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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2020/03/11 19:37:00 UTC
[jira] [Closed] (SPARK-22523) Janino throws StackOverflowError on
nested structs with many fields
[ https://issues.apache.org/jira/browse/SPARK-22523?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun closed SPARK-22523.
---------------------------------
> Janino throws StackOverflowError on nested structs with many fields
> -------------------------------------------------------------------
>
> Key: SPARK-22523
> URL: https://issues.apache.org/jira/browse/SPARK-22523
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core, SQL
> Affects Versions: 2.2.0
> Environment: * Linux
> * Scala: 2.11.8
> * Spark: 2.2.0
> Reporter: Utku Demir
> Priority: Minor
>
> When running the below application, Janino throws StackOverflow:
> {code}
> Exception in thread "main" java.lang.StackOverflowError
> at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:370)
> at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
> at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
> at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
> at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
> {code}
> Problematic code:
> {code:title=Example.scala|borderStyle=solid}
> import org.apache.spark.sql._
> case class Foo(
> f1: Int = 0,
> f2: Int = 0,
> f3: Int = 0,
> f4: Int = 0,
> f5: Int = 0,
> f6: Int = 0,
> f7: Int = 0,
> f8: Int = 0,
> f9: Int = 0,
> f10: Int = 0,
> f11: Int = 0,
> f12: Int = 0,
> f13: Int = 0,
> f14: Int = 0,
> f15: Int = 0,
> f16: Int = 0,
> f17: Int = 0,
> f18: Int = 0,
> f19: Int = 0,
> f20: Int = 0,
> f21: Int = 0,
> f22: Int = 0,
> f23: Int = 0,
> f24: Int = 0
> )
> case class Nest[T](
> a: T,
> b: T
> )
> object Nest {
> def apply[T](t: T): Nest[T] = new Nest(t, t)
> }
> object Main {
> def main(args: Array[String]) {
> val spark: SparkSession = SparkSession.builder().appName("test").master("local[*]").getOrCreate()
> import spark.implicits._
> val foo = Foo(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
> Seq.fill(10)(Nest(Nest(foo))).toDS.groupByKey(identity).count.map(s => s).collect
> }
> }
> {code}
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