9.22 Release notes (with behavior changes): Preview¶

Data quality: Using expectations to define quality checks (General availability)¶

You can use an expectation to define the threshold for a data metric function (DMF). After you add the expectation to an association between a DMF and an object, if a value returned by the DMF does not match the Boolean expression of the expectation, it is flagged as a violation of the data quality check.

Tracing SQL statements run from handler code (General availability)¶

When you have enabled tracing, Snowflake traces SQL statements executed in conjunction with other traced code, such as within the handler for a stored procedure or user-defined function.

Dynamic tables: Support for immutability constraints¶

Immutability constraints give you finer control over dynamic table updates by allowing parts of the table to remain unchanged instead of always reflecting the latest query results.

By marking specific regions as immutable, you can:

• Prevent propagation of updates or deletions to existing data.

• Restrict inserts, updates, and deletes for rows matching a condition.

• Limit future modifications while still allowing incremental updates to other parts of the table.

To define immutability constraints, use the IMMUTABLE WHERE parameter in the CREATE DYNAMIC TABLE or ALTER DYNAMIC TABLE command.

Dynamic tables: Support for backfill¶

You can now create a dynamic table with its initial data backfilled from a regular table. Backfilling is a zero-copy, low-cost operation that makes the source data immediately available in the dynamic table.

You can backfill data into a dynamic table while still defining a custom refresh query for future updates. With immutability constraints, backfilled data remains unchanged even if it no longer matches the upstream source, ensuring it persists over time.