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NEW QUESTION: 1
Which process makes use of the Cisco Installed Base Lifecycle Management (IBLM) initiative and transformative network approach?
A. a detailed approach in understanding the customer business model
B. a detailed approach in analyzing the existing customer infrastructure
C. a high-level approach in understanding the customer business model
D. a high-level approach in analyzing the existing customer infrastructure
Answer: B

NEW QUESTION: 2
Refer to the exhibit. You are a network manager for your organization. You are looking at your Syslog server reports. Based on the Syslog message shown, which two statements are true? (Choose two.)

A. This message is a level 5 notification message.
B. Service timestamps have been globally enabled.
C. This message is unimportant and can be ignored.
D. This is a normal system-generated information message and does not require further investigation.
Answer: A,B
Explanation:
Explanation

NEW QUESTION: 3
What does a profound transformation in the workplace mean to the customer?
A. They need low-priced products
B. They need longer battery fife
C. They are looking for notebooks that are thin and light, because their professional and business lives are blurring.
D. They have an increased expectation for productivity and style.
Answer: D
Explanation:
http://smartcommute.ca/mississauga/wp-content/uploads/sites/14/2015/01/HP-Canada-Co.-Gillian-Hrycko-Carmen-Chimenti-Presentation.pdf

NEW QUESTION: 4
You configure Hadoop cluster with both MapReduce frameworks, MapReduce v1 (MRv1) and MapReduce v2 (MRv2/YARN). Which two MapReduce (computational) daemons do you need to configure to run on your master nodes?
A. JobTracker
B. JournalNode
C. ResourceManager
D. NodeManager
E. ApplicationMaster
Answer: C,E
Explanation:
MapReduce has undergone a complete overhaul in hadoop-0.23 and we now have,
what we call, MapReduce 2.0 (MRv2) or YARN.
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 ResourceManager and per-node slave, the NodeManager (NM), form the data-computation
framework. The ResourceManager is the ultimate authority that arbitrates resources among all the
applications in the system.
The per-application ApplicationMaster is, in effect, a framework specific library and is tasked with
negotiating resources from the ResourceManager and working with the NodeManager(s) to
execute and monitor the tasks.
Note:
* MRV2 maintains API compatibility with previous stable release (hadoop-0.20.205). This means that all Map-Reduce jobs should still run unchanged on top of MRv2 with just a recompile.
Reference: Apache Hadoop NextGen MapReduce (YARN)