[jira] [Created] (SPARK-31920) Failure in converting pandas DataFrames with columns via Arrow

["Stephen Caraher (Jira)" <ji...@apache.org>]

Stephen Caraher created SPARK-31920:
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             Summary: Failure in converting pandas DataFrames with columns via Arrow
                 Key: SPARK-31920
                 URL: https://issues.apache.org/jira/browse/SPARK-31920
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 2.4.5, 3.0.0, 3.1.0
         Environment: pandas: 1.0.0 - 1.0.4
pyarrow: 0.15.1 - 0.17.1
            Reporter: Stephen Caraher


When calling {{createDataFrame}} on a pandas DataFrame in which any of the columns are backed by an array implementing {{\_\_arrow_array\_\_}} ({{StringArray}}, {{IntegerArray}}, etc), the conversion will fail.

With pyarrow >= 0.17.0, the following exception occurs:
{noformat}
Traceback (most recent call last):
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/tests/test_arrow.py", line 470, in test_createDataFrame_from_integer_extension_dtype
    df_from_integer_ext_dtype = self.spark.createDataFrame(pdf_integer_ext_dtype)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/session.py", line 601, in createDataFrame
    data, schema, samplingRatio, verifySchema)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/conversion.py", line 277, in createDataFrame
    return self._create_from_pandas_with_arrow(data, schema, timezone)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/conversion.py", line 435, in _create_from_pandas_with_arrow
    jrdd = self._sc._serialize_to_jvm(arrow_data, ser, reader_func, create_RDD_server)
  File "/Users/stephen/Documents/github/spark/python/pyspark/context.py", line 570, in _serialize_to_jvm
    serializer.dump_stream(data, tempFile)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/serializers.py", line 204, in dump_stream
    super(ArrowStreamPandasSerializer, self).dump_stream(batches, stream)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/serializers.py", line 88, in dump_stream
    for batch in iterator:
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/serializers.py", line 203, in <genexpr>
    batches = (self._create_batch(series) for series in iterator)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/serializers.py", line 194, in _create_batch
    arrs.append(create_array(s, t))
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/serializers.py", line 161, in create_array
    array = pa.Array.from_pandas(s, mask=mask, type=t, safe=self._safecheck)
  File "pyarrow/array.pxi", line 805, in pyarrow.lib.Array.from_pandas
  File "pyarrow/array.pxi", line 215, in pyarrow.lib.array
  File "pyarrow/array.pxi", line 104, in pyarrow.lib._handle_arrow_array_protocol
ValueError: Cannot specify a mask or a size when passing an object that is converted with the __arrow_array__ protocol.
{noformat}

With pyarrow < 0.17.0, the conversion will fail earlier in the process, during schema extraction:
{noformat}
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/tests/test_arrow.py", line 470, in test_createDataFrame_from_integer_extension_dtype
    df_from_integer_ext_dtype = self.spark.createDataFrame(pdf_integer_ext_dtype)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/session.py", line 601, in createDataFrame
    data, schema, samplingRatio, verifySchema)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/conversion.py", line 277, in createDataFrame
    return self._create_from_pandas_with_arrow(data, schema, timezone)
  File "/Users/stephen/Documents/github/spark/python/pyspark/sql/pandas/conversion.py", line 397, in _create_from_pandas_with_arrow
    arrow_schema = pa.Schema.from_pandas(pdf, preserve_index=False)
  File "pyarrow/types.pxi", line 1078, in pyarrow.lib.Schema.from_pandas
  File "/Users/stephen/opt/miniconda3/envs/spark-dev/lib/python3.7/site-packages/pyarrow/pandas_compat.py", line 519, in dataframe_to_types
    type_ = pa.lib._ndarray_to_arrow_type(values, type_)
  File "pyarrow/array.pxi", line 53, in pyarrow.lib._ndarray_to_arrow_type
  File "pyarrow/array.pxi", line 64, in pyarrow.lib._ndarray_to_type
  File "pyarrow/error.pxi", line 107, in pyarrow.lib.check_status
pyarrow.lib.ArrowTypeError: Did not pass numpy.dtype object
{noformat}



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