MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate
daemons? Select two.

A.
Heath states checks (heartbeats)

B.
Resource management

C.
Job scheduling/monitoring

D.
Job coordination between the ResourceManager and NodeManager

E.
Launching tasks

F.
Managing file system metadata

G.
MapReduce metric reporting

H.
Managing tasks

Explanation:
The fundamental idea of MRv2 is to split up the two major functionalities of the
JobTracker, resource management and job scheduling/monitoring, into separate daemons. The
idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM). An
application is either a single job in the classical sense of Map-Reduce jobs or a DAG of jobs.
Note:
The central goal of YARN is to clearly separate two things that are unfortunately smushed together
in current Hadoop, specifically in (mainly) JobTracker:
/ Monitoring the status of the cluster with respect to which nodes have which resources available.
Under YARN, this will be global.
/ Managing the parallelization execution of any specific job. Under YARN, this will be done
separately for each job.

Reference: Apache Hadoop YARN – Concepts & Applications