How to use join in sql

The JOIN operator is used to merge related data from different tables and associate rows in the tables by specifying join conditions. Common JOIN types include INNER JOIN (returns matching rows), LEFT JOIN (returns all left table rows), RIGHT JOIN (returns all right table rows), and FULL JOIN (returns all table rows). JOIN queries should be capitalized and specify the join columns. Performance is an important factor to consider when writing JOIN queries.

Usage of JOIN in SQL

JOIN is used in SQL to combine related data from different tables operator. It allows you to extract data from multiple tables and relate them based on their common columns.

Syntax

<code>SELECT column_list
FROM table1
JOIN table2 ON join_condition;</code>

Where:

• column_list is the column to be retrieved from the joined table.
• table1 and table2 are the tables to be joined.
• join_condition Specifies the condition used to join rows in the table.

Common JOIN types

• INNER JOIN: Return only the children of rows that match in both tables set.
• LEFT JOIN: Returns all rows in table1, and a subset of matching rows in table2.
• RIGHT JOIN: Returns all rows in table2, and a subset of matching rows in table1.
• FULL JOIN: Returns all rows from both tables, regardless of whether they match.

Usage Example

For example, the following query uses INNER JOIN to get from the customers table and the orders table Customer's Orders:

<code>SELECT *
FROM customers
INNER JOIN orders ON customers.customer_id = orders.customer_id;</code>

This query will return a table with the following columns:

• customer_id
• ##customer_name
• order_id
• order_date

customer_id column will be in the two tables rows are associated. INNER JOIN ensures that only orders from customers that appear in both tables are returned.

Note

The JOIN operator is case-sensitive and should always be capitalized.
• The column used to join the table must be specified, that is,
• join_condition.
If the JOIN type is not specified, the default is INNER JOIN.
• When writing JOIN queries, it is important to consider performance. Complex JOINs on large tables can be slow.

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