What are the Differences Between Inner, Left, Right, and Outer SQL Joins?

In-depth understanding of the nuances of SQL JOIN

SQL JOIN plays a vital role in data processing and aggregation. Among various JOIN types, inner JOIN (INNER JOIN), left outer JOIN (LEFT OUTER JOIN), right outer JOIN (RIGHT OUTER JOIN) and full outer JOIN (FULL OUTER JOIN) are often used to combine data from multiple tables based on specific conditions. data.

INNER JOIN (INNER JOIN)

Inner JOIN retrieves only rows from two or more tables where the joining columns match. It only includes rows that have a match in both tables, effectively filtering out any non-matching rows.

OUTER JOIN (OUTER JOIN)

Use outer JOIN when you want to include all rows from one table, regardless of whether they match rows in another table. There are three types of external JOIN:

• LEFT OUTER JOIN: Contains all rows from the left table and any matching rows from the right table. Unmatched rows in the left table will be populated with NULL values.
• RIGHT OUTER JOIN: Similar to left OUTER JOIN, but includes all rows from the right table and any matching rows from the left table. Unmatched rows in the right table will be populated with NULL values.
• FULL OUTER JOIN: Contains all rows from the left and right tables. If there is a match on one side, the matching row is displayed; if there is no match, it is filled with NULL values.

Example

Consider the example provided in the article:

表1 (Customers)	表2 (Orders)
ID	Name		ID	Customer ID	Order Date
1	John		1	1	2023-01-01
2	Mary		2	1	2023-01-02
3	Tom		3	2	2023-01-03
4	Alice		4	3	2023-01-04

The inner JOIN will only return rows where the Customer ID matches in both tables:

Customer ID	Name	Order Date
1	John	2023-01-01
1	John	2023-01-02

Performance Notes

JOIN performance depends on various factors, including the size and complexity of the table, the query optimizer used, and the database engine. Generally, inner JOINs are more efficient because they filter out unmatched rows. External JOINs can be more resource intensive, especially when dealing with large tables with few matches. Choosing the appropriate JOIN type is critical to optimizing database queries.

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