[jira] [Commented] (SPARK-11303) sample (without replacement) + filter returns wrong results in DataFrame

["Yanbo Liang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-11303?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14973896#comment-14973896 ] 

Yanbo Liang commented on SPARK-11303:
-------------------------------------

I think the reason of this bug is the same as SPARK-4963, I will send a PR to resolve it.

> 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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