Download Cloudera CCA-500 Answers Online

NEW QUESTION 1
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 2
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

NEW QUESTION 3
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

NEW QUESTION 4
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

NEW QUESTION 5
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

Answer: B

NEW QUESTION 6
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/

• A. Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.
• B. You don’t need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster
• C. 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
• D. Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores to match the capacity you require under YARN for each NodeManager

Answer: D

NEW QUESTION 7
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/

NEW QUESTION 8
You have just run a MapReduce job to filter user messages to only those of a selected geographical region. The output for this job is in a directory named westUsers, located just below your home directory in HDFS. Which command gathers these into a single file on your local file system?

• A. Hadoop fs –getmerge –R westUsers.txt
• B. Hadoop fs –getemerge westUsers westUsers.txt
• C. Hadoop fs –cp westUsers/* westUsers.txt
• D. Hadoop fs –get westUsers westUsers.txt

Answer: B

NEW QUESTION 9
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

NEW QUESTION 10
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

Answer: A

NEW QUESTION 11
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

NEW QUESTION 12
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 13
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 14
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 15
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

Answer: B

Explanation:
Apache Flume is a service for streaming logs into Hadoop.
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS). It has a simple and flexible architecture based on streaming data flows; and is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.

NEW QUESTION 16
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

NEW QUESTION 17
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 18
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 fina
• D. You do not need to set this value on the NameNode
• E. 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
• F. Set dfs.block.size to 134217728 on all the worker nodes and client machines, and set the parameter to fina
• G. You do not need to set this value on the NameNode

Answer: C

NEW QUESTION 19
Which YARN process run as “container 0” of a submitted job and is responsible for resource qrequests?

• A. ApplicationManager
• B. JobTracker
• C. ApplicationMaster
• D. JobHistoryServer
• E. ResoureManager
• F. NodeManager

Answer: C

NEW QUESTION 20
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 21
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 exist
• F. The file is not written to HDFS
• G. You get an error message telling you that input is not a directory
• H. The write silently fails

Answer: CE

NEW QUESTION 22
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 23
You are running a Hadoop cluster with MapReduce version 2 (MRv2) on YARN. You consistently see that MapReduce map tasks on your cluster are running slowly because of excessive garbage collection of JVM, how do you increase JVM heap size property to 3GB to optimize performance?

• A. yarn.application.child.java.opts=-Xsx3072m
• B. yarn.application.child.java.opts=-Xmx3072m
• C. mapreduce.map.java.opts=-Xms3072m
• D. mapreduce.map.java.opts=-Xmx3072m

Answer: C

Explanation:
Reference:http://hortonworks.com/blog/how-to-plan-and-configure-yarn-in-hdp-2-0/

NEW QUESTION 24
What does CDH packaging do on install to facilitate Kerberos security setup?

• A. Automatically configures permissions for log files at & MAPRED_LOG_DIR/userlogs
• B. Creates users for hdfs and mapreduce to facilitate role assignment
• C. Creates directories for temp, hdfs, and mapreduce with the correct permissions
• D. Creates a set of pre-configured Kerberos keytab files and their permissions
• E. Creates and configures your kdc with default cluster values

Answer: B

NEW QUESTION 25
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 nam
• C. 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)
• D. They will see the file with a ._COPYING_ extension on its nam
• E. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the cluster
• F. They will see the file with its original nam
• G. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the cluster

Answer: B

NEW QUESTION 26
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