sam created SPARK-1867:
--------------------------
Summary: 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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