Exam CCA-500 VCE

By blog Admin | Posted Thu, 19 Mar 2015 14:07:31 GMT

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CCA-500 Latest DumpsExam Code: CCA-500
Exam Name: Cloudera Certified Administrator for Apache Hadoop (CCAH)
One year free update, No help, Full refund!
CCA-500 Exam PDF Total Q&A: 60 Questions and Answers
Last Update: 03-18,2015

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NO.1 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
Answer: C,E

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NO.2 Identify two features/issues that YARN is designated to address:
A. Standardize on a single MapReduce API
B. Single point of failure in the NameNode
C. Reduce complexity of the MapReduce APIs
D. Resource pressure on the JobTracker
E. Ability to run framework other than MapReduce, such as MPI
F. HDFS latency
Answer: D,E

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Reference: http://www.revelytix.com/?q=content/hadoop-ecosystem (YARN, first para)

NO.3 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

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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.

NO.4 You decide to create a cluster which runs HDFS in High Availability mode with automatic
failover, using Quorum Storage. What is the purpose of ZooKeeper in such a configuration?
A. It only keeps track of which NameNode is Active at any given time
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. If only manages the Edits file, which is log of changes to the HDFS filesystem
E. Clients connect to ZooKeeper to determine which NameNode is Active
Answer: A

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

NO.5 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?
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

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NO.6 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

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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 FileSystem (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.

NO.7 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

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NO.8 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: D

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Posted 2015/3/19 14:07:31  |  Category: Cloudera  |  Tag: CCA-500 Study GuideCloudera
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