Github user xuanyuanking commented on a diff in the pull request:
https://github.com/apache/spark/pull/22369#discussion_r216189359
--- Diff: docs/sql-programming-guide.md ---
@@ -1901,6 +1901,7 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
## Upgrading From Spark SQL 2.3.0 to 2.3.1 and above
- As of version 2.3.1 Arrow functionality, including `pandas_udf` and
`toPandas()`/`createDataFrame()` with `spark.sql.execution.arrow.enabled` set
to `True`, has been marked as experimental. These are still evolving and not
currently recommended for use in production.
+ - In version 2.3.1 and earlier, it is possible for PySpark to create a
Row object by providing more value than column number through the customized
Row class. Since Spark 2.3.3, Spark will confirm value length is less or equal
than column length in PySpark. See
[SPARK-25072](https://issues.apache.org/jira/browse/SPARK-25072) for details.
--- End diff --
Thanks Bryan, I'll address this after discussion.
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