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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/07/18 17:10:20 UTC
[jira] [Assigned] (SPARK-16589) Chained cartesian produces
incorrect number of records
[ https://issues.apache.org/jira/browse/SPARK-16589?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-16589:
------------------------------------
Assignee: Apache Spark
> 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
> Assignee: Apache Spark
>
> 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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