December 04-05, 2023 — 7.43 Release Notes¶

Finalizer Task — General Availability¶

With this release, we are pleased to announce the general availability of the finalizer task. A finalizer task handles the release and cleanup of resources that a DAG uses. You can create a finalizer task that is associated with a root task or change an existing standalone task to a finalizer task.

The finalizer task is guaranteed to run regardless of the DAG’s success or failure and ensures proper resource cleanup and completion of necessary steps in all scenarios. For example, if a DAG run uses intermediate tables to track data for processing and fails before the table rows are consumed, the next run will encounter duplicate rows and reprocess data resulting in longer execution time or wasting compute resources. The finalizer task can address this issue by dropping the rows or truncating the table as needed.

For more information, see Finalizer Task.

New SQL functions¶

The following function(s) are now available with this release:

Python Snowpark Local Testing Framework — Preview¶

With this release, we are pleased to announce the Snowpark Python local testing framework as a preview feature to all accounts. The Snowpark Python local testing framework allows you to create and operate on Snowpark Python DataFrames locally without connecting to a Snowflake account. You can use this to test your DataFrame operations locally, on your development machine or in a CI (continuous integration) pipeline, before deploying code changes to your account. The API is the same, so you can either run your tests locally or against a Snowflake account, without making code changes.

For more information, see Local testing framework.

Load Files onto Stages and Managed Staged Files using Snowsight — General Availability¶

With this release, we are pleased to announce the general availability of the following Snowsight features:

• Loading files onto internal stages.

• Browsing files on an internal or external stage.

With Snowsight, you can load files onto internal named stages and prepare to load data into tables or load dependencies for Python worksheets. You can also use Snowsight to view and manage staged files.

For more information, see Staging files using Snowsight.