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

Question

Options

• AHeath states checks (heartbeats)
• BResource management
• CJob scheduling/monitoring
• DJob coordination between the ResourceManager and NodeManager
• ELaunching tasks
• FManaging file system metadata
• GMapReduce metric reporting
• HManaging tasks

• B
  78% (21)
• D
  4% (1)
• F
  4% (1)
• G
  4% (1)
• H
  11% (3)

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. 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.

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