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From "Kazuaki Ishizaki (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-19372) Code generation for Filter predicate including many OR conditions exceeds JVM method size limit
Date Sun, 13 Aug 2017 17:06:01 GMT

    [ https://issues.apache.org/jira/browse/SPARK-19372?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16124982#comment-16124982
] 

Kazuaki Ishizaki edited comment on SPARK-19372 at 8/13/17 5:05 PM:
-------------------------------------------------------------------

[~srinivasanm] I can reproduce this issue by using the master branch. I think that this is
another problem.
Could you please create another JIRA entry to track this issue? I will work for this.



was (Author: kiszk):
[~srinivasanm] I can reproduce this issue by using the master branch. I think that this is
another problem.
Could you please create another JIRA entry to track this issue?


> Code generation for Filter predicate including many OR conditions exceeds JVM method
size limit 
> ------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-19372
>                 URL: https://issues.apache.org/jira/browse/SPARK-19372
>             Project: Spark
>          Issue Type: Bug
>    Affects Versions: 2.1.0
>            Reporter: Jay Pranavamurthi
>            Assignee: Kazuaki Ishizaki
>             Fix For: 2.2.0, 2.3.0
>
>         Attachments: wide400cols.csv
>
>
> For the attached csv file, the code below causes the exception "org.codehaus.janino.JaninoRuntimeException:
Code of method "(Lorg/apache/spark/sql/catalyst/InternalRow;)Z" of class "org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificPredicate"
grows beyond 64 KB
> Code:
> {code:borderStyle=solid}
>   val conf = new SparkConf().setMaster("local[1]")
>   val sqlContext = SparkSession.builder().config(conf).getOrCreate().sqlContext
>   val dataframe =
>     sqlContext
>       .read
>       .format("com.databricks.spark.csv")
>       .load("wide400cols.csv")
>   val filter = (0 to 399)
>     .foldLeft(lit(false))((e, index) => e.or(dataframe.col(dataframe.columns(index))
=!= s"column${index+1}"))
>   val filtered = dataframe.filter(filter)
>   filtered.show(100)
> {code}



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