SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION - Amazon Redshift
Table columnsExamples

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 .

SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION

Use SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION to view the usage periods in which Amazon Redshift ran automatic optimization tasks using extra compute resources. For more information on automatic optimization, see Automatic database optimization. For more information on automatic optimizations run using extra compute resources, see Allocating extra compute resources for automatic database optimization.

SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION is available only for provisioned clusters.

SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION is visible only to superusers. For more information, see Visibility of data in system tables and views.

Table columns

Column name Data type Description
start_time timestamp without time zone The time that the extra compute optimization period starts.
end_time timestamp without time zone The time that the extra compute optimization period ends.
query_count bigint The number of automatic optimization queries run during the usage period.
compute_seconds numeric(27,0) The number of seconds in the usage period that Amazon Redshift spent running automatic optimization tasks using extra compute resources.

Examples

Following is an example query looking for automatic optimizations performed on September 16, 2025.

SELECT *
FROM sys_extra_compute_for_automatic_optimization
WHERE start_time BETWEEN '2025-09-16 00:00:00' AND '2025-09-16 23:59:59';

start_time           | end_time            | query_count | compute_seconds
---------------------+---------------------+-------------+-----------------
 2025-09-16 00:00:00  | 2025-09-16 00:00:59 | 1           | 59
 2025-09-16 00:01:05  | 2025-09-16 00:01:58 | 2           | 53