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https://issues.apache.org/jira/browse/SPARK-13587?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15218659#comment-15218659
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Mike Sukmanowsky commented on SPARK-13587:
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That's the (hopefully) beautiful thing about pex.
{noformat}
$ pex numpy pandas -o c_requirements.pex
$ ./c_requirements.pex
Python 2.7.10 (default, Aug 4 2015, 19:54:05)
[GCC 4.2.1 Compatible Apple LLVM 6.1.0 (clang-602.0.53)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
(InteractiveConsole)
>>> import numpy
>>> import pandas
>>> print numpy.__version__
1.11.0
>>> print pandas.__version__
0.18.0
>>>
{noformat}
The catch of course is that the pex file itself would have to be built on a
node with the same arch as Spark workers (i.e. can't build pex on Mac OS and
ship to Linux cluster unless all dependencies are pure python). To build a
platform agnostic env, we'd have to look at conda.
I know there was an effort to support pex with pyspark
https://github.com/URXtech/spex but it hasn't seen much activity recently. I
tried reaching out to the author but got no response.
I could take a shot at adding support for this unless @zjffdu already has plans.
> Support virtualenv in PySpark
> -----------------------------
>
> Key: SPARK-13587
> URL: https://issues.apache.org/jira/browse/SPARK-13587
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
> Reporter: Jeff Zhang
>
> Currently, it's not easy for user to add third party python packages in
> pyspark.
> * One way is to using --py-files (suitable for simple dependency, but not
> suitable for complicated dependency, especially with transitive dependency)
> * Another way is install packages manually on each node (time wasting, and
> not easy to switch to different environment)
> Python has now 2 different virtualenv implementation. One is native
> virtualenv another is through conda. This jira is trying to migrate these 2
> tools to distributed environment
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