Github user danielvdende commented on a diff in the pull request:
https://github.com/apache/spark/pull/20057#discussion_r159371171
--- Diff: docs/sql-programming-guide.md ---
@@ -1339,6 +1339,13 @@ the following case-insensitive options:
This is a JDBC writer related option. When
<code>SaveMode.Overwrite</code> is enabled, this option causes Spark to
truncate an existing table instead of dropping and recreating it. This can be
more efficient, and prevents the table metadata (e.g., indices) from being
removed. However, it will not work in some cases, such as when the new data has
a different schema. It defaults to <code>false</code>. This option applies only
to writing.
</td>
</tr>
+
+ <tr>
+ <td><code>cascadeTruncate</code></td>
+ <td>
+ This is a JDBC writer related option. If enabled and supported by
the JDBC database (PostgreSQL and Oracle at the moment), this options allows
execution of a <code>TRUNCATE TABLE t CASCADE</code>. This will affect other
tables, and thus should be used with case. This option applies only to writing.
--- End diff --
@dongjoon-hyun one thing I'm thinking of (just curious to hear your
opinion): could we use the value of `isCascadingTruncateTable` for each dialect
as the default value for the `cascade` boolean? In that way, there is only a
single boolean per dialect specifying what the default behaviour is with regard
to cascading during truncates.
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