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
STL_USAGE_CONTROL
The STL_USAGE_CONTROL view contains information that is logged when a usage limit is reached. For more information about usage limits, see Managing Usage Limits in the Amazon Redshift Management Guide.
STL_USAGE_CONTROL is visible only to superusers. For more information, see Visibility of data in system tables and views.
Table columns
| Column name | Data type | Description |
|---|---|---|
| eventtime | timestamp | The time (UTC) when the query exceeded a usage limit. |
| query | integer | The query identifier. You can use this ID to join various other system tables and views. |
| xid | bigint | The transaction identifier. |
| pid | integer | The process identifier associated with the query. |
| usage_limit_id | character(40) | A universally unique identifier (UUID) generated by Amazon Redshift, for example
25d9297e-3e7b-41c8-9f4d-c4b6eb731c09. |
| feature_type | character(30) | The feature whose usage limit was exceeded.
Possible values include CONCURRENCY_SCALING and
SPECTRUM. |
Sample query
The following SQL example returns some of the information logged when a usage limit is reached.
select query, pid, eventtime, feature_type from stl_usage_control order by eventtime desc limit 5;
