Oozie Bundles: Relaunching a coordinator inside an oozie bundle - bundle

Say I have a currently running oozie bundle running coordinators A and B.
I do development work on coordinator B and I want to relaunch coordinator B.
Is there any way to relaunch a coordinator inside of an oozie bundle, without restarting the bundle itself? This is because I don't want to restart coordinator A.
Otherwise, is there a way to add/remove a coordinator from a currently running oozie bundle?

Related

Restart oozie bundle job in killed state

I want to restart an oozie bundle job that is in a killed state.
The bundle job has one coordinator job.
I accidentally killed the coordinator job instead of killing a particular action id.
Due to this the bundle job is also marked as killed.
I tried -rerun on the individual actions on the coordinator job, but no new actions are getting created.
I tried -rerun on the bundle job but don't see any change in the bundle job status. It is still showing as killed.
Please suggest if there is a way to make the bundle job into running again.
Thanks

Get list of executed job on Hadoop cluster after cluster reboot

I have a hadoop cluster 2.7.4 version. Due to some reason, I have to restart my cluster. I need job IDs of those jobs that were executed on cluster before cluster reboot. Command mapred -list provide currently running of waiting jobs details only
You can see a list of all jobs on the Yarn Resource Manager Web UI.
In your browser go to http://ResourceManagerIPAdress:8088/
This is how the history looks on the Yarn cluster I am currently testing on (and I restarted the services several times):
See more info here

Forcing Oozie job to run on specific node

I have a 6 node cluster.
When trying to run an oozie job, it triggers the job in any of the 6 nodes
Is there a way to specify the node in which the oozie shell action should be triggered

Spark jobserver is not finishing YARN processes

I have configured Spark jobserver to run on YARN.
I am able to send spark jobs to YARN but even after the job finishes it does not quit on YARN
For eg:
I tried to make a simple spark context.
The context is reflecting in jobserver but YARN is still running the process and is not quieting I have to manually kill the tasks.
Yarn Job
Spark Context
Job server reflects the contexts but as soon as I try to run any task in it Job server give me an error
{
"status": "ERROR",
"result": "context test-context2 not found"
}
My Spark UI is also not very helpful

how to start and check job history on hadoop 2.5.2

in the mapreduce webconsole for each application there is a tracking ui link which points to xx:19888/jobhistory/, but how to start the service on 19888 (i have started 4 services: yarn-resource-manager, yarn-node-manager, hdfs-name-node, hdfs-data-node, what i have missed?)
is the jobtracker removed in 2.5.2
I want to check the job.xml generated for my job, where can i find it. I have specified "mapreduce.jobtracker.jobhistory.location" but nothing is there
Thank you.
To access the JobHistory server's web interface then you have start the hadoop-mapreduce-historyserver service, which will bind to 19888 by default.
If your are running YARN in the cluster then you don't need jobtracker anymore, the work done jobtracker is offloaded to ResourceManager, NodeManager's & ApplicationMaster's. But, you could still install just MRv1 in that case you will install JobTracker and TaskTracker's (which is not recommended).
You could check the job.xml from the ResourceManager's UI by navigating to http://RESOURCEMANAGER_HOST:8088/cluster -> select your application's Tracking UI -> Select your Job ID -> On the left tab you'll be able to see Configuration. Or simply if you already know you'r job's id then visit this link: http://JOBHISTORY_SERVER:19888/jobhistory/conf/YOUR_JOB_ID.
$HADOOP_HOME/sbin/mr-jobhistory-daemon.sh --config $HADOOP_HOME/etc/hadoop start historyserver
then run jps to see if it is running.
Please try 'jps' command to verify all the services are running.
try //jhs_host:port/ Default HTTP port is 19888."
Make sure that your hadoop services are running.

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