PostgreSQL – FULL OUTER JOIN

A FULL OUTER JOIN is used to retrieve data from two or more tables based on a specified condition, including all rows from both the left (or first) table and the right (or second) table. If there’s no match for a row in one table, the columns from the other table will be filled with NULL values. This type of join is useful when you want to combine data from both tables while ensuring that no data is left out.

The basic syntax of a FULL OUTER JOIN in PostgreSQL is as follows:

SELECT column_list FROM left_table FULL OUTER JOIN right_table ON join_condition;

Here’s a breakdown of the components:

• SELECT column_list: This is the list of columns you want to retrieve from the tables.
• left_table: The table from which you want to retrieve data and which will be on the left side of the join operation.
• right_table: The table you want to join with the left table, which will be on the right side of the join operation.
• ON join_condition: This is the condition that specifies how the tables should be joined. It defines the relationship between the columns in the left and right tables.

Example: Consider two tables: “employees” and “departments.” The following query retrieves a list of all employees and their corresponding department information, including employees without a department and departments without employees using a FULL OUTER JOIN:

SELECT e.employee_name, d.department_name FROM employees e FULL OUTER JOIN departments d ON e.department_id = d.department_id;

Above query retrieves the employee names from the “employees” table and the department names from the “departments” table. The FULL OUTER JOIN ensures that all rows from both tables are included in the result, even if there is no matching department for an employee or no matching employee for a department.

While FULL OUTER JOINs can be useful for certain scenarios, they can also produce large result sets, especially if the tables being joined are large. It’s important to understand the data and the relationship between the tables to use the appropriate type of join for your specific needs.