I am trying to submit a M/R job from windows machine to hadoop cluster on linux. I am using hadoop 2.2.0 (HDP 2.0).
I am getting following error:
2014-06-06 08:32:37,684 [main] INFO Job.monitorAndPrintJob - Job job_1399458460502_0053 running in uber mode : false
2014-06-06 08:32:37,704 [main] INFO Job.monitorAndPrintJob - map 0% reduce 0%
2014-06-06 08:32:37,717 [main] INFO Job.monitorAndPrintJob - Job job_1399458460502_0053 failed with state FAILED due to: Application application_1399458460502_0053 failed 2 times due to AM Container for appattempt_1399458460502_0053_000002 exited with exitCode: 1 due to: Exception from container-launch:
org.apache.hadoop.util.Shell$ExitCodeException: /bin/bash: line 0: fg: no job control
at org.apache.hadoop.util.Shell.runCommand(Shell.java:464)
at org.apache.hadoop.util.Shell.run(Shell.java:379)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:589)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:195)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:283)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:79)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
.Failing this attempt.. Failing the application.
java.io.IOException: Job failed!
I using configuration taken from the cluster so there should be exact match.
Any hints or clue, what might be wrong?
Thx
conf.set("mapreduce.app-submission.cross-platform", "true");
I found solution. It is officially reported bug
https://issues.apache.org/jira/browse/MAPREDUCE-4052
with workaround mentioned down in discussion.
Workaround works fine for me. Seems that those bugs with something resolved on a client side are ever green.
I had a similar issue .Now it is working for me .
Check the below link
Error while running Mapreduce(yarn)from windows eclipse
Related
On executing jar in hadoop, I get the following error:
16/11/04 18:32:59 INFO mapreduce.Job: Task Id : attempt_1478261728730_0005_m_000000_2, Status : FAILED
Exception from container-launch.
Container id: container_1478261728730_0005_01_000004
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:538)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:211)
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:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 1
16/11/04 18:33:09 INFO mapreduce.Job: map 100% reduce 0%
This is application log:
Native code library failed to load.
java.lang.UnsatisfiedLinkError: no opencv_java2411 in java.library.pathopencv_java2411
I don't know what it mean, can anybody help with this please?
You are missing opencv on your cluster nodes.
See here for all the details on how to handle this.
Long story short though, you need to install opencv on your executors. You cannot really compile it into your job's .jar in a portable way since it's C and not Java code.
Update:
Note that the environment on your Hadoop executors is set by your hadoop-env.sh. So it needs to contain a line like:
JAVA_LIBRARY_PATH=${JAVA_LIBRARY_PATH}:/etc/opencv/lib
I am running a small private cluster of linux machines with Hadoop 2.6.2 and yarn. I launch yarn jobs from a linux edge node. The canned Yarn example to approximate the value of pi works perfectly when run by the hadoop (superuser, owner of the cluster) user, but fails when run from my personal account on the edge node. In both cases (hadoop, me) I run the job exactly like this:
clott#edge: /home/hadoop/hadoop-2.6.2/bin/yarn jar /home/hadoop/hadoop-2.6.2/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.2.jar pi 2 5
It fails; the full output is below. I think the file-not-found exception is totally bogus. I think something causes the launch of the container to fail, and so there's no output to be found. What causes container launches to fail, and how can this be debugged?
Because this identical same command works perfectly when run by the hadoop user but not when run by a different account on the same edge node, I suspect a permission or other yarn configuration problem; I don't suspect a missing-jar file problem. My personal account uses the same environment variables as the hadoop account, for what that's worth.
These questions are similar but I didn't find a solution:
https://issues.cloudera.org/browse/DISTRO-577
Running a map reduce job as a different user
Yarn MapReduce Job Issue - AM Container launch error in Hadoop 2.3.0
I have tried these remedies without any success:
In core-site.xml, set the value of hadoop.tmp.dir to /tmp/temp-${user.name}
Add my personal user account to every node in the cluster
I guess that many installations run with just a single user, but I'm trying to allow two people to work together on the cluster without trashing each other's intermediate results. Am I totally nuts?
Full output:
Number of Maps = 2
Samples per Map = 5
Wrote input for Map #0
Wrote input for Map #1
Starting Job
15/12/22 15:29:18 INFO client.RMProxy: Connecting to ResourceManager at ac1.mycompany.com/1.2.3.4:8032
15/12/22 15:29:18 INFO input.FileInputFormat: Total input paths to process : 2
15/12/22 15:29:19 INFO mapreduce.JobSubmitter: number of splits:2
15/12/22 15:29:19 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1450815437271_0002
15/12/22 15:29:19 INFO impl.YarnClientImpl: Submitted application application_1450815437271_0002
15/12/22 15:29:19 INFO mapreduce.Job: The url to track the job: http://ac1.mycompany.com:8088/proxy/application_1450815437271_0002/
15/12/22 15:29:19 INFO mapreduce.Job: Running job: job_1450815437271_0002
15/12/22 15:29:31 INFO mapreduce.Job: Job job_1450815437271_0002 running in uber mode : false
15/12/22 15:29:31 INFO mapreduce.Job: map 0% reduce 0%
15/12/22 15:29:31 INFO mapreduce.Job: Job job_1450815437271_0002 failed with state FAILED due to: Application application_1450815437271_0002 failed 2 times due to AM Container for appattempt_1450815437271_0002_000002 exited with exitCode: 1
For more detailed output, check application tracking page:http://ac1.mycompany.com:8088/proxy/application_1450815437271_0002/Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_1450815437271_0002_02_000001
Exit code: 1
Stack trace: ExitCodeException exitCode=1:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:538)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:211)
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:262)
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)
Container exited with a non-zero exit code 1
Failing this attempt. Failing the application.
15/12/22 15:29:31 INFO mapreduce.Job: Counters: 0
Job Finished in 13.489 seconds
java.io.FileNotFoundException: File does not exist: hdfs://ac1.mycompany.com/user/clott/QuasiMonteCarlo_1450816156703_163431099/out/reduce-out
at org.apache.hadoop.hdfs.DistributedFileSystem$18.doCall(DistributedFileSystem.java:1122)
at org.apache.hadoop.hdfs.DistributedFileSystem$18.doCall(DistributedFileSystem.java:1114)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1114)
at org.apache.hadoop.io.SequenceFile$Reader.<init>(SequenceFile.java:1817)
at org.apache.hadoop.io.SequenceFile$Reader.<init>(SequenceFile.java:1841)
at org.apache.hadoop.examples.QuasiMonteCarlo.estimatePi(QuasiMonteCarlo.java:314)
at org.apache.hadoop.examples.QuasiMonteCarlo.run(QuasiMonteCarlo.java:354)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at org.apache.hadoop.examples.QuasiMonteCarlo.main(QuasiMonteCarlo.java:363)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:71)
at org.apache.hadoop.util.ProgramDriver.run(ProgramDriver.java:144)
at org.apache.hadoop.examples.ExampleDriver.main(ExampleDriver.java:74)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
Yes Manjunath Ballur you were right it was a permissions problem! Finally learned how to preserve the yarn application logs, which clearly revealed the problem. Here are the steps:
Edit yarn-site.xml and add a property to delay yarn log deletion:
<property>
<name>yarn.nodemanager.delete.debug-delay-sec</name>
<value>600</value>
</property>
Push yarn-site.xml to all nodes (ARGH I forgot this for a long time) and restart cluster.
Run yarn example to estimate pi as shown above, it fails. Look at http://namenode:8088/cluster/apps/FAILED to see the failed application, click on the link for the most recent failure, look at the bottom to see which nodes in the cluster were used.
Open a window on one of the nodes in the cluster where the app failed. Find the job directory, which in my case was
~hadoop/hadoop-2.6.2/logs/userlogs/application_1450815437271_0004/container_1450815437271_0004_01_000001/
Et voila, I saw files stdout (only log4j bitching), stderr (nearly empty) and syslog (winner winner chicken dinner). In the syslog file I found this gem:
2015-12-23 08:31:42,376 INFO [main] org.apache.hadoop.service.AbstractService: Service JobHistoryEventHandler failed in state INITED; cause: org.apache.hadoop.yarn.exceptions.YarnRuntimeException: org.apache.hadoop.security.AccessControlException: Permission denied: user=clott, access=EXECUTE, inode="/tmp/hadoop-yarn/staging/history":hadoop:supergroup:drwxrwx---
So the problem was permissions on hdfs:///tmp/hadoop-yarn/staging/history. A simple chmod 777 put me right, I'm not fighting the group perms anymore. Now a non-hadoop non-superuser can run a yarn job.
I am unable to submit the job in yarn cluster.The job is running fine under yarn-client option. When submit it to yarn-cluster only this log is coming multiple times.
Application report for application_1421828570504_0002 (state: ACCEPTED)
and got failed with the following exception.
diagnostics: Application application_1421828570504_0002 failed 10 times due to AM Container for app
attempt_1421828570504_0002_000010 exited with exitCode: 1 due to: Exception from container-launch: org.apache.hadoop.util.Shell$ExitCodeException:
org.apache.hadoop.util.Shell$ExitCodeException:
You should have a look at the logs of your application:
> yarn logs --applicationId application_1421828570504_0002
This will yield some debug information of the actual run within the spark containers.
Since it is running locally but not on the cluster my wild guess would be a missing SparkContext definition. Have a look at my answer to this question for a fix.
I am running a storm (trident) topology that reads avro from kafka & writes the records in hbase.
The topology is running as expected in Localcluster mode, but while using Stormsubmitter I'm facing below issues.
In Distributed Hadoop mode I'm getting the below error [1] while launching the YARN application.
In Hadoop (local mode, with 1 box only) Yarn is spawnning the nimbus server and storm-ui. But there are no supervisor(s) running to run the spout/bolts in the topology. I guess the reason might be insufficient memory (4G to run the topology + hbase, hdfs, kafka, zookeeper etc...).
Can you help me out in understanding the reason of this container failure? There are no errors/info present in application logs.
[1] YARN container fails to launch with below error on running.
storm-yarn launch /homext/storm-yarn.yml --queue default -appname storm-yarn-demo --stormZip /tmp/storm-0.9.zip
Application application_1415038356032_0304 failed 2 times due to AM Container for appattempt_1415038356032_0304_000002 exited with exitCode: 127 due to: Exception from container-launch: org.apache.hadoop.util.Shell$ExitCodeException:
org.apache.hadoop.util.Shell$ExitCodeException:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:505)
at org.apache.hadoop.util.Shell.run(Shell.java:418)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:650)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:195)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:283)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:79)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 127
.Failing this attempt.. Failing the application.
This log is insufficient to diagnose. All it says is that the container failed to launch. You should look into the container output. Check the ${yarn.nodemanager.log-dirs} on the nodes, there will be an application folder (application_1415038356032_0304) and in there there will be a container folder for each attempt (...1415038356032_0304_000002) containing the stderr, stdout and syslog of this attempt. Read those and you'll likely identify the problem.
If these don't exist, look in ${yarn.nodemanager.local-dirs} you'll find the container launch script (I thinks is called container-launch.sh) for this app/container attempt. In it will be the actual command to launch the container. Try to run that from the shell prompt and see what you get.
If it fails at an early stage then the logs can be found in HDFS under:
/tmp/logs/<user>/logs/
This should give enough information to diagnose the problem.
In my case I found a log file:
/tmp/logs/hdfs/logs/application_1426618997634_0004/vagrant-cdh-node4_8041
With some errors like:
/bin/bash: /usr/lib/jvm/java-7-oracle/bin/java: No such file or directory
And fixing the JAVA_HOME environment variable did the trick.
I am new to EMR and whenever I run a job I get this error in syslog:
2014-05-27 03:59:57,220 INFO org.apache.hadoop.mapreduce.Job (main): Job job_1401143947501_0009 failed with state FAILED due to: Application application_1401143947501_0009 failed 2 times due to AM Container for appattempt_1401143947501_0009_000002 exited with exitCode: 1 due to: Exception from container-launch:
org.apache.hadoop.util.Shell$ExitCodeException:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:464)
at org.apache.hadoop.util.Shell.run(Shell.java:379)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:589)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:195)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:283)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:79)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
I have no idea what this means and what I should look into. I have looked around quite a bit and there seems to be lot of different opinions. Some have suggested removing yarn.application.classpath from yarn-site.xml and/or changing yarn.nodemanager.resource.memory-mb in the same file. But, nothing has worked so far. I feel like I am shooting in the dark. If someone can point me what I should look for, then it will be really helpful.
Thanks in advance