Snowflake Data Clean Rooms releases API version 18.9

Snowflake Data Clean Rooms received API version 18.9, delivering general bug fixes and performance improvements. The release can be accessed directly through the web UI or applied to the account API environment.

Use cases

Imagine your organization collaborates with partners on sensitive data using Snowflake Data Clean Rooms. Keeping the environment binaries up to date ensures all analytical procedures run smoothly and benefit from recent fixes.

With this update mechanism you can:

• Receive bug fixes and stability enhancements for API procedures.
• Choose between automatic seamless updates or scheduled manual patches using SQL.

How to use

Users accessing clean rooms through the web interface only need to log out and log back in to load the updated interface session.

For API environments, you can check your current version with:

SELECT * FROM SAMOOHA_BY_SNOWFLAKE_LOCAL_DB.ADMIN.VERSION;

To enable automatic upgrades on release:

USE ROLE SAMOOHA_APP_ROLE;
CALL SAMOOHA_BY_SNOWFLAKE_LOCAL_DB.library.enable_local_db_auto_upgrades();

What happens in this code:

1. Switches the active role to SAMOOHA_APP_ROLE.
2. Enables automated local database upgrades whenever a new version is published.

If you prefer to manually patch your environment on demand:

USE ROLE SAMOOHA_APP_ROLE;
CALL SAMOOHA_BY_SNOWFLAKE_LOCAL_DB.library.apply_patch();

What happens in this code:

1. Sets execution context to SAMOOHA_APP_ROLE.
2. Executes all pending migrations sequentially to bring the environment to the latest version.

Limitations and requirements

• Environment update management for Snowflake Data Clean Rooms is GA (Generally Available).
• Not available in government cloud regions or VPS (Virtual Private Snowflake) deployments.
• Requires SAMOOHA_APP_ROLE privileges to run update procedures.
• Accounts running version 12.3 or older might have automatic updates disabled and require re-running the mount procedure before re-enabling automatic updates.
• Delaying manual updates over multiple releases increases execution time for apply_patch, as intermediate versions are applied sequentially.