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Spark and Java: Exception thrown in awaitResult

Tags:

java

scala

apache-spark

protocol-buffers

hdfs

I am trying to connect a Spark cluster running within a virtual machine with IP 10.20.30.50 and port 7077 from within a Java application and run the word count example:

SparkConf conf = new SparkConf().setMaster("spark://10.20.30.50:7077").setAppName("wordCount");
JavaSparkContext sc = new JavaSparkContext(conf);
JavaRDD<String> textFile = sc.textFile("hdfs://localhost:8020/README.md");
String result = Long.toString(textFile.count());
JavaRDD<String> words = textFile.flatMap((FlatMapFunction<String, String>) s -> Arrays.asList(s.split(" ")).iterator());
JavaPairRDD<String, Integer> pairs = words.mapToPair((PairFunction<String, String, Integer>) s -> new Tuple2<>(s, 1));
JavaPairRDD<String, Integer> counts = pairs.reduceByKey((Function2<Integer, Integer, Integer>) (a, b) -> a + b);
counts.saveAsTextFile("hdfs://localhost:8020/tmp/output");
sc.stop();
return result;

The Java application shows the following stack trace:

Running Spark version 2.0.1
Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Changing view acls to: lii5ka
Changing modify acls to: lii5ka
Changing view acls groups to:
Changing modify acls groups to:
SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(lii5ka); groups with view permissions: Set(); users  with modify permissions: Set(lii5ka); groups with modify permissions: Set()
Successfully started service 'sparkDriver' on port 61267.
Registering MapOutputTracker
Registering BlockManagerMaster
Created local directory at /private/var/folders/4k/h0sl02993_99bzt0dzv759000000gn/T/blockmgr-51de868d-3ba7-40be-8c53-f881f97ced63
MemoryStore started with capacity 2004.6 MB
Registering OutputCommitCoordinator
Logging initialized @48403ms
jetty-9.2.z-SNAPSHOT
Started o.s.j.s.ServletContextHandler@1316e7ec{/jobs,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@782de006{/jobs/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@2d0353{/jobs/job,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@381e24a0{/jobs/job/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@1c138dc8{/stages,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@b29739c{/stages/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@63f6de31{/stages/stage,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@2a04ddcb{/stages/stage/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@2af9688e{/stages/pool,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@6a0c5bde{/stages/pool/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@3f5e17f8{/storage,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@33b86f5d{/storage/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@5264dcbc{/storage/rdd,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@5a3ebf85{/storage/rdd/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@159082ed{/environment,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@6522c585{/environment/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@115774a1{/executors,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@3e3a3399{/executors/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@2f2c5959{/executors/threadDump,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@5c51afd4{/executors/threadDump/json,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@76893a83{/static,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@19c07930{/,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@54eb0dc0{/api,null,AVAILABLE}
Started o.s.j.s.ServletContextHandler@5953786{/stages/stage/kill,null,AVAILABLE}
Started ServerConnector@2eeb8bd6{HTTP/1.1}{0.0.0.0:4040}
Started @48698ms
Successfully started service 'SparkUI' on port 4040.
Bound SparkUI to 0.0.0.0, and started at http://192.168.0.104:4040
Connecting to master spark://10.20.30.50:7077...
Successfully created connection to /10.20.30.50:7077 after 25 ms (0 ms spent in bootstraps)
Connecting to master spark://10.20.30.50:7077...
Still have 2 requests outstanding when connection from /10.20.30.50:7077 is closed
Failed to connect to master 10.20.30.50:7077

org.apache.spark.SparkException: Exception thrown in awaitResult
        at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36) ~[scala-library-2.11.8.jar:na]
        at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167) ~[scala-library-2.11.8.jar:na]
        at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:88) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:96) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106) ~[spark-core_2.11-2.0.1.jar:2.0.1]
        at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) [na:1.8.0_102]
        at java.util.concurrent.FutureTask.run(FutureTask.java:266) [na:1.8.0_102]
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) [na:1.8.0_102]
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) [na:1.8.0_102]
        at java.lang.Thread.run(Thread.java:745) [na:1.8.0_102]
Caused by: java.io.IOException: Connection from /10.20.30.50:7077 closed
        at org.apache.spark.network.client.TransportResponseHandler.channelInactive(TransportResponseHandler.java:128) ~[spark-network-common_2.11-2.0.1.jar:2.0.1]
        at org.apache.spark.network.server.TransportChannelHandler.channelInactive(TransportChannelHandler.java:109) ~[spark-network-common_2.11-2.0.1.jar:2.0.1]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:208) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:194) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.ChannelInboundHandlerAdapter.channelInactive(ChannelInboundHandlerAdapter.java:75) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.handler.timeout.IdleStateHandler.channelInactive(IdleStateHandler.java:257) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:208) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:194) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.ChannelInboundHandlerAdapter.channelInactive(ChannelInboundHandlerAdapter.java:75) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:208) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:194) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.ChannelInboundHandlerAdapter.channelInactive(ChannelInboundHandlerAdapter.java:75) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at org.apache.spark.network.util.TransportFrameDecoder.channelInactive(TransportFrameDecoder.java:182) ~[spark-network-common_2.11-2.0.1.jar:2.0.1]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:208) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:194) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.DefaultChannelPipeline.fireChannelInactive(DefaultChannelPipeline.java:828) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.AbstractChannel$AbstractUnsafe$7.run(AbstractChannel.java:621) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:357) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:357) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111) ~[netty-all-4.0.29.Final.jar:4.0.29.Final]
        ... 1 common frames omitted

In the Spark Master log on 10.20.30.50, I get the following error message:

16/11/05 14:47:20 ERROR OneForOneStrategy: Error while decoding incoming Akka PDU of length: 1298
akka.remote.transport.AkkaProtocolException: Error while decoding incoming Akka PDU of length: 1298
Caused by: akka.remote.transport.PduCodecException: Decoding PDU failed.
    at akka.remote.transport.AkkaPduProtobufCodec$.decodePdu(AkkaPduCodec.scala:167)
    at akka.remote.transport.ProtocolStateActor.akka$remote$transport$ProtocolStateActor$$decodePdu(AkkaProtocolTransport.scala:580)
    at akka.remote.transport.ProtocolStateActor$$anonfun$4.applyOrElse(AkkaProtocolTransport.scala:375)
    at akka.remote.transport.ProtocolStateActor$$anonfun$4.applyOrElse(AkkaProtocolTransport.scala:343)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
    at akka.actor.FSM$class.processEvent(FSM.scala:604)
    at akka.remote.transport.ProtocolStateActor.processEvent(AkkaProtocolTransport.scala:269)
    at akka.actor.FSM$class.akka$actor$FSM$$processMsg(FSM.scala:598)
    at akka.actor.FSM$$anonfun$receive$1.applyOrElse(FSM.scala:592)
    at akka.actor.Actor$class.aroundReceive(Actor.scala:467)
    at akka.remote.transport.ProtocolStateActor.aroundReceive(AkkaProtocolTransport.scala:269)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    at akka.actor.ActorCell.invoke(ActorCell.scala:487)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
    at akka.dispatch.Mailbox.run(Mailbox.scala:220)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: com.google.protobuf.InvalidProtocolBufferException: Protocol message contained an invalid tag (zero).
    at com.google.protobuf.InvalidProtocolBufferException.invalidTag(InvalidProtocolBufferException.java:89)
    at com.google.protobuf.CodedInputStream.readTag(CodedInputStream.java:108)
    at akka.remote.WireFormats$AkkaProtocolMessage.<init>(WireFormats.java:6643)
    at akka.remote.WireFormats$AkkaProtocolMessage.<init>(WireFormats.java:6607)
    at akka.remote.WireFormats$AkkaProtocolMessage$1.parsePartialFrom(WireFormats.java:6703)
    at akka.remote.WireFormats$AkkaProtocolMessage$1.parsePartialFrom(WireFormats.java:6698)
    at com.google.protobuf.AbstractParser.parsePartialFrom(AbstractParser.java:141)
    at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:176)
    at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:188)
    at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:193)
    at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:49)
    at akka.remote.WireFormats$AkkaProtocolMessage.parseFrom(WireFormats.java:6821)
    at akka.remote.transport.AkkaPduProtobufCodec$.decodePdu(AkkaPduCodec.scala:168)
    ... 19 more

Additional Information

  • The example works fine when I use new SparkConf().setMaster("local") instead
  • I can connect to the Spark Master with spark-shell --master spark://10.20.30.50:7077 on the very same machine
like image 575
Michael Lihs Avatar asked Nov 05 '16 14:11

Michael Lihs

2 Answers

Looks like network error in the first place (but actually NOT) in the disguise of version mismatch of spark . You can point to correct version of spark jars mostly assembly jars.

This issue may happen due to version miss match in Hadoop RPC call using Protobuffer.

when a protocol message being parsed is invalid in some way, e.g. it contains a malformed varint or a negative byte length.

  • My experience with protobuf, InvalidProtocolBufferException can happen, only when the message was not able to parse(programatically if you are parsing protobuf message, may be message legth is zero or message is corrupted...).

  • Spark uses Akka Actors for Message Passing between Master/Driver and Workers and Internally akka uses googles protobuf to communicate. see method below from AkkaPduCodec.scala)

    override def decodePdu(raw: ByteString): AkkaPdu = {
    try {
      val pdu = AkkaProtocolMessage.parseFrom(raw.toArray)
      if (pdu.hasPayload) Payload(ByteString(pdu.getPayload.asReadOnlyByteBuffer()))
      else if (pdu.hasInstruction) decodeControlPdu(pdu.getInstruction)
      else throw new PduCodecException("Error decoding Akka PDU: Neither message nor control message were contained", null)
    } catch {
      case e: InvalidProtocolBufferException ⇒ throw new PduCodecException("Decoding PDU failed.", e)
    }
  }

But in your case, since its version mismatch, new protobuf version message cant be parsed from old version of parser... or something like...

If you are using maven other dependencies, pls. review.

like image 179
Ram Ghadiyaram Avatar answered Oct 05 '22 23:10

Ram Ghadiyaram

It turned out that I had Spark version 1.5.2 running in the virtual machine and used version 2.0.1 of the Spark library in Java. I fixed the issue by using the appropriate Spark library version in my pom.xml which is

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-core_2.10</artifactId>
    <version>1.5.2</version>
</dependency>

Another problem (that occurred later) was, that I also had to pin the Scala version with which the library was build. This is the _2.10 suffix in the artifactId.

Basically @RamPrassad's answer pointed me into the right direction but didn't give a clear advice what I need to do to fix my problem.

By the way: I couldn't update Spark in the virtual machine, since it was brought to me by the HortonWorks distribution...

like image 20
Michael Lihs Avatar answered Oct 06 '22 01:10

Michael Lihs
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