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Github user HyukjinKwon commented on the issue:
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(re) cc @Stibbons for reviewing. I think you are another right one to
review this given https://github.com/apache/spark/pull/14180. Let's start to
incrementally improve this feature unless you
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@holdenk @ueshin @HyukjinKwon Thanks for review the long pending PR. Will
refine the PR soon.
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cc @ueshin too. I think we definitely need this. Will try to proceed
reviewing, probably after rc1 of 2.3.0.
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+1
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Github user Stibbons commented on the issue:
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I would be so pleased to see proper support for virtualenv and conda. I
also lobby for support of wheelhouse. Now there is Pipfile that is replacing
requirements.txt. Having truly independent
Github user holdenk commented on the issue:
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So this certainly seems interesting, although like the linked PR it's also
a non-trivial change. By attempting to also handle the interactive case (which
certainly is important) we've got many
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+1
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@holdenk Do you have time to review this ? Thanks
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I created a google doc about how to use it,
https://docs.google.com/document/d/1KB9RYW8_bSeOzwVqZFc_zy_vXqqqctwrU5TROP_16Ds/edit?usp=sharing
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Github user Stibbons commented on the issue:
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Maybe we can try to split this work in several parts to ease merge. I
clearly think python job should be deployed a bit like jar dependencies are
specified for scala (with `--packages`), and this
Github user zjffdu commented on the issue:
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Thanks for the review @mridulm , this approach is trying the move the
overhead from user to cluster. User just need to specify the requirement file
and spark will set up the virtualenv
Github user zjffdu commented on the issue:
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custom properties file is natively supported by spark, it is user's choice
to use --conf or --properties-file.
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Github user Stibbons commented on the issue:
https://github.com/apache/spark/pull/13599
yes. This file is only written once, dependending the configuration of the
Spark Cluster, and each time you want to send a Python job that will use
virtualenv/conda, user would just add
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