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https://issues.apache.org/jira/browse/SPARK-1867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14220736#comment-14220736
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Michał Kosmulski commented on SPARK-1867:
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I ran into the same issue (with Spark 1.1.0). In my case the cause was
incompatibility of serialziation protocols between the Java versions that Spark
and my application were compiled with. Originally, I ran Spark from the binary
package downloaded from http://spark.apache.org/downloads.html and was getting
"java.lang.IllegalStateException: unread block data" for a trivial job. I
confirmed that using in-memory data instead of data from a textFile() caused
the issue to disappear.
I got rid of the problem by downloading Spark source package and compiling it
on my machine using the same Java version I later used to compile my
application. With this setup, the error disappeared.
I had previously tested with Spark binary package and checked what happened
when I compiled my application using JDK 8 and JDK 7 but the error persisted in
both cases, which suggests that Spark binary package was compiled with JDK 6 or
even earlier. When compiling Spark from source using the same version of Java
as for compiling my application, I got it to work with JDK 8.
> Spark Documentation Error causes java.lang.IllegalStateException: unread
> block data
> -----------------------------------------------------------------------------------
>
> Key: SPARK-1867
> URL: https://issues.apache.org/jira/browse/SPARK-1867
> Project: Spark
> Issue Type: Bug
> Reporter: sam
>
> I've employed two System Administrators on a contract basis (for quite a bit
> of money), and both contractors have independently hit the following
> exception. What we are doing is:
> 1. Installing Spark 0.9.1 according to the documentation on the website,
> along with CDH4 (and another cluster with CDH5) distros of hadoop/hdfs.
> 2. Building a fat jar with a Spark app with sbt then trying to run it on the
> cluster
> I've also included code snippets, and sbt deps at the bottom.
> When I've Googled this, there seems to be two somewhat vague responses:
> a) Mismatching spark versions on nodes/user code
> b) Need to add more jars to the SparkConf
> Now I know that (b) is not the problem having successfully run the same code
> on other clusters while only including one jar (it's a fat jar).
> But I have no idea how to check for (a) - it appears Spark doesn't have any
> version checks or anything - it would be nice if it checked versions and
> threw a "mismatching version exception: you have user code using version X
> and node Y has version Z".
> I would be very grateful for advice on this.
> The exception:
> Exception in thread "main" org.apache.spark.SparkException: Job aborted: Task
> 0.0:1 failed 32 times (most recent failure: Exception failure:
> java.lang.IllegalStateException: unread block data)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1020)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1018)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1018)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:604)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:190)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> 14/05/16 18:05:31 INFO scheduler.TaskSetManager: Loss was due to
> java.lang.IllegalStateException: unread block data [duplicate 59]
> My code snippet:
> val conf = new SparkConf()
> .setMaster(clusterMaster)
> .setAppName(appName)
> .setSparkHome(sparkHome)
> .setJars(SparkContext.jarOfClass(this.getClass))
> println("count = " + new SparkContext(conf).textFile(someHdfsPath).count())
> My SBT dependencies:
> // relevant
> "org.apache.spark" % "spark-core_2.10" % "0.9.1",
> "org.apache.hadoop" % "hadoop-client" % "2.3.0-mr1-cdh5.0.0",
> // standard, probably unrelated
> "com.github.seratch" %% "awscala" % "[0.2,)",
> "org.scalacheck" %% "scalacheck" % "1.10.1" % "test",
> "org.specs2" %% "specs2" % "1.14" % "test",
> "org.scala-lang" % "scala-reflect" % "2.10.3",
> "org.scalaz" %% "scalaz-core" % "7.0.5",
> "net.minidev" % "json-smart" % "1.2"
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