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https://issues.apache.org/jira/browse/SPARK-16331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin resolved SPARK-16331.
---------------------------------
       Resolution: Fixed
         Assignee: Hiroshi Inoue
    Fix Version/s: 2.1.0

> [SQL] Reduce code generation time 
> ----------------------------------
>
>                 Key: SPARK-16331
>                 URL: https://issues.apache.org/jira/browse/SPARK-16331
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.0.0, 2.1.0
>            Reporter: Hiroshi Inoue
>            Assignee: Hiroshi Inoue
>             Fix For: 2.1.0
>
>
> During the code generation, a {{LocalRelation}} often has a huge {{Vector}} 
> object as {{data}}. In the simple example below, a {{LocalRelation}} has a 
> Vector with 1000000 elements of {{UnsafeRow}}. 
> {quote}
> val numRows = 1000000
> val ds = (1 to numRows).toDS().persist()
> benchmark.addCase("filter+reduce") { iter =>
>   ds.filter(a => (a & 1) == 0).reduce(_ + _)
> }
> {quote}
> At {{TreeNode.transformChildren}}, all elements of the vector is 
> unnecessarily iterated to check whether any children exist in the vector 
> since {{Vector}} is Traversable. This part significantly increases code 
> generation time.
> This patch avoids this overhead by checking the number of children before 
> iterating all elements; {{LocalRelation}} does not have children since it 
> extends {{LeafNode}}.
> The performance of the above example 
> {quote}
> without this patch
> Java HotSpot(TM) 64-Bit Server VM 1.8.0_91-b14 on Mac OS X 10.11.5
> Intel(R) Core(TM) i5-5257U CPU @ 2.70GHz
> compilationTime:                         Best/Avg Time(ms)    Rate(M/s)   Per 
> Row(ns)   Relative
> ------------------------------------------------------------------------------------------------
> filter+reduce                                 4426 / 4533          0.2        
> 4426.0       1.0X
> with this patch
> compilationTime:                         Best/Avg Time(ms)    Rate(M/s)   Per 
> Row(ns)   Relative
> ------------------------------------------------------------------------------------------------
> filter+reduce                                 3117 / 3391          0.3        
> 3116.6       1.0X
> {quote}



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