holdenk commented on a change in pull request #29719:
URL: https://github.com/apache/spark/pull/29719#discussion_r678531129
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File path: python/pyspark/sql/pandas/conversion.py
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@@ -297,8 +297,11 @@ class SparkConversionMixin(object):
"""
Min-in for the conversion from pandas to Spark. Currently, only
:class:`SparkSession`
can use this class.
+ pandasRDD=True creates a DataFrame from an RDD of pandas dataframes
+ (currently only supported using arrow)
Review comment:
So let's say the user specifies a schema, in that case inside of
_createFromRDD we can just look at the type of each element that were
processing and see if it's a DataFrame or a Row or a Dictionary and dispatch
the logic there. What do you think? Or is there a reason I'm missing why we
couldn't do the dispatch inside of _createFromRDD based on type?
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