Big Data Quiz For Students!

Approved & Edited by ProProfs Editorial Team

The editorial team at ProProfs Quizzes consists of a select group of subject experts, trivia writers, and quiz masters who have authored over 10,000 quizzes taken by more than 100 million users. This team includes our in-house seasoned quiz moderators and subject matter experts. Our editorial experts, spread across the world, are rigorously trained using our comprehensive guidelines to ensure that you receive the highest quality quizzes.

Learn about Our Editorial Process

| By AdewumiKoju

AdewumiKoju

Community Contributor

Quizzes Created: 810 | Total Attempts: 1,101,124

Questions: 10 | Attempts: 3,999 | Updated: Sep 15, 2023

Questions

Settings

Feedback

During the Quiz End of Quiz

Difficulty

Sequential Easy First Hard First

Play as

Quiz Flashcard

Create your own Quiz

Share on Facebook Share on Twitter Share on Whatsapp Share on Pinterest Share on Email Copy to Clipboard Embed on your website

Big data is an evolving term that describes a large volume of structured, unstructured, and semi-structured data that has the potential to be mined for information and used in machine learning projects and other advanced analytics applications. This quiz tests your knowledge of big data analytics.

Questions and Answers

1.

Which of these is among the 3Vs of data?
- A.
  
  Velocity
- B.
  
  Virtually
- C.
  
  Versatility
- D.
  
  Vacuum
Correct Answer
A. Velocity

Explanation
Velocity is one of the 3Vs of data. The 3Vs of data, also known as the three dimensions of big data, are Volume, Velocity, and Variety. Velocity refers to the speed at which data is generated, processed, and analyzed. In the context of big data, velocity represents the rapid rate at which data is being produced and the need to handle and analyze it in real-time.

Rate this question:
2.

As companies move past the experimental phase with Hadoop, many cite the need for additional capabilities, including:
- A.
  
  Improved data warehousing functionality
- B.
  
  Improved security, workload management and SQL support
- C.
  
  Improved data warehousing functionality
- D.
  
  Improved extract, transform and load features for data integration
Correct Answer
B. Improved security, workload management and SQL support

Explanation
As companies become more experienced with Hadoop, they realize the need for additional capabilities. One of the key needs is improved security to protect their data from unauthorized access. Workload management is also important to ensure efficient resource allocation and prioritize critical tasks. Additionally, SQL support is crucial for companies to easily query and analyze their data using familiar language and tools. These capabilities help companies enhance the overall functionality and usability of their Hadoop systems.

Rate this question:
3.

Which of these accurately describes Hadoop?
- A.
  
  Real-time
- B.
  
  Open source
- C.
  
  None of the above
- D.
  
  All of the above
Correct Answer
B. Open source

Explanation
Hadoop is accurately described as "Open source" because it is an open-source software framework used for distributed storage and processing of large datasets. It allows for the processing of big data across clusters of computers using simple programming models, making it accessible to a wide range of users. Being open-source means that the source code is freely available, allowing users to modify and customize it according to their needs.

Rate this question:
4.

Hadoop is a framework that works with a variety of related tools. Common cohorts include:
- A.
  
  MapReduce, Heron and Trumpe
- B.
  
  MapReduce, Hive and HBase
- C.
  
  MySQL, MapReduce, and Google Apps
- D.
  
  Hummer, MapReduce, Hummer and Iguana
Correct Answer
B. MapReduce, Hive and HBase

Explanation
Hadoop is a framework that is commonly used with various related tools. One of the common cohorts or combinations of tools that work with Hadoop includes MapReduce, Hive, and HBase. MapReduce is a programming model and software framework for processing large amounts of data in parallel, Hive is a data warehouse infrastructure that provides data summarization, query, and analysis, and HBase is a distributed, scalable, and consistent NoSQL database that is built on top of Hadoop. Together, these tools can be used to efficiently process and analyze big data.

Rate this question:

1
0
5.

Which of these is the main component of Big Data?
- A.
  
  YARN
- B.
  
  MapReduce
- C.
  
  HDFS
- D.
  
  All of the above
Correct Answer
D. All of the above

Explanation
All of the above are important components of Big Data. YARN (Yet Another Resource Negotiator) is a key component of Hadoop that manages and allocates resources in a Hadoop cluster. It is used to schedule and manage resources for running data processing jobs. MapReduce is a programming model and processing framework for processing large datasets in parallel across a distributed cluster. It is one of the core components of the Hadoop ecosystem. HDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop to store and manage large volumes of data across a distributed cluster.

Rate this question:

1
2
6.

Hadoop named after
- A.
  
  A sound Cutting’s laptop made during Hadoop development
- B.
  
  Cutting's son's toy elephant
- C.
  
  Creator Doug Cutting’s favorite circus act
- D.
  
  Cutting’s high school rock band
Correct Answer
B. Cutting's son's toy elepHant

Explanation
The correct answer is Cutting's son's toy elephant. Hadoop was named after Doug Cutting's son's toy elephant. This suggests that the name "Hadoop" was chosen based on a personal connection and not related to any technical aspect or specific event during the development of Hadoop.

Rate this question:
7.

The following frameworks are built on Spark except
- A.
  
  GraphX
- B.
  
  D-Streams
- C.
  
  Millib
- D.
  
  SparkSQL
Correct Answer
B. D-Streams

Explanation
The question asks for a framework that is not built on Spark. GraphX, Millib, and SparkSQL are all frameworks that are built on top of Spark and provide additional functionalities. D-Streams, on the other hand, is not a framework built on Spark. D-Streams stands for Discretized Streams and it is a Spark component that provides support for processing real-time streaming data.

Rate this question:
8.

Which technology is best suited for batch data processing?
- A.
  
  Hive
- B.
  
  Storm
- C.
  
  MapR
- D.
  
  Apache Zeppelin
Correct Answer
C. MapR

Explanation
MapR is the correct answer because it is a technology that is specifically designed for batch data processing. MapR provides a distributed file system and a set of tools and frameworks that enable efficient and scalable batch processing of large volumes of data. It offers features like data replication, fault tolerance, and high availability, making it well-suited for handling batch data processing workloads. Hive, Storm, and Apache Zeppelin are also technologies used in big data processing, but they are more commonly associated with other types of data processing tasks such as data querying, real-time stream processing, and data visualization, respectively.

Rate this question:
9.

Which of these frameworks was developed by Google?
- A.
  
  MapReduce
- B.
  
  Hive
- C.
  
  ZooKeeper
- D.
  
  Spark
Correct Answer
A. MapReduce

Explanation
MapReduce is a framework developed by Google. It is used for processing and generating large data sets in a distributed computing environment. The framework provides a programming model for parallel processing and a distributed file system for storing and accessing data. MapReduce has been widely adopted and is the basis for many big data processing systems, including Apache Hadoop.

Rate this question:
10.

Which of these format does Sqoop use for importing the data from SQL to Hadoop?
- A.
  
  JPEG
- B.
  
  Doc
- C.
  
  Text File Format
- D.
  
  Sequence file format
Correct Answer
C. Text File Format

Explanation
Sqoop uses the Text File Format for importing the data from SQL to Hadoop. This format allows the data to be stored as plain text files, making it easy to read and process. Sqoop converts the SQL data into text format and imports it into Hadoop, where it can be further analyzed and processed using various tools and frameworks.

Rate this question: