[jira] [Resolved] (SPARK-11704) Optimize the Cartesian Join

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-11704?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-11704.
----------------------------------
    Resolution: Incomplete

> Optimize the Cartesian Join
> ---------------------------
>
>                 Key: SPARK-11704
>                 URL: https://issues.apache.org/jira/browse/SPARK-11704
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>            Reporter: Zhan Zhang
>            Priority: Major
>              Labels: bulk-closed
>
> Currently CartesianProduct relies on RDD.cartesian, in which the computation is realized as follows
>   override def compute(split: Partition, context: TaskContext): Iterator[(T, U)] = {
>     val currSplit = split.asInstanceOf[CartesianPartition]
>     for (x <- rdd1.iterator(currSplit.s1, context);
>          y <- rdd2.iterator(currSplit.s2, context)) yield (x, y)
>   }
> From the above loop, if rdd1.count is n, rdd2 needs to be recomputed n times. Which is really heavy and may never finished if n is large, especially when rdd2 is coming from ShuffleRDD.
> We should have some optimization on CartesianProduct by caching rightResults. The problem is that we don’t have cleanup hook to unpersist rightResults AFAIK. I think we should have some cleanup hook after query execution.
> With the hook available, we can easily optimize such Cartesian join. I believe such cleanup hook may also benefit other query optimizations.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

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