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Exam Code: CCA-500Exam Name: Cloudera Certified Administrator for Apache Hadoop (CCAH)
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CCA-500 Exam Prep Total Q&A: 60 Questions and Answers
Last Update: 11-02,2015
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Exam Code: CCD-410Exam Name: Cloudera Certified Developer for Apache Hadoop (CCDH)
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CCD-410 Exam Prep Total Q&A: 60 Questions and Answers
Last Update: 11-02,2015
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NO.1 You want to understand more about how users browse your public website, such as which
pages they visit prior to placing an order. You have a farm of 200 web servers hosting your website.
How will you gather this data for your analysis?
A. Ingest the server web logs into HDFS using Flume.
B. Write a MapReduce job, with the web servers for mappers, and the Hadoop cluster nodes for
reduces.
C. Import all users' clicks from your OLTP databases into Hadoop, using Sqoop.
D. Channel these clickstreams inot Hadoop using Hadoop Streaming.
E. Sample the weblogs from the web servers, copying them into Hadoop using curl.
Answer: A
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NO.2 Table metadata in Hive is:
A. Stored as metadata on the NameNode.
B. Stored along with the data in HDFS.
C. Stored in the Metastore.
D. Stored in ZooKeeper.
Answer: C
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NO.3 You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values
pairs with the key consisting of the matching text, and the value containing the filename and byte
offset. Determine the difference between setting the number of reduces to one and settings the
number of reducers to zero.
A. There is no difference in output between the two settings.
B. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances
of matching patterns are stored in a single file on HDFS.
C. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS.
With one reducer, instances of matching patterns are stored in multiple files on HDFS.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one
reducer, all instances of matching patterns are gathered together in one file on HDFS.
Answer: D
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NO.4 For each intermediate key, each reducer task can emit:
A. As many final key-value pairs as desired. There are no restrictions on the types of those key-value
pairs (i.e., they can be heterogeneous).
B. As many final key-value pairs as desired, but they must have the same type as the intermediate
key-value pairs.
C. As many final key-value pairs as desired, as long as all the keys have the same type and all the
values have the same type.
D. One final key-value pair per value associated with the key; no restrictions on the type.
E. One final key-value pair per key; no restrictions on the type.
Answer: C
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NO.5 On a cluster running MapReduce v1 (MRv1), a TaskTracker heartbeats into the JobTracker on
your cluster, and alerts the JobTracker it has an open map task slot.
What determines how the JobTracker assigns each map task to a TaskTracker?
A. The amount of RAM installed on the TaskTracker node.
B. The amount of free disk space on the TaskTracker node.
C. The number and speed of CPU cores on the TaskTracker node.
D. The average system load on the TaskTracker node over the past fifteen (15) minutes.
E. The location of the InsputSplit to be processed in relation to the location of the node.
Answer: E
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NO.6 To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory.
What is the best way to accomplish this?
A. Serialize the data file, insert in it the JobConf object, and read the data into memory in the
configure method of the mapper.
B. Place the data file in the DistributedCache and read the data into memory in the map method of
the mapper.
C. Place the data file in the DataCache and read the data into memory in the configure method of the
mapper.
D. Place the data file in the DistributedCache and read the data into memory in the configure method
of the mapper.
Answer: C
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