Improve SQL syntax for MERGE

Existing SQL syntax (see here and here) for MEGRE could be improved by adding an alternative for ON <merge_condition>

Main assumption In common cases target and source tables have the same column names used in <merge_condition> as keys. For example ON target.id = source.id or ON target.name = source.name AND target.surname = source.surname It would be more convenient to use ON COLUMNS (id) and ON COLUMNS (name, surname) or similar instead. The same approach is used for JOIN where join_criteria syntax is ON boolean_expression | USING ( column_name [ , ... ] )

Improvement proposal Syntax

MERGE INTO target_table_identifier [AS target_alias]
USING source_table_identifier [<time_travel_version>] [AS source_alias]
ON { <merge_condition> | COLUMNS ( column_name [ , ... ] ) }
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN NOT MATCHED [ AND <condition> ]  THEN <not_matched_action> ]

Example

MERGE INTO target
USING source
ON COLUMNS (name, surname)
WHEN MATCHED THEN
    UPDATE SET *
WHEN NOT MATCHED THEN
    INSERT *

[tdas]

I doubt this syntax improvement will be supported by Spark. MERGE has a clear SQL standard, and I am not sure if something like USING is supported in that. We have been able to convince Spark to support UPDATE SET * and INSERT * (completely outside the SQL standard) only because of the major usability improvement that it gives. But for something smaller like this, I doubt we will be able to convince Spark community to adopt this non-standard approach.

[dnskr]

Closing in favor of the ticket created in Spark JIRA https://issues.apache.org/jira/browse/SPARK-36472