While creating the configuration of nutch in deploy mode using the config/create endpoint it is throwing NoSuchMethodError.
java.lang.NoSuchMethodError: com.fasterxml.jackson.databind.ObjectReader.forType(Lcom/fasterxml/jackson/databind/JavaType;)Lcom/fasterxml/jackson/databind/ObjectReader;
at com.fasterxml.jackson.jaxrs.base.ProviderBase.readFrom(ProviderBase.java:803)
at org.apache.cxf.jaxrs.utils.JAXRSUtils.readFromMessageBodyReader(JAXRSUtils.java:1379)
at org.apache.cxf.jaxrs.utils.JAXRSUtils.readFromMessageBody(JAXRSUtils.java:1330)
at org.apache.cxf.jaxrs.utils.JAXRSUtils.processParameter(JAXRSUtils.java:856)
at org.apache.cxf.jaxrs.utils.JAXRSUtils.processParameters(JAXRSUtils.java:815)
at org.apache.cxf.jaxrs.interceptor.JAXRSInInterceptor.processRequest(JAXRSInInterceptor.java:215)
at org.apache.cxf.jaxrs.interceptor.JAXRSInInterceptor.handleMessage(JAXRSInInterceptor.java:78)
at org.apache.cxf.phase.PhaseInterceptorChain.doIntercept(PhaseInterceptorChain.java:308)
at org.apache.cxf.transport.ChainInitiationObserver.onMessage(ChainInitiationObserver.java:121)
at org.apache.cxf.transport.http.AbstractHTTPDestination.invoke(AbstractHTTPDestination.java:267)
at org.apache.cxf.transport.http_jetty.JettyHTTPDestination.doService(JettyHTTPDestination.java:234)
at org.apache.cxf.transport.http_jetty.JettyHTTPHandler.handle(JettyHTTPHandler.java:76)
at org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1129)
at org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1065)
at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:141)
at org.eclipse.jetty.server.handler.ContextHandlerCollection.handle(ContextHandlerCollection.java:215)
at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:97)
at org.eclipse.jetty.server.Server.handle(Server.java:499)
at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:311)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:258)
at org.eclipse.jetty.io.AbstractConnection$2.run(AbstractConnection.java:544)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:635)
at org.eclipse.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:555)
at java.lang.Thread.run(Thread.java:748)
19/03/22 01:46:25 WARN thread.QueuedThreadPool:
java.lang.NoSuchMethodError: javax.servlet.http.HttpServletResponse.getStatus()
at org.apache.cxf.transport.http_jetty.JettyHTTPServerEngine$1.handle(JettyHTTPServerEngine.java:368)
at org.eclipse.jetty.server.Response.sendError(Response.java:597)
at org.eclipse.jetty.server.HttpChannel.handleException(HttpChannel.java:487)
at org.eclipse.jetty.server.HttpConnection$HttpChannelOverHttp.handleException(HttpConnection.java:621)
at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:387)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:258)
at org.eclipse.jetty.io.AbstractConnection$2.run(AbstractConnection.java:544)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:635)
at org.eclipse.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:555)
at java.lang.Thread.run(Thread.java:748)
This method belongs to jackson-databind-2.9.5.jar when I checked into apache-nutch-1.15.job the same version jar exists in it.
Related
I need help please getting spark working in windows cluster of 3 nodes. I am able to download and configure and run the master node and worker nodes. the worker nodes are registered successfully with the master. Im able to see both worker nodes in the Master UI. When I try to submit a job using:
spark-submit --master spark://IP:7077 hello_world.py
Spark continuously try to start multiple executors but the all failed with code exit 1 and it doesnt stop until I kill it. when I check the log in the UI for each worker Im seeing the following error:
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1894)
at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:61)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.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$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
Im using Spark: spark-3.3.1-bin-hadoop3
Please help.
Thanks
The application to run
I am using spark 3.x, java8 and delta 1.0.0 i.e. delta-core_2.12_1.0.0 in my spark job.
data is persisted in AWS S3 path in "delta" format of parquet.
Below are details of Jars I am using in my spark job.
spark-submit.sh
export SPARK_HOME=/local/apps/pkg/spark-3.0.2-bin-hadoop2.9.1-custom
--packages org.apache.spark:spark-sql_2.12:3.0.2,io.delta:delta-core_2.12:1.0.0
pom.xml
<spark.version>3.0.2</spark.version>
While saving bigger set of data job failing to write data with below error
Caused by: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231)
at org.apache.spark.sql.delta.files.TransactionalWrite.$anonfun$writeFiles$1(TransactionalWrite.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.delta.files.TransactionalWrite.writeFiles(TransactionalWrite.scala:130)
at org.apache.spark.sql.delta.files.TransactionalWrite.writeFiles$(TransactionalWrite.scala:115)
at org.apache.spark.sql.delta.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:81)
at org.apache.spark.sql.delta.files.TransactionalWrite.writeFiles(TransactionalWrite.scala:108)
at org.apache.spark.sql.delta.files.TransactionalWrite.writeFiles$(TransactionalWrite.scala:107)
at org.apache.spark.sql.delta.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:81)
at org.apache.spark.sql.delta.commands.WriteIntoDelta.write(WriteIntoDelta.scala:106)
at org.apache.spark.sql.delta.commands.WriteIntoDelta.$anonfun$run$1(WriteIntoDelta.scala:65)
at org.apache.spark.sql.delta.commands.WriteIntoDelta.$anonfun$run$1$adapted(WriteIntoDelta.scala:64)
at org.apache.spark.sql.delta.DeltaLog.withNewTransaction(DeltaLog.scala:188)
at org.apache.spark.sql.delta.commands.WriteIntoDelta.run(WriteIntoDelta.scala:64)
at org.apache.spark.sql.delta.sources.DeltaDataSource.createRelation(DeltaDataSource.scala:148)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:126)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:962)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:962)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:414)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:345)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:287)
at com.spgmi.ca.benchmark.datasource.DeltaDataSource.write(DeltaDataSource.java:47)
... 8 more
Caused by: org.apache.spark.SparkException: Job 67 cancelled because SparkContext was shut down
at org.apache.spark.scheduler.DAGScheduler.$anonfun$cleanUpAfterSchedulerStop$1(DAGScheduler.scala:979)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$cleanUpAfterSchedulerStop$1$adapted(DAGScheduler.scala:977)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:79)
at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:977)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:2257)
at org.apache.spark.util.EventLoop.stop(EventLoop.scala:84)
at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:2170)
at org.apache.spark.SparkContext.$anonfun$stop$12(SparkContext.scala:1988)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1357)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1988)
at org.apache.spark.SparkContext.$anonfun$new$35(SparkContext.scala:638)
at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:214)
at org.apache.spark.util.SparkShutdownHookManager.$anonfun$runAll$2(ShutdownHookManager.scala:188)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1934)
at org.apache.spark.util.SparkShutdownHookManager.$anonfun$runAll$1(ShutdownHookManager.scala:188)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at scala.util.Try$.apply(Try.scala:213)
at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178)
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:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200)
So what is wrong here ?
how to debug and fix this issue ? Any help is highly appreciated.
You're using Delta version that is incompatible with your Spark. The last version of Delta working with Spark 2.4 was version 0.6.x (0.6.2 as I remember, although I didn't check). See the versions compatibility matrix for more information.
P.S. It really makes no sense to use Spark 2.4 in 2022nd - Spark 3.0+ has a lot of optimizations compared to 2.x...
I'm trying to run : https://github.com/conker84/zep-neo4j-gc2k18
The 1st paragraph Add Neo4j-Spark-Connector dependency:
%spark.dep
z.reset()
z.load("neo4j-contrib:neo4j-spark-connector:2.2.1-M5")
but an error occurred as follow:
java.lang.NullPointerException
at org.sonatype.aether.impl.internal.DefaultRepositorySystem.resolveDependencies(DefaultRepositorySystem.java:352)
at org.apache.zeppelin.spark.dep.SparkDependencyContext.fetchArtifactWithDep(SparkDependencyContext.java:171)
at org.apache.zeppelin.spark.dep.SparkDependencyContext.fetch(SparkDependencyContext.java:121)
at org.apache.zeppelin.spark.DepInterpreter.interpret(DepInterpreter.java:247)
at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:103)
at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:633)
at org.apache.zeppelin.scheduler.Job.run(Job.java:188)
at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:140)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
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)
What should I do to correct the error?
You are looking at an outdated version of Zeppelin integration. Nowadays Zeppelin supports querying Neo4j out of the box with https://zeppelin.apache.org/docs/0.8.0/interpreter/neo4j.html.
You can check out how I have done it in my repo: https://github.com/tomasonjo/zeppelin-graph-algo
Trying to use SPARK as hive execution engine, Getting below error
Job failed with java.lang.ClassNotFoundException: org.apache.spark.AccumulatorParam
FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. java.lang.NoClassDefFoundError: org/apache/spark/AccumulatorParam
at org.apache.hive.spark.counter.SparkCounterGroup.createCounter(SparkCounterGroup.java:52)
at org.apache.hive.spark.counter.SparkCounters.createCounter(SparkCounters.java:71)
at org.apache.hive.spark.counter.SparkCounters.createCounter(SparkCounters.java:67)
at org.apache.hadoop.hive.ql.exec.spark.RemoteHiveSparkClient$JobStatusJob.call(RemoteHiveSparkClient.java:337)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:358)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:323)
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: java.lang.ClassNotFoundException: org.apache.spark.AccumulatorParam
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
... 10 more
Spark versions : 3.1.1
Hive version : 3.1.2 (also tried with - version2.3.8 got same error though)
Hadoop version : 3.3.0
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.