HI @dbompart Yes the logic you mentioned is perfectly I have some more clarification regarding containers on Map Reduce and Spark In Map Reduce running sqoop Import In Spark running PySpark shell on top of yarn Now the configuration : MapReduce:- yarn.scheduler.maximum-allocation-MB :- 36864 * 2 = 73728 But my concern is now how can i limit the Running containers per user basics (I cant set Different queues in capacitor scheduler as mentioned above) -> When ever i am running spark application is also running on top of yarn Running Containers :- 3 Allocated CPU's :- 3 Total Memory allocated :- 5120 Will you help me the logic what is happening behind these Thanks a lot
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