Capacity Scheduler queue is not working

[#1]

I have added new queue developer and given a capacity 40 %. Below is my change:

yarn.scheduler.capacity.maximum-am-resource-percent=0.2 yarn.scheduler.capacity.maximum-applications=10000 yarn.scheduler.capacity.node-locality-delay=40 yarn.scheduler.capacity.root.accessible-node-labels=* yarn.scheduler.capacity.root.acl_administer_queue=* yarn.scheduler.capacity.root.capacity=100 yarn.scheduler.capacity.root.default.acl_submit_applications=root yarn.scheduler.capacity.root.default.capacity=60 yarn.scheduler.capacity.root.default.maximum-capacity=100 yarn.scheduler.capacity.root.default.state=RUNNING yarn.scheduler.capacity.root.default.user-limit-factor=1 yarn.scheduler.capacity.root.queues=default,developers yarn.scheduler.capacity.queue-mappings-override.enable=false yarn.scheduler.capacity.root.default.priority=0 yarn.scheduler.capacity.root.developers.acl_administer_queue=* yarn.scheduler.capacity.root.developers.acl_submit_applications=hdfs yarn.scheduler.capacity.root.developers.capacity=40 yarn.scheduler.capacity.root.developers.maximum-capacity=40 yarn.scheduler.capacity.root.developers.minimum-user-limit-percent=100 yarn.scheduler.capacity.root.developers.ordering-policy=fifo yarn.scheduler.capacity.root.developers.priority=0 yarn.scheduler.capacity.root.developers.state=RUNNING yarn.scheduler.capacity.root.developers.user-limit-factor=1 yarn.scheduler.capacity.root.priority=0

When i execute query from hdfs user that belong to developer group then it is going in default queue instead of developer.

Please note that i am using hdp 2.5 and ambari 2.6 version,

[#2]

@Fahad Sarwar

The "acl_submit_applications" property controls who can (has permission to) submit applications to the given queue but it in itself doesn't say anything about which queue to actually use.

Defining which YARN queue to use is application specific, for example in MapReduce, you need this property: mapreduce.job.queuename.

[#3]

@Fahad Sarwar, Capacity scheduler does not have placement rules, where you can configure that if userX is running job, place the job in QueueX.

Capacity scheduler ACLS only check whether the application is allowed to run in specific queue or not.

In order to be able to run the job in a specific queue, you will need to set the queue config while running apps. ( If the queue config is not set, by default application gets launched in "default" queue)

For mapreduce jobs : set -Dmapred.job.queue.name=<queue-name> or -Dmapred.job.queuename=<queue-name>

yarn jar /usr/lib/gphd/hadoop-mapreduce/hadoop-mapreduce-examples-x.x.x-alpha-gphd-x.x.x.x.jar wordcount -D mapreduce.job.queuename=<queue-name> /tmp/test_input /user/fail_user/test_output

For spark jobs: set --queue <queue-name>

spark-submit --class org.apache.spark.examples.SparkPi --master yarn-cluster --queue <queue-name> /usr/hdp/2.x.x.x-xxxx/spark/lib/spark-examples-x.x.x.x.x.x.x-xxxx-hadoopx.x.x.x.x.x.x-xxxx.jar 10