I have a cluster with Cloudera 5.10.
For profiling I'm running spark-submit with parameters:
--conf "spark.driver.extraJavaOptions= -agentpath:/root/yjp-2017.02/bin/linux-x86-64/libyjpagent.so=sampling"
--conf "spark.executor.extraJavaOptions= -agentpath:/root/yjp-2017.02/bin/linux-x86-64/libyjpagent.so=sampling"
And it is working good only for driver. When i'm using this option for executor i'm getting the exception
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:601)
at org.apache.hadoop.util.Shell.run(Shell.java:504)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:786)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:213)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
I couldn't find any useful logs and the same exception I've got on every node.
The same if I'am using this manual enter link description here
And if I leave only configuration for driver, everything is working fine and i can use YourKit to connect to the driver
What can be the problem?
May be an executor launches 32-bit JVM? So path to 32-bit YourKit agent should be specified?
I experianced the same issue. You have to install YourKit on all nodes in the cluster.
Related
I am running a on-prem k8s cluster and am running juypterhub on it.
I can successfully submit the job to an yarn queue, however the job will fail because users notebook pod IP is not resolvable and therefore it can’t talk back to the spark driver running on said pod and I get an error like:
Caused by: java.io.IOException: Failed to connect to podIP:33630 at
org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)
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:
java.net.UnknownHostException: pod-ip
I believe I’m missing something in my setup that will allow yarn to talk back to the spawned notebook pods on the kubernetes cluster.
Any help or hints are greatly appreciated .
For now I am passing the spark driver the internal Kubernetes Pod IP of juypterhub by setting:
"spark.driver.host" to str(socket.gethostbyname(socket.gethostname())). Could I change this to something else in the notebook I am running? I am not too sure what to change it to.
Thanks!
i am trying submit pyspark job from yarnclient. getting below error from RM without any further logs.
org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.ipc.StandbyException):
Operation category READ is not supported in state standby ENOENT: No
such file or directory at
org.apache.hadoop.io.nativeio.NativeIO$POSIX.chmodImpl(Native Method)
at
org.apache.hadoop.io.nativeio.NativeIO$POSIX.chmod(NativeIO.java:231)
at
org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:773)
at
org.apache.hadoop.fs.DelegateToFileSystem.setPermission(DelegateToFileSystem.java:218)
at org.apache.hadoop.fs.FilterFs.setPermission(FilterFs.java:266) at
org.apache.hadoop.fs.FileContext$11.next(FileContext.java:1008) at
org.apache.hadoop.fs.FileContext$11.next(FileContext.java:1004) at
org.apache.hadoop.fs.FSLinkResolver.resolve(FSLinkResolver.java:90) at
org.apache.hadoop.fs.FileContext.setPermission(FileContext.java:1011)
at org.apache.hadoop.yarn.util.FSDownload$3.run(FSDownload.java:483)
at org.apache.hadoop.yarn.util.FSDownload$3.run(FSDownload.java:481)
at java.security.AccessController.doPrivileged(Native Method) at
javax.security.auth.Subject.doAs(Subject.java:422) at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1875)
at
org.apache.hadoop.yarn.util.FSDownload.changePermissions(FSDownload.java:481)
at org.apache.hadoop.yarn.util.FSDownload.call(FSDownload.java:419) at
org.apache.hadoop.yarn.server.nodemanager.containermanager.localizer.ContainerLocalizer$FSDownloadWrapper.doDownloadCall(ContainerLocalizer.java:242)
at
org.apache.hadoop.yarn.server.nodemanager.containermanager.localizer.ContainerLocalizer$FSDownloadWrapper.call(ContainerLocalizer.java:235)
at
org.apache.hadoop.yarn.server.nodemanager.containermanager.localizer.ContainerLocalizer$FSDownloadWrapper.call(ContainerLocalizer.java:223)
at java.util.concurrent.FutureTask.run(FutureTask.java:266) 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) For more detailed output,
check the application tracking page:
https://.com:8090/cluster/app/application_1638972290118_64750
Then click on links to logs of each attempt. . Failing the
application.
cluster is fine and other pyspark jobs running fine.
Please help
Thanks in advance
What do you mean by "cluster is fine and other pyspark jobs running fine"?
Did you run them on Yarn or just on Standalone mode?
However, I think it's better to check your yarn cluster first to see if it works (without spark).
you can do it using hadoop MapR examples:
yarn jar $HadoopDir/share/hadoop/mapreduce/hadoop-mapreduce-examples-$version.jar wordcount inputFilePath OutputDir
Check link 1 and link 2 too. They may help.
For reference: I solved this issue by adding Netty 4.1.17 in hadoop/share/hadoop/common
No matter what jar I try and run (including the example from https://spark.apache.org/docs/latest/running-on-yarn.html), I keep getting an error regarding container failure when running Spark on Yarn. I get this error in the command prompt:
Diagnostics: Exception from container-launch.
Container id: container_1530118456145_0001_02_000001
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:585)
at org.apache.hadoop.util.Shell.run(Shell.java:482)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:776)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
When I look at the logs, I then find this error:
Exception in thread "main" java.lang.NoSuchMethodError:io.netty.buffer.PooledByteBufAllocator.metric()Lio/netty/buffer/PooledByteBufAllocatorMetric;
at org.apache.spark.network.util.NettyMemoryMetrics.registerMetrics(NettyMemoryMetrics.java:80)
at org.apache.spark.network.util.NettyMemoryMetrics.<init>(NettyMemoryMetrics.java:76)
at org.apache.spark.network.client.TransportClientFactory.<init>(TransportClientFactory.java:109)
at org.apache.spark.network.TransportContext.createClientFactory(TransportContext.java:99)
at org.apache.spark.rpc.netty.NettyRpcEnv.<init>(NettyRpcEnv.scala:71)
at org.apache.spark.rpc.netty.NettyRpcEnvFactory.create(NettyRpcEnv.scala:461)
at org.apache.spark.rpc.RpcEnv$.create(RpcEnv.scala:57)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:530)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:347)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$2.apply$mcV$sp(ApplicationMaster.scala:260)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$2.apply(ApplicationMaster.scala:260)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$2.apply(ApplicationMaster.scala:260)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$5.run(ApplicationMaster.scala:815)
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:1758)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:814)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:259)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:839)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:869)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Any idea why this is happening? This is running on a pseudo-distributed cluster set up according to this tutorial: https://wiki.apache.org/hadoop/Hadoop2OnWindows. Spark runs fine locally, and seeing as this jar was provided with Spark, I doubt it's a problem within the jar. (Regardless, I added a Netty dependency inside another jar and I'm still getting the same error).
The only thing set in my spark-defaults.conf is spark.yarn.jars, which points to a hdfs directory where I uploaded all of Spark's jars. io.netty.buffer.PooledByteBufAllocator is contained within these jars.
Spark 2.3.1, Hadoop 2.7.6
I had exactly same issue. Previously I used Hadoop 2.6.5 and the compatible spark version, things worked out fine. When I switched to Hadoop 2.7.6, problem occurred. Not sure what is cause, but I copied to netty.4.1.17.Final jar file to the hadoop library folder then the problem goes away.
Seems like you have multiple netty version on your classpath ,
mvn clean compile
Remove all and add latest one.
This may have the version problem between your yarn and spark. check the compatibility of the versions are installed.
I strongly suggest to read more about NoSuchMethodError and some other similar Exceptions like NoClassDefFoundError and ClassNotFoundException. This suggestions reason is that when you start using spark in different situations these are the much more confusing errors and exception for the people are not so experienced. NosuchMethodError
Of course caring a lot is the best practice strategy for a programmer absolutely the ones working on distributed systems like spark. Well Done. ;)
I can connect to the driver just fine by adding the following:
spark.driver.extraJavaOptions=-Dcom.sun.management.jmxremote \
-Dcom.sun.management.jmxremote.port=9178 \
-Dcom.sun.management.jmxremote.authenticate=false \
-Dcom.sun.management.jmxremote.ssl=false
But doing ...
spark.executor.extraJavaOptions=-Dcom.sun.management.jmxremote \
-Dcom.sun.management.jmxremote.port=9178 \
-Dcom.sun.management.jmxremote.authenticate=false \
-Dcom.sun.management.jmxremote.ssl=false
... only yield a bunch of errors on the driver ...
Container id: container_1501548048292_0024_01_000003
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:972)
at org.apache.hadoop.util.Shell.run(Shell.java:869)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:1170)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:236)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:305)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:84)
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:748)
Container exited with a non-zero exit code 1
... and finally crashes the job.
There are no errors on the workers, it simply exits with:
[org.apache.spark.util.ShutdownHookManager] - Shutdown hook called
Spark v2.2.0, and the cluster is a simple 1m-2w-configuration, and my jobs run without issues without the executor parameters.
As Rick Mortiz pointed out, the issue was conflicting ports for the executor jmx.
Setting:
-Dcom.sun.management.jmxremote.port=0
yields a random port, and removed the errors from Spark. To figure out which port it ends up using do:
netstat -alp | grep LISTEN.*<executor-pid>/java
which lists the currently open ports for that process.
Passing following configuration with spark-submit worked for me
--conf "spark.executor.extraJavaOptions=-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=9178 -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false"
I'm trying to launch a cluster using AWS Cli. I use the following command:
aws emr create-cluster --name "Config1" --release-label emr-5.0.0 --applications Name=Spark --use-default-role --log-uri 's3://aws-logs-813591802533-us-west-2/elasticmapreduce/' --instance-groups InstanceGroupType=MASTER,InstanceCount=1,InstanceType=m1.medium InstanceGroupType=CORE,InstanceCount=2,InstanceType=m1.medium
The cluster is created successfully. Then I add this command:
aws emr add-steps --cluster-id ID_CLUSTER --region us-west-2 --steps Name=SparkSubmit,Jar="command-runner.jar",Args=[spark-submit,--deploy-mode,cluster,--master,yarn,--executor-memory,1G,--class,Traccia2014,s3://tracceale/params/scalaProgram.jar,s3://tracceale/params/configS3.txt,30,300,2,"s3a://tracceale/Tempi1"],ActionOnFailure=CONTINUE
After some time, the step failed. This is the LOG file:
17/02/22 11:00:07 INFO RMProxy: Connecting to ResourceManager at ip-172-31- 31-190.us-west-2.compute.internal/172.31.31.190:8032
17/02/22 11:00:08 INFO Client: Requesting a new application from cluster with 2 NodeManagers
17/02/22 11:00:08 INFO Client: Verifying our application has not requested
Exception in thread "main" org.apache.spark.SparkException: Application application_1487760984275_0001 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1132)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1175)
at org.apache.spark.deploy.yarn.Client.main(Client.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.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
17/02/22 11:01:02 INFO ShutdownHookManager: Shutdown hook called
17/02/22 11:01:02 INFO ShutdownHookManager: Deleting directory /mnt/tmp/spark-27baeaa9-8b3a-4ae6-97d0-abc1d3762c86
Command exiting with ret '1'
Locally (on SandBox Hortonworks HDP 2.5) I run:
./spark-submit --class Traccia2014 --master local[*] --executor-memory 2G /usr/hdp/current/spark2-client/ScalaProjects/ScripRapportoBatch2.1/target/scala-2.11/traccia-22-ottobre_2.11-1.0.jar "/home/tracce/configHDFS.txt" 30 300 3
and everything works fine.
I've already read something related to my problem, but I can't figure it out.
UPDATE
Checked into Application Master, I get this error:
17/02/22 15:29:54 ERROR ApplicationMaster: User class threw exception: java.io.FileNotFoundException: s3:/tracceale/params/configS3.txt (No such file or directory)
at java.io.FileInputStream.open0(Native Method)
at java.io.FileInputStream.open(FileInputStream.java:195)
at java.io.FileInputStream.<init>(FileInputStream.java:138)
at scala.io.Source$.fromFile(Source.scala:91)
at scala.io.Source$.fromFile(Source.scala:76)
at scala.io.Source$.fromFile(Source.scala:54)
at Traccia2014$.main(Rapporto.scala:40)
at Traccia2014.main(Rapporto.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.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:627)
17/02/22 15:29:55 INFO ApplicationMaster: Final app status: FAILED, exitCode: 15, (reason: User class threw exception: java.io.FileNotFoundException: s3:/tracceale/params/configS3.txt (No such file or directory))
I pass the path mentioned "s3://tracceale/params/configS3.txt" from S3 to the function 'fromFile' like this:
for(line <- scala.io.Source.fromFile(logFile).getLines())
How could I solve it? Thanks in advance.
Because you are using cluster deploy mode, the logs you have included are not useful at all. They just say that the application failed but not why it failed. To figure out why it failed, you at least need to look at the Application Master logs, since that is where the Spark driver runs in cluster deploy mode, and it will probably give a better hint as to why the application failed.
Since you have configured your cluster with a --log-uri, you will find the logs for the Application Master underneath s3://aws-logs-813591802533-us-west-2/elasticmapreduce/<CLUSTER ID>/containers/<YARN Application ID>/ where the YARN Application ID is (based on the logs you included above) application_1487760984275_0001, and the container ID should be something like container_1487760984275_0001_01_000001. (The first container for an application is the Application Master.)
What you have there is a URL to an object store, reachable from the Hadoop filesystem APIs, and a stack trace coming from java.io.File, which can't read it because it doesn't refer to anything in the local disk.
Use SparkContext.hadoopRDD() as the operation to convert the path into an RDD
There is a probability of file missing in the location, may be you can see it after ssh into EMR cluster but still the steps command wouldn't be able to figure out by itself and starts throwing that file not found exception.
In this scenario what I did is :
Step 1: Checked for the file existence in the project directory which we copied to EMR.
for example mine was in `//usr/local/project_folder/`
Step 2: Copy the script which you're expecting to run on the EMR.
for example I copied from `//usr/local/project_folder/script_name.sh` to `/home/hadoop/`
Step 3: Then executed the script from /home/hadoop/ by passing the absolute path to the command-runner.jar
command-runner.jar bash /home/hadoop/script_name.sh
Thus I found my script running. Hope this may be helpful to someone