When it comes to working with databases, SQL is a powerful tool that is widely used. As an essential part of any database management system, SQL provides users with several commands that serve different purposes. However, when it comes to joining tables, users often get confused about the differences between the different types of SQL joins. One such comparison is between the Left Outer Join Vs Left Join in SQL.
Although these two SQL joins seem to be similar, there are subtle differences that set them apart. This article will explain what these differences are, and when to use them, by comparing Left Outer Join Vs Left Join in SQL.
Firstly, let’s define what these joins are.
What is the Left Join in SQL?
A Left Join in SQL is a command that combines two tables to retrieve data where one table has data and the other doesn’t. With Left Join, all rows from the table on the left side of the JOIN clause are displayed, regardless of whether there is a match between the two tables.
What is the Left Outer Join in SQL?
A Left Outer Join in SQL is also a command that combines two tables to retrieve data where one table has data and the other doesn’t. However, different from Left Join, Left Outer Join returns all the rows from the table on the left and the matching rows from the table on the right. If there is no matching row in the table on the right, the Left Outer Join command returns NULL.
Now that we know what Left Join and Left Outer Join in SQL are let’s compare the differences between the two.
Left Join Vs Left Outer Join: The Differences
The primary distinction between Left Join Vs Left Outer Join is in the result set that is produced. While both SQL commands return rows from one table and matching rows from another table, Left Join only returns the matching rows in both tables. On the other hand, Left Outer Join, returns all the rows from the table on the left side and the matching rows from the table on the right.
The best way to illustrate the difference is through an example. Imagine we have two tables, a ‘Students’ table, and a ‘Grades’ table. Both tables contain information about our students, and the ‘Grades’ table has varying degrees of information about the students. Using these tables, let’s try to create different SQL queries using Left Join and Left Outer Join.
Example 1: Left Join
SELECT *
FROM Students
LEFT JOIN Grades ON Students.student_id = Grades.student_id
In this SQL code, we are returning all the rows from the Students table, and the matching rows from the Grades table. The column on which we matched the tables is the student_id column.
Example 2: Left Outer Join
SELECT *
FROM Students
LEFT OUTER JOIN Grades ON Students.student_id = Grades.student_id
In this SQL code, we are returning all the rows from the Students table, with the matching rows from the Grades table. However, if there is no matching row in the ‘Grades’ table, instead of blank cell, the query will return a ‘NULL’ value in the corresponding column.
When to Use Left Join and Left Outer Join in SQL?
Now that we know the differences between the two, let’s talk about when to use Left Join and Left Outer Join in SQL.
Left Join is commonly used to retrieve rows that match or have a relationship with another table. It can help in cases where we want to find records that have a connection to another table, but it’s not necessary that the connection exists.
On the other hand, Left Outer Join is used when we want to select all rows from a table, including the matching rows from another table, and nulls for non-matching rows. This is useful for situations when we want to ensure that all the data from one table is displayed, even if there are not any matches from the referenced table.
Conclusion
In conclusion, Left Join Vs Left Outer Join in SQL may seem similar but have a distinct difference. Left Join is used when we need to retrieve the matching rows from two tables, whereas Left Outer Join is used when we require all rows from one table and matching rows from another table. Therefore, it’s essential to know which command to use to get the desired results. By understanding the differences between the two commands, users can create more efficient queries and retrieve the data they need without confusion.