Cloudera CCAH CCA-505 Questions & Answers

• Question 1:

  You are migrating a cluster from MapReduce version 1 (MRv1) to MapReduce version2 (MRv2) on YARN. To want to maintain your MRv1 TaskTracker slot capacities when you migrate. What should you do?

  A. Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.cpu- vcores so that ApplicationMaster container allocations match the capacity you require.

  B. You don't need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster

  C. Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu- vcores to match the capacity you require under YARN for each NodeManager

  D. Configure mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum ub yarn.site.xml to match your cluster's configured capacity set by yarn.scheduler.minimum-allocation

  Correct Answer: C

• Question 2:

  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

  Correct Answer: E

• Question 3:

  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 all transactions up to transaction ID N)

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

  Correct Answer: C

• Question 4:

  A user comes to you, complaining that when she attempts to submit a Hadoop job, it fails. There is a directory in HDFS named /data/input. The Jar is named j.jar, and the driver class is named DriverClass. She runs command:

  hadoop jar j.jar DriverClass /data/input/data/output

  The error message returned includes the line:

  PrivilegedActionException as:training (auth:SIMPLE) cause.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exits: file :/data/input

  What is the cause of the error?

  A. The Hadoop configuration files on the client do not point to the cluster

  B. The directory name is misspelled in HDFS

  C. The name of the driver has been spelled incorrectly on the command line

  D. The output directory already exists

  E. The user is not authorized to run the job on the cluster

  Correct Answer: A

• Question 5:

  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

  Correct Answer: A

• Question 6:

  A slave node in your cluster has four 2TB hard drives installed (4 x 2TB). The DataNode is configured to store HDFS blocks on the disks. You set the value of the dfs.datanode.du.reserved parameter to 100GB. How does this alter HDFS block storage?

  A. A maximum of 100 GB on each hard drive may be used to store HDFS blocks

  B. All hard drives may be used to store HDFS blocks as long as atleast 100 GB in total is available on the node

  C. 100 GB on each hard drive may not be used to store HDFS blocks

  D. 25 GB on each hard drive may not be used to store HDFS blocks

  Correct Answer: B

• Question 7:

  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

  Correct Answer: DE

• Question 8:

  What processes must you do if you are running a Hadoop cluster with a single NameNode and six DataNodes, and you want to change a configuration parameter so that it affects all six DataNodes.

  A. You must modify the configuration file on each of the six DataNode machines.

  B. You must restart the NameNode daemon to apply the changes to the cluster

  C. You must restart all six DatNode daemon to apply the changes to the cluste

  D. You don't need to restart any daemon, as they will pick up changes automatically

  E. You must modify the configuration files on the NameNode only. DataNodes read their configuration from the master nodes.

  Correct Answer: BE

• Question 9:

  You are working on a project where you need to chain together MapReduce, Pig jobs. You also needs the ability to use forks, decision, and path joins. Which ecosystem project should you use to perform these actions?

  A. Oozie

  B. Zookeeper

  C. HBase

  D. Sqoop

  E. HUE

  Correct Answer: A

• Question 10:

  On a cluster running MapReduce v2 (MRv2) on YARN, a MapReduce job is given a directory of 10 plain text as its input directory. Each file is made up of 3 HDFS blocks. How many Mappers will run?

  A. We cannot say; the number of Mappers is determined by the RsourceManager

  B. We cannot say; the number of Mappers is determined by the ApplicationManager

  C. We cannot say; the number of Mappers is determined by the developer

  D. 30

  E. 3

  F. 10

  Correct Answer: E