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Code d'Examen: DS-200
Nom d'Examen: Cloudera (Data Science Essentials Beta)
Questions et réponses: 60 Q&As

Code d'Examen: CCA-505
Nom d'Examen: Cloudera (Cloudera Certified Administrator for Apache Hadoop (CCAH) CDH5 Upgrade Exam)
Questions et réponses: 45 Q&As

Code d'Examen: CCA-500
Nom d'Examen: Cloudera (Cloudera Certified Administrator for Apache Hadoop (CCAH))
Questions et réponses: 60 Q&As

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NO.1 Your Hadoop cluster is configured with HDFS and MapReduce version 2 (MRv2) on YARN. Can
you configure a worker node to run aNodeManager daemon but not a DataNode daemon and still
have a function 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 Reduce tasks only
Answer: A

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NO.2 Which Yarn daemon or service monitors a Container's per-application resource usage (e.g,
memory, CPU)?
A. NodeManager
B. ApplicationMaster
C. ApplicationManagerService
D. ResourceManager
Answer: A

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Reference:http://docs.hortonworks.com/HDPDocuments/HDP2 /HDP-2.0.0.2 /bk_usingapache-hadoo
p/content/ch_using-apache-hadoop-4.html(4th para)

NO.3 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
Answer: B

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NO.4 You are 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 replication
factor of 3). One of the nodes holding this file (a single block) fails. How will the cluster handle the
replication of this file in this situation/
A. The cluster will re-replicate the file the next time the system administrator reboots the
NameNode daemon (as long as the file's replication doesn't fall two)
B. This file will be immediately re-replicated and all other HDFS operations on the cluster will halt
until the cluster's replication values are restored
C. The file will remain under-replicated until the administrator brings that nodes back online
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 DataNodes
Answer: B

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NO.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?
A. free
B. df
C. memcat
D. top
E. vmstat
F. swapinfo
Answer: C

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NO.6 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 becomes the standby NameNode and nn01 becomes the active NameNode
B. nn02 is fenced, and nn01 becomes the active NameNode
C. nn01 becomes the standby NamNode and nn02 becomes the active NAmeNode
D. nn01 is fenced, and nn02 becomes the active NameNode
Answer: D

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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 state without error. If the first NameNode is in
the Active state, an attempt will be made to gracefully transition it to the Standby state. If this fails,
the fencing methods (as configured by dfs.ha.fencing.methods) will be attempted in order until one
of the methods succeeds. Only after this process will the second NameNode be transitioned to the
Active state. If no fencing method succeeds, the second NameNode will not be transitioned to the
Active state, and an error will be returned.

NO.7 You decide to create a cluster which runs HDFS in High Availability mode with automatic
failover, using Quorum-based Storage. What is the purpose of ZooKeeper in such a configuration?
A. It manages the Edits file, which is a log changes to the HDFS filesystem.
B. It monitors an NFS mount point and reports if the mount point disappears
C. It 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 filesystem
D. It only keeps track of which NameNode is Active at any given time
E. Clients connect toZoneKeeper to determine which NameNode is Active
Answer: D

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Reference:http://www.cloudera.com/content/cloudera-content/clouderadocs/CDH4 /latest/PDF/CD
H4-High-Availability-Guide.pdf(page 15)

NO.8 Your cluster's mapped-site.xml includes the following parameters
<name>mapreduce.map.memory.mb</name> <value>4096<value/>
<name>mapreduce.reduce.memory,mb</name> <value>8192</value>
And your cluster's yarn-site.xml includes the following parameters
<name>yarn.nodemanager/vmen-pmem-ratio</name> <value>2.1</value>
What is the maximum amount of virtual memory allocated for each map before YARN will kill its
Container?
A. 4 GB
B. 17.2 GB
C. 24.6 GB
D. 8.2 GB
Answer: B

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Code d'Examen: CCA-500
Nom d'Examen: Cloudera (Cloudera Certified Administrator for Apache Hadoop (CCAH))
Questions et réponses: 60 Q&As

Code d'Examen: CCA-505
Nom d'Examen: Cloudera (Cloudera Certified Administrator for Apache Hadoop (CCAH) CDH5 Upgrade Exam)
Questions et réponses: 45 Q&As

Code d'Examen: DS-200
Nom d'Examen: Cloudera (Data Science Essentials Beta)
Questions et réponses: 60 Q&As

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NO.1 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.
Answer: D

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NO.2 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

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NO.3 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: B

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Reference:https://www.inkling.com/read/hadoop-definitive-guide-tom-white-3rd/chapter10/hdfs

NO.4 Choose three reasons why should you run the HDFS balancer periodically?
A. To ensure that there is capacity in HDFS for additional data
B. To ensure that all blocks in the cluster are 128MB in size
C. To help HDFS deliver consistent performance under heavy loads
D. To ensure that there is consistent disk utilization across the DataNodes
E. To improve data locality MapReduce
Answer: D

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Explanation:
NOTE: There is only one correct answer in the options for this question. Please check the following
reference:
http://www.quora.com/Apache-Hadoop/It-is-recommended-that-you-run-the-HDFSbalancer-period
ically-Why-Choose-3

NO.5 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

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NO.6 You have installed a cluster HDFS and MapReduce version 2 (MRv2) on YARN. You have no
dfs.hosts entry(ies) in your hdfs-site.xml configuration file. You configure a new worker node by
setting fs.default.name in its configuration files to point to the NameNode on your cluster, and you
start the DataNode daemon on that worker node. What do you have to do on the cluster to allow
the worker node to join, and start sorting HDFS blocks?
A. Without creating a dfs.hosts file or making any entries, run the commands
hadoop.dfsadmin-refreshModes on the NameNode
B. Restart the NameNode
C. Creating a dfs.hosts file on the NameNode, add the worker Node's name to it, then issue the
command hadoop dfsadmin -refresh Nodes = on the Namenode
D. Nothing; the worker node will automatically join the cluster when NameNode daemon is started
Answer: A

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NO.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?
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
Answer: A

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NO.8 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

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