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https://issues.apache.org/jira/browse/SPARK-10773?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14906022#comment-14906022
]
Bo soon Park commented on SPARK-10773:
--------------------------------------
I also so this error like this in mapr-spark-1.4.1
[Code]
import org.apache.spark.{SparkContext, SparkConf}
import org.apache.spark.streaming.{Seconds, StreamingContext}
object Justtest {
def main(args: Array[String]) {
val sparkConf = new
SparkConf().setMaster("spark://maprdemo:7077").setAppName("LogNormalizer").set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
val sc = new SparkContext(sparkConf)
val a = sc.parallelize(List(1, 2, 10, 4, 5, 2, 1, 1, 1), 3).repartition(6)
}
}
> Repartition operation failing on RDD with "argument type mismatch" error
> ------------------------------------------------------------------------
>
> Key: SPARK-10773
> URL: https://issues.apache.org/jira/browse/SPARK-10773
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.4.1
> Reporter: Da Fox
>
> Hello,
> Erorr occures in following Spark application:
> {code}
> object RunSpark {
> def main(args: Array[String]) {
> val sparkContext: SparkContext = new SparkContext()
> val data: RDD[String] = sparkContext.textFile("banana-big.tsv")
> val repartitioned: RDD[String] = data.repartition(5)
> val mean: Double = repartitioned
> .groupBy((s: String) => s.split("\t")(1))
> .mapValues((strings: Iterable[String]) =>strings.size)
> .values.mean()
> println(mean)
> }
> }
> {code}
> The exception:
> {code}
> Exception in thread "main" java.lang.IllegalArgumentException: argument type
> mismatch
> at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> at
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
> at
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
> at
> org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$instantiateClass(ClosureCleaner.scala:330)
> at
> org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$22.apply(ClosureCleaner.scala:268)
> at
> org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$22.apply(ClosureCleaner.scala:262)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
> at
> org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:262)
> at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:132)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:1893)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1.apply(RDD.scala:700)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1.apply(RDD.scala:699)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
> at org.apache.spark.rdd.RDD.mapPartitionsWithIndex(RDD.scala:699)
> at org.apache.spark.rdd.RDD$$anonfun$coalesce$1.apply(RDD.scala:381)
> at org.apache.spark.rdd.RDD$$anonfun$coalesce$1.apply(RDD.scala:367)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
> at org.apache.spark.rdd.RDD.coalesce(RDD.scala:366)
> at org.apache.spark.rdd.RDD$$anonfun$repartition$1.apply(RDD.scala:342)
> at org.apache.spark.rdd.RDD$$anonfun$repartition$1.apply(RDD.scala:342)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
> at org.apache.spark.rdd.RDD.repartition(RDD.scala:341)
> at repartitionissue.RunSpark$.main(RunSpark.scala:10)
> at repartitionissue.RunSpark.main(RunSpark.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:665)
> at
> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:170)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:193)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> {code}
> Application is executed using spark-submit on Yarn hadoop 2.7 with
> yarn-client mode. When I run same application using spark-shell it's
> completed successfully.
> I suspect problem is in code of Spark Utils's ClosureCleaner.class (can be
> found in stack trace). The method in ClosureCleaner distinguishes between
> REPL (spark-shell) and spark-submit . When application is executed on Spark
> 1.3.1 no error occured and computation is successful (in case of
> spark-submit).
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