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Join Types
One of the key aspects of Tabula is the ability to join tables together to retrieve information from multiple sources. In this tutorial, we will cover the main types of SQL joins and provide examples for each, using tables with data to illustrate each join type.
Join operation, in simple terms, is a process used to combine information from two or more different tables in a database. This operation is essential when you need to gather data that is spread across multiple tables and create a single, comprehensive view.
Consider you have two tables: 'employees' and 'departments’. You want to get one table with employees’ names and corresponding departments’ names.
Example
employees:
id | name | department_id |
|---|---|---|
1 | John Smith | 10 |
2 | Jane Doe | 20 |
3 | Mike Brown | 40 |
departments:
id | name |
|---|---|
10 | HR |
20 | IT |
30 | Finance |
The join operation works by identifying a common "link" or "key" between the tables, such as departament_id in 'employees' or id in 'departments’. It then merges the tables based on this link, creating a new table with the combined information.
Join operation is a method used in databases to combine information from two or more different tables based on a common column or relationship. It is similar to the VLOOKUP function in spreadsheets like Microsoft Excel or Google Sheets, as both are used to merge data from separate sources based on a shared identifier.
VLOOKUP is a function that searches for a specific value in the first column of a table and returns a corresponding value from another column in the same row. It is commonly used to look up and retrieve related information from one table using a shared identifier present in another table.
Join operation, on the other hand, is used in databases like SQL to combine entire tables based on a common column or relationship. Unlike VLOOKUP, join operations can merge multiple columns and rows from two or more tables, providing a more comprehensive view of the combined data.
An INNER JOIN returns only the rows where there is a match between the columns specified in the join condition from both tables.
Result:
name | name |
|---|---|
John Smith | HR |
Jane Doe | IT |
A LEFT JOIN (or LEFT OUTER JOIN) returns all rows from the left table and the matched rows from the right table. If there is no match, NULL values are returned for the right table's columns.
Result:
name | name |
|---|---|
John Smith | HR |
Jane Doe | IT |
Mike Brown | NULL |
A RIGHT JOIN (or RIGHT OUTER JOIN) returns all rows from the right table and the matched rows from the left table. If there is no match, NULL values are returned for the left table's columns.
Result:
name | name |
|---|---|
John Smith | HR |
Jane Doe | IT |
NULL | Finance |
A FULL JOIN (or FULL OUTER JOIN) returns all rows when there is a match in either the left or right table. If there is no match, NULL values are returned for the columns of the table with no match.
Result:
name | name |
|---|---|
John Smith | HR |
Jane Doe | IT |
Mike Brown | NULL |
NULL | Finance |
A CROSS JOIN returns the Cartesian product of two tables, i.e., it combines each row from the first table with each row from the second table. This type of join is not commonly used in practice but can be helpful in specific scenarios.
Example. Consider two tables: 'colors' and 'sizes'.
colors:
id | name |
|---|---|
1 | Red |
2 | Blue |
3 | Green |
sizes:
id | name |
|---|---|
1 | Small |
2 | Medium |
3 | Large |
Result:
color_name | size_name |
|---|---|
Red | Small |
Red | Medium |
Red | Large |
Blue | Small |
Blue | Medium |
Blue | Large |
Green | Small |
Green | Medium |
Green | Large |
In the example above, the CROSS JOIN combines each color with each size, resulting in 9 rows (3 colors * 3 sizes).
Last modified 2mo ago