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Welcome to the Introduction to Big Data MCQs Page

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

Introduction to Big Data MCQs | Page 33 of 43

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Q321.
What does Couchbase use to ensure reliability and high availability of data storage?

a.

Multiple copies of data stored within each cluster.

b.

Daily backups.

c.

RAID storage.

d.

A distributed file system.

Discuss
Answer: (a).Multiple copies of data stored within each cluster. Explanation:Couchbase ensures reliability and high availability of data storage by maintaining multiple copies of data within each cluster.
Q322.
What is eXist's primary use case?

a.

Real-time data processing

b.

Large-scale machine learning

c.

Storage of XML documents

d.

Scientific simulations

Discuss
Answer: (c).Storage of XML documents Explanation:eXist is primarily used for the storage of XML documents.
Q323.
How is eXist typically deployed?

a.

As a standalone server process

b.

As a desktop application

c.

As a mobile app

d.

As a cloud-based service

Discuss
Answer: (a).As a standalone server process Explanation:eXist is typically deployed as a standalone server process or embedded into an application.
Q324.
What query language does eXist use?

a.

SQL

b.

XPath

c.

JavaScript

d.

Python

Discuss
Answer: (b).XPath Explanation:eXist uses an extended XPath syntax for querying XML documents.
Q325.
What programming model for processing Big Data is used by Google?

a.

Java

b.

C++

c.

Map-Reduce

d.

SQL

Discuss
Answer: (c).Map-Reduce Explanation:Google uses the Map-Reduce programming model for processing Big Data.
Q326.
What are the key components of Map-Reduce?

a.

Map and Fold

b.

Map and Reduce

c.

Select and Group

d.

Filter and Sort

Discuss
Answer: (b).Map and Reduce Explanation:The key components of Map-Reduce are Map and Reduce functions.
Q327.
What is the main advantage of the Map-Reduce programming model?

a.

It is easy to implement.

b.

It is a single-threaded processing model.

c.

It allows for distributed and parallel processing of data.

d.

It is specifically designed for real-time data processing.

Discuss
Answer: (c).It allows for distributed and parallel processing of data. Explanation:The main advantage of the Map-Reduce programming model is its ability to perform distributed and parallel processing of data.
Q328.
Which NoSQL database is known for its support of multi-dimensional arrays and declarative query language?

a.

Couchbase

b.

MongoDB

c.

Cassandra

d.

Redis

Discuss
Answer: (a).Couchbase Explanation:Couchbase is known for its support of multi-dimensional arrays and a declarative query language.
Q329.
What is the primary purpose of Memcached in the Couchbase architecture?

a.

It provides a schema for managing data.

b.

It optimizes network protocols and hardware.

c.

It handles data replication.

d.

It performs complex data analysis.

Discuss
Answer: (b).It optimizes network protocols and hardware. Explanation:Memcached in the Couchbase architecture is responsible for optimizing network protocols and hardware.
Q330.
In which sector is metadata particularly important for data analysis?

a.

Healthcare

b.

Banking

c.

Media distribution

d.

E-commerce

Discuss
Answer: (a).Healthcare Explanation:Metadata is particularly important in the healthcare sector for data analysis.
Page 33 of 43

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