BryanCutler commented on a change in pull request #27383: 
[SPARK-29367][DOC][2.4] Add compatibility note for Arrow 0.15.0 to SQL guide
URL: https://github.com/apache/spark/pull/27383#discussion_r372638413
 
 

 ##########
 File path: docs/sql-pyspark-pandas-with-arrow.md
 ##########
 @@ -165,3 +165,20 @@ Note that a standard UDF (non-Pandas) will load timestamp 
data as Python datetim
 different than a Pandas timestamp. It is recommended to use Pandas time series 
functionality when
 working with timestamps in `pandas_udf`s to get the best performance, see
 [here](https://pandas.pydata.org/pandas-docs/stable/timeseries.html) for 
details.
+
+### Compatibiliy Setting for PyArrow >= 0.15.0 and Spark 2.3.x, 2.4.x
 
 Review comment:
   This is mostly for people that are stuck on an existing Spark version and 
upgrade pyarrow somehow. They would end up seeing some crazy errors that aren't 
obvious. Hopefully if they see this, they can fix it instead of making a JIRA, 
etc. I don't think this is advertising to use an old Spark version, but If you 
think it's better to remove, I can.

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