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Github user HyukjinKwon commented on the issue:
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retest this please
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retest this please
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Jenkins test this please
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retest this please
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retest this please
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ok to test
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python2.7: 0.17.0
python3: 0.18.1
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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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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?
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Jenkins, retest this please
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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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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
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Working on duplicating PySpark failures...
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I just posted the 2.0 pull request.
https://github.com/apache/spark/pull/19538
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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
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
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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