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https://issues.apache.org/jira/browse/SPARK-24644?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon resolved SPARK-24644.
----------------------------------
    Resolution: Invalid

Let me leave this resolved. Please reopen this if the same issue exists in 
higher version of Pandas.

> Pyarrow exception while running pandas_udf on pyspark 2.3.1
> -----------------------------------------------------------
>
>                 Key: SPARK-24644
>                 URL: https://issues.apache.org/jira/browse/SPARK-24644
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.3.1
>         Environment: os: centos
> pyspark 2.3.1
> spark 2.3.1
> pyarrow >= 0.8.0
>            Reporter: Hichame El Khalfi
>            Priority: Major
>
> Hello,
> When I try to run a `pandas_udf` on my spark dataframe, I get this error
>  
> {code:java}
>   File 
> "/mnt/ephemeral3/yarn/nm/usercache/user/appcache/application_1524574803975_205774/container_e280_1524574803975_205774_01_000044/pyspark.zip/pyspark/serializers.py",
>  lin
> e 280, in load_stream
>     pdf = batch.to_pandas()
>   File "pyarrow/table.pxi", line 677, in pyarrow.lib.RecordBatch.to_pandas 
> (/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:43226)
>     return Table.from_batches([self]).to_pandas(nthreads=nthreads)
>   File "pyarrow/table.pxi", line 1043, in pyarrow.lib.Table.to_pandas 
> (/arrow/python/build/temp.linux-x86_64-2.7/lib.cxx:46331)
>     mgr = pdcompat.table_to_blockmanager(options, self, memory_pool,
>   File "/usr/lib64/python2.7/site-packages/pyarrow/pandas_compat.py", line 
> 528, in table_to_blockmanager
>     blocks = _table_to_blocks(options, block_table, nthreads, memory_pool)
>   File "/usr/lib64/python2.7/site-packages/pyarrow/pandas_compat.py", line 
> 622, in _table_to_blocks
>     return [_reconstruct_block(item) for item in result]
>   File "/usr/lib64/python2.7/site-packages/pyarrow/pandas_compat.py", line 
> 446, in _reconstruct_block
>     block = _int.make_block(block_arr, placement=placement)
> TypeError: make_block() takes at least 3 arguments (2 given)
> {code}
>  
>  More than happy to provide any additional information



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