Spark and Java: Exception thrown in awaitResult

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 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

4 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.

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...

This error also happens when you have strange characters that you wanna insert into a table, for example:

INSERT INTO mytable (select 'GARDENﬠy para el uso para el control de rat쟣om﷠rata' as text) 

So the solution is to change the encoding text or to remove these special characters like this:

INSERT INTO mytable (select regexp_replace('GARDENﬠy para el uso para el control de rat쟣om﷠rata', '[\u0100-\uffff]', '') as text) 

I got this same error while trying to read in data from my SQL table. My particular issue was that I did not give the SQL user sufficient permissions to read in the data.

My SQL user had permission to run a SELECT statement, but when I look at the log via select * from stv_recents (on redshift) I saw that it also performs a UNLOAD command to s3. Here's a resource to GRANT permissions on redshift

Not sure if this is still relevant for you seeing that this was almost 6 years ago, but I see this in your error:

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()

which looks like you also didn't have sufficient permissions set on your SQL user

ncG1vNJzZmirpJawrLvVnqmfpJ%2Bse6S7zGiorp2jqbawutJoa2lsY26Ddn6OrKeaqptirq%2BwjKOYr5ldmsWksc%2BtoKimXam1s7vWp2Sipl2WxKK106ucrK2cqQ%3D%3D