You have converted your Hadoop cluster from a MapReduce 1 (MRv1) architecture to
aMapReduce 2 (MRv2) on YARN architecture. Your developers are accustomed to
specifying map and reduce tasks (resource allocation) tasks when they run jobs. A
developer wants to know how specify to reduce tasks when a specific job runs. Which
method should you tell that developer to implement?

A.
In YARN, resource allocation is a function of virtual cores specified by the
ApplicationMaster making requests to the NodeManager where a reduce task is handled by
a single container (and this a single virtual core). Thus, the developer needs to specify the
number of virtual cores to the NodeManager by executing –p
yarn.nodemanager.cpuvcores= 2

B.
MapReduce version 2 (MRv2) on YARN abstracts resource allocation away from the idea
of “tasks” into memory and virtual cores, thus eliminating the need for a developer to specify
the number of reduce tasks, and indeed preventing the developer from specifying the
number of reduce tasks.

C.
In YARN, resource allocation is a function of megabytes of memory in multiple of
1024mb. Thus, they should specify the amount of memory resource they need by executing
–D mapreduce.reduce.memory-mp-2040

D.
In YARN, the ApplicationMaster is responsible for requesting the resources required for a

specific job. Thus, executing –p yarn.applicationmaster.reduce.tasks-2 will specify that the
ApplicationMaster launch two task containers on the worker nodes.

E.
Developers specify reduce tasks in the exact same way for both MapReduce version 1
(MRv1) and MapReduce version 2 (MRv2) on YARN. Thus, executing –p
mapreduce.job.reduce-2 will specify 2 reduce tasks.