[jira] [Updated] (SPARK-16589) Chained cartesian produces incorrect number of records

["Nicholas Chammas (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-16589?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nicholas Chammas updated SPARK-16589:
-------------------------------------
    Labels: correctness  (was: )

> 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: 1.4.0, 1.5.0, 1.6.0, 2.0.0
>            Reporter: Maciej Szymkiewicz
>              Labels: correctness
>
> 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
> rdd.cartesian(rdd).cartesian(rdd).distinct().count()
> ## 251
> {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()
> ## 1000
> {code}
> or insert identity map:
> {code}
> rdd.cartesian(rdd).map(lambda x: x).cartesian(rdd).count()
> ## 1000
> {code}
> it yields correct results.
>  



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org