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NO.1 MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate
daemons? Select two.
A. Resource management
B. Job scheduling/monitoring
C. MapReduce metric reporting
D. Launching tasks
E. Heath states checks (heartbeats)
F. Managing file system metadata
G. Job coordination between the ResourceManager and NodeManager
H. Managing tasks
Answer: A,B

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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

NO.2 Which one of the following classes would a Pig command use to store data in a table defined in
HCatalog?
A. org.apache.hcatalog.pig.HCatStorer
B. Pig scripts cannot use an HCatalog table
C. org.apache.hcatalog.pig.HCatOutputFormat
D. No special class is needed for a Pig script to store data in an HCatalog table
Answer: A

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