การสืบค้น SQL ขั้นสูงและการเชื่อมตาราง

Welcome to Advanced SQL Queries! So far, you've learned to select, filter, and sort data. But real-world applications often need to combine data from multiple sources or perform complex calculations.

This lesson will equip you with powerful techniques to retrieve sophisticated datasets, making your Supabase applications even smarter.

Let's quickly refresh our memory on joins. A JOIN combines rows from two or more tables based on a related column between them.

An INNER JOIN returns only the rows where there is a match in both tables. If a row in one table doesn't have a match in the other, it's excluded.

Try running this example to set up our tables and see an INNER JOIN:

What if you want to see all employees, even those not assigned to a department yet? That's where LEFT JOIN (or LEFT OUTER JOIN) comes in handy.

A LEFT JOIN returns all rows from the 'left' table (the first one mentioned) and the matching rows from the 'right' table. If there's no match on the right, NULL values are returned for the right table's columns.

Run this to see employee Eve Adams, who has no department:

The opposite of a LEFT JOIN is a RIGHT JOIN (or RIGHT OUTER JOIN). It returns all rows from the 'right' table and matching rows from the 'left' table.

If there's no match on the left, NULL values are returned for the left table's columns. This is less common, as you can often rewrite it as a LEFT JOIN by swapping table order.

Let's find all departments, including 'HR' which currently has no employees:

Want to see everything? A FULL OUTER JOIN (or just FULL JOIN) returns all rows when there is a match in either the left or the right table.

If a row doesn't have a match in the other table, the columns from the non-matching side will have NULL values. It's like combining a LEFT and a RIGHT join.

Observe how both Eve (no department) and HR (no employees) appear:

Sometimes, you need to join a table to itself. This is called a SELF JOIN and is useful for finding relationships within the same table, like 'employees and their managers'.

To do this, you use table aliases to treat the same table as two separate entities in your query.

Let's add a manager column and find out who manages whom:

Beyond joins, subqueries (also called inner queries or nested queries) are another powerful tool. A subquery is simply a SQL query nested inside a larger query.

They can be used to:

• Filter data in a WHERE clause.
• Define columns in a SELECT clause.
• Create derived tables in a FROM clause.

Subqueries execute first, and their result is then used by the outer query.

A common use for subqueries is in the WHERE clause to filter results dynamically. You can use operators like IN, EXISTS, =, <, > with subqueries.

For example, let's find all employees who work in the 'Sales' department without knowing the department_id beforehand:

A scalar subquery is a subquery that returns a single value (one row, one column). These are often used in the SELECT clause to add a calculated value to each row of the main query.

Let's find each employee's name and also show the total number of employees in their department. This demonstrates how a subquery can compute a value for each row.

You've gained some serious SQL superpowers today!

• Joins: Beyond INNER JOIN, you learned about LEFT, RIGHT, and FULL OUTER JOINs to handle different data inclusion needs.
• Self Join: How to join a table to itself for hierarchical data.
• Subqueries: Nesting queries to filter data (WHERE clause) or compute scalar values (SELECT clause).

These techniques are fundamental for building powerful and flexible data retrieval logic in your Supabase projects. Keep practicing!