Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14086
The followings are my opinions according to the priority.
* First of all, `TRUNCATE` is the lower privilege than DROP/CREATE.
- You know that DROP/CREATE privilege do anything harm.
* Second, we are assuming the original table is generated by
`DataFrameWriter`, not any other general database table.
- Why do you consider the descendant tables? If you consider `descendant
tables`, you should say `DROP` will also delete them all, too.
* Third, do we use rollback with `DataFrameWriter`?
I'm worrying about losing the focus. The all the concerns are based on the
correct facts, but the scope of arguments seems to be slightly too general to
this PR. Please see the description of this PR. The context of this PR is
**providing truncate option for the Spark JDBC tables generated by
df.write.mode("overwrite").jdbc(url, "table_with_index", prop)**.
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