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CCA-505 Examination questions (September)

Achieve New Updated (September) Cloudera CCA-505 Examination Questions 21-30

September 24, 2015

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QUESTION 21

Which YARN process runs as “controller O” of a submitted job and is responsible for resource requests?

 

A.

ResourceManager

B.

NodeManager

C.

JobHistoryServer

D.

ApplicationMaster

E.

JobTracker

F.

ApplicationManager

 

Answer: D

 

 

QUESTION 22

Which process instantiates user code, and executes map and reduce tasks on a cluster running MapReduce V2 (MRv2) on YARN?

 

A.

NodeManager

B.

ApplicationMaster

C.

ResourceManager

D.

TaskTracker

E.

JobTracker

F.

DataNode

G.

NameNode

 

Answer: E

 

 

QUESTION 23

You decide to create a cluster which runs HDFS in High Availability mode with automatic failover, using Quorum-based Storage. What is the purpose of ZooKeeper in such a configuration?

 

A.

It manages the Edits file, which is a log changes to the HDFS filesystem.

B.

It monitors an NFS mount point and reports if the mount point disappears

C.

It both keeps track of which NameNode is Active at any given time, and manages the Edits file, which is a log of changes to the HDFS filesystem

 

 

 

 

D.

It only keeps track of which NameNode is Active at any given time

E.

Clients connect to ZoneKeeper to determine which NameNode is Active

 

Answer: D

Reference: http://www.cloudera.com/content/cloudera-content/cloudera- docs/CDH4/latest/PDF/CDH4-High-Availability-Guide.pdf (page 15)

 

 

QUESTION 24

You are upgrading a Hadoop cluster from HDFS and MapReduce version 1 (MRv1) to one running HDFS and MapReduce version 2 (MRv2) on YARN. You want to set and enforce a block of 128MB for all new files written to the cluster after the upgrade. What should you do?

 

A.

Set dfs.block.size to 128M on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final.

B.

Set dfs.block.size to 134217728 on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final.

C.

Set dfs.block.size to 134217728 on all the worker nodes and client machines, and set the parameter to final. You do need to set this value on the NameNode.

D.

Set dfs.block.size to 128M on all the worker nodes and client machines, and set the parameter to final. You do need to set this value on the NameNode.

E.

You cannot enforce this, since client code can always override this value.

 

Answer: C

 

 

QUESTION 25

You are planning a Hadoop cluster and considering implementing 10 Gigabit Ethernet as the network fabric. Which workloads benefit the most from a faster network fabric?

 

A.

When your workload generates a large amount of output data, significantly larger than amount of intermediate data

B.

When your workload generates a large amount of intermediate data, on the order of the input data itself

C.

When workload consumers a large amount of input data, relative to the entire capacity of HDFS

D.

When your workload consists of processor-intensive tasks

 

 

 

 

 

Answer: B

 

 

QUESTION 26

Which Yarn daemon or service monitors a Container’s per-application resource usage (e.g, memory, CPU)?

 

A.

NodeManager

B.

ApplicationMaster

C.

ApplicationManagerService

D.

ResourceManager

 

Answer: A

Reference: http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.0.0.2/bk_using- apache-hadoop/content/ch_using-apache-hadoop-4.html (4th para)

 

 

QUESTION 27

Each node in your Hadoop cluster, running YARN, has 64 GB memory and 24 cores. Your yarn-site.xml has the following configuration:

 

<property>

 

<name>yarn.nodemanager.resource.memory-mb</name>

 

<value>32768</value>

 

</property>

 

<property>

 

<name>yarn.nodemanager.resource.cpu-vcores</name>

 

<value>23</value>

 

</property>

 

You want YARN to launch no more than 16 containers per node. What should you do?

 

 

 

 

 

A.

No action is needed: YARN’s dynamic resource allocation automatically optimizes the node memory and cores

B.

Modify yarn-site.xml with the following property:

<name>yarn.nodemanager.resource.cpu-vcores</name>

<value>16</value>

C.

Modify yarn-site.xml with the following property:

<name>yarn.scheduler.minimum-allocation-mb</name>

<value>2048</value>

D.

Modify yarn-site.xml with the following property:

<name>yarn.scheduler.minimum-allocation-mb</name>

<value>4096</value>

 

Answer: B

 

 

QUESTION 28

Identify two features/issues that YARN is designed to address:

 

A.

Standardize on a single MapReduce API

B.

Single point of failure in the NameNode

C.

Reduce complexity of the MapReduce APIs

D.

Resource pressures on the JobTracker

E.

Ability to run frameworks other than MapReduce, such as MPI

F.

HDFS latency

 

Answer: DE

 

 

QUESTION 29

Your cluster is running MapReduce vserion 2 (MRv2) on YARN. Your ResourceManager is configured to use the FairScheduler. Now you want to configure your scheduler such that a new user on the cluster can submit jobs into their own queue application submission.

Which configuration should you set?

 

A.

You can specify new queue name when user submits a job and new queue can be created dynamically if yarn.scheduler.fair.user-as-default-queue = false

B.

Yarn.scheduler.fair.user-as-default-queue = false and yarn.scheduler.fair.allow- undeclared-people = true

C.

You can specify new queue name per application in allocation.fair.allow-undeclared- people = true automatically assigned to the application queue

 

 

 

 

D.

You can specify new queue name when user submits a job and new queue can be created dynamically if the property yarn.scheduler.fair.allow-undecleared-pools = true

 

Answer: A

 

 

QUESTION 30

Which three basic configuration parameters must you set to migrate your cluster from MapReduce1 (MRv1) to MapReduce v2 (MRv2)?

 

A.

Configure the NodeManager hostname and enable services on YARN by setting the following property in yarn-site.xml:

<name>yarn.nodemanager.hostname</name>

<value>your_nodeManager_hostname</value>

B.

Configure the number of map tasks per job on YARN by setting the following property in mapred-site.xml:

<name>mapreduce.job.maps</name>

<value>2</value>

C.

Configure MapReduce as a framework running on YARN by setting the following property in mapred-site.xml:

<name>mapreduce.framework.name</name>

<value>yarn</value>

D.

Configure the ResourceManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:

<name>yarn.resourcemanager.hostname</name>

<value>your_responseManager_hostname</value>

E.

Configure a default scheduler to run on YARN by setting the following property in sapred-site.xml:

<name>mapreduce.jobtracker.taskScheduler</name>

<value>org.apache.hadoop.mapred.JobQueueTaskScheduler</value>

F.

Configure the NodeManager to enable MapReduce services on YARN by adding following property in yarn-site.xml:

<name>yarn.nodemanager.aux-services</name>

<value>mapreduce_shuffle</value>

 

Answer: ABD

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