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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 35 of 43

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Q341.
What is Hive's primary purpose?

a.

Real-time data processing

b.

Data warehousing and analytics

c.

Document storage and retrieval

d.

Graph database management

Discuss
Answer: (b).Data warehousing and analytics Explanation:Hive's primary purpose is data warehousing and analytics.
Q342.
What query language does Hive support?

a.

SQL

b.

Python

c.

JavaScript

d.

Ruby

Discuss
Answer: (a).SQL Explanation:Hive supports queries expressed in an SQL-like declarative language called HiveQL.
Q343.
What is the core computation paradigm used by Hive?

a.

Spark

b.

Flink

c.

Map-Reduce

d.

Storm

Discuss
Answer: (c).Map-Reduce Explanation:Hive uses the Map-Reduce paradigm for computation.
Q344.
What does the Metastore in Hive contain?

a.

Custom Map-Reduce scripts

b.

Data storage information

c.

Schemas and statistics

d.

HiveQL queries

Discuss
Answer: (c).Schemas and statistics Explanation:The Metastore in Hive contains schemas and statistics.
Q345.
How is Hive used at Facebook?

a.

For real-time data processing

b.

For ad-hoc analyses

c.

For document storage and retrieval

d.

For graph database management

Discuss
Answer: (b).For ad-hoc analyses Explanation:Hive is used at Facebook for ad-hoc analyses, reporting, and data exploration.
Q346.
What is the primary application domain of MonetDB?

a.

Social networking

b.

Business Intelligence and Decision Support

c.

Real-time gaming

d.

Web development

Discuss
Answer: (b).Business Intelligence and Decision Support Explanation:MonetDB is designed for applications in the field of Business Intelligence and Decision Support.
Q347.
How does MonetDB store relational tables?

a.

In a single table

b.

In separate tables for each column

c.

In a hierarchical structure

d.

In a graph database

Discuss
Answer: (b).In separate tables for each column Explanation:MonetDB stores relational tables using vertical fragmentation, with each column stored in a separate table called a BAT (Binary Association Table).
Q348.
What is the purpose of the head column in MonetDB's storage model?

a.

To store the actual attribute values

b.

To store object IDs

c.

To store XML data

d.

To store JSON data

Discuss
Answer: (b).To store object IDs Explanation:The head column in MonetDB's storage model is used to store object IDs.
Q349.
Which query language does MonetDB support?

a.

SQL

b.

NoSQL

c.

SPARQL

d.

HiveQL

Discuss
Answer: (a).SQL Explanation:MonetDB provides a full SQL interface.
Q350.
What is the third version of MonetDB under development to introduce support for?

a.

XML databases

b.

NoSQL databases

c.

RDF and SPARQL

d.

Graph databases

Discuss
Answer: (c).RDF and SPARQL Explanation:The third version of MonetDB is under development to introduce support for RDF and SPARQL.
Page 35 of 43

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