Skip to content
This repository has been archived by the owner on Nov 23, 2017. It is now read-only.

Getting InvalidClassException when running SparkPi example locally but pointing to master on AWS #92

Open
matthewadams opened this issue Mar 8, 2017 · 2 comments
Open

Getting InvalidClassException when running SparkPi example locally but pointing to master on AWS #92

matthewadams opened this issue Mar 8, 2017 · 2 comments

Comments

@matthewadams
Copy link

I'm getting the error below when attempting to bin/run-example --master spark://ec2-000-000-000-000.compute-1.amazonaws.com:7077 SparkPi 10 from my local machine (ips changed to protect the innocent). This was run with a custom build/distribution of spark 2.0.2 using scala 2.10 with hadoop 2.4 (via build commands ./dev/change-scala-version.sh 2.10 && ./dev/make-distribution.sh --name custom-spark --tgz -Phadoop-2.4 -Dscala-2.10 -DskipTests).

Note that this also happens using vanilla binary distributions of spark 2.0.2 & 2.1.0 (as mentioned in #91 (comment)).

$ bin/run-example --master spark://ec2-000-000-000-000.compute-1.amazonaws.com:7077 SparkPi 10
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Users/matthew/Documents/spark-2.0.2-bin-custom-spark/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/matthew/Documents/spark-2.0.2/hadoop-2.4.1/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
17/03/08 10:16:49 INFO spark.SparkContext: Running Spark version 2.0.2
17/03/08 10:16:50 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/03/08 10:16:50 INFO spark.SecurityManager: Changing view acls to: matthew
17/03/08 10:16:50 INFO spark.SecurityManager: Changing modify acls to: matthew
17/03/08 10:16:50 INFO spark.SecurityManager: Changing view acls groups to:
17/03/08 10:16:50 INFO spark.SecurityManager: Changing modify acls groups to:
17/03/08 10:16:50 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(matthew); groups with view permissions: Set(); users  with modify permissions: Set(matthew); groups with modify permissions: Set()
17/03/08 10:16:51 INFO util.Utils: Successfully started service 'sparkDriver' on port 56731.
17/03/08 10:16:51 INFO spark.SparkEnv: Registering MapOutputTracker
17/03/08 10:16:51 INFO spark.SparkEnv: Registering BlockManagerMaster
17/03/08 10:16:51 INFO storage.DiskBlockManager: Created local directory at /private/var/folders/8c/4kr7cmf109b4778xj0sxct8w0000gn/T/blockmgr-85536df3-360a-4a21-9ad3-eadaa5efec32
17/03/08 10:16:51 INFO memory.MemoryStore: MemoryStore started with capacity 366.3 MB
17/03/08 10:16:51 INFO spark.SparkEnv: Registering OutputCommitCoordinator
17/03/08 10:16:51 INFO util.log: Logging initialized @2615ms
17/03/08 10:16:51 INFO server.Server: jetty-9.2.z-SNAPSHOT
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@27953a83{/jobs,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@556d0826{/jobs/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@66ce957f{/jobs/job,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@55b5f5d2{/jobs/job/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5bfa8cc5{/stages,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@666b83a4{/stages/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@749c877b{/stages/stage,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@efde75f{/stages/stage/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@16ecee1{/stages/pool,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3b220bcb{/stages/pool/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2b95e48b{/storage,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4a3329b9{/storage/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3dddefd8{/storage/rdd,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@160ac7fb{/storage/rdd/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@12bfd80d{/environment,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@41925502{/environment/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@13e3c1c7{/executors,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5316e95f{/executors/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3f053c80{/executors/threadDump,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@6c6c5427{/executors/threadDump/json,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@618c5d94{/static,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5b40ceb{/,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@13c3c1e1{/api,null,AVAILABLE}
17/03/08 10:16:51 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1d8062d2{/stages/stage/kill,null,AVAILABLE}
17/03/08 10:16:51 INFO server.ServerConnector: Started ServerConnector@3e34ace1{HTTP/1.1}{0.0.0.0:4040}
17/03/08 10:16:51 INFO server.Server: Started @2796ms
17/03/08 10:16:51 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
17/03/08 10:16:51 INFO ui.SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.86.165:4040
17/03/08 10:16:51 INFO spark.SparkContext: Added JAR file:/Users/matthew/Documents/spark-2.0.2-bin-custom-spark/./examples/jars/scopt_2.10-3.3.0.jar at spark://192.168.86.165:56731/jars/scopt_2.10-3.3.0.jar with timestamp 1488989811622
17/03/08 10:16:51 INFO spark.SparkContext: Added JAR file:/Users/matthew/Documents/spark-2.0.2-bin-custom-spark/./examples/jars/spark-examples_2.10-2.0.2.jar at spark://192.168.86.165:56731/jars/spark-examples_2.10-2.0.2.jar with timestamp 1488989811623
17/03/08 10:16:51 INFO client.StandaloneAppClient$ClientEndpoint: Connecting to master spark://ec2-000-000-000-000.compute-1.amazonaws.com:7077...
17/03/08 10:16:51 INFO client.TransportClientFactory: Successfully created connection to ec2-000-000-000-000.compute-1.amazonaws.com/54.242.200.97:7077 after 89 ms (0 ms spent in bootstraps)
17/03/08 10:16:52 WARN client.StandaloneAppClient$ClientEndpoint: Failed to connect to master ec2-000-000-000-000.compute-1.amazonaws.com:7077
org.apache.spark.SparkException: Exception thrown in awaitResult
	at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
	at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
	at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
	at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
	at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
	at scala.PartialFunction$OrElse.apply(PartialFunction.scala:162)
	at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
	at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:88)
	at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:96)
	at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106)
	at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
	at java.util.concurrent.FutureTask.run(FutureTask.java:266)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: java.io.InvalidClassException: org.apache.spark.rpc.netty.RequestMessage; local class incompatible: stream classdesc serialVersionUID = -2221986757032131007, local class serialVersionUID = -5447855329526097695
	at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:612)
	at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1827)
	at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1711)
	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1982)
	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1533)
	at java.io.ObjectInputStream.readObject(ObjectInputStream.java:420)
	at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
	at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:108)
	at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1$$anonfun$apply$1.apply(NettyRpcEnv.scala:259)
	at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
	at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:308)
	at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1.apply(NettyRpcEnv.scala:258)
	at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
	at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:257)
	at org.apache.spark.rpc.netty.NettyRpcHandler.internalReceive(NettyRpcEnv.scala:578)
	at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:563)
	at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:158)
	at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:106)
	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:119)
	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
	at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
	at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
	at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
	at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
	at java.lang.Thread.run(Thread.java:745)

	at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:189)
	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:121)
	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
	at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85)
	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
	at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
	at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
	at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
	at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
	... 1 more
^C17/03/08 10:17:07 INFO storage.DiskBlockManager: Shutdown hook called
17/03/08 10:17:07 INFO util.ShutdownHookManager: Shutdown hook called
17/03/08 10:17:07 INFO util.ShutdownHookManager: Deleting directory /private/var/folders/8c/4kr7cmf109b4778xj0sxct8w0000gn/T/spark-3ee19a3f-06d8-49d0-bfeb-107440f39b86/userFiles-8766d2fb-8a8f-4743-9fe2-c0a8194d5d4e
17/03/08 10:17:07 INFO util.ShutdownHookManager: Deleting directory /private/var/folders/8c/4kr7cmf109b4778xj0sxct8w0000gn/T/spark-3ee19a3f-06d8-49d0-bfeb-107440f39b86

It is worth noting that if I ssh into the master and run the example from there, everything works fine:

$ ssh -i ~/.ssh/spark-test.pem [email protected]
The authenticity of host 'ec2-000-000-000-000.compute-1.amazonaws.com (000.000.000.000)' can't be established.
ECDSA key fingerprint is SHA256:oJSRdeS1dzKORChh/lIQPTEEbR1y7zOxsH6q8f2beqY.
Are you sure you want to continue connecting (yes/no)? yes
Warning: Permanently added 'ec2-000-000-000-000.compute-1.amazonaws.com,000.000.000.000' (ECDSA) to the list of known hosts.
Last login: Wed Mar  8 16:07:52 2017 from ip-172-31-35-30.ec2.internal

       __|  __|_  )
       _|  (     /   Amazon Linux AMI
      ___|\___|___|

https://aws.amazon.com/amazon-linux-ami/2013.03-release-notes/
Amazon Linux version 2016.09 is available.
root@ip-172-31-35-30 ~]$ cd spark
root@ip-172-31-35-30 spark]$ ls -al
total 116
drwxr-xr-x 13 hadoop ec2-user  4096 Mar  8 16:11 .
drwxr-xr-x 18 root   root      4096 Mar  8 16:11 ..
drwxr-xr-x  2 hadoop ec2-user  4096 Jul 19  2016 bin
drwxr-xr-x  2 hadoop ec2-user  4096 Mar  8 16:11 conf
drwxr-xr-x  5 hadoop ec2-user  4096 Jul 19  2016 data
drwxr-xr-x  4 hadoop ec2-user  4096 Jul 19  2016 examples
drwxr-xr-x  2 hadoop ec2-user 12288 Jul 19  2016 jars
-rw-r--r--  1 hadoop ec2-user 17811 Jul 19  2016 LICENSE
drwxr-xr-x  2 hadoop ec2-user  4096 Jul 19  2016 licenses
drwxr-xr-x  2 root   root      4096 Mar  8 16:11 logs
-rw-r--r--  1 hadoop ec2-user 24749 Jul 19  2016 NOTICE
drwxr-xr-x  6 hadoop ec2-user  4096 Jul 19  2016 python
drwxr-xr-x  3 hadoop ec2-user  4096 Jul 19  2016 R
-rw-r--r--  1 hadoop ec2-user  3828 Jul 19  2016 README.md
-rw-r--r--  1 hadoop ec2-user   120 Jul 19  2016 RELEASE
drwxr-xr-x  2 hadoop ec2-user  4096 Jul 19  2016 sbin
drwxr-xr-x  2 hadoop ec2-user  4096 Jul 19  2016 yarn
root@ip-172-31-35-30 spark]$ echo $PATH
/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/root/scala/bin
root@ip-172-31-35-30 spark]$ bin/run-example SparkPi 10
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
17/03/08 16:22:04 INFO SparkContext: Running Spark version 2.0.0
17/03/08 16:22:05 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/03/08 16:22:05 INFO SecurityManager: Changing view acls to: root
17/03/08 16:22:05 INFO SecurityManager: Changing modify acls to: root
17/03/08 16:22:05 INFO SecurityManager: Changing view acls groups to:
17/03/08 16:22:05 INFO SecurityManager: Changing modify acls groups to:
17/03/08 16:22:05 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(root); groups with view permissions: Set(); users  with modify permissions: Set(root); groups with modify permissions: Set()
17/03/08 16:22:06 INFO Utils: Successfully started service 'sparkDriver' on port 51608.
17/03/08 16:22:06 INFO SparkEnv: Registering MapOutputTracker
17/03/08 16:22:06 INFO SparkEnv: Registering BlockManagerMaster
17/03/08 16:22:06 INFO DiskBlockManager: Created local directory at /mnt/spark/blockmgr-dc6fefba-3b3c-4f16-8383-b09687429150
17/03/08 16:22:06 INFO DiskBlockManager: Created local directory at /mnt2/spark/blockmgr-718052d3-6022-4f55-8d30-0673994c1f25
17/03/08 16:22:06 INFO MemoryStore: MemoryStore started with capacity 366.3 MB
17/03/08 16:22:06 INFO SparkEnv: Registering OutputCommitCoordinator
17/03/08 16:22:07 INFO Utils: Successfully started service 'SparkUI' on port 4040.
17/03/08 16:22:07 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://ec2-54-242-200-97.compute-1.amazonaws.com:4040
17/03/08 16:22:07 INFO SparkContext: Added JAR file:/root/spark/examples/jars/spark-examples_2.11-2.0.0.jar at spark://172.31.35.30:51608/jars/spark-examples_2.11-2.0.0.jar with timestamp 1488990127275
17/03/08 16:22:07 INFO SparkContext: Added JAR file:/root/spark/examples/jars/scopt_2.11-3.3.0.jar at spark://172.31.35.30:51608/jars/scopt_2.11-3.3.0.jar with timestamp 1488990127276
17/03/08 16:22:07 INFO StandaloneAppClient$ClientEndpoint: Connecting to master spark://ec2-54-242-200-97.compute-1.amazonaws.com:7077...
17/03/08 16:22:07 INFO TransportClientFactory: Successfully created connection to ec2-54-242-200-97.compute-1.amazonaws.com/172.31.35.30:7077 after 67 ms (0 ms spent in bootstraps)
17/03/08 16:22:07 INFO StandaloneSchedulerBackend: Connected to Spark cluster with app ID app-20170308162207-0000
17/03/08 16:22:07 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 47935.
17/03/08 16:22:07 INFO NettyBlockTransferService: Server created on 172.31.35.30:47935
17/03/08 16:22:07 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 172.31.35.30, 47935)
17/03/08 16:22:07 INFO BlockManagerMasterEndpoint: Registering block manager 172.31.35.30:47935 with 366.3 MB RAM, BlockManagerId(driver, 172.31.35.30, 47935)
17/03/08 16:22:07 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 172.31.35.30, 47935)
17/03/08 16:22:07 INFO StandaloneAppClient$ClientEndpoint: Executor added: app-20170308162207-0000/0 on worker-20170308161225-172.31.41.253-58836 (172.31.41.253:58836) with 2 cores
17/03/08 16:22:07 INFO StandaloneSchedulerBackend: Granted executor ID app-20170308162207-0000/0 on hostPort 172.31.41.253:58836 with 2 cores, 6.0 GB RAM
17/03/08 16:22:08 INFO StandaloneAppClient$ClientEndpoint: Executor updated: app-20170308162207-0000/0 is now RUNNING
17/03/08 16:22:08 INFO StandaloneSchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
17/03/08 16:22:08 WARN SparkContext: Use an existing SparkContext, some configuration may not take effect.
17/03/08 16:22:08 INFO SharedState: Warehouse path is 'file:/root/spark/spark-warehouse'.
17/03/08 16:22:08 INFO SparkContext: Starting job: reduce at SparkPi.scala:38
17/03/08 16:22:08 INFO DAGScheduler: Got job 0 (reduce at SparkPi.scala:38) with 10 output partitions
17/03/08 16:22:08 INFO DAGScheduler: Final stage: ResultStage 0 (reduce at SparkPi.scala:38)
17/03/08 16:22:08 INFO DAGScheduler: Parents of final stage: List()
17/03/08 16:22:08 INFO DAGScheduler: Missing parents: List()
17/03/08 16:22:08 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34), which has no missing parents
17/03/08 16:22:09 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 1832.0 B, free 366.3 MB)
17/03/08 16:22:09 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1169.0 B, free 366.3 MB)
17/03/08 16:22:09 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.31.35.30:47935 (size: 1169.0 B, free: 366.3 MB)
17/03/08 16:22:09 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1012
17/03/08 16:22:09 INFO DAGScheduler: Submitting 10 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34)
17/03/08 16:22:09 INFO TaskSchedulerImpl: Adding task set 0.0 with 10 tasks
17/03/08 16:22:11 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Registered executor NettyRpcEndpointRef(null) (172.31.41.253:59470) with ID 0
17/03/08 16:22:11 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, 172.31.41.253, partition 0, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:11 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, 172.31.41.253, partition 1, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:11 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 0 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:11 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 1 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:11 INFO BlockManagerMasterEndpoint: Registering block manager 172.31.41.253:48508 with 3.0 GB RAM, BlockManagerId(0, 172.31.41.253, 48508)
17/03/08 16:22:12 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.31.41.253:48508 (size: 1169.0 B, free: 3.0 GB)
17/03/08 16:22:13 INFO TaskSetManager: Starting task 2.0 in stage 0.0 (TID 2, 172.31.41.253, partition 2, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 2 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Starting task 3.0 in stage 0.0 (TID 3, 172.31.41.253, partition 3, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 3 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 1567 ms on 172.31.41.253 (1/10)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 1527 ms on 172.31.41.253 (2/10)
17/03/08 16:22:13 INFO TaskSetManager: Starting task 4.0 in stage 0.0 (TID 4, 172.31.41.253, partition 4, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 4 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Starting task 5.0 in stage 0.0 (TID 5, 172.31.41.253, partition 5, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 5 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Finished task 2.0 in stage 0.0 (TID 2) in 140 ms on 172.31.41.253 (3/10)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 3.0 in stage 0.0 (TID 3) in 138 ms on 172.31.41.253 (4/10)
17/03/08 16:22:13 INFO TaskSetManager: Starting task 6.0 in stage 0.0 (TID 6, 172.31.41.253, partition 6, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 4.0 in stage 0.0 (TID 4) in 91 ms on 172.31.41.253 (5/10)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 6 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Starting task 7.0 in stage 0.0 (TID 7, 172.31.41.253, partition 7, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 5.0 in stage 0.0 (TID 5) in 91 ms on 172.31.41.253 (6/10)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 7 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Starting task 8.0 in stage 0.0 (TID 8, 172.31.41.253, partition 8, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 6.0 in stage 0.0 (TID 6) in 97 ms on 172.31.41.253 (7/10)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 8 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Starting task 9.0 in stage 0.0 (TID 9, 172.31.41.253, partition 9, PROCESS_LOCAL, 5476 bytes)
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching task 9 on executor id: 0 hostname: 172.31.41.253.
17/03/08 16:22:13 INFO TaskSetManager: Finished task 7.0 in stage 0.0 (TID 7) in 95 ms on 172.31.41.253 (8/10)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 8.0 in stage 0.0 (TID 8) in 95 ms on 172.31.41.253 (9/10)
17/03/08 16:22:13 INFO TaskSetManager: Finished task 9.0 in stage 0.0 (TID 9) in 87 ms on 172.31.41.253 (10/10)
17/03/08 16:22:13 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
17/03/08 16:22:13 INFO DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:38) finished in 4.653 s
17/03/08 16:22:13 INFO DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 4.983803 s
Pi is roughly 3.1415351415351416
17/03/08 16:22:13 INFO SparkUI: Stopped Spark web UI at http://ec2-54-242-200-97.compute-1.amazonaws.com:4040
17/03/08 16:22:13 INFO StandaloneSchedulerBackend: Shutting down all executors
17/03/08 16:22:13 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Asking each executor to shut down
17/03/08 16:22:13 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/03/08 16:22:13 INFO MemoryStore: MemoryStore cleared
17/03/08 16:22:13 INFO BlockManager: BlockManager stopped
17/03/08 16:22:13 INFO BlockManagerMaster: BlockManagerMaster stopped
17/03/08 16:22:13 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/03/08 16:22:13 INFO SparkContext: Successfully stopped SparkContext
17/03/08 16:22:13 INFO ShutdownHookManager: Shutdown hook called
17/03/08 16:22:13 INFO ShutdownHookManager: Deleting directory /mnt/spark/spark-f7efb8fc-a042-4892-8f47-f6ff0a1c4ecc
17/03/08 16:22:13 INFO ShutdownHookManager: Deleting directory /mnt2/spark/spark-781f6c72-86b1-4b54-b8d8-d705c7796bf0
root@ip-172-31-35-30 spark]$
@shivaram
Copy link
Contributor

shivaram commented Mar 8, 2017

I dont think spark-ec2 is designed to run with the client on your machine and a cluster on EC2. Its designed to run with the client on the master machine and the cluster on EC2. FWIW I think the version of Spark running on cluster needs to exactly match the version on the client for things to work -- that is anyway a question for the user mailing list / stack overflow.

@matthewadams
Copy link
Author

@shivaram said:

the version of Spark running on cluster needs to exactly match the version on the client for things to work

@shivaram, that is exactly what I did. I ensured that my local scala, spark & hadoop versions exactly matched what was on the server.

Since I've burned so much time on spark-ec2, I'm now trying to use Amazon EMR and having good success. Pointers to comparisons between spark-ec2 and Spark on Amazon EMR would be appreciated.

Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@shivaram @matthewadams