Delta Lake API

When using Delta Lake, the API does not go through the normal Spark execution path. This means that Immuta's Spark extensions do not provide protection for the API. To solve this issue and ensure that Immuta has control over what a user can access, the Delta Lake API is blocked.

Spark SQL can be used instead to give the same functionality with all of Immuta's data protections.

Requests

Below is a table of the Delta Lake API with the Spark SQL that may be used instead.

Delta Lake API	Spark SQL
DeltaTable.convertToDelta	CONVERT TO DELTA parquet./path/to/parquet/
DeltaTable.delete	DELETE FROM [table_identifier delta./path/to/delta/] WHERE condition
DeltaTable.generate	GENERATE symlink_format_manifest FOR TABLE [table_identifier delta./path/to/delta]
DeltaTable.history	DESCRIBE HISTORY [table_identifier delta./path/to/delta] (LIMIT x)
DeltaTable.merge	MERGE INTO
DeltaTable.update	UPDATE [table_identifier delta./path/to/delta/] SET column = valueWHERE (condition)
DeltaTable.vacuum	VACUUM [table_identifier delta./path/to/delta]

See here for a complete list of the Delta SQL Commands.

Merging tables in native workspaces

When a table is created in a native workspace, you can merge a different Immuta data source from that workspace into that table you created.

1. Create a table in the native workspace.

2. Create a temporary view of the Immuta data source you want to merge into that table.

3. Use that temporary view as the data source you add to the project workspace.

4. Run the following command:

   MERGE INTO delta_native.target_native as target
   USING immuta_temp_view_data_source as source
   ON target.dr_number = source.dr_number
   WHEN MATCHED THEN
   UPDATE SET target.date_reported = source.date_reported