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Q1. Which three basic configuration parameters must you set to migrate your cluster from MapReduce 1 (MRv1) to MapReduce V2 (MRv2)?(Choose three)
A. Configure the NodeManager to enable MapReduce services on YARN by setting the following property in yarn-site.xml:
<name>yarn.nodemanager.hostname</name>
<value>your_nodeManager_shuffle</value>
B. Configure the NodeManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:
<name>yarn.nodemanager.hostname</name>
<value>your_nodeManager_hostname</value>
C. Configure a default scheduler to run on YARN by setting the following property in mapred-site.xml:
<name>mapreduce.jobtracker.taskScheduler</name>
<Value>org.apache.hadoop.mapred.JobQueueTaskScheduler</value>
D. Configure the number of map tasks per jon YARN by setting the following property in mapred:
<name>mapreduce.job.maps</name>
<value>2</value>
E. 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_resourceManager_hostname</value>
F. 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>
Answer: A,E,F
Q2. 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?(Select all that apply)
A. free
B. df
C. memcat
D. top
E. jps
F. vmstat
G. swapinfo
Answer: A,D,F
Explanation: Reference:http://www.cyberciti.biz/faq/linux-check-swap-usage-command/
Q3. 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
Q4. Which two are features of Hadoop’s rack topology?(Choose two)
A. Configuration of rack awareness is accomplished using a configuration file. You cannot use a rack topology script.
B. Hadoop gives preference to intra-rack data transfer in order to conserve bandwidth
C. Rack location is considered in the HDFS block placement policy
D. HDFS is rack aware but MapReduce daemon are not
E. Even for small clusters on a single rack, configuring rack awareness will improve performance
Answer: B,C
Q5. 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
Q6. Which scheduler would you deploy to ensure that your cluster allows short jobs to finish within a reasonable time without starting long-running jobs?
A. Complexity Fair Scheduler (CFS)
B. Capacity Scheduler
C. Fair Scheduler
D. FIFO Scheduler
Answer: C
Explanation: Reference:http://hadoop.apache.org/docs/r1.2.1/fair_scheduler.html
Q7. 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?
A. 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
B. Yarn.scheduler.fair.user.fair-as-default-queue = false and yarn.scheduler.fair.allow- undecleared-pools = true
C. 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 = false
D. You can specify new queue name per application in allocations.xml file and have new jobs automatically assigned to the application queue
Answer: A
Q8. For each YARN job, the Hadoop framework generates task log file. Where are Hadoop task log files stored?
A. Cached by the NodeManager managing the job containers, then written to a log directory on the NameNode
B. Cached in the YARN container running the task, then copied into HDFS on job completion
C. In HDFS, in the directory of the user who generates the job
D. On the local disk of the slave mode running the task
Answer: D
Q9. 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
Q10. 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?
A. The directory will appear to be empty until the entire file write is completed on the cluster
B. 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)
C. 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 cluster
D. They 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
Answer: B
Q11. 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.
Q12. 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. TaskTracker
D. JobTracker
E. NameNode
F. DataNode
G. ResourceManager
Answer: A
Q13. Which command does Hadoop offer to discover missing or corrupt HDFS data?
A. Hdfs fs –du
B. Hdfs fsck
C. Dskchk
D. The map-only checksum
E. Hadoop does not provide any tools to discover missing or corrupt data; there is not need because three replicas are kept for each data block
Answer: B
Explanation: Reference:https://twiki.grid.iu.edu/bin/view/Storage/HadoopRecovery
Q14. 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: C
Explanation: Reference:http://mikepluta.com/tag/namenode/
Q15. Your company stores user profile records in an OLTP databases. You want to join these records with web server logs you have already ingested into the Hadoop file system. What is the best way to obtain and ingest these user records?
A. Ingest with Hadoop streaming
B. Ingest using Hive’s IQAD DATA command
C. Ingest with sqoop import
D. Ingest with Pig’s LOAD command
E. Ingest using the HDFS put command
Answer: C
Q16. Given:
You want to clean up this list by removing jobs where the State is KILLED. What command you enter?
A. Yarn application –refreshJobHistory
B. Yarn application –kill application_1374638600275_0109
C. Yarn rmadmin –refreshQueue
D. Yarn rmadmin –kill application_1374638600275_0109
Answer: B
Explanation: Reference:http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.1-latest/bk_using-apache-hadoop/content/common_mrv2_commands.html
Q17. 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: A,D
Q18. You want to node to only swap Hadoop daemon data from RAM to disk when absolutely necessary. What should you do?
A. Delete the /dev/vmswap file on the node
B. Delete the /etc/swap file on the node
C. Set the ram.swap parameter to 0 in core-site.xml
D. Set vm.swapfile file on the node
E. Delete the /swapfile file on the node
Answer: D