[GitHub] [spark] BryanCutler commented on a change in pull request #34509: [SPARK-34521][PYTHON][SQL] Fix spark.createDataFrame when using pandas with StringDtype

[GitBox <gi...@apache.org>]

BryanCutler commented on a change in pull request #34509:
URL: https://github.com/apache/spark/pull/34509#discussion_r759567576



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File path: python/pyspark/sql/pandas/serializers.py
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@@ -169,6 +169,8 @@ def create_array(s, t):
             elif is_categorical_dtype(s.dtype):
                 # Note: This can be removed once minimum pyarrow version is >= 0.16.1
                 s = s.astype(s.dtypes.categories.dtype)
+            elif t is not None and pa.types.is_string(t):
+                s = s.astype(str)

Review comment:
       I agree with @ueshin , the correct thing to do would be to continue to use pyarrow to convert the column in this case with `mask = None`, that way the implementation is sure to do the conversion most efficiently. I think for this case it should then produce a standard arrow UTF-8 array that PySpark could handle.




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