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NEW QUESTION: 1
You are managing the APPPROD database as a DBA which is not using the Oracle-managed files. You plan to duplicate this database in the same system with the name DUPDB.You want to create the same directory structure for duplicate database files as of the target database.
You executed the following RMAN commands:
RMAN> CONNECT TARGET sys/sys@APPPROD
RMAN> CONNECT AUXILIARY sys/sys@DUPDB
RMAN> DUPLICATE TARGET DATABASE
TO dupdb
FROM ACTIVE DATABASE
PASSWORD FILE
SPILE
NOFILENAMECHECK;
What are the implications of this command?
A. It overwrites data files of the target database because a different location for data files is not mentioned for the duplicate database.
B. It creates database files for the duplicate database under the same Oracle home as that of the target database with the same directory structure.
C. It creates database files for the duplicate database under the Oracle base with a different directory for the duplicate database.
D. It creates database files for the duplicate database under the same Oracle home as that of the target but with a different directory for the duplicate database.
Answer: A
NEW QUESTION: 2
Which of the following memory form factors is MOST commonly found in laptops?
A. SODIMM
B. RAMBUS
C. DIMM
D. SDRAM
Answer: A
NEW QUESTION: 3
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate daemons? Select two.
A. Resource management
B. Job scheduling/monitoring
C. Job coordination between the ResourceManager and NodeManager
D. Managing file system metadata
E. Heath states checks (heartbeats)
F. MapReduce metric reporting
G. Managing tasks
H. Launching tasks
Answer: A,B
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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