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Welcome to the Hadoop Frameworks MCQs Page

Dive deep into the fascinating world of Hadoop Frameworks with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Hadoop Frameworks, a crucial aspect of Hadoop. In this section, you will encounter a diverse range of MCQs that cover various aspects of Hadoop Frameworks, 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 Hadoop Frameworks. 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 Hadoop Frameworks. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Hadoop Frameworks MCQs | Page 2 of 20

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Q11.
Which of the following can be used to launch Spark jobs inside MapReduce?

a.

SIM

b.

SIMR

c.

SIR

d.

RIS

Discuss
Answer: (b).SIMR
Q12.
Which of the following language is not supported by Spark?

a.

Java

b.

Pascal

c.

Scala

d.

Python

Discuss
Answer: (b).Pascal
Q13.
Spark is packaged with higher level libraries, including support for _________ queries.

a.

SQL

b.

C

c.

C++

d.

None of the mentioned

Discuss
Answer: (a).SQL
Q14.
Spark includes a collection over ________ operators for transforming data and familiar data frame APIs for manipulating semi-structured data.

a.

50

b.

60

c.

70

d.

80

Discuss
Answer: (d).80
Q15.
Spark is engineered from the bottom-up for performance, running ___________ faster than Hadoop by exploiting in memory computing and other optimizations.

a.

100x

b.

150x

c.

200x

d.

None of the mentioned

Discuss
Answer: (a).100x
Q16.
Spark powers a stack of high-level tools including Spark SQL, MLlib for _________

a.

regression models

b.

statistics

c.

machine learning

d.

reproductive research

Discuss
Answer: (c).machine learning
Q17.
Apache Flume 1.3.0 is the fourth release under the auspices of Apache of the so-called ________ codeline.

a.

NG

b.

ND

c.

NF

d.

NR

Discuss
Answer: (a).NG
Q18.
___________ was created to allow you to flow data from a source into your Hadoop environment.

a.

Imphala

b.

Oozie

c.

Flume

d.

All of the mentioned

Discuss
Answer: (c).Flume
Q19.
A ____________ is an operation on the stream that can transform the stream.

a.

Decorator

b.

Source

c.

Sinks

d.

All of the mentioned

Discuss
Answer: (b).Source
Q20.
A number of ____________ source adapters give you the granular control to grab a specific file.

a.

multimedia file

b.

text file

c.

image file

d.

none of the mentioned

Discuss
Answer: (b).text file
Page 2 of 20

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