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SQL JOIN EXPLAINED

SQL JOIN

A JOIN clause is used to combine rows from two or more tables, based on a related column between them. SQL Server has 4 types of joins:

INNER JOIN/simple join
LEFT OUTER JOIN/LEFT JOIN
RIGHT OUTER JOIN/RIGHT JOIN
FULL OUTER JOIN

SELECT Columns
FROM table1
INNER JOIN table2
ON table1.column=table2.column

We will use the two tables we created in our previous post, which can be found here to demonstrate; Employees and Departments tables

Employees Table
Departments Table
INNER JOIN


This type of JOIN returns rows from all tables in which the join condition is true. It takes the following syntax:

Example
--INNER JOIN
SELECT e.Id,e.FirrstName,e.MiddleName,e.LastName,e.Address,e.PhoneNumber,e.DateOfBirth,d.DeptName
FROM employees e
INNER JOIN departments d
ON e.DepartmentId=d.Id

Result

LEFT OUTER JOIN

This type of join will return all rows from the left-hand table plus records in the right-hand table with matching values.

Example
-- LEFT OUTER JOIN
SELECT e.Id,e.FirrstName,e.MiddleName,e.LastName,e.Address,e.PhoneNumber,e.DateOfBirth,d.DeptName
FROM employees e
LEFT OUTER JOIN departments d
ON e.DepartmentId=d.Id

Result
The records without matching values are replaced with NULLs in the respective columns as shown above.

RIGHT OUTER JOIN


This type of join returns all rows from the right-hand table and only those with matching values in the left-hand table.

Example
--RIGHT OUTER JOIN
SELECT e.Id,e.FirrstName,e.MiddleName,e.LastName,e.Address,e.PhoneNumber,e.DateOfBirth,d.DeptName
FROM employees e
RIGHT OUTER JOIN departments d
ON e.DepartmentId=d.Id

Result
The records without matching values are replaced with NULLs in the respective columns.

FULL OUTER JOIN

This type of join returns all rows from both tables with NULL values where the JOIN condition is not true.

Example
--FULL OUTER JOIN
SELECT e.Id,e.FirrstName,e.MiddleName,e.LastName,e.Address,e.PhoneNumber,e.DateOfBirth,d.DeptName
FROM employees e
FULL OUTER JOIN departments d
ON e.DepartmentId=d.Id


Result

The records without matching values are replaced with NULLs in the respective columns.

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