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From "Marco Gaido (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-23986) CompileException when using too many avg aggregation after joining
Date Tue, 11 Sep 2018 08:37:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23986?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16610259#comment-16610259
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Marco Gaido edited comment on SPARK-23986 at 9/11/18 8:36 AM:
--------------------------------------------------------------

[~dzanozin] thanks for reporting this, may you please provide a reproducer for that? Thanks.
Anyway, it seems that this patch is not applied according to the code you have pasted here
(after the patch, we should have {{agg_doConsume_1}} as function name).


was (Author: mgaido):
[~dzanozin] thanks for reporting this, may you please provide a reproducer for that? Thanks.

> CompileException when using too many avg aggregation after joining
> ------------------------------------------------------------------
>
>                 Key: SPARK-23986
>                 URL: https://issues.apache.org/jira/browse/SPARK-23986
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Michel Davit
>            Assignee: Marco Gaido
>            Priority: Major
>             Fix For: 2.3.1, 2.4.0
>
>         Attachments: spark-generated.java
>
>
> Considering the following code:
> {code:java}
>     val df1: DataFrame = sparkSession.sparkContext
>       .makeRDD(Seq((0, 1, 2, 3, 4, 5, 6)))
>       .toDF("key", "col1", "col2", "col3", "col4", "col5", "col6")
>     val df2: DataFrame = sparkSession.sparkContext
>       .makeRDD(Seq((0, "val1", "val2")))
>       .toDF("key", "dummy1", "dummy2")
>     val agg = df1
>       .join(df2, df1("key") === df2("key"), "leftouter")
>       .groupBy(df1("key"))
>       .agg(
>         avg("col2").as("avg2"),
>         avg("col3").as("avg3"),
>         avg("col4").as("avg4"),
>         avg("col1").as("avg1"),
>         avg("col5").as("avg5"),
>         avg("col6").as("avg6")
>       )
>     val head = agg.take(1)
> {code}
> This logs the following exception:
> {code:java}
> ERROR CodeGenerator: failed to compile: org.codehaus.commons.compiler.CompileException:
File 'generated.java', Line 467, Column 28: Redefinition of parameter "agg_expr_11"
> {code}
> I am not a spark expert but after investigation, I realized that the generated {{doConsume}}
method is responsible of the exception.
> Indeed, {{avg}} calls several times {{org.apache.spark.sql.execution.CodegenSupport.constructDoConsumeFunction}}.
The 1st time with the 'avg' Expr and a second time for the base aggregation Expr (count and
sum).
> The problem comes from the generation of parameters in CodeGenerator:
> {code:java}
>   /**
>    * Returns a term name that is unique within this instance of a `CodegenContext`.
>    */
>   def freshName(name: String): String = synchronized {
>     val fullName = if (freshNamePrefix == "") {
>       name
>     } else {
>       s"${freshNamePrefix}_$name"
>     }
>     if (freshNameIds.contains(fullName)) {
>       val id = freshNameIds(fullName)
>       freshNameIds(fullName) = id + 1
>       s"$fullName$id"
>     } else {
>       freshNameIds += fullName -> 1
>       fullName
>     }
>   }
> {code}
> The {{freshNameIds}} already contains {{agg_expr_[1..6]}} from the 1st call.
>  The second call is made with {{agg_expr_[1..12]}} and generates the following names:
>  {{agg_expr_[11|21|31|41|51|61|11|12]}}. We then have a parameter name conflicts in the
generated code: {{agg_expr_11.}}
> Appending the 'id' in s"$fullName$id" to generate unique term name is source of conflict.
Maybe simply using undersoce can solve this issue : $fullName_$id"



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