CCA-500: Cloudera Certified Administrator for Apache Hadoop Exam Practice Test 2 | Practice Test / Quiz / MCQs

1. Identify features/issues that YARN is designated to address:

Reduce complexity of the MapReduce APIsResource pressure on the JobTracker - Ability to run framework other than MapReduce, such as MPIStandardize on a single MapReduce APISingle point of failure in the NameNode

2. Which two features does Kerberos security add to a Hadoop cluster?

A.User authentication on all remote procedure calls (RPCs) - Authentication for user access to the cluster against a central serverRoot access to the cluster for users hdfs and mapred but non-root access for clientsEncryption for data on disk (at rest")"Encryption for data during transfer between the Mappers and Reducers

3. During the execution of a MapReduce v2 (MRv2) job on YARN, where does the Mapper place the intermediate data of each Map Task?

The Mapper stores the intermediate data on the underlying filesystem of the local disk in the directories yarn.nodemanager.locak-DIFSThe Mapper stores the intermediate data on the node running the Job's ApplicationMaster so that it is available to YARN ShuffleService before the data is presented to the ReducerThe Mapper transfers the intermediate data immediately to the reducers as it is generated by the Map TaskThe Mapper stores the intermediate data in HDFS on the node where the Map tasks ran in the HDFS /usercache/&(user)/apache/application_&(appid) directory for the user who ran the job

4. You want to understand more about how users browse your public website. For example, you want to know which pages they visit prior to placing an order. You have a server farm of 200 web servers hosting your website. Which is the most efficient process to gather these web server across logs into your Hadoop cluster analysis?

Import all user clicks from your OLTP databases into Hadoop using SqoopIngest the server web logs into HDFS using FlumeChannel these clickstreams into Hadoop using Hadoop StreamingSample the web server logs web servers and copy them into HDFS using curl

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

Connect to http://mynamenode:50070/dfshealth.jsp and locate the DFS remaining valueRun hdfs dfs / and subtract NDFS Used from configured CapacityRun hdfs fs du / and locate the DFS Remaining valueRun hdfs dfsadmin report and locate the DFS Remaining value

7. Your Hadoop cluster is configuring with HDFS and MapReduce version 2 (MRv2) on YARN. Can you configure a worker node to run a NodeManager daemon but not a DataNode daemon and still have a functional cluster?

Yes. The daemon will receive data from the NameNode to run Map tasksYes. The daemon will receive Reducer tasks onlyYes. The daemon will get data from another (non-local) DataNode to run Map tasksYes. The daemon will receive Map tasks only

9. 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 the command: Hadoop jar j.jar DriverClass /data/input/data/output The error message returned includes the line: PriviligedActionException as:training (auth:SIMPLE) cause:org.apache.hadoop.mapreduce.lib.input.invalidInputException: Input path does not exist: file:/data/input What is the cause of the error?

The name of the driver has been spelled incorrectly on the command lineThe directory name is misspelled in HDFSThe output directory already existsThe user is not authorized to run the job on the cluster

10. You suspect that your NameNode is incorrectly configured, and is swapping memory to disk. Which Linux commands help you to identify whether swapping is occurring?

dfmemcatfree - top - vmstatjps

11. You need to analyze 60,000,000 images stored in JPEG format, each of which is approximately 25 KB. Because you Hadoop cluster isn't optimized for storing and processing many small files, you decide to do the following actions: 1. Group the individual images into a set of larger files 2. Use the set of larger files as input for a MapReduce job that processes them directly with python using Hadoop streaming. Which data serialization system gives the flexibility to do this?

CSVSequenceFilesXMLHTML

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

It only keeps track of which NameNode is Active at any given timeIt monitors an NFS mount point and reports if the mount point disappearsIt 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 filesystemIf only manages the Edits file, which is log of changes to the HDFS filesystem

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

Set dfs.block.size to 128 M on all the worker nodes and client machines, and set the parameter to final. You do not need to set this value on the NameNodeSet dfs.block.size to 128M on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to finalYou cannot enforce this, since client code can always override this valueSet dfs.block.size to 134217728 on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final

14. Your cluster is running MapReduce version 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?

You can specify new queue name when user submits a job and new queue can be created dynamically if yarn .schedule.fair.user-as-default-queue = falseYou can specify new queue name per application in allocations.xml file and have new jobs automatically assigned to the application queueYou can specify new queue name when user submits a job and new queue can be created dynamically if the property yarn.scheduler.fair.allow-undeclearedpools = trueYarn.scheduler.fair.user.fair-as-default-queue = false and yarn.scheduler.fair.allow-undecleared-pools = true

15. On a cluster running CDH 5.0 or above, you use the hadoop fs put command to write a 300MB file into a previously empty directory using an HDFS block size of 64 MB. Just after this command has finished writing 200 MB of this file, what would another use see when they look in directory?

They will see the file with a ._COPYING_ extension on its name. If they view the file, they will see contents of the file up to the last completed block (as each 64MB block is written, that block becomes available)They will see the file with a ._COPYING_ extension on its name. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the clusterThe directory will appear to be empty until the entire file write is completed on the clusterThey will see the file with its original name. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the cluster

16. Your cluster's mapred-start.xml includes the following parameters mapreduce.map.memory.mb 4096 mapreduce.reduce.memory.mb 8192 And any cluster's yarn-site.xml includes the following parameters yarn.nodemanager.vmen-pmen-ration 2.1 What is the maximum amount of virtual memory allocated for each map task before YARN will kill its Container?

8.9 GB4GB17.2 GB8.2 GB

17. Assume you have a file named foo.txt in your local directory. You issue the following three commands: Hadoop fs mkdir input Hadoop fs put foo.txt input/foo.txt Hadoop fs put foo.txt input What happens when you issue the third command?

You get an error message telling you that foo.txt already exists, and asking you if you would like to overwrite it.The write succeeds, overwriting foo.txt in HDFS with no warningThe file is uploaded and stored as a plain file named inputYou get a warning that foo.txt is being overwritten - You get a error message telling you that foo.txt already exists. The file is not written to HDFS

18. Your Hadoop cluster contains nodes in three racks. You have not configured the dfs.hosts property in the NameNode's configuration file. What results?

Presented with a blank dfs.hosts property, the NameNode will permit DataNodes specified in mapred.hosts to join the clusterAny machine running the DataNode daemon can immediately join the clusterThe NameNode will update the dfs.hosts property to include machines running the DataNode daemon on the next NameNode reboot or with the command dfsadmin refreshNodesNo new nodes can be added to the cluster until you specify them in the dfs.hosts file

19. Your cluster has the following characteristics: A rack aware topology is configured and on Replication is set to 3 Cluster block size is set to 64MB Which describes the file read process when a client application connects into the cluster and requests a 50MB file?

The client queries the NameNode for the locations of the block, and reads from the first location in the list it receives.The client queries the NameNode which retrieves the block from the nearest DataNode to the client then passes that block back to the client.The client queries the NameNode for the locations of the block, and reads all three copies. The first copy to complete transfer to the client is the one the client reads as part of hadoop's speculative execution framework.The client queries the NameNode for the locations of the block, and reads from a random location in the list it receives to eliminate network I/O loads by balancing which nodes it retrieves data from any given time.

20. You observed that the number of spilled records from Map tasks far exceeds the number of map output records. Your child heap size is 1GB and your io.sort.mb value is set to 1000MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?

Increase the io.sort.mb to 1GBFor a 1GB child heap size an io.sort.mb of 128 MB will always maximize memory to disk I/OTune the io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.Decrease the io.sort.mb value to 0

21. You are migrating a cluster from MApReduce version 1 (MRv1) to MapReduce version 2 (MRv2) on YARN. You want to maintain your MRv1 TaskTracker slot capacities when you migrate. What should you do/

You don't need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your clusterConfigure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores to match the capacity you require under YARN for each NodeManagerConfigure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.Configure mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster's capacity set by the yarn-scheduler.minimum-allocation

22. You have a cluster running with the fair Scheduler enabled. There are currently no jobs running on the cluster, and you submit a job A, so that only job A is running on the cluster. A while later, you submit Job B. now Job A and Job B are running on the cluster at the same time. How will the Fair Scheduler handle these two jobs?

When Job B gets submitted, Job A has to finish first, before job B can gets scheduled.When Job B gets submitted, it will get assigned tasks, while job A continues to run with fewer tasks.When Job A gets submitted, it consumes all the task slots.When Job A gets submitted, it doesn't consumes all the task slots.

23. Cluster Summary: 45 files and directories, 12 blocks = 57 total. Heap size is 15.31 MB/193.38MB(7%) Refer to the above screenshot. You configure a Hadoop cluster with seven DataNodes and on of your monitoring UIs displays the details shown in the exhibit. What does the this tell you?

The DataNode JVM on one host is not activeBecause your under-replicated blocks count matches the Live Nodes, one node is dead, and your DFS Used % equals 0%, you can't be certain that your cluster has all the data you've written it.The HDFS cluster is in safe modeYour cluster has lost all HDFS data which had bocks stored on the dead DatNode

24. You have a cluster running with a FIFO scheduler enabled. You submit a large job A to the cluster, which you expect to run for one hour. Then, you submit job B to the cluster, which you expect to run a couple of minutes only. You submit both jobs with the same priority. Which two best describes how FIFO Scheduler arbitrates the cluster resources for job and its tasks?

The order of execution of job may varyBecause there is a more than a single job on the cluster, the FIFO Scheduler will enforce a limit on the percentage of resources allocated to a particular job at any given time - Given job A and submitted in that order, all tasks from job A are guaranteed to finish before all tasks from job BThe FIFO Scheduler will give, on average, and equal share of the cluster resources over the job lifecycleTasks are scheduled on the order of their job submission

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25 Questions

❤ If you liked Fatskills, consider supporting us by checking out The Life Manuals You Never Got.

About | Explore | User Guide | Topics | Subjects | Doubt Solver | Career Aptitude Test | Answers | Free Tools | OSHA Basics Quiz | What Should We Know? Privacy | Terms |

Without work one finishes nothing. - Ralph Waldo Emerson© 2026 Fatskills.com

All trademarks, logos and brand names are the property of their respective owners. All company, product and service names used in this website are for identification purposes only. Use of these names, trademarks and brands does not imply endorsement.

About | Explore | User Guide | Topics | Subjects | Doubt Solver | Career Aptitude Test | Answers | Free Tools | OSHA Basics Quiz | What Should We Know?
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Without work one finishes nothing. - Ralph Waldo Emerson
© 2026 Fatskills.com