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Welcome to the MapReduce Basics MCQs Page

Dive deep into the fascinating world of MapReduce Basics with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of MapReduce Basics, a crucial aspect of Hadoop. In this section, you will encounter a diverse range of MCQs that cover various aspects of MapReduce Basics, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Hadoop.

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Check out the MCQs below to embark on an enriching journey through MapReduce Basics. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Hadoop.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of MapReduce Basics. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

MapReduce Basics MCQs | Page 7 of 8

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Q61.
Point out the correct statement.

a.

With TextInputFormat and KeyValueTextInputFormat, each mapper receives a variable number of lines of input

b.

StreamXmlRecordReader, the page elements can be interpreted as records for processing by a mapper

c.

The number depends on the size of the split and the length of the lines.

d.

All of the mentioned

Discuss
Answer: (d).All of the mentioned
Q62.
Point out the wrong statement.

a.

Hadoop sequence file format stores sequences of binary key-value pairs

b.

SequenceFileAsBinaryInputFormat is a variant of SequenceFileInputFormat that retrieves the sequence file’s keys and values as opaque binary objects

c.

SequenceFileAsTextInputFormat is a variant of SequenceFileInputFormat that retrieves the sequence file’s keys and values as opaque binary objects.

d.

None of the mentioned

Discuss
Answer: (c).SequenceFileAsTextInputFormat is a variant of SequenceFileInputFormat that retrieves the sequence file’s keys and values as opaque binary objects.
Q63.
Point out the correct statement.

a.

The minimum split size is usually 1 byte, although some formats have a lower bound on the split size

b.

Applications may impose a minimum split size

c.

The maximum split size defaults to the maximum value that can be represented by a Java long type

d.

All of the mentioned

Discuss
Answer: (a).The minimum split size is usually 1 byte, although some formats have a lower bound on the split size
Q64.
Point out the wrong statement.

a.

Hadoop works better with a small number of large files than a large number of small files

b.

CombineFileInputFormat is designed to work well with small files

c.

CombineFileInputFormat does not compromise the speed at which it can process the input in a typical MapReduce job

d.

None of the mentioned

Discuss
Answer: (c).CombineFileInputFormat does not compromise the speed at which it can process the input in a typical MapReduce job
Q65.
The MapReduce algorithm contains two important tasks, namely __________.

a.

mapped, reduce

b.

mapping, Reduction

c.

Map, Reduction

d.

Map, Reduce

Discuss
Answer: (d).Map, Reduce
Q66.
_____ takes a set of data and converts it into another set of data, where individual elements are broken down into tuples (key/value pairs).

a.

Map

b.

Reduce

c.

both a and b

d.

Node

Discuss
Answer: (a).Map
Q67.
______ task, which takes the output from a map as an input and combines those data tuples into a smaller set of tuples.

a.

Map

b.

Reduce

c.

Node

d.

both a and b

Discuss
Answer: (b).Reduce
Q68.
In how many stages the MapReduce program executes?

a.

2

b.

3

c.

4

d.

5

Discuss
Answer: (b).3
Q69.
Which of the following is used to schedules jobs and tracks the assign jobs to Task tracker?

a.

SlaveNode

b.

MasterNode

c.

JobTracker

d.

Task Tracker

Discuss
Answer: (c).JobTracker
Q70.
Which of the following is used for an execution of a Mapper or a Reducer on a slice of data?

a.

Task

b.

Job

c.

Mapper

d.

PayLoad

Discuss
Answer: (a).Task
Page 7 of 8

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