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

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

Answer: B,C

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 C Concepts & Applications