Cloudera Exam CCA-500 Topic 4 Question 2 Discussion

Actual exam question for Cloudera's CCA-500 exam

Question #: 2
Topic #: 4

You have recently converted your Hadoop cluster from a MapReduce 1 (MRv1) architecture to MapReduce 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 developers to implement?

AMapReduce 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.

BIn YARN, resource allocations is a function of megabytes of memory in multiples of 1024mb.
Thus, they should specify the amount of memory resource they need by executing --D mapreducereduces.
memory-mb-2048

CIn YARN, the ApplicationMaster is responsible for requesting the resource required for a
specific launch. Thus, executing --D yarn.applicationmaster.reduce.tasks=2 will specify that the
ApplicationMaster launch two task contains on the worker nodes.

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

EIn YARN, resource allocation is function of virtual cores specified by the ApplicationManager
making requests to the NodeManager where a reduce task is handeled by a single container (and
thus a single virtual core). Thus, the developer needs to specify the number of virtual cores to the
NodeManager by executing --p yarn.nodemanager.cpu-vcores=2

Show Suggested Answer

Suggested Answer: D

by Elouise at Dec 28, 2022, 01:45 PM

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