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Welcome to the Advanced Data Analytics for Business MCQs Page

Dive deep into the fascinating world of Advanced Data Analytics for Business with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Advanced Data Analytics for Business, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Advanced Data Analytics for Business, 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 Big Data Computing.

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Check out the MCQs below to embark on an enriching journey through Advanced Data Analytics for Business. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

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

Advanced Data Analytics for Business MCQs | Page 8 of 15

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Q71.
What is the primary purpose of the Reduce phase in a MapReduce program?

a.

To execute the Map function

b.

To transfer files from Map nodes' local disks

c.

To store output records with the same hash value

d.

To process or combine records assigned to it and write output records

Discuss
Answer: (d).To process or combine records assigned to it and write output records Explanation:The primary purpose of the Reduce phase in a MapReduce program is to process or combine records assigned to it and write output records as part of the computation's final output.
Q72.
What determines which Reduce instance consumes output records with the same hash value from the Map phase?

a.

The MapReduce scheduler

b.

The number of Map instances

c.

The size of the input data set

d.

The Map instance that produced the data

Discuss
Answer: (a).The MapReduce scheduler Explanation:The MapReduce scheduler determines which Reduce instance consumes output records with the same hash value from the Map phase.
Q73.
What is the purpose of the MapReduce main controller?

a.

To execute the Map phase

b.

To handle network file transfers

c.

To coordinate system activities on each node

d.

To write output records to a distributed file system

Discuss
Answer: (c).To coordinate system activities on each node Explanation:The purpose of the MapReduce main controller is to coordinate system activities on each node.
Q74.
What is the typical implementation of PageRank using MapReduce?

a.

Serializing the graph as adjacency matrices

b.

Serializing the graph as adjacency lists

c.

Using a control program for all iterations

d.

Running PageRank to convergence in a single iteration

Discuss
Answer: (b).Serializing the graph as adjacency lists Explanation:The typical implementation of PageRank using MapReduce involves serializing the graph as adjacency lists.
Q75.
What is one of the key advantages of MapReduce?

a.

Low fault tolerance

b.

Inability to scale horizontally

c.

Complexity of programming semantics

d.

Ability to horizontally scale to petabytes of data

Discuss
Answer: (d).Ability to horizontally scale to petabytes of data Explanation:One of the key advantages of MapReduce is the ability to horizontally scale to petabytes of data on thousands of servers.
Q76.
How does the MapReduce program handle output records with the same hash value?

a.

They are assigned to different Reduce instances.

b.

They are combined into a single output record.

c.

They are stored in separate output files.

d.

They are ignored in the Reduce phase.

Discuss
Answer: (c).They are stored in separate output files. Explanation:Output records with the same hash value are stored in separate output files in the MapReduce program.
Q77.
What is the role of the control program in the implementation of PageRank using MapReduce?

a.

To perform MapReduce tasks

b.

To serialize the graph as adjacency lists

c.

To handle network file transfers

d.

To check for convergence and repeat iterations

Discuss
Answer: (d).To check for convergence and repeat iterations Explanation:The role of the control program in the implementation of PageRank using MapReduce is to check for convergence and repeat iterations.
Q78.
What characteristic of MapReduce contributes to its high fault tolerance?

a.

Use of a single function for data processing

b.

Unfussy programming semantics

c.

Lack of scalability

d.

Dependency on complex algorithms

Discuss
Answer: (b).Unfussy programming semantics Explanation:The unfussy programming semantics of MapReduce contribute to its high fault tolerance.
Q79.
What is the typical number of Reduce instances in a MapReduce program?

a.

Thousands

b.

Hundreds

c.

One per node

d.

Equal to the number of Map instances

Discuss
Answer: (c).One per node Explanation:The typical number of Reduce instances in a MapReduce program is one per node.
Q80.
What is the primary function of the MapReduce scheduler?

a.

To execute the Map and Reduce functions

b.

To decide how many Map instances to run

c.

To write output records to a distributed file system

d.

To gather key-value pairs with the same destination vertex

Discuss
Answer: (b).To decide how many Map instances to run Explanation:The primary function of the MapReduce scheduler is to decide how many Map instances to run.
Page 8 of 15

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