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https://issues.apache.org/jira/browse/SPARK-17972?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15582977#comment-15582977
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Apache Spark commented on SPARK-17972:
--------------------------------------

User 'liancheng' has created a pull request for this issue:
https://github.com/apache/spark/pull/15517

> Query planning slows down dramatically for large query plans even when 
> sub-trees are cached
> -------------------------------------------------------------------------------------------
>
>                 Key: SPARK-17972
>                 URL: https://issues.apache.org/jira/browse/SPARK-17972
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.6.2, 2.0.1
>            Reporter: Cheng Lian
>            Assignee: Cheng Lian
>
> The following Spark shell snippet creates a series of query plans that grow 
> exponentially. The {{i}}-th plan is created using 4 *cached* copies of the 
> {{i - 1}}-th plan.
> {code}
> (0 until 6).foldLeft(Seq(1, 2, 3).toDS) { (plan, iteration) =>
>   val start = System.currentTimeMillis()
>   val result = plan.join(plan, "value").join(plan, "value").join(plan, 
> "value").join(plan, "value")
>   result.cache()
>   System.out.println(s"Iteration $iteration takes time 
> ${System.currentTimeMillis() - start} ms")
>   result.as[Int]
> }
> {code}
> We can see that although all plans are cached, the query planning time still 
> grows exponentially and quickly becomes unbearable.
> {noformat}
> Iteration 0 takes time 9 ms
> Iteration 1 takes time 19 ms
> Iteration 2 takes time 61 ms
> Iteration 3 takes time 219 ms
> Iteration 4 takes time 830 ms
> Iteration 5 takes time 4080 ms
> {noformat}
> Similar scenarios can be found in iterative ML code and significantly affects 
> usability.



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