Full OUTER JOIN vs. FULL JOIN

sql

join

data-quality

query-optimization

byAlex Kataev·Nov 28, 2024

In SQL Server and other SQL databases, FULL OUTER JOIN and FULL JOIN are functionally alike, serving to align every record from both input tables. Where relationships are absent, they return NULL values, preventing data exclusion because of missing correspondences.

SELECT 
  a.name, 
  b.salary -- because who doesn’t want to know everyone’s salary 😉
FROM 
  employees a 
  FULL JOIN jobs b 
  ON a.job_id = b.id; -- Yep! This is where the magic happens.

This SQL query returns all employee names and their job salaries, leaving no stone unturned—even if an employee or a job lacks a corresponding match in the other table.

Deciphering JOIN semantics

The LEFT OUTER JOIN is identical to the LEFT JOIN, and similarly, RIGHT OUTER JOIN is synonymous with the RIGHT JOIN. The OUTER keyword, while not affecting the query outputs, serves to enhance readability by more explicitly illustrating the query's intention.

The OUTER keyword: To use or not to use?

The choice of employing OUTER in your JOIN clauses typically arises from a preference for code clarity versus compactness. Although it’s not mandatory and doesn’t affect the outcome, its usage may facilitate a clearer understanding of the code's objective to future users or during the process of code review. Consistency in style choice, however, is crucial for code maintainability.

Importance of documentation

Reiterate on the necessity for maintaining thorough documentation. This not only further assists in comprehension of your SQL queries but also stands as a significant contributor to your codebase's maintainability.

Using FULL JOINs wisely

Data Completeness: FULL JOINs ensure a full representation of all records, significantly aiding in data reconciliation.
Performance Constraints: FULL JOINs may be resource-hungry on large datasets. Proper indexing and query optimization are your best friends here.
Handling NULLs: Pay attention to the **NULL**s that arise from unlinked records as they can impact data quality and subsequent processes.
Ideal use cases: FULL JOINs often shine in data auditing, reporting, or situations where data omission due to mismatches is unwanted.