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QUESTION 1
You are running Hadoop cluster with all monitoring facilities properly configured.
Which scenario will go undeselected?
A. HDFS is almost full
B. The NameNode goes down
C. A DataNode is disconnected from the cluster
D. Map or reduce tasks that are stuck in an infinite loop
E. MapReduce jobs are causing excessive memory swaps
Correct Answer: B

QUESTION 2
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
Correct Answer: C

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
Correct Answer: B

QUESTION 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?
A. Sample the web server logs web servers and copy them into HDFS using curl B. Ingest the server web logs into HDFS using Flume
C. Channel these clickstreams into Hadoop using Hadoop Streaming
D. Import all user clicks from your OLTP databases into Hadoop using Sqoop
E. Write a MapReeeduce job with the web servers for mappers and the Hadoop cluster nodes for reducers
Correct Answer: B

QUESTION 5
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
Correct Answer: ADF

QUESTION 6
Which YARN daemon or service negotiations map and reduce Containers from the Scheduler, tracking their status and
monitoring progress?
A. NodeManager
B. ApplicationMaster
C. ApplicationManager
D. ResourceManager
Correct Answer: B

QUESTION 7
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?
A. For a 1GB child heap size an io.sort.mb of 128 MB will always maximize memory to disk I/O
B. Increase the io.sort.mb to 1GB
C. Decrease the io.sort.mb value to 0 D. Tune 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.
Correct Answer: D

QUESTION 8
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
Correct Answer: A

QUESTION 9
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.
Correct Answer: B

QUESTION 10
Cluster Summary:
45 files and directories, 12 blocks = 57 total. Heap size is 15.31 MB/193.38MB(7%)
pass4itsure question
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?
A. The DataNode JVM on one host is not active
B. Because 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.
C. Your cluster has lost all HDFS data which had bocks stored on the dead DatNode
D. The HDFS cluster is in safe mode
Correct Answer: A

QUESTION 11
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 andquot;Last
Checkpointandquot; information
D. Connect to the web UI of the NameNode (http://mynamenode:50070) and look at the andquot;Last
Checkpointandquot; information
Correct Answer: C

QUESTION 12
You are configuring a server running HDFS, MapReduce version 2 (MRv2) on YARN running Linux. How must youformat underlying file system of each DataNode?
A. They must be formatted as HDFS
B. They must be formatted as either ext3 or ext4
C. They may be formatted in any Linux file system
D. They must not be formatted – – HDFS will format the file system automatically
Correct Answer: B

QUESTION 13
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
Correct Answer: D

QUESTION 14
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?
A. Yes. The daemon will receive data from the NameNode to run Map tasks
B. Yes. The daemon will get data from another (non-local) DataNode to run Map tasks
C. Yes. The daemon will receive Map tasks only
D. Yes. The daemon will receive Reducer tasks only
Correct Answer: B

QUESTION 15
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? A. The write succeeds, overwriting foo.txt in HDFS with no warning
B. The file is uploaded and stored as a plain file named input
C. You get a warning that foo.txt is being overwritten
D. You get an error message telling you that foo.txt already exists, and asking you if you would like to overwrite it.
E. You get a error message telling you that foo.txt already exists. The file is not written to HDFS
F. You get an error message telling you that input is not a directory
G. The write silently fails
Correct Answer: CE

QUESTION 16
You are working on a project where you need to chain together MapReduce, Pig jobs. You also need the ability to use
forks, decision points, 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 17
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/andamp;(user)/apache/application_andamp;(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
Correct Answer: E

QUESTION 18
You have a Hadoop cluster HDFS, and a gateway machine external to the cluster from which clients submit jobs. What
do you need to do in order to run Impala on the cluster and submit jobs from the command line of the gatewaymachine?
A. Install the impalad daemon statestored daemon, and daemon on each machine in the cluster, and the impala shell on
your gateway machine
B. Install the impalad daemon, the statestored daemon, the catalogd daemon, and the impala shell on your gateway
machine
C. Install the impalad daemon and the impala shell on your gateway machine, and the statestored daemon and catalogd
daemon on one of the nodes in the cluster
D. Install the impalad daemon on each machine in the cluster, the statestored daemon and catalogd daemon on one
machine in the cluster, and the impala shell on your gateway machine
E. Install the impalad daemon, statestored daemon, and catalogd daemon on each machine in the cluster and on the
gateway node
Correct Answer: D

QUESTION 19
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
Correct Answer: A

QUESTION 20
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
Correct Answer: D

QUESTION 21
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
Correct Answer: B

QUESTION 22
Assuming a cluster running HDFS, MapReduce version 2 (MRv2) on YARN with all settings at their default, what do you
need to do when adding a new slave node to cluster?
A. Nothing, other than ensuring that the DNS (or/etc/hosts files on all machines) contains any entry for the new node.
B. Restart the NameNode and ResourceManager daemons and resubmit any running jobs.
C. Add a new entry to /etc/nodes on the NameNode host.
D. Restart the NameNode of dfs.number.of.nodes in hdfs-site.xml
Correct Answer: A

QUESTION 23
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
Correct Answer: C

QUESTION 24
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
Correct Answer: A

QUESTION 25
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?
A. You cannot enforce this, since client code can always override this value
B. Set dfs.block.size to 128M on all the worker nodes, on all client machines, and on the NameNode, and set the
parameter to final
C. 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 NameNode
D. Set dfs.block.size to 134217728 on all the worker nodes, on all client machines, and on the NameNode, and set the
parameter to final
E. Set dfs.block.size to 134217728 on all the worker nodes and client machines, and set the parameter to final. You do
not need to set this value on the NameNode
Correct Answer: C

QUESTION 26
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
Correct Answer: A

QUESTION 27
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?
A. The user is not authorized to run the job on the cluster
B. The output directory already exists
C. The name of the driver has been spelled incorrectly on the command line
D. The directory name is misspelled in HDFS
E. The Hadoop configuration files on the client do not point to the cluster
Correct Answer: A

QUESTION 28
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
Correct Answer: BC

QUESTION 29
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 copies. The first copy to complete
transfer to the client is the one the client reads as part of hadoop\’s speculative execution framework.
B. The client queries the NameNode for the locations of the block, and reads from the first location in the list it receives.
C. 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. D. The client queries the NameNode which retrieves the block from the nearest DataNode to the client then passes that
block back to the client.
Correct Answer: B

QUESTION 30
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
Correct Answer: E

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