LEFT JOIN keyword is used in SQL to combine two or more tables together, with the goal of returning all rows from the left table (also known as the first table), and any matching rows from the right table (also known as the second table). If there is no match, the result will contain
NULL values for all columns of the right table.
Here's an example of how you might use the LEFT JOIN keyword in a SQL query:
SELECT orders.id, customers.name FROM orders LEFT JOIN customers ON orders.customer_id = customers.id;
In this example, the query is selecting the
name columns from the
customers tables, respectively. The
ON clause specifies the relationship between the two tables, in this case, the
customer_id column of the
orders table is matched with the
id column of the
customers table. This query will return all rows from the
orders table, along with the corresponding name from the
customers table for each order. If there is no match in the
customers table, it will return a
NULL value for the
LEFT JOIN is similar to
INNER JOIN but the
INNER JOIN returns only the matching rows from both tables, where as
LEFT JOIN returns all the rows of left table along with matching rows of the right table.
It's worth noting that you can use the
LEFT JOIN keyword with more than two tables, as well as other types of joins such as
RIGHT JOIN and
FULL OUTER JOIN.
Here are some best practices for using
LEFT JOIN in SQL:
LEFT JOINwhen you want to include unmatched rows from the left table in the result set. If you use a regular (
JOIN, unmatched rows from the left table will be excluded from the result set.
Be sure to use the correct join condition in the
ONclause. The join condition should match the related column(s) between the left and right tables.
Be aware that
LEFT JOINcan be very slow if the right table is large, especially if it doesn't have an index on the join column(s). To improve performance, create an index on the joined column(s) in the right table.
Keep in mind that the use of
LEFT JOINon multiple tables can make the query more complex and harder to understand. It's a good idea to break them down into smaller queries, and then use the results of those queries to join with other tables.