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Cloudera CCA-500 Exam Dumps

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Description

Status: RETIRED

Exam Name: Cloudera Certified Administrator for Apache Hadoop

Exam Code: CCA-500 CCAH

Related Certification(s): Cloudera Certified Administrator Cloudera CCA Certification

Certification Provider: Cloudera

Actual Exam Duration: 90 Minutes

Number of CCA-500 practice questions in our database: 60

Expected CCA-500 Exam Topics, as suggested by Cloudera :

Module1: Describe the function of HDFS daemons
Module 2: Describe the normal operation of an Apache Hadoop cluster
Module 3: both in data storage and in data processing
Module 4: Identify current features of computing systems that motivate a system like Apache Hadoop

Description
Reviews (0)

Description

Status: RETIRED

Exam Name: Cloudera Certified Administrator for Apache Hadoop

Exam Code: CCA-500 CCAH

Related Certification(s): Cloudera Certified Administrator Cloudera CCA Certification

Certification Provider: Cloudera

Actual Exam Duration: 90 Minutes

Number of CCA-500 practice questions in our database: 60

Expected CCA-500 Exam Topics, as suggested by Cloudera :

Module1: Describe the function of HDFS daemons
Module 2: Describe the normal operation of an Apache Hadoop cluster
Module 3: both in data storage and in data processing
Module 4: Identify current features of computing systems that motivate a system like Apache Hadoop

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Q1. You have just run a MapReduce job to filter user messages to only those of a selected geographical region. The output for this job is in a directory named westUsers, located just below your home directory in HDFS. Which command gathers these into a single file on your local file system?

A.Hadoop fs --getmerge --R westUsers.txt

B. Hadoop fs --getemerge westUsers westUsers.txt

C. Hadoop fs --cp westUsers/* westUsers.txt

D. Hadoop fs --get westUsers westUsers.txt

Answer

Correct Answer: B

Q2. In CDH4 and later, which file contains a serialized form of all the directory and files inodes in the filesystem, giving the NameNode a persistent checkpoint of the filesystem metadata?

A.fstime

B. VERSION

C. Fsimage_N (where N reflects transactions up to transaction ID N)

D. Edits_N-M (where N-M transactions between transaction ID N and transaction ID N)

Answer

Correct Answer: C

Q3. You are running a Hadoop cluster with a NameNode on host mynamenode. What are two ways to determine available HDFS space in your cluster?

A.Run hdfs fs --du / and locate the DFS Remaining value

B. Run hdfs dfsadmin --report and locate the DFS Remaining value

C. Run hdfs dfs / and subtract NDFS Used from configured Capacity

D. Connect to http://mynamenode:50070/dfshealth.jsp and locate the DFS remaining value

Answer

Correct Answer: C, D

Q4. You have recently converted your Hadoop cluster from a MapReduce 1 (MRv1) architecture to MapReduce 2 (MRv2) on YARN architecture. Your developers are accustomed to specifying map and reduce tasks (resource allocation) tasks when they run jobs: A developer wants to know how specify to reduce tasks when a specific job runs. Which method should you tell that developers to implement?

A.MapReduce version 2 (MRv2) on YARN abstracts resource allocation away from the idea of ''tasks'' into memory and virtual cores, thus eliminating the need for a developer to specify the number of reduce tasks, and indeed preventing the developer from specifying the number of reduce tasks.

B. In YARN, resource allocations is a function of megabytes of memory in multiples of 1024mb. Thus, they should specify the amount of memory resource they need by executing --D mapreducereduces. memory-mb-2048

C. In YARN, the ApplicationMaster is responsible for requesting the resource required for a specific launch. Thus, executing --D yarn.applicationmaster.reduce.tasks=2 will specify that the ApplicationMaster launch two task contains on the worker nodes.

D. Developers specify reduce tasks in the exact same way for both MapReduce version 1 (MRv1) and MapReduce version 2 (MRv2) on YARN. Thus, executing --D mapreduce.job.reduces-2 will specify reduce tasks.

E. In YARN, resource allocation is function of virtual cores specified by the ApplicationManager making requests to the NodeManager where a reduce task is handeled by a single container (and thus a single virtual core). Thus, the developer needs to specify the number of virtual cores to the NodeManager by executing --p yarn.nodemanager.cpu-vcores=2

Answer

Correct Answer: D

Answer

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Q1. You have just run a MapReduce job to filter user messages to only those of a selected geographical region. The output for this job is in a directory named westUsers, located just below your home directory in HDFS. Which command gathers these into a single file on your local file system?

A.Hadoop fs --getmerge --R westUsers.txt

B. Hadoop fs --getemerge westUsers westUsers.txt

C. Hadoop fs --cp westUsers/* westUsers.txt

D. Hadoop fs --get westUsers westUsers.txt

Q2. In CDH4 and later, which file contains a serialized form of all the directory and files inodes in the filesystem, giving the NameNode a persistent checkpoint of the filesystem metadata?

A.fstime

B. VERSION

C. Fsimage_N (where N reflects transactions up to transaction ID N)

D. Edits_N-M (where N-M transactions between transaction ID N and transaction ID N)

Q3. You are running a Hadoop cluster with a NameNode on host mynamenode. What are two ways to determine available HDFS space in your cluster?

A.Run hdfs fs --du / and locate the DFS Remaining value

B. Run hdfs dfsadmin --report and locate the DFS Remaining value

C. Run hdfs dfs / and subtract NDFS Used from configured Capacity

D. Connect to http://mynamenode:50070/dfshealth.jsp and locate the DFS remaining value

A.MapReduce version 2 (MRv2) on YARN abstracts resource allocation away from the idea of ''tasks'' into memory and virtual cores, thus eliminating the need for a developer to specify the number of reduce tasks, and indeed preventing the developer from specifying the number of reduce tasks.

B. In YARN, resource allocations is a function of megabytes of memory in multiples of 1024mb. Thus, they should specify the amount of memory resource they need by executing --D mapreducereduces. memory-mb-2048

C. In YARN, the ApplicationMaster is responsible for requesting the resource required for a specific launch. Thus, executing --D yarn.applicationmaster.reduce.tasks=2 will specify that the ApplicationMaster launch two task contains on the worker nodes.

D. Developers specify reduce tasks in the exact same way for both MapReduce version 1 (MRv1) and MapReduce version 2 (MRv2) on YARN. Thus, executing --D mapreduce.job.reduces-2 will specify reduce tasks.

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