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https://issues.apache.org/jira/browse/SPARK-20184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Fei Wang updated SPARK-20184:
-----------------------------
    Summary: performance regression for complex/long sql when enable whole 
stage codegen  (was: performance regression for complex/long sql when enable 
codegen)

> performance regression for complex/long sql when enable whole stage codegen
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-20184
>                 URL: https://issues.apache.org/jira/browse/SPARK-20184
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 1.6.0, 2.1.0
>            Reporter: Fei Wang
>
> The performance of following SQL get much worse in spark 2.x  in contrast 
> with codegen off.
>     SELECT
>        sum(COUNTER_57) 
>         ,sum(COUNTER_71) 
>         ,sum(COUNTER_3)  
>         ,sum(COUNTER_70) 
>         ,sum(COUNTER_66) 
>         ,sum(COUNTER_75) 
>         ,sum(COUNTER_69) 
>         ,sum(COUNTER_55) 
>         ,sum(COUNTER_63) 
>         ,sum(COUNTER_68) 
>         ,sum(COUNTER_56) 
>         ,sum(COUNTER_37) 
>         ,sum(COUNTER_51) 
>         ,sum(COUNTER_42) 
>         ,sum(COUNTER_43) 
>         ,sum(COUNTER_1)  
>         ,sum(COUNTER_76) 
>         ,sum(COUNTER_54) 
>         ,sum(COUNTER_44) 
>         ,sum(COUNTER_46) 
>         ,DIM_1 
>         ,DIM_2 
>               ,DIM_3
>     FROM aggtable group by DIM_1, DIM_2, DIM_3 limit 100;
> Num of rows of aggtable is about 35000000.
> whole stage codegen on(spark.sql.codegen.wholeStage = true):    40s
> whole stage codegen  off(spark.sql.codegen.wholeStage = false):    6s
> After some analysis i think this is related to the huge java method(a java 
> method of thousand lines) which generated by codegen.
> And If i config -XX:-DontCompileHugeMethods the performance get much 
> better(about 7s).



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