How Do INNER, LEFT, RIGHT, and FULL JOINs Differ in SQL?
In-depth understanding of SQL JOIN: detailed explanation of INNER, LEFT, RIGHT and FULL JOIN
SQL JOIN is a core operation in data retrieval, allowing us to combine rows from multiple tables based on common fields. In MySQL, there are several JOIN types to choose from, each providing a specific way of handling matching and unmatched rows.
Differences between different SQL JOIN types
INNER JOIN
- Join two tables based on matching conditions.
- Only return rows whose common fields match in both tables.
LEFT JOIN
- Join two tables based on matching conditions.
- Returns all rows from the left table, even if there are no matching rows in the right table.
- Unmatched rows in the right table are filled with NULL values.
RIGHT JOIN
- Similar to LEFT JOIN, but returns all rows from the right table, even if there are no matching rows in the left table.
- Unmatched rows in the left table are filled with NULL values.
FULL JOIN
- The result of combining LEFT and RIGHT OUTER JOIN.
- Returns all rows from both tables, regardless of whether there is a match.
- Unmatched rows in either table are filled with NULL values.
Actual case
Consider the following example table:
<code>表A: | id | firstName | lastName | |---|---|---| | 1 | Arun | Prasanth | | 2 | Ann | Antony | | 3 | Sruthy | Abc | | 6 | New | Abc | 表B: | id2 | age | place | |---|---|---| | 1 | 24 | Kerala | | 2 | 24 | Usa | | 3 | 25 | Ekm | | 5 | 24 | Chennai |</code>
INNER JOIN:
<code>SELECT * FROM 表A INNER JOIN 表B ON 表A.id = 表B.id2;</code>
Result:
firstName | lastName | age | place |
---|---|---|---|
Arun | Prasanth | 24 | Kerala |
Ann | Antony | 24 | Usa |
Sruthy | Abc | 25 | Ekm |
LEFT JOIN:
<code>SELECT * FROM 表A LEFT JOIN 表B ON 表A.id = 表B.id2;</code>
Result:
firstName | lastName | age | place |
---|---|---|---|
Arun | Prasanth | 24 | Kerala |
Ann | Antony | 24 | Usa |
Sruthy | Abc | 25 | Ekm |
New | Abc | NULL | NULL |
RIGHT JOIN:
<code>SELECT * FROM 表A RIGHT JOIN 表B ON 表A.id = 表B.id2;</code>
Result:
firstName | lastName | age | place |
---|---|---|---|
Arun | Prasanth | 24 | Kerala |
Ann | Antony | 24 | Usa |
Sruthy | Abc | 25 | Ekm |
NULL | NULL | 24 | Chennai |
Full Join:
<code>表A: | id | firstName | lastName | |---|---|---| | 1 | Arun | Prasanth | | 2 | Ann | Antony | | 3 | Sruthy | Abc | | 6 | New | Abc | 表B: | id2 | age | place | |---|---|---| | 1 | 24 | Kerala | | 2 | 24 | Usa | | 3 | 25 | Ekm | | 5 | 24 | Chennai |</code>
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