[GitHub] [spark] BryanCutler commented on a change in pull request #28743: [SPARK-31920][PYTHON] Fix pandas conversion using Arrow with __arrow_array__ columns

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

BryanCutler commented on a change in pull request #28743:
URL: https://github.com/apache/spark/pull/28743#discussion_r438466149



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File path: python/pyspark/sql/pandas/conversion.py
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@@ -394,10 +394,11 @@ def _create_from_pandas_with_arrow(self, pdf, schema, timezone):
 
         # Create the Spark schema from list of names passed in with Arrow types
         if isinstance(schema, (list, tuple)):
-            arrow_schema = pa.Schema.from_pandas(pdf, preserve_index=False)
+            inferred_types = [pa.infer_type(s, mask=s.isna(), from_pandas=True)

Review comment:
       `pa.Schema.from_pandas` will return a type that is a subclass of `pa.ExtensionType`. From that instance, there is a `storage_type` that is defined, which could then be checked as a Spark supported type. Assuming the Pandas extension array implemented `__arrow_array__`, which is recommended, see https://arrow.apache.org/docs/python/extending_types.html#controlling-conversion-to-pyarrow-array-with-the-arrow-array-protocol.




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