Organized collection of data in computing.
SQL subqueries, also known as inner queries or nested queries, are a powerful tool in SQL that allow you to retrieve data using multiple queries simultaneously. They are used to manipulate the data in such a way that the result of one query is used in another query.
A subquery is a query that is embedded within another SQL query. It can be used in various parts of a query, including the SELECT, FROM, WHERE, and HAVING clauses. The result of a subquery can be used as an expression or a value for comparison in the main query.
Subqueries are used when the result of one query depends on the result of another query. They can simplify complex queries by breaking them down into more manageable parts. Subqueries can also be used to perform operations that cannot be performed in a single SQL statement.
There are three main types of subqueries:
Nested subqueries are subqueries that are nested inside another subquery. A subquery can be nested inside the WHERE or HAVING clause of an outer SQL statement. An inner subquery can be used in the WHERE clause of an outer SQL statement to further filter the results.
Let's look at some examples of how to use subqueries in SQL.
SELECT employee_name, salary FROM employees WHERE salary > (SELECT salary FROM employees WHERE employee_name = 'John');
This query will return the names and salaries of employees who earn more than John.
SELECT employee_name, department_id FROM employees WHERE department_id IN (SELECT department_id FROM departments WHERE location = 'New York');
This query will return the names of employees who work in departments located in New York.
SELECT e1.employee_name, e1.department_id FROM employees e1 WHERE salary > (SELECT AVG(salary) FROM employees e2 WHERE e1.department_id = e2.department_id);
This query will return the names of employees who earn more than the average salary in their department.
By understanding and implementing SQL subqueries, you can write more complex and powerful SQL statements to retrieve and manipulate data in your database.