Daniel Fithian created ARROW-2590:
-------------------------------------
Summary: Pyspark python_udf serialization error on grouped map
(Amazon EMR)
Key: ARROW-2590
URL: https://issues.apache.org/jira/browse/ARROW-2590
Project: Apache Arrow
Issue Type: Bug
Components: Python
Affects Versions: 0.9.0
Environment: Amazon EMR 5.13
Spark 2.3.0
PyArrow 0.9.0 (and 0.8.0)
Pandas 0.22.0 (and 0.21.1)
Numpy 1.14.1
Reporter: Daniel Fithian
I am writing a python_udf grouped map aggregation on Spark 2.3.0 in Amazon EMR.
When I try to run any aggregation, I get the following Python stack trace:
{{18/05/16 14:08:56 ERROR Utils: Aborting task}}
{{org.apache.spark.api.python.PythonException: Traceback (most recent call
last):}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/worker.py",
line 229, in m}}
{{ain}}
{{ process()}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/worker.py",
line 224, in p}}
{{rocess}}
{{ serializer.dump_stream(func(split_index, iterator), outfile)}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/serializers.py",
line 261,}}
{{ in dump_stream}}
{{ batch = _create_batch(series, self._timezone)}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/serializers.py",
line 239,}}
{{ in _create_batch}}
{{ arrs = [create_array(s, t) for s, t in series]}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/serializers.py",
line 239,}}
{{ in <listcomp>}}
{{ arrs = [create_array(s, t) for s, t in series]}}
{{ File
"/mnt/yarn/usercache/hadoop/appcache/application_1526400761989_0068/container_1526400761989_0068_01_000002/pyspark.zip/pyspark/serializers.py",
line 237, in create_array}}
{{ return pa.Array.from_pandas(s, mask=mask, type=t)}}
{{ File "array.pxi", line 372, in pyarrow.lib.Array.from_pandas}}
{{ File "array.pxi", line 177, in pyarrow.lib.array}}
{{ File "array.pxi", line 77, in pyarrow.lib._ndarray_to_array}}
{{ File "error.pxi", line 98, in pyarrow.lib.check_status}}
{{pyarrow.lib.ArrowException: Unknown error: 'utf-32-le' codec can't decode
bytes in position 0-3: code point not in range(0x110000)}}
To be clear, this happens when I run any aggregation, including the identity
aggregation (return the Pandas DataFrame that was passed in). I do not get this
error when I return an empty DataFrame, so it seems to be a symptom of the
serialization of the Pandas DataFrame back to Spark.
I have observed this behavior with the following versions:
* Spark 2.3.0
* PyArrow 0.9.0 (also 0.8.0)
* Pandas 0.22.0 (also 0.22.1)
* Numpy 1.14.1
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
