[High Quality Questions] Most Reliable Cisco IINS 210-260 Dumps Exams Questions And Answers Youtube Online

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Exam Code: 210-260
Exam Name: Implementing Cisco Network Security
Q&As: 310

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210-260 dumps

QUESTION 12
Which tasks is the session management path responsible for? (Choose three.)
A. Verifying IP checksums
B. Performing route lookup
C. Performing session lookup
D. Allocating NAT translations
E. Checking TCP sequence numbers
F. Checking packets against the access list
210-260 exam Correct Answer: BDF
QUESTION 13
Which statement about extended access lists is true?
A. Extended access lists perform filtering that is based on source and destination and are most effective
when applied to the destination
B. Extended access lists perform filtering that is based on source and destination and are most effective
when applied to the source
C. Extended access lists perform filtering that is based on destination and are most effective when applied
to the source
D. Extended access lists perform filtering that is based on source and are most effective when applied to
the destination
Correct Answer: B
QUESTION 14
Refer to the exhibit.
210-260 dumps

If a supplicant supplies incorrect credentials for all authentication methods configured on the switch, how
will the switch respond?
A. The supplicant will fail to advance beyond the webauth method.
B. The switch will cycle through the configured authentication methods indefinitely.
C. The authentication attempt will time out and the switch will place the port into the unauthorized state.
D. The authentication attempt will time out and the switch will place the port into VLAN 101.
210-260 dumps Correct Answer: A
QUESTION 15
Refer to the exhibit.
210-260 dumps

Which statement about the device time is true?
A. The time is authoritative, but the NTP process has lost contact with its servers.
B. The time is authoritative because the clock is in sync.
C. The clock is out of sync.
D. NTP is configured incorrectly.
E. The time is not authoritative.
Correct Answer: A
QUESTION NO: 16
Your Hadoop cluster has 25 nodes with a total of 100 TB (4 TB per node) of raw disk space
allocated HDFS storage. Assuming Hadoop’s default configuration, how much data will you be
able to store?
A. Approximately 100TB
B. Approximately 25TB
C. Approximately 10TB
D. Approximately 33 TB
210-260 pdf Answer: D
In default configuration there are total 3 copies of a datablock on HDFS, 2 copies
are stored on datanodes on same rack and 3rd copy on a different rack.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, How the
HDFS Blocks are replicated?
QUESTION NO: 17
You set up the Hadoop cluster using NameNode Federation. One NameNode manages the/users
namespace and one NameNode manages the/data namespace. What happens when client tries
to write a file to/reports/myreport.txt?
A. The file successfully writes to /users/reports/myreports/myreport.txt.
B. The client throws an exception.
C. The file successfully writes to /report/myreport.txt. The metadata for the file is managed by the
first NameNode to which the client connects.
D. The file writes fails silently; no file is written, no error is reported.
Answer: C
Note:
* The current HDFS architecture allows only a single namespace for the entire cluster. A single
Namenode manages this namespace. HDFS Federation addresses limitation of current
architecture by adding support multiple Namenodes/namespaces to HDFS file system.
* HDFS Federation enables multiple NameNodes in a cluster for horizontal scalability of
NameNode. All these NameNodes work independently and don’t require any co-ordination. A
DataNode can register with multiple NameNodes in the cluster and can store the data blocks for
multiple NameNodes.

QUESTION NO: 18
Identify two features/issues that MapReduce v2 (MRv2/YARN) is designed to address:
A. Resource pressure on the JobTrackr
B. HDFS latency.
C. Ability to run frameworks other than MapReduce, such as MPI.
D. Reduce complexity of the MapReduce APIs.
E. Single point of failure in the NameNode.
F. Standardize on a single MapReduce API.
210-260 vce Answer: A,C
A: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.
C: YARN, as an aspect of Hadoop, has two major kinds of benefits:
The ability to use programmingframeworks other than MapReduce
Scalability, no matter what programming framework you use.
QUESTION NO: 19
The most important consideration for slave nodes in a Hadoop cluster running production jobs that
require short turnaround times is:
A. The ratio between the amount of memory and the number of disk drives.
B. The ratio between the amount of memory and the total storage capacity.
C. The ratio between the number of processor cores and the amount of memory.
D. The ratio between the number of processor cores and total storage capacity.
E. The ratio between the number of processor cores and number of disk drives.
210-260 exam Answer: D
QUESTION NO: 20
The failure of which daemon makes HDFS unavailable on a cluster running MapReduce v1
(MRv1)?
A. Node Manager
B. Application Manager
C. Resource Manager
D. Secondary NameNode
E. NameNode
F. DataNode
Answer: E
The NameNode is the centerpiece of an HDFS file system. It keeps the directory
tree of all files in the file system, and tracks where across the cluster the file data is kept. It does
not store the data of these files itself. There is only One NameNode process run on any hadoop
cluster. NameNode runs on its own JVM process. In a typical production cluster its run on a
separate machine. The NameNode is a Single Point of Failure for the HDFS Cluster. When the

NameNode goes down, the file system goes offline.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, What is a
NameNode? How many instances of NameNode run on a Hadoop Cluster?

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