When submitting the Spark Application to Spark REST URL, always got the exception like the following:
18/04/13 11:54:29 ERROR TransportResponseHandler: Still have 1 requests outstanding when connection from /10.11.9.2:6066 is closed
18/04/13 11:54:29 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master 10.11.9.2:6066
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.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.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:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
18/04/13 11:55:09 ERROR SparkContext: Error initializing SparkContext.
java.lang.IllegalArgumentException: requirement failed: Can only call getServletHandlers on a running MetricsSystem
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.metrics.MetricsSystem.getServletHandlers(MetricsSystem.scala:91)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:524)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:918)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:910)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:910)
at io.kf.etl.context.Context$$anonfun$getSparkSession$2.apply(Context.scala:76)
at io.kf.etl.context.Context$$anonfun$getSparkSession$2.apply(Context.scala:59)
at scala.Option.map(Option.scala:146)
at io.kf.etl.context.Context$.getSparkSession(Context.scala:59)
at io.kf.etl.context.Context$.sparkSession$lzycompute(Context.scala:20)
at io.kf.etl.context.Context$.sparkSession(Context.scala:20)
at io.kf.etl.processors.common.inject.ProcessorInjectModule.sparkSession$lzycompute(ProcessorInjectModule.scala:8)
at io.kf.etl.processors.common.inject.ProcessorInjectModule.sparkSession(ProcessorInjectModule.scala:8)
at io.kf.etl.processors.download.inject.DownloadInjectModule.getContext(DownloadInjectModule.scala:40)
at io.kf.etl.processors.download.inject.DownloadInjectModule.getProcessor(DownloadInjectModule.scala:54)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:104)
at com.google.inject.internal.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:40)
at com.google.inject.internal.InjectorImpl$4$1.call(InjectorImpl.java:978)
at com.google.inject.internal.InjectorImpl.callInContext(InjectorImpl.java:1024)
at com.google.inject.internal.InjectorImpl$4.get(InjectorImpl.java:974)
at com.google.inject.internal.InjectorImpl.getInstance(InjectorImpl.java:1013)
at io.kf.etl.ETLMain$.delayedEndpoint$io$kf$etl$ETLMain$1(ETLMain.scala:42)
at io.kf.etl.ETLMain$delayedInit$body.apply(ETLMain.scala:17)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at io.kf.etl.ETLMain$.main(ETLMain.scala:17)
at io.kf.etl.ETLMain.main(ETLMain.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:58)
at org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
18/04/13 11:55:09 INFO SparkContext: SparkContext already stopped.
18/04/13 11:55:09 INFO SparkContext: Successfully stopped SparkContext
I am running Spark 2.2.1 on MacOS
The configurations look like this:
SPARK_LOCAL_IP=10.11.9.2
SPARK_MASTER_HOST=10.11.9.2
The submission command line is
${SPARK_HOME}/bin/spark-submit --master spark://10.11.9.2:6066 --deploy-mode cluster --class ....
If I submitted the application to port 7077, everything is fine.
Hidden REST API is not suppose to be used with spark-submit. Instead all arguments and job definition should be submitted as a http request to http://rest-ip:6066/v1/submissions/create.
Apache spark rest API
Triggering spark jobs with REST
I figured it out by myself.
The submission command line is fine, but when I initialized SparkSession, I also passed in spark://10.11.9.2:6066 as the master string.
if passing in spark://10.11.9.2:7077, everything just works well.
Related
I need help please getting spark working in windows cluster of 3 nodes. I am able to download and configure and run the master node and worker nodes. the worker nodes are registered successfully with the master. Im able to see both worker nodes in the Master UI. When I try to submit a job using:
spark-submit --master spark://IP:7077 hello_world.py
Spark continuously try to start multiple executors but the all failed with code exit 1 and it doesnt stop until I kill it. when I check the log in the UI for each worker Im seeing the following error:
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1894)
at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:61)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.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$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
Im using Spark: spark-3.3.1-bin-hadoop3
Please help.
Thanks
The application to run
I'm using delta lake on using pyspark by submitting below command
spark-sql --packages io.delta:delta-core_2.12:0.8.0 --conf "spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension" --conf "spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog"
System Specs:
Spark - 3.0.3
scala - 2.12.10
java - 1.8.0
hadoop - 2.7
i'm looking at reference blog https://docs.delta.io/latest/quick-start.html
https://www.confessionsofadataguy.com/introduction-to-delta-lake-on-apache-spark-for-data-engineers/
but when I use spark without the delta config spark works fine.
Error (trucated the stacktrace):
22/12/29 20:38:10 INFO Executor: Starting executor ID driver on host 192.168.0.100
22/12/29 20:38:10 INFO Executor: Fetching spark://192.168.0.100:50920/jars/org.antlr_antlr4-runtime-4.7.jar with timestamp 1672326488255
22/12/29 20:38:23 WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped
22/12/29 20:38:23 INFO Executor: Told to re-register on heartbeat
22/12/29 20:38:23 INFO BlockManager: BlockManager null re-registering with master
22/12/29 20:38:23 INFO BlockManagerMaster: Registering BlockManager null
22/12/29 20:38:23 ERROR Inbox: Ignoring error
java.lang.NullPointerException
at org.apache.spark.storage.BlockManagerMasterEndpoint.org$apache$spark$storage$BlockManagerMasterEndpoint$$register(BlockManagerMasterEndpoint.scala:404)
at org.apache.spark.storage.BlockManagerMasterEndpoint$$anonfun$receiveAndReply$1.applyOrElse(BlockManagerMasterEndpoint.scala:97)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:103)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:213)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100)
at org.apache.spark.rpc.netty.MessageLoop.org$apache$spark$rpc$netty$MessageLoop$$receiveLoop(MessageLoop.scala:75)
at org.apache.spark.rpc.netty.MessageLoop$$anon$1.run(MessageLoop.scala:41)
at java.util.concurrent.Executors$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$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
22/12/29 20:38:23 WARN Executor: Issue communicating with driver in heartbeater
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:302)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:103)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:87)
at org.apache.spark.storage.BlockManagerMaster.registerBlockManager(BlockManagerMaster.scala:66)
at org.apache.spark.storage.BlockManager.reregister(BlockManager.scala:567)
at org.apache.spark.executor.Executor.reportHeartBeat(Executor.scala:934)
at org.apache.spark.executor.Executor.$anonfun$heartbeater$1(Executor.scala:200)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1934)
at org.apache.spark.Heartbeater$$anon$1.run(Heartbeater.scala:46)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException
at org.apache.spark.storage.BlockManagerMasterEndpoint.org$apache$spark$storage$BlockManagerMasterEndpoint$$register(BlockManagerMasterEndpoint.scala:404)
at org.apache.spark.storage.BlockManagerMasterEndpoint$$anonfun$receiveAndReply$1.applyOrElse(BlockManagerMasterEndpoint.scala:97)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:103)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:213)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
... 3 more
22/12/29 20:38:31 ERROR Utils: Aborting task
java.io.IOException: Failed to connect to /192.168.0.100:50920
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:253)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:195)
at org.apache.spark.rpc.netty.NettyRpcEnv.downloadClient(NettyRpcEnv.scala:392)
at org.apache.spark.rpc.netty.NettyRpcEnv.$anonfun$openChannel$4(NettyRpcEnv.scala:360)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:931)
at org.apache.spark.sql.hive.thriftserver.SparkSQLEnv$.init(SparkSQLEnv.scala:49)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.<init>(SparkSQLCLIDriver.scala:321)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Connection timed out: no further information: /192.168.0.100:50920
Caused by: java.net.ConnectException: Connection timed out: no further information
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:330)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:334)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:702)
at java.lang.Thread.run(Thread.java:745)
22/12/29 20:38:31 ERROR SparkContext: Error initializing SparkContext.
java.io.IOException: Failed to connect to /192.168.0.100:50920
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:253)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:195)
at org.apache.spark.rpc.netty.NettyRpcEnv.downloadClient(NettyRpcEnv.scala:392)
at org.apache.spark.rpc.netty.NettyRpcEnv.$anonfun$openChannel$4(NettyRpcEnv.scala:360)
at java.lang.reflect.Method.invoke(Method.java:498)
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:330)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:745)
22/12/29 20:38:31 INFO SparkUI: Stopped Spark web UI at http://192.168.0.100:4041
22/12/29 20:38:31 ERROR Utils: Uncaught exception in thread main
java.lang.NullPointerException
at org.apache.spark.scheduler.local.LocalSchedulerBackend.org$apache$spark$scheduler$local$LocalSchedulerBackend$$stop(LocalSchedulerBackend.scala:168)
at org.apache.spark.scheduler.local.LocalSchedulerBackend.stop(LocalSchedulerBackend.scala:144)
at org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:734)
at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:2171)
java.lang.NullPointerException
at org.apache.spark.executor.Executor.$anonfun$stop$3(Executor.scala:304)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:221)
at org.apache.spark.executor.Executor.stop(Executor.scala:304)
at org.apache.spark.executor.Executor.$anonfun$stopHookReference$1(Executor.scala:74)
at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:214)
at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178)
at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
22/12/29 20:38:31 INFO ShutdownHookManager: Shutdown hook called
what is being missed?
Try it like this:
!pip3 install findspark --user
import findspark
findspark.init()
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages io.delta:delta- core_2.12:2.2.0 --driver-memory 2g pyspark-shell'
spark = SparkSession.builder.appName("your application") \
.config("spark.jars.packages", "io.delta:delta-core_2.12:2.2.0") \
.config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension") \
.config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog") \
.getOrCreate()
In order to fit the efficiency requirements, I am forced to stop SparkContext and restart it with a new configuration more optimal in terms of number of executors, memory per executor, executor memory overhead...
I can achieve this launching my spark-submit in client mode :
spark-submit --num-executors 5 \
--deploy-mode client \
--class className spark.jar
And then within my code executing:
spark.stop()
val spark2 : SparkSession = SparkSession.builder
.config("spark.submit.deployMode", "client")
.config("spark.executor.instances", "8")
.getOrCreate()
And everything works OK.
However, when launching in client mode, stopping the SparkContext and restarting sparkContext in cluster mode, I get the following error:
20/05/28 18:05:24 ERROR spark.SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: Detected yarn cluster mode, but isn't running on a cluster. Deployment to YARN is not supported directly by SparkContext. Please use spark-submit.
at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2520)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:935)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:926)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:926)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
20/05/28 18:05:24 ERROR util.Utils: Uncaught exception in thread main
java.lang.NullPointerException
at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$postApplicationEnd(SparkContext.scala:2416)
at org.apache.spark.SparkContext$$anonfun$stop$1.apply$mcV$sp(SparkContext.scala:1931)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1385)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1930)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:585)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2520)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:935)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:926)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:926)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I have also tried launching spark-submit in cluster mode, stopping SparkCOntext and restarting it again in cluster mode. In this case I get the error:
Exception in thread "main" org.apache.spark.SparkException: Application application_1583287354042_80626 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1171)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1608)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I am not sure if it might be related to the fact that the driver is running on the cluster...
I'd be very grateful if someone could provide a solution to achieve these requirements.
I'm trying to run a jar file with this spark-submit command:
spark-submit --master yarn --deploy-mode cluster --executor-memory 3g --class my.package.Main my-jar-file.jar
The class Main is the jar's main class, and here's the contents (all in Scala):
object Main{
def main(args: Array[String]){
val server = HttpServer.create(new InetSocketAddress("master", 8000), 0)
val backend = new MainProcess()
val handlerRoot = new RootHandler()
handlerRoot.initProcess(backend)
server.createContext("/", handlerRoot)
server.setExecutor(null)
server.start()
println("Server is started at " + server.getAddress().getHostString() + ":" + server.getAddress().getPort())
}
}
The class MainProcess is the class where I do the stuff with Spark and Spark GraphX library using the files obtained from HDFS. This is how I configure the SparkContext in MainProcess class:
class MainProcess{
val config = new SparkConf()
config.setAppName("Final GraphX App - Main")
val sc = new SparkContext(config)
...
}
The app seems to be running okay and the final status returned a success, but the app simply closes instead of running continuously as it's supposed to be a running server. I can only open the link master:8000 once and it's back to unable to connect when I tried refreshing the page. Here's the log from running the app:
18/04/06 15:45:59 ERROR yarn.YarnAllocator: Failed to launch executor 2 on container container_1522920902032_0027_01_000003
org.apache.spark.SparkException: Exception while starting container container_1522920902032_0027_01_000003 on host slave2
at org.apache.spark.deploy.yarn.ExecutorRunnable.startContainer(ExecutorRunnable.scala:125)
at org.apache.spark.deploy.yarn.ExecutorRunnable.run(ExecutorRunnable.scala:65)
at org.apache.spark.deploy.yarn.YarnAllocator$$anonfun$runAllocatedContainers$1$$anon$1.run(YarnAllocator.scala:523)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: Failed on local exception: java.io.IOException: java.io.EOFException; Host Details : local host is: "master/10.100.69.207"; destination host is: "slave2":57914;
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:776)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy19.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy20.startContainers(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.NMClientImpl.startContainer(NMClientImpl.java:201)
at org.apache.spark.deploy.yarn.ExecutorRunnable.startContainer(ExecutorRunnable.scala:122)
... 5 more
Caused by: java.io.IOException: java.io.EOFException
at org.apache.hadoop.ipc.Client$Connection$1.run(Client.java:687)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.hadoop.ipc.Client$Connection.handleSaslConnectionFailure(Client.java:650)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:737)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 18 more
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.hadoop.security.SaslRpcClient.saslConnect(SaslRpcClient.java:367)
at org.apache.hadoop.ipc.Client$Connection.setupSaslConnection(Client.java:560)
at org.apache.hadoop.ipc.Client$Connection.access$1900(Client.java:375)
at org.apache.hadoop.ipc.Client$Connection$2.run(Client.java:729)
at org.apache.hadoop.ipc.Client$Connection$2.run(Client.java:725)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:725)
... 21 more
This app is basically a web app made using Java HTTP Server (com.sun.net.httpserver.HttpServer) and it uses Spark to process big data. The requests sent are accepted by the handler class and a new thread is made to run the Spark job on background. The user can send another request to check if the Spark job is finished, so the finished result can be shown to the web page. The problem is, the server is "killed" every time Spark claims to have finished a job (but in this case, failed a job).
I'm using Spark 2.2.0 built for Hadoop 2.7 and Hadoop 2.7.1. All data files are in HDFS.
I am having CDH 5.1 (Hadoop 2.3.0-cdh5.1.3) installed on my cluster, version:
I have installed and configured a prebuilt version of Spark 1.1.0 (Apache Version), built for hadoop 2.3 on my cluster.
when I run the Pi example in the ‘client mode’, it runs successfully, but it fails in the ‘yarn-cluster’ mode. The spark job is successfully submitted, but fails after polling the application master for sometime:
More Logs:
Application application_1415193640322_0016 failed 2 times due to Error launching appattempt_1415193640322_0016_000002. Got exception: org.apache.hadoop.yarn.exceptions.YarnException: java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.yarn.ipc.RPCUtil.instantiateException(RPCUtil.java:53)
at org.apache.hadoop.yarn.ipc.RPCUtil.unwrapAndThrowException(RPCUtil.java:101)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:99)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.launch(AMLauncher.java:118)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.run(AMLauncher.java:249)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.yarn.exceptions.YarnException): java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at org.apache.hadoop.ipc.Client.call(Client.java:1409)
at org.apache.hadoop.ipc.Client.call(Client.java:1362)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
at com.sun.proxy.$Proxy69.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
... 5 more
. Failing the application.
When I go to node Manager logs:
Log Type: stderr
Log Length: 87
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
Can you please suggest any solution.Do you think I should compile the spark code on my cluster. Or should I use Spark provided with CDH5.1.
Any help will be appreciated!
spark-shell does not work with spark yarn-cluster mode. You should add --master yarn-client
Example:
path/to/pyspark --master yarn-client