HyukjinKwon commented on a change in pull request #34042:
URL: https://github.com/apache/spark/pull/34042#discussion_r711838027
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File path: docs/sql-data-sources-jdbc.md
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@@ -29,7 +29,9 @@ as a DataFrame and they can easily be processed in Spark SQL
or joined with othe
The JDBC data source is also easier to use from Java or Python as it does not
require the user to
provide a ClassTag.
(Note that this is different than the Spark SQL JDBC server, which allows
other applications to
-run queries using Spark SQL).
+run queries using Spark SQL).
+
+All columns are automatically converted to be nullable for compatibility
reasons.
Review comment:
I actually think this is something we should fix but we couldn't because
it is a too much breaking change. This is not only for JDBC but for other filed
based sources.
We should better have an option or configuration to set the nullability
correctly, and make it disabled by default.
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