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Github user shaneknapp commented on the issue:
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python2.7: 0.17.0
python3: 0.18.1
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Github user srowen commented on the issue:
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I don't think there are any more 1.x releases coming, and doubt there are
more 2.0.x releases. Do you really need this in Spark or is it something you
can apply to your own release branch?
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Github user ambauma commented on the issue:
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I have a release in my fork for my immediate needs. However, Spark 1.6 is
still included in Hortonworks and is default in Cloudera. This patch addresses
CVE-2017-7678. Some companies in strict re
Github user srowen commented on the issue:
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(Spark 1.x is legacy in Cloudera, but, it has its own 1.x branch anyway)
I think it's not a big deal to backport if it goes into later branches
first, sure. But I doubt there is another 1.x releas
Github user ambauma commented on the issue:
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I just posted the 2.0 pull request.
https://github.com/apache/spark/pull/19538
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Working on duplicating PySpark failures...
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Github user ambauma commented on the issue:
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Able to duplicate. Working theory is that this is related to numpy 1.12.1.
Here is my conda env:
(spark-1.6) andrew@andrew-Inspiron-7559:~/git/spark$ conda list
# packages in environment at
Github user ambauma commented on the issue:
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Believed fixed. Hard to say for sure without knowing the precise python
and numpy versions the build is using.
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Jenkins, retest this please
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Github user ambauma commented on the issue:
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I'm unable to duplicate the PySpark failures locally. I assume I need a
specific version of SciPy to duplicate the error. Is there a way I could get
what versions the build server is running? Som
Github user felixcheung commented on the issue:
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@shaneknapp - could you help check - what version of SciPy Jenkins is
running with? thanks!
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ok to test
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