Worker failed to connect to master in Spark Apache - apache-spark

I'm deploying a Spark Apache application using standalone cluster manager. My architecture uses 2 Windows machines: one set as a master, and another set as a slave (worker).
Master: on which I run: \bin>spark-class org.apache.spark.deploy.master.Master and this is what the web UI shows:
Slave: on which I run: \bin>spark-class org.apache.spark.deploy.worker.Worker spark://192.*.*.186:7077 and this what what the web UI shows:
The problem is that the worker node can not connect to the master node and shows the following error:
17/09/26 16:05:17 INFO Worker: Connecting to master 192.*.*.186:7077...
17/09/26 16:05:22 WARN Worker: Failed to connect to master 192.*.*.186:7077
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:108)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1$$anon$1.run(Worker.scala:241)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Failed to connect to /192.*.*.186:7077
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:232)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:182)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:197)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:194)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:190)
... 4 more
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Connection timed out: no further information: /192.*.*.186:7077
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:257)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:291)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:631)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:566)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:480)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:442)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
... 1 more
What can be the case of this error knowing that the firewall is disabled for both machines and I tested the connection between them both (using nmap) and everything is OK! But using telnet I receive this error: Connecting To 192.*.*.186...Could not open connection to the host, on port 23: Connect failed

Can you show me your spark-env.sh conf? This would help to pinpoint your problem.
My first idea is that you need to export SPARK_MASTER_HOST=(master ip) instead of SPARK_MASTER_IP in spark-env.sh file. You need to do it for both master and slave. Also export SPARK_LOCAL_IP for both master and slave.

You need to set your environment path to SPARK_MASTER_HOST & SPARK_LOCAL_HOST to localhost.
SPARK_LOCAL_IP & SPARK_MASTER_IP is now deprecated.

Related

Apache Spark Cluster\Windows: Getting Connection refused: no further information from worker node

I need help please getting spark working in windows cluster of 3 nodes. I am able to download and configure and run the master node and worker nodes. the worker nodes are registered successfully with the master. Im able to see both worker nodes in the Master UI. When I try to submit a job using:
spark-submit --master spark://IP:7077 hello_world.py
Spark continuously try to start multiple executors but the all failed with code exit 1 and it doesnt stop until I kill it. when I check the log in the UI for each worker Im seeing the following error:
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1894)
at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:61)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:424)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:413)
at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:301)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:102)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.$anonfun$run$9(CoarseGrainedExecutorBackend.scala:444)
at scala.runtime.java8.JFunction1$mcVI$sp.apply(JFunction1$mcVI$sp.java:23)
at scala.collection.TraversableLike$WithFilter.$anonfun$foreach$1(TraversableLike.scala:985)
at scala.collection.immutable.Range.foreach(Range.scala:158)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:984)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.$anonfun$run$7(CoarseGrainedExecutorBackend.scala:442)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:62)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:61)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878)
... 4 more
**Caused by: java.io.IOException: Failed to connect to <Master DNS>/<Master IP>:56785
at **org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:288)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:204)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:202)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:198)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Connection refused: no further information: <Master DNS>/<Master IP>:56785
Caused by: java.net.ConnectException: Connection refused: no further information
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:715)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:330)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:334)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:710)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:658)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:584)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:496)
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:986)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
Im using Spark: spark-3.3.1-bin-hadoop3
Please help.
Thanks
The application to run

How to handle dynamic port in Apache Spark / Hadoop Yarn

I have setup a Hadoop cluster with 1 name node and 2 data nodes. I've also installed Yarn and Spark on top of that in the name node.
I notice that whenever I try run the example jar here:
spark-submit --deploy-mode cluster --class org.apache.spark.examples.SparkPi $SPARK_HOME/examples/jars/spark-examples_*.jar 10
I will always get the no route to host exception:
Uncaught exception: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:301)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:102)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:110)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:558)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:277)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:926)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:925)
at java.base/java.security.AccessController.doPrivileged(Native Method)
at java.base/javax.security.auth.Subject.doAs(Subject.java:423)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:925)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:957)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.io.IOException: Failed to connect to lnx-pen205/xx.xx.xx.xx:9222
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:288)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:204)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:202)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:198)
at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: io.netty.channel.AbstractChannel$AnnotatedNoRouteToHostException: No route to host: lnx-pen205/xx.xx.xx.xx:9222
Caused by: java.net.NoRouteToHostException: No route to host
at java.base/sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at java.base/sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:777)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:330)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:334)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:710)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:658)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:584)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:496)
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:986)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.base/java.lang.Thread.run(Thread.java:829)
I noticed that the port being used will be randomly assigned during the runtime, the example .jar will work if for example I set the spark.driver.port as 9222 then opening said port with the firewall. But then if any other session is started (for example, pyspark shell), it wouldn't start as the port is already in use.
My question is: How do I allow connections to the ports dynamically defined by Spark/Yarn? I read somewhere that I should disable the firewall, but that does not sound like a good idea.. Thanks in advance.
There's spark.driver.port as well as spark.driver.blockManager.port. Both are starting ranges to spark.port.maxRetries (default 16).
So, you'll need to open at least 32 ports for these.
I did some testing with dynamic Spark ports in Mesos + Docker a few years ago - https://stackoverflow.com/a/56486271/2308683

Apache Zeppelin - Zeppelin tutorial failed to create interpreter - Connection refused

I am trying to test Zeppelin 0.6.2 with a Spark 2.0.1 installed in a Windows Server 2012.
I started the Spark master and tested the Spark Shell.
Then I configured the following in the conf\zeppeling-env.cmd file:
set SPARK_HOME=C:\spark-2.0.1-bin-hadoop2.7
set MASTER=spark://100.79.240.26:7077
I have not set the HADOOP_CONF_DIR and SPARK_SUBMIT_OPTIONS (that is optional according to the documentation)
I checked the values in the Interpreter configuration page and the spark master is Ok.
When I run the Zeppelin tutorial --> "Load data into table" note I am getting a connection refused error. Here is part of the messages in the error log:
INFO [2016-11-17 21:58:12,518] ({pool-1-thread-11} Paragraph.java[jobRun]:252) - run paragraph 20150210-015259_1403135953 using null org.apache.zeppelin.interpreter.LazyOpenInterpreter#8bbfd7
INFO [2016-11-17 21:58:12,518] ({pool-1-thread-11} RemoteInterpreterProcess.java[reference]:148) - Run interpreter process [C:\zeppelin-0.6.2-bin-all\bin\interpreter.cmd, -d, C:\zeppelin-0.6.2-bin-all\interpreter\spark, -p, 50163, -l, C:\zeppelin-0.6.2-bin-all/local-repo/2C3FBS414]
INFO [2016-11-17 21:58:12,614] ({Exec Default Executor} RemoteInterpreterProcess.java[onProcessFailed]:288) - Interpreter process failed {}
org.apache.commons.exec.ExecuteException: Process exited with an error: 255 (Exit value: 255)
at org.apache.commons.exec.DefaultExecutor.executeInternal(DefaultExecutor.java:404)
at org.apache.commons.exec.DefaultExecutor.access$200(DefaultExecutor.java:48)
at org.apache.commons.exec.DefaultExecutor$1.run(DefaultExecutor.java:200)
at java.lang.Thread.run(Thread.java:745)
ERROR [2016-11-17 21:58:43,846] ({Thread-49} RemoteScheduler.java[getStatus]:255) - Can't get status information
org.apache.zeppelin.interpreter.InterpreterException: org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection refused: connect
at org.apache.zeppelin.interpreter.remote.ClientFactory.create(ClientFactory.java:53)
at org.apache.zeppelin.interpreter.remote.ClientFactory.create(ClientFactory.java:37)
at org.apache.commons.pool2.BasePooledObjectFactory.makeObject(BasePooledObjectFactory.java:60)
at org.apache.commons.pool2.impl.GenericObjectPool.create(GenericObjectPool.java:861)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:435)
at org.apache.commons.pool2.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:363)
at org.apache.zeppelin.interpreter.remote.RemoteInterpreterProcess.getClient(RemoteInterpreterProcess.java:189)
at org.apache.zeppelin.scheduler.RemoteScheduler$JobStatusPoller.getStatus(RemoteScheduler.java:253)
at org.apache.zeppelin.scheduler.RemoteScheduler$JobStatusPoller.run(RemoteScheduler.java:211)
Caused by: org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection refused: connect
at org.apache.thrift.transport.TSocket.open(TSocket.java:187)
at org.apache.zeppelin.interpreter.remote.ClientFactory.create(ClientFactory.java:51)
... 8 more
Caused by: java.net.ConnectException: Connection refused: connect
at java.net.DualStackPlainSocketImpl.connect0(Native Method)
at java.net.DualStackPlainSocketImpl.socketConnect(DualStackPlainSocketImpl.java:79)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:339)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:200)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:182)
at java.net.PlainSocketImpl.connect(PlainSocketImpl.java:172)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:579)
at org.apache.thrift.transport.TSocket.open(TSocket.java:182)
... 9 more
ERROR [2016-11-17 21:58:43,846] ({pool-1-thread-11} Job.java[run]:189) - Job failed
org.apache.zeppelin.interpreter.InterpreterException: org.apache.zeppelin.interpreter.InterpreterException: org.apache.thrift.transport.TTransportException: java.net.ConnectException: Connection refused: connect
at org.apache.zeppelin.interpreter.remote.RemoteInterpreter.init(RemoteInterpreter.java:165)
at org.apache.zeppelin.interpreter.remote.RemoteInterpreter.getFormType(RemoteInterpreter.java:328)
at org.apache.zeppelin.interpreter.LazyOpenInterpreter.getFormType(LazyOpenInterpreter.java:105)
at org.apache.zeppelin.notebook.Paragraph.jobRun(Paragraph.java:260)
at org.apache.zeppelin.scheduler.Job.run(Job.java:176)
at org.apache.zeppelin.scheduler.RemoteScheduler$JobRunner.run(RemoteScheduler.java:328)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
In the Zeppelin logs there is only one file for zeppelin, the interpreter is an external Spark installation, which is not logging any error because it is never reached by the interpreter process.
I read some suggestion about the max and min memory of the JVM but I could not fix it yet.
Any comment will be appreciated.
Paul

Spark ec2 web services start up error

I am starting spark cluster in amazon EC2. In web UI I could see 2 instances(1 master and 1 slave) running and I am able to ssh to those instances. I opened up port 7077 inbound. When I try to launch the spark shell using the below command, I am getting an error. Any help would be appreciated.
spark-shell --master spark://ec2-54-173-210-192.compute-1.amazonaws.com:7077
Logs:
java.io.IOException: Failed to connect to ec2-54-173-210-192.compute-1.amazonaws.com/54.173.210.192:7077
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:200)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:187)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:183)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: ec2-54-173-210-192.compute-1.amazonaws.com/54.173.210.192:7077
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
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
Not really solving the problem but just a suggestion: If you want a Spark cluster on Amazon, try Spark on Amazon EMR before EC2. EMR lets you launch a managed cluster of any size to which Spark can be added as a preinstalled application. No need to configure hosts/ports yourself.

Intellij connect hortonwork spark remotely failed

I have a hortonwork sandbox 2.4 with spark 1.6 set up. Then I create Intellij spark development environment in windows using hdp spark jar and scala 2.10.5. So both spark and scala version are matched between my windows and hdp environment as indicated here. And my Intellij dev environment works with local as Master.
Then I'm trying to connect hdp in windows using
val sparkConf = new SparkConf()
.setAppName("spark-word-count")
.setMaster("spark://10.33.241.160:7077")
And I get below error information and have no clue to resolve it. Please help!
6/03/21 16:27:40 INFO SparkUI: Started SparkUI at http://10.33.240.126:4040
16/03/21 16:27:40 INFO AppClient$ClientEndpoint: Connecting to master spark://10.33.241.160:7077...
16/03/21 16:27:41 WARN AppClient$ClientEndpoint: Failed to connect to master 10.33.241.160:7077
java.io.IOException: Failed to connect to /10.33.241.160:7077
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:200)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:187)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:183)
at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:334)
at java.util.concurrent.FutureTask.run(FutureTask.java:166)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:722)
Caused by: java.net.ConnectException: Connection refused: no further information: /10.33.241.160:7077
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:692)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
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$2.run(SingleThreadEventExecutor.java:111)
... 1 more
16/03/21 16:28:40 ERROR MapOutputTrackerMaster: Error communicating with MapOutputTracker
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer.tryAcquireSharedNanos(AbstractQueuedSynchronizer.java:1325)
at scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:208)
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:218)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
at scala.concurrent.Await$.result(package.scala:107)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
at org.apache.spark.MapOutputTracker.askTracker(MapOutputTracker.scala:110)
at org.apache.spark.MapOutputTracker.sendTracker(MapOutputTracker.scala:120)
at org.apache.spark.MapOutputTrackerMaster.stop(MapOutputTracker.scala:462)
at org.apache.spark.SparkEnv.stop(SparkEnv.scala:93)
at org.apache.spark.SparkContext$$anonfun$stop$12.apply$mcV$sp(SparkContext.scala:1756)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1229)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1755)
at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.dead(SparkDeploySchedulerBackend.scala:127)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint.markDead(AppClient.scala:264)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$anonfun$run$1.apply$mcV$sp(AppClient.scala:134)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1163)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2.run(AppClient.scala:129)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:722)
It turns out I need to setup my hortonworks Spark as master server every time server restart. Then use my intellij dev environment to connect with hdp as slave. Just run ./sbin/start-master.sh in hdp as this link.

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