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https://issues.apache.org/jira/browse/SPARK-1867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14322647#comment-14322647
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Sean Owen commented on SPARK-1867:
----------------------------------
With Bjorn Jonsson here, we think we located the cause, at least for those
people here using CDH 5.2. It seems to occur with the "MR1" flavor, when using
standalone mode (not YARN). The cause seemed to be that the MR1-flavored
dependencies get on the classpath along with non-MR1 Hadoop dependencies, and
So I'm going to re-resolve as not a problem _with Spark_ but a particular
packaging. Bjorn mentions it seems to be worked around with temporarily
changing an env variable for Spark's jobs: {{HADOOP_CONF_DIR to
/etc/hadoop/conf.cloudera.YARN-1}} It doesn't seem to happen with 5.3.
This might explain why people got it to work by using a 'stock' distribution;
in that case they'd not have any "MR1" dependencies, I believe.
This also relates to https://issues.apache.org/jira/browse/SPARK-4048 which may
have been the eventual fix; Marcelo might be able to comment.
(Also of interest, note that https://bugs.openjdk.java.net/browse/JDK-7172206
may be causing the real underlying exception to be masked, which doesn't help)
I don't know if it's specific to the CDH 5.2 MR1 stuff, and appears resolved
anyway later. If so, let's re-close as NotAProblem since it's not to do with
Spark, but I'll pause a beat for that.
> 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
> Components: Spark Core
> 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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