cloud-fan commented on code in PR #56553:
URL: https://github.com/apache/spark/pull/56553#discussion_r3424792805


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python/docs/source/migration_guide/pyspark_upgrade.rst:
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@@ -27,6 +27,14 @@ Upgrading from PySpark 4.1 to 4.2
 * In Spark 4.2, columnar data exchange between PySpark and the JVM uses Apache 
Arrow by default. The configuration 
``spark.sql.execution.arrow.pyspark.enabled`` now defaults to true. To restore 
the legacy (non-Arrow) row-based data exchange, set 
``spark.sql.execution.arrow.pyspark.enabled`` to ``false``.
 * In Spark 4.2, regular Python UDFs are Arrow-optimized by default. The 
configuration ``spark.sql.execution.pythonUDF.arrow.enabled`` now defaults to 
true. To restore the legacy behavior for Python UDF execution, set 
``spark.sql.execution.pythonUDF.arrow.enabled`` to ``false``.
 * In Spark 4.2, regular Python UDTFs are Arrow-optimized by default. The 
configuration ``spark.sql.execution.pythonUDTF.arrow.enabled`` now defaults to 
true. To restore the legacy behavior for Python UDTF execution, set 
``spark.sql.execution.pythonUDTF.arrow.enabled`` to ``false``.
+* In Spark 4.2, PyPy is no longer officially supported. Run PySpark on CPython 
instead.
+* In Spark 4.2, the minimum supported version of pandas for Spark Connect has 
been raised to 2.2.0. Upgrade pandas to 2.2.0 or later.

Review Comment:
   do we need this or pyspark already have a doc page for version bumps? cc 
@HyukjinKwon @gaogaotiantian 



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