CCD-470 Real Exam Questions and Verified Answers

Question 1 Single choice

In the standard word count MapReduce algorithm, why might using a combiner reduce the overall Job running time?

A
Because combiners perform local aggregation of word counts, thereby allowing the mappers to
process input data faster.
B
Because combiners perform local aggregation of word counts, thereby reducing the number of mappers that need to run.
C
Because combiners perform local aggregation of word counts, and then transfer that data to reducers without writing the intermediate data to disk.
D
Because combiners perform local aggregation of word counts, thereby reducing the number of key-value pairs that need to be snuff let across the network to the reducers.

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Correct answer: A

Question 2 Single choice

What is a Writable?

A
Writable is an interface that all keys and values in MapReduce must implement. Classes implementing this interface must implement methods for serializing and deserializing themselves.
B
Writable is an abstract class that all keys and values in MapReduce must extend. Classes extending this abstract base class must implement methods for serializing and deserializing themselves
C
Writable is an interface that all keys, but not values, in MapReduce must implement. Classes implementing this interface must implement methods for serializing and deserializing themselves.
D
Writable is an abstract class that all keys, but not values, in MapReduce must extend. Classes extending this abstract base class must implement methods for serializing and deserializing themselves.

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Correct answer: A

Question 3 Single choice

You are developing a MapReduce job for sales reporting. The mapper will process input keys representing the year (IntWritable) and input values representing product indentifies (Text). Indentify what determines the data types used by the Mapper for a given job.

A
The key and value types specified in the JobConf.setMapInputKeyClass and JobConf.setMapInputValuesClass methods
B
The data types specified in HADOOP_MAP_DATATYPES environment variable
C
The mapper-specification.xml file submitted with the job determine the mapper s input key and value types.
D
The InputFormat used by the job determines the mapper s input key and value types.

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Correct answer: D

Question 4 Single choice

Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?

A
HBase
B
Hue
C
Pig
D
Hive
E
Oozie
F
Flume
G
Sqoop

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Correct answer: A

Question 5 Single choice

Which process describes the lifecycle of a Mapper?

A
The JobTracker calls the TaskTracker s configure () method, then its map () method and finally its close () method.
B
The TaskTracker spawns a new Mapper to process all records in a single input split.
C
The TaskTracker spawns a new Mapper to process each key-value pair.
D
The JobTracker spawns a new Mapper to process all records in a single file.

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Correct answer: C

Question 6 Single choice

During the standard sort and shuffle phase of MapReduce, keys and values are passed to reducers.

Which of the following is true?

A
Keys are presented to a reducer in sorted order; values for a given key are not sorted.
B
Keys are presented to a reducer in soiled order; values for a given key are sorted in ascending order.
C
Keys are presented to a reducer in random order; values for a given key are not sorted.
D
Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.

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Correct answer: D

Question 7 Single choice

What types of algorithms are difficult to express in MapReduce v1 (MRv1)?

A
Algorithms that require applying the same mathematical function to large numbers of individual binary records.
B
Relational operations on large amounts of structured and semi-structured data.
C
Algorithms that require global, sharing states.
D
Large-scale graph algorithms that require one-step link traversal.
E
Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).

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Correct answer: C

Question 8 Single choice

You wrote a map function that throws a runtime exception when it encounters a control character in input data. The input supplied to your mapper contains twelve such characters totals, spread across five file splits. The first four file splits each have two control characters and the last split has four control characters.
Indentify the number of failed task attempts you can expect when you run the job with mapred.max.map.attempts set to 4:

A
You will have forty-eight failed task attempts
B
You will have seventeen failed task attempts
C
You will have five failed task attempts
D
You will have twelve failed task attempts
E
You will have twenty failed task attempts

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Correct answer: E

Question 9 Single choice

You are running a job that will process a single InputSplit on a cluster which has no other jobs currently running. Each node has an equal number of open Map slots.
On which node will Hadoop first attempt to run the Map task?

A
The node with the most memory
B
The node with the lowest system load
C
The node on which this InputSplit is stored
D
The node with the most free local disk space

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Correct answer: C

Question 10 Single choice

In a large MapReduce job with m mappers and n reducers, how many distinct copy operations will there be in the sort/shuffle phase?

A
mXn (i.e., m multiplied by n)
B
n
C
m
D
m+n (i.e., m plus n)
E
m+n (i.e., m to the power of n)

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Correct answer: A