SQL joins are used to combine rows from two or more tables based on a related column between them. Different types of joins are used depending on the desired output.
Here are the main types of SQL joins and their use cases:
1. INNER JOIN
Definition:
Returns only the records that have matching values in both tables.
SELECT columns
FROM table1
INNER JOIN table2
ON table1.common_column = table2.common_column;
Use Cases:
When you only want records that exist in both tables.
Combining customer orders with customer details where both exist.
Retrieving employee data with department details only if they are assigned to a department.
2. LEFT (OUTER) JOIN
Definition:
Returns all records from the left table and matching records from the right table. If no match is found, NULL values are returned for columns from the right table.
SELECT columns
FROM table1
LEFT JOIN table2
ON table1.common_column = table2.common_column;
Use Cases:
When you need all records from the left table, regardless of whether they have corresponding records in the right table.
Listing all customers, even if they have no orders.
Showing all employees, including those without assigned projects.
3. RIGHT (OUTER) JOIN
Definition:
Returns all records from the right table and matching records from the left table. If no match is found, NULL values are returned for columns from the left table.
SELECT columns
FROM table1
RIGHT JOIN table2
ON table1.common_column = table2.common_column;
Use Cases:
When you need all records from the right table, even if they have no matching entries in the left table.
Finding all orders, including those without customer details.
Displaying all departments, even those without assigned employees.
4. FULL (OUTER) JOIN
Definition:
Returns all records when there is a match in either the left or right table. If there is no match, NULL values will be shown for the columns from the non-matching table.
SELECT columns
FROM table1
FULL OUTER JOIN table2
ON table1.common_column = table2.common_column;
Use Cases:
When you need all data from both tables, regardless of whether there is a match or not.
Merging customer and order data, showing customers without orders and orders without customers.
Creating a combined dataset of employees and project assignments, even if one does not have the other.
5. CROSS JOIN
Definition:
Returns the Cartesian product of both tables, meaning every row from the first table is combined with every row from the second table.
SELECT columns
FROM table1
CROSS JOIN table2;
Use Cases:
When you need to generate all possible combinations of rows.
Creating test datasets by combining products and customer segments.
Assigning default permissions by combining all users with available roles.
6. SELF JOIN
Definition:
A join in which a table is joined with itself to compare rows within the same table.
SELECT A.column, B.column
FROM table A
INNER JOIN table B
ON A.common_column = B.common_column;
Use Cases:
When you need to compare rows within the same table.
Finding employees who report to the same manager.
Comparing customers with similar purchase patterns.
7. NATURAL JOIN
Definition:
Automatically joins tables based on columns with the same name and data type in both tables.
SELECT columns
FROM table1
NATURAL JOIN table2;
Use Cases:
Simplifying joins when column names and data types match in both tables.
Automatically linking related tables without specifying join conditions explicitly.
Choosing the Right SQL JOIN:
Use INNER JOIN for strict matching.
Use LEFT JOIN when you need all records from the left table.
Use RIGHT JOIN when the right table is the primary focus.
Use FULL JOIN to capture all data from both tables.
Use CROSS JOIN for generating combinations.
Use SELF JOIN for comparisons within the same table.
Use NATURAL JOIN for automatic joins (if applicable).