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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-18161) Default PickleSerializer pickle protocol doesn't handle > 4GB objects
Date Wed, 28 Feb 2018 08:54:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-18161?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16379971#comment-16379971
] 

Apache Spark commented on SPARK-18161:
--------------------------------------

User 'inpefess' has created a pull request for this issue:
https://github.com/apache/spark/pull/20691

> Default PickleSerializer pickle protocol doesn't handle > 4GB objects
> ---------------------------------------------------------------------
>
>                 Key: SPARK-18161
>                 URL: https://issues.apache.org/jira/browse/SPARK-18161
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark
>    Affects Versions: 2.0.0, 2.0.1
>            Reporter: Sloane Simmons
>            Priority: Major
>
> When broadcasting a fairly large numpy matrix in a Spark 2.0.1 program, there is an error
serializing the object with:
> {{OverflowError: cannot serialize a bytes object larger than 4 GiB}}
> in the stack trace.
> This is because Python's pickle serialization (with protocol <= 3) uses a 32-bit integer
for the object size, and so cannot handle objects larger than 4 gigabytes.  This was changed
in Protocol 4 of pickle (https://www.python.org/dev/peps/pep-3154/#bit-opcodes-for-large-objects)
and is available in Python 3.4+.  
> I would like to use this protocol for broadcasting and in the default PickleSerializer
where available to make pyspark more robust to broadcasting large variables.



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