Cloudera CCA-500 Test Prep 2021

NEW QUESTION 1
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?(Choose two)

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

Answer: B

NEW QUESTION 2
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: B

NEW QUESTION 3
Which is the default scheduler in YARN?

• A. YARN doesn’t configure a default scheduler, you must first assign an appropriate scheduler class in yarn-site.xml
• B. Capacity Scheduler
• C. Fair Scheduler
• D. FIFO Scheduler

Answer: B

Explanation: Reference:http://hadoop.apache.org/docs/r2.4.1/hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html

NEW QUESTION 4
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 1024m
• C. Thus, they should specify the amount of memory resource they need by executing –D mapreduce-reduces.memory-mb-2048
• D. In YARN, the ApplicationMaster is responsible for requesting the resource required for a specific launc
• E. Thus, executing –D yarn.applicationmaster.reduce.tasks=2 will specify that the ApplicationMaster launch two task contains on the worker nodes.
• F. Developers specify reduce tasks in the exact same way for both MapReduce version 1 (MRv1) and MapReduce version 2 (MRv2) on YAR
• G. Thus, executing –D mapreduce.job.reduces-2 will specify reduce tasks.
• H. 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: D

NEW QUESTION 5
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?

• A. CSV
• B. XML
• C. HTML
• D. Avro
• E. SequenceFiles
• F. JSON

Answer: E

Explanation: Sequence files are block-compressed and provide direct serialization and deserialization of several arbitrary data types (not just text). Sequence files can be generated as the output of other MapReduce tasks and are an efficient intermediate representation for data that is passing from one MapReduce job to anther.

NEW QUESTION 6
You are running a Hadoop cluster with a NameNode on host mynamenode, a secondary NameNode on host mysecondarynamenode and several DataNodes.
Which best describes how you determine when the last checkpoint happened?

• A. Execute hdfs namenode –report on the command line and look at the Last Checkpoint information
• B. Execute hdfs dfsadmin –saveNamespace on the command line which returns to you the last checkpoint value in fstime file
• C. Connect to the web UI of the Secondary NameNode (http://mysecondary:50090/) and look at the “Last Checkpoint” information
• D. Connect to the web UI of the NameNode (http://mynamenode:50070) and look at the “Last Checkpoint” information

Answer: C

Explanation: Reference:https://www.inkling.com/read/hadoop-definitive-guide-tom-white-3rd/chapter- 10/hdfs

NEW QUESTION 7
Which two features does Kerberos security add to a Hadoop cluster?(Choose two)

• A. User authentication on all remote procedure calls (RPCs)
• B. Encryption for data during transfer between the Mappers and Reducers
• C. Encryption for data on disk (“at rest”)
• D. Authentication for user access to the cluster against a central server
• E. Root access to the cluster for users hdfs and mapred but non-root access for clients

Answer: AD

NEW QUESTION 8
Which YARN daemon or service monitors a Controller’s per-application resource using (e.g., memory CPU)?

• A. ApplicationMaster
• B. NodeManager
• C. ApplicationManagerService
• D. ResourceManager

Answer: A

NEW QUESTION 9
A slave node in your cluster has 4 TB hard drives installed (4 x 2TB). The DataNode is configured to store HDFS blocks on all disks. You set the value of the dfs.datanode.du.reserved parameter to 100 GB. How does this alter HDFS block storage?

• A. 25GB on each hard drive may not be used to store HDFS blocks
• B. 100GB on each hard drive may not be used to store HDFS blocks
• C. All hard drives may be used to store HDFS blocks as long as at least 100 GB in total is available on the node
• D. A maximum if 100 GB on each hard drive may be used to store HDFS blocks

Answer: B

NEW QUESTION 10
On a cluster running MapReduce v2 (MRv2) on YARN, a MapReduce job is given a directory of 10 plain text files 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 ResourceManager
• B. We cannot say; the number of Mappers is determined by the developer
• C. 30
• D. 3
• E. 10
• F. We cannot say; the number of mappers is determined by the ApplicationMaster

Answer: E

NEW QUESTION 11
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?(Choose two)

• A. Because 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
• B. Tasks are scheduled on the order of their job submission
• C. The order of execution of job may vary
• D. Given job A and submitted in that order, all tasks from job A are guaranteed to finish before all tasks from job B
• E. The FIFO Scheduler will give, on average, and equal share of the cluster resources over the job lifecycle
• F. The FIFO Scheduler will pass an exception back to the client when Job B is submitted, since all slots on the cluster are use

Answer: AD

NEW QUESTION 12
You use the hadoop fs –put command to add a file “sales.txt” to HDFS. This file is small enough that it fits into a single block, which is replicated to three nodes in your cluster (with a replicationfactor of 3). One of the nodes holding this file (a single block) fails. How will the cluster handle the replication of file in this situation?

• A. The file will remain under-replicated until the administrator brings that node back online
• B. The cluster will re-replicate the file the next time the system administrator reboots the NameNode daemon (as long as the file’s replication factor doesn’t fall below)
• C. This will be immediately re-replicated and all other HDFS operations on the cluster will halt until the cluster’s replication values are resorted
• D. The file will be re-replicated automatically after the NameNode determines it is under- replicated based on the block reports it receives from the NameNodes

Answer: D

NEW QUESTION 13
During the execution of a MapReduce v2 (MRv2) job on YARN, where does the Mapper place the intermediate data of each Map Task?

• A. The 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 Reducer
• B. The 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
• C. The Mapper transfers the intermediate data immediately to the reducers as it is generated by the Map Task
• D. YARN holds the intermediate data in the NodeManager’s memory (a container) until it is transferred to the Reducer
• E. The Mapper stores the intermediate data on the underlying filesystem of the local disk in the directories yarn.nodemanager.locak-DIFS

Answer: E

NEW QUESTION 14
You are planning a Hadoop cluster and considering implementing 10 Gigabit Ethernet as the network fabric. Which workloads benefit the most from faster network fabric?

• A. When your workload generates a large amount of output data, significantly larger than the amount of intermediate data
• B. When your workload consumes a large amount of input data, relative to the entire capacity if HDFS
• C. When your workload consists of processor-intensive tasks
• D. When your workload generates a large amount of intermediate data, on the order of the input data itself

Answer: A

NEW QUESTION 15
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?

• A. The client queries the NameNode for the locations of the block, and reads all three copie
• B. The first copy to complete transfer to the client is the one the client reads as part of hadoop’s speculative execution framework.
• C. The client queries the NameNode for the locations of the block, and reads from the first location in the list it receives.
• D. 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.
• E. The client queries the NameNode which retrieves the block from the nearest DataNode to the client then passes that block back to the client.

Answer: B

NEW QUESTION 16
Your cluster implements HDFS High Availability (HA). Your two NameNodes are named nn01 and nn02. What occurs when you execute the command: hdfs haadmin –failover nn01 nn02?

• A. nn02 is fenced, and nn01 becomes the active NameNode
• B. nn01 is fenced, and nn02 becomes the active NameNode
• C. nn01 becomes the standby NameNode and nn02 becomes the active NameNode
• D. nn02 becomes the standby NameNode and nn01 becomes the active NameNode

Answer: B

Explanation: failover – initiate a failover between two NameNodes
This subcommand causes a failover from the first provided NameNode to the second. If the first
NameNode is in the Standby state, this command simply transitions the second to the Active statewithout error. If the first NameNode is in the Active state, an attempt will be made to gracefullytransition it to the Standby state. If this fails, the fencing methods (as configured bydfs.ha.fencing.methods) will be attempted in order until one of the methods succeeds. Only afterthis process will the second NameNode be transitioned to the Active state. If no fencing methodsucceeds, the second NameNode will not be transitioned to the Active state, and an error will bereturned.

NEW QUESTION 17
Your cluster is configured with HDFS and MapReduce version 2 (MRv2) on YARN. What is the result when you execute: hadoop jar SampleJar MyClass on a client machine?

• A. SampleJar.Jar is sent to the ApplicationMaster which allocates a container for SampleJar.Jar
• B. Sample.jar is placed in a temporary directory in HDFS
• C. SampleJar.jar is sent directly to the ResourceManager
• D. SampleJar.jar is serialized into an XML file which is submitted to the ApplicatoionMaster

Answer: A

NEW QUESTION 18
You are configuring your cluster to run HDFS and MapReducer v2 (MRv2) on YARN. Which two daemons needs to be installed on your cluster’s master nodes?(Choose two)

• A. HMaster
• B. ResourceManager
• C. TaskManager
• D. JobTracker
• E. NameNode
• F. DataNode

Answer: BE