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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 27 of 43

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Q261.
Which NoSQL database category is suitable for modeling relationships among data and is often used in fields such as geospatial analysis and network analysis?

a.

Key-value stores

b.

Wide column stores

c.

Document stores

d.

Graph databases

Discuss
Answer: (d).Graph databases Explanation:Graph databases are suitable for modeling relationships among data and are often used in fields such as geospatial analysis and network analysis.
Q262.
What does the CAP theorem state about distributed storage systems?

a.

They can provide consistency and partition tolerance.

b.

They can provide availability and partition tolerance.

c.

They can provide consistency and availability.

d.

They can provide consistency, availability, and partition tolerance simultaneously.

Discuss
Answer: (c).They can provide consistency and availability. Explanation:The CAP theorem states that distributed storage systems can provide consistency and availability but not both simultaneously with partition tolerance.
Q263.
Which property of the CAP theorem refers to the system's ability to provide the same data to all clients after an operation?

a.

Consistency

b.

Availability

c.

Partition tolerance

d.

Eventual consistency

Discuss
Answer: (a).Consistency Explanation:Consistency, in the context of the CAP theorem, refers to the system's ability to provide the same data to all clients after an operation.
Q264.
What is the main difference between the ACID and BASE properties in the context of database transactions?

a.

ACID ensures eventual consistency, while BASE ensures strong consistency.

b.

ACID focuses on availability, while BASE focuses on durability.

c.

ACID emphasizes soft state, while BASE emphasizes atomicity.

d.

ACID guarantees strong consistency, while BASE allows eventual consistency.

Discuss
Answer: (d).ACID guarantees strong consistency, while BASE allows eventual consistency. Explanation:The main difference between the ACID and BASE properties is that ACID guarantees strong consistency, while BASE allows eventual consistency.
Q265.
Which category of NoSQL databases is known for its high scalability and suitability for managing large lists of elements?

a.

Key-value stores

b.

Wide column stores

c.

Document stores

d.

Graph databases

Discuss
Answer: (a).Key-value stores Explanation:Key-value stores are known for their high scalability and suitability for managing large lists of elements.
Q266.
What are the main performance bottlenecks for NoSQL data stores?

a.

CPU performance and network latency

b.

Network, disk, memory performance, and CPU capabilities

c.

Disk I/O and data modeling

d.

Query complexity and database size

Discuss
Answer: (b).Network, disk, memory performance, and CPU capabilities Explanation:The main performance bottlenecks for NoSQL data stores include network, disk, memory performance, and the computational capabilities of the associated CPUs.
Q267.
How does the number of nodes in a cluster typically affect the completion times of jobs in a clustering solution?

a.

A greater number of nodes in a cluster corresponds to longer completion times.

b.

A greater number of nodes in a cluster corresponds to lower completion times.

c.

The number of nodes in a cluster has no impact on job completion times.

d.

The completion times of jobs are inversely proportional to the number of nodes.

Discuss
Answer: (b).A greater number of nodes in a cluster corresponds to lower completion times. Explanation:A greater number of nodes in a cluster corresponds to lower completion times of jobs in a clustering solution.
Q268.
Why is memory caching or memory-based storage important for high-performance databases?

a.

To reduce CPU usage

b.

To improve disk I/O performance

c.

To optimize memory performance

d.

To minimize network latency

Discuss
Answer: (c).To optimize memory performance Explanation:Memory caching or memory-based storage is important for high-performance databases to optimize memory performance.
Q269.
What role does the network capability play in the performance of Big Data management?

a.

It has no impact on performance.

b.

It primarily affects CPU performance.

c.

It affects the performance of disk I/O.

d.

It affects the final performance of the entire Big Data management.

Discuss
Answer: (d).It affects the final performance of the entire Big Data management. Explanation:The network capability affects the final performance of the entire Big Data management, as network connections are used extensively during read and write operations and for algorithms like Map-Reduce.
Q270.
How can data organization impact storage and access performance?

a.

Data organization has no impact on storage and access performance.

b.

Data organization can improve storage performance but not access performance.

c.

Data organization can improve access performance but not storage performance.

d.

Data organization impacts storage, access, and indexing performance.

Discuss
Answer: (d).Data organization impacts storage, access, and indexing performance. Explanation:Data organization impacts storage, access, and indexing performance of data.
Page 27 of 43

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