[jira] [Commented] (SPARK-17972) Query planning slows down dramatically for large query plans even when sub-trees are cached

2016-10-31 Thread Yin Huai (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-17972?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15623363#comment-15623363
 ] 

Yin Huai commented on SPARK-17972:
--

This issue has been resolved by https://github.com/apache/spark/pull/15651.

> 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
> Fix For: 2.1.0
>
>
> 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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[jira] [Commented] (SPARK-17972) Query planning slows down dramatically for large query plans even when sub-trees are cached

2016-10-26 Thread Apache Spark (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-17972?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15610110#comment-15610110
 ] 

Apache Spark commented on SPARK-17972:
--

User 'liancheng' has created a pull request for this issue:
https://github.com/apache/spark/pull/15651

> 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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