Amazon Redshift will no longer support the creation of new Python UDFs starting November 1, 2025. If you would like to use Python UDFs, create the UDFs prior to that date. Existing Python UDFs will continue to function as normal. For more information, see the blog post .

TRUNCATE

Deletes all of the rows from a table without doing a table scan: this operation is a faster alternative to an unqualified DELETE operation. To run a TRUNCATE command, you must have the TRUNCATE permission for the table, be the owner of the table, or be a superuser. To grant permissions to truncate a table, use the GRANT command.

TRUNCATE is much more efficient than DELETE and doesn't require a VACUUM and ANALYZE. However, be aware that TRUNCATE commits the transaction in which it is run.

Syntax

TRUNCATE [ TABLE ] table_name

The command also works on a materialized view.

TRUNCATE materialized_view_name

Parameters

Usage notes

The TRUNCATE command commits the transaction in which it is run; therefore, you can't roll back a TRUNCATE operation, and a TRUNCATE command may commit other operations when it commits itself.

Examples

Use the TRUNCATE command to delete all of the rows from the CATEGORY table:

truncate category;

Attempt to roll back a TRUNCATE operation:

begin;

truncate date;

rollback;

select count(*) from date;
count
-------
0
(1 row)

The DATE table remains empty after the ROLLBACK command because the TRUNCATE command committed automatically.

The following example uses the TRUNCATE command to delete all of the rows from a materialized view.

truncate my_materialized_view;

It deletes all records in the materialized view and leaves the materialized view and its schema intact. In the query, the materialized view name is a sample.