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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-16589) Chained cartesian produces incorrect number of records
Date Mon, 18 Jul 2016 17:10:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-16589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15382620#comment-15382620
] 

Apache Spark commented on SPARK-16589:
--------------------------------------

User 'zero323' has created a pull request for this issue:
https://github.com/apache/spark/pull/14248

> Chained cartesian produces incorrect number of records
> ------------------------------------------------------
>
>                 Key: SPARK-16589
>                 URL: https://issues.apache.org/jira/browse/SPARK-16589
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.6.0, 2.0.0
>            Reporter: Maciej Szymkiewicz
>
> Chaining cartesian calls in PySpark results in the number of records lower than expected.
It can be reproduced as follows:
> {code}
> rdd = sc.parallelize(range(10), 1)
> rdd.cartesian(rdd).cartesian(rdd).count()
> ## 355
> {code}
> It looks like it is related to serialization. If we reserialize after initial cartesian:
> {code}
> rdd.cartesian(rdd)._reserialize(BatchedSerializer(PickleSerializer(), 1)).cartesian(rdd).count()
> {code}
> or insert identity map:
> {code}
> rdd.cartesian(rdd).map(lambda x: x).cartesian(rdd).count()
> {code}
> it yields correct results.
>  



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