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NEW QUESTION: 1
The Huawei OceanStor 9000 InfoTier file pool policy will determine the storage location of the file creation and the target grading when the file is re-striped.
Which one is incorrect about the file pool strategy?
A. Support up to 128 file pool policies
B. default policy has the lowest priority
C. default policy can be modified
D. Relationship between policy parameter combinations is OR
Answer: D

NEW QUESTION: 2
Which two statement about the DNS are true? (Choose two.)
A. The client-server architecture is based on query and response messages.
B. In the DNS message header, the QR flag set to 1 indicates a query.
C. In the DNS header, an Opcode value of 2 represents a client status request.
D. Query and response messages have different format.
E. In the DNS header, the Rcode value is set to 0 in Query message.
Answer: A,E

NEW QUESTION: 3
In a private sharing model, what is a possible reason a user can view an account record without being the record owner or system administrator?
A. The user is a member of the account team.
B. The user is in a public group at the top of the group hierarchy.
C. The user's direct report in the role hierarchy owns the account.
D. The user is a member of a queue that owns the account.
Answer: A,C

NEW QUESTION: 4
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate
daemons? Select two.
A. Managing file system metadata
B. Resource management
C. MapReduce metric reporting
D. Launching tasks
E. Job coordination between the ResourceManager and NodeManager
F. Managing tasks
G. Heath states checks (heartbeats)
H. Job scheduling/monitoring
Answer: B,H
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


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