Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/18849
> If that is not the point of "Hive compatibility", then there is no point
in creating data source tables in a Hive compatible way to start with. Just
always create them as "not Hive compatible" because then Spark is free to do
whatever it wants with them.
For most usage scenarios of Spark native file source tables, they do not
use Hive to query the tables. Thus, breaking/maintaining Hive compatibility
will not affect them. Their DDL commands on the data source tables should not
be blocked even if Hive metastore complains it.
For Hive users who want to query Spark native file source tables, we can
introduce the property like `DATASOURCE_HIVE_COMPATIBLE` for ensuring the Hive
compatibility will not be broken in the whole life cycle of these tables. This
property has to be manually set by users, instead of adding by Spark SQL.
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