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NEW QUESTION: 1

A. Option C
B. Option D
C. Option B
D. Option A
Answer: A,B
Explanation:
Guest Memory is actually the memory usage of a virtual machine. And the host memory includes VM overhead. Reference:http://www.vmwarearena.com/2012/08/performance-metrics-of-vmware-virtual.html

NEW QUESTION: 2
Why Describe the Data Selected? In order for Automated Analytics
features to interpret and analyze your data, the data must be described.
To put it another way, the description file must specify the nature of
each variable, determining their:
Note: There are 2 correct answers to this question.
A. Type: continuous, nominal, ordinal or textual
B. Storage format: number
C. A Java Runtime Environment installed on the client machine to connect to the server
D. A valid SAP Predictive Analytics License
Answer: A,B

NEW QUESTION: 3
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate daemons? Select two.
A. Job coordination between the ResourceManager and NodeManager
B. Heath states checks (heartbeats)
C. Job scheduling/monitoring
D. Resource management
E. Managing tasks
F. MapReduce metric reporting
G. Launching tasks
H. Managing file system metadata
Answer: A,D
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