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https://issues.apache.org/jira/browse/SPARK-11303?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14973993#comment-14973993
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Yanbo Liang edited comment on SPARK-11303 at 10/26/15 10:29 AM:
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It looks like this bug caused by mutable row copy related problem similar with
SPARK-4963. But after adding *copy* to *sample*, it still can not resolve this
issue. I found *map(_copy())* was removed by
https://github.com/apache/spark/pull/8040/files, [~rxin] Could you tell us the
motivation of removing *map(_copy())* for withReplacement = false in that PR?
was (Author: yanboliang):
It looks like this bug caused by mutable row copy related problem similar with
SPARK-4963. But after adding *copy* to *sample*, it still can not resolve this
issue. I found *map(_copy())* was removed by
https://github.com/apache/spark/pull/8040/files, [~rxin] Could you tell us the
motivation of removing *map(_copy())* in that PR?
> sample (without replacement) + filter returns wrong results in DataFrame
> ------------------------------------------------------------------------
>
> Key: SPARK-11303
> URL: https://issues.apache.org/jira/browse/SPARK-11303
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.1
> Environment: pyspark local mode, linux.
> Reporter: Yuval Tanny
>
> When sampling and then filtering DataFrame from python, we get inconsistent
> result when not caching the sampled DataFrame. This bug doesn't appear in
> spark 1.4.1.
> d = sqlContext.createDataFrame(sc.parallelize([[1]] * 50 + [[2]] * 50),['t'])
> d_sampled = d.sample(False, 0.1, 1)
> print d_sampled.count()
> print d_sampled.filter('t = 1').count()
> print d_sampled.filter('t != 1').count()
> d_sampled.cache()
> print d_sampled.count()
> print d_sampled.filter('t = 1').count()
> print d_sampled.filter('t != 1').count()
> output:
> 14
> 7
> 8
> 14
> 7
> 7
> Thanks!
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