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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/06/06 15:05:00 UTC
[jira] [Assigned] (SPARK-31920) Failure in converting pandas
DataFrames with Arrow when columns implement __arrow_array__
[ https://issues.apache.org/jira/browse/SPARK-31920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-31920:
------------------------------------
Assignee: (was: Apache Spark)
> Failure in converting pandas DataFrames with Arrow when columns implement __arrow_array__
> -----------------------------------------------------------------------------------------
>
> 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
> Priority: Major
>
> 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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