I want to get top 3 yarn applications in running state from all clusters
output : AppicationId, Application Type, Memory occupied, start time
Related
Run 3 Topologies On Storm Clusters,Through storm list command line ,show me 3 topologies and the state all ACTIVE ,But In /home/storm/data/supervisor/stormdist/ Dir only 2 topologies, One Of them Not Run?
let's consider a following scenario:
[user#host ~]$ yarn applicationattempt -list application_1620157095390_0392
Total number of application attempts :1
ApplicationAttempt-Id State AM-Container-Id
appattempt_1620157095390_0392_000001 FINISHED container_1620157095390_0392_01_000001
[user#host ~]$ yarn container -list appattempt_1620157095390_0392_000001
Total number of containers :0
Container-Id Start Time Finish Time State Host Node Http Address LOG-URL
Could someone explain me why it does not show any container? I am sure that for this app some containers were executed.
My version of hadoop is 3.
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
I have two spark contexts running on a box, 1 from python and 1 from scala. They are similarly configured, yet only the python application appears in the spark history page pointed to by the yarn tracking URL. Is there extra configuration I am missing here? (both run in yarn-client mode)
I have a cluster of 3 macOS machines running Hadoop and Spark-1.5.2 (though with Spark-2.0.0 the same problem exists). With 'yarn' as the Spark master URL, I am running into a strange issue where tasks are only allocated to 2 of the 3 machines.
Based on the Hadoop dashboard (port 8088 on the master) it is clear that all 3 nodes are part of the cluster. However, any Spark job I run only uses 2 executors.
For example here is the "Executors" tab on a lengthy run of the JavaWordCount example:
"batservers" is the master. There should be an additional slave, "batservers2", but it's just not there.
Why might this be?
Note that none of my YARN or Spark (or, for that matter, HDFS) configurations are unusual, except provisions for giving the YARN resource- and node-managers extra memory.
Remarkably, all it took was a detailed look at the spark-submit help message to discover the answer:
YARN-only:
...
--num-executors NUM Number of executors to launch (Default: 2).
If I specify --num-executors 3 in my spark-submit command, the 3rd node is used.