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Posted to issues@spark.apache.org by "Vishal Patel (JIRA)" <ji...@apache.org> on 2014/10/30 18:12:35 UTC
[jira] [Commented] (SPARK-1867) Spark Documentation Error causes
java.lang.IllegalStateException: unread block data
[ https://issues.apache.org/jira/browse/SPARK-1867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14190391#comment-14190391 ]
Vishal Patel commented on SPARK-1867:
-------------------------------------
I am getting the exact same error with Spark 1.1.0 and CDH 5.2.0.
I removed all mr1 artifacts from my pom file,
<!--Hadoop-->
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.5.0-cdh5.2.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.5.0-cdh5.2.0</version>
</dependency>
Even counting lines in a text file from HDFS with Kerberos on Yarn fails. However when I start spark-shell (and it essentially runs in local mode) the code works fine. Running on yarn with the only executor being the client also works. But when there are multiple worker nodes it fails with this error.
> 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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