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Welcome to the MapReduce Development and Features MCQs Page

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

MapReduce Development and Features MCQs | Page 7 of 11

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Q61.
__________ get events indicating completion (success/failure) of component tasks.

a.

getJobName()

b.

getJobState()

c.

getPriority()

d.

getTaskCompletionEvents(int startFrom)

Discuss
Answer: (d).getTaskCompletionEvents(int startFrom)
Q62.
_________ gets the diagnostic messages for a given task attempt.

a.

getTaskOutputFilter(Configuration conf)

b.

getTaskReports(TaskType type)

c.

getTrackingURL()

d.

all of the mentioned

Discuss
Answer: (a).getTaskOutputFilter(Configuration conf)
Q63.
reduceProgress() gets the progress of the job’s reduce-tasks, as a float between _________

a.

0.0-1.0

b.

1.0-2.0

c.

2.0-3.0

d.

None of the mentioned

Discuss
Answer: (a).0.0-1.0
Q64.
The Job makes a copy of the _____________ so that any necessary internal modifications do not reflect on the incoming parameter.

a.

Component

b.

Configuration

c.

Collector

d.

None of the mentioned

Discuss
Answer: (b).Configuration
Q65.
________ is the architectural center of Hadoop that allows multiple data processing engines.

a.

YARN

b.

Hive

c.

Incubator

d.

Chuckwa

Discuss
Answer: (a).YARN
Q66.
YARN’s dynamic allocation of cluster resources improves utilization over more static _______ rules used in early versions of Hadoop.

a.

Hive

b.

MapReduce

c.

Imphala

d.

All of the mentioned

Discuss
Answer: (b).MapReduce
Q67.
The __________ is a framework-specific entity that negotiates resources from the ResourceManager.

a.

NodeManager

b.

ResourceManager

c.

ApplicationMaster

d.

All of the mentioned

Discuss
Answer: (c).ApplicationMaster
Q68.
Apache Hadoop YARN stands for _________

a.

Yet Another Reserve Negotiator

b.

Yet Another Resource Network

c.

Yet Another Resource Negotiator

d.

All of the mentioned

Discuss
Answer: (c).Yet Another Resource Negotiator
Q69.
MapReduce has undergone a complete overhaul in hadoop is _________

a.

0.21

b.

0.23

c.

0.24

d.

0.26

Discuss
Answer: (b).0.23
Q70.
The ____________ is the ultimate authority that arbitrates resources among all the applications in the system.

a.

NodeManager

b.

ResourceManager

c.

ApplicationMaster

d.

All of the mentioned

Discuss
Answer: (b).ResourceManager
Page 7 of 11

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