINCT city FROM customers; lists unique cities. Subqueries can also be embedded within SELECT, FROM, or WHERE clauses for dynamic filtering. These components enable developers to handle complex data relationships and optimize output for specific use cases.