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Welcome to the Application of Big Data in Analyzing Electric Meter Data MCQs Page

Dive deep into the fascinating world of Application of Big Data in Analyzing Electric Meter Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Application of Big Data in Analyzing Electric Meter Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Application of Big Data in Analyzing Electric Meter 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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Application of Big Data in Analyzing Electric Meter Data MCQs | Page 4 of 12

Explore more Topics under Big Data Computing

Q31.
What is the primary purpose of the Map step in MapReduce?

a.

Combining the results from worker nodes

b.

Distributing tasks into smaller subproblems

c.

Processing smaller problems

d.

Storing data in a structured database

Discuss
Answer: (b).Distributing tasks into smaller subproblems Explanation:The primary purpose of the Map step in MapReduce is to distribute tasks into smaller subproblems.
Q32.
What is Hadoop's approach to achieving high availability in distributed computing?

a.

Relying on hardware for high availability

b.

Handling failures at the application layer

c.

Running on single servers to avoid failures

d.

Using grid computing for fault tolerance

Discuss
Answer: (b).Handling failures at the application layer Explanation:Hadoop achieves high availability in distributed computing by handling failures at the application layer.
Q33.
Which database system is designed to manage large amounts of structured data, allowing scaling across many commodity servers with no single point of failure?

a.

MongoDB

b.

PostgreSQL

c.

Apache Cassandra

d.

MySQL

Discuss
Answer: (c).Apache Cassandra Explanation:Apache Cassandra is designed to manage large amounts of structured data and allows scaling across many commodity servers with no single point of failure.
Q34.
Who originally developed Apache Cassandra?

a.

Google

b.

Facebook

c.

Microsoft

d.

Amazon

Discuss
Answer: (b).Facebook Explanation:Apache Cassandra was originally developed at Facebook.
Q35.
What is the primary characteristic of HBase that distinguishes it from traditional RDBMS?

a.

Typed columns

b.

Secondary indices

c.

Advanced query languages

d.

Lack of RDBMS features

Discuss
Answer: (d).Lack of RDBMS features Explanation:HBase lacks many of the features typically found in traditional RDBMS, such as typed columns, secondary indices, triggers, and advanced query languages.
Q36.
Which distributed file system is designed to store very large data sets reliably and stream them at high bandwidth to user applications?

a.

NoSQL

b.

HBase

c.

Hadoop Distributed File System (HDFS)

d.

R

Discuss
Answer: (c).Hadoop Distributed File System (HDFS) Explanation:Hadoop Distributed File System (HDFS) is designed for storing large data sets and streaming them at high bandwidth to user applications.
Q37.
What is the primary use of the R programming language?

a.

Managing large data sets

b.

Developing web applications

c.

Data analysis and statistical software development

d.

High-performance computing

Discuss
Answer: (c).Data analysis and statistical software development Explanation:The primary use of the R programming language is for data analysis and statistical software development.
Q38.
What is one of R's strengths in terms of data visualization?

a.

Ease of use for data manipulation

b.

Extensive support for web applications

c.

Generation of mathematical symbols and formulae

d.

Production of publication-quality plots

Discuss
Answer: (d).Production of publication-quality plots Explanation:One of R's strengths is its ability to produce publication-quality plots, including mathematical symbols and formulae.
Q39.
Which distributed database system is modeled on Google's Big Table and designed as a distributed, scalable, and Big Data store?

a.

MongoDB

b.

Cassandra

c.

HBase

d.

Redis

Discuss
Answer: (c).HBase Explanation:HBase is a distributed database system modeled on Google's Big Table, designed as a distributed, scalable, and Big Data store.
Q40.
What is the main reason for the shift of Big Data services to the cloud?

a.

Cost of storage, CPU, and bandwidth

b.

Availability of open-source cloud platforms

c.

Increasing data complexity

d.

High network access costs

Discuss
Answer: (a).Cost of storage, CPU, and bandwidth Explanation:The shift of Big Data services to the cloud is primarily driven by the dropping cost of storage, CPU, and bandwidth.
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