Big Data and Distributed Computing MCQ Questions and Answers

1.
What is the primary characteristic of "big data"?

A. Small volume of data

B. High velocity of data

C. Variety of data sources

D. Low complexity of data

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2.
In the context of big data, what does the "3Vs" represent?

A. Velocity, Value, Variability

B. Volume, Variety, Velocity

C. Volume, Value, Variety

D. Velocity, Veracity, Variety

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3.
Which programming framework is commonly used for processing large-scale data in a distributed computing environment?

A. Java

B. Python

C. Hadoop

D. SQL

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4.
What is the main purpose of the Hadoop Distributed File System (HDFS) in a Hadoop ecosystem?

A. Real-time data processing

B. Data storage and retrieval

C. Data visualization

D. Data encryption

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5.
In distributed computing, what is the term for a group of computers connected over a network that work together to solve a problem or perform a task?

A. Hadoop Cluster

B. Data Center

C. Distributed System

D. Supercomputer Cluster

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6.
Which technology is commonly used for distributed data processing and can handle both batch and stream data processing?

A. Apache Kafka

B. Apache HBase

C. Apache Spark

D. Apache Hive

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7.
What is the primary advantage of using distributed computing frameworks like Hadoop and Spark for big data processing?

A. Reduced data volume

B. Scalability and parallel processing capabilities

C. Simplicity of programming

D. Real-time data processing

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8.
Which distributed computing framework is known for its in-memory processing capabilities and is often used for iterative machine learning algorithms?

A. Apache Kafka

B. Apache HBase

C. Apache Spark

D. Apache Hive

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9.
What is the main goal of data partitioning in distributed computing?

A. To increase data complexity

B. To simplify data storage and retrieval

C. To maximize data storage capacity

D. To distribute data across multiple nodes

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10.
Which technology is commonly used for real-time stream processing of big data and is part of the Apache ecosystem?

A. Apache Kafka

B. Apache HBase

C. Apache Spark

D. Apache Hive

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Big Data and Distributed Computing MCQ Questions and Answers | Data Science MCQs

1. What is the primary characteristic of "big data"?

Answer & Solution

2. In the context of big data, what does the "3Vs" represent?

Answer & Solution

3. Which programming framework is commonly used for processing large-scale data in a distributed computing environment?

Answer & Solution

4. What is the main purpose of the Hadoop Distributed File System (HDFS) in a Hadoop ecosystem?

Answer & Solution

5. In distributed computing, what is the term for a group of computers connected over a network that work together to solve a problem or perform a task?

Answer & Solution

6. Which technology is commonly used for distributed data processing and can handle both batch and stream data processing?

Answer & Solution

7. What is the primary advantage of using distributed computing frameworks like Hadoop and Spark for big data processing?

Answer & Solution

8. Which distributed computing framework is known for its in-memory processing capabilities and is often used for iterative machine learning algorithms?

Answer & Solution

9. What is the main goal of data partitioning in distributed computing?

Answer & Solution

10. Which technology is commonly used for real-time stream processing of big data and is part of the Apache ecosystem?

Answer & Solution

1.
What is the primary characteristic of "big data"?

2.
In the context of big data, what does the "3Vs" represent?

3.
Which programming framework is commonly used for processing large-scale data in a distributed computing environment?

4.
What is the main purpose of the Hadoop Distributed File System (HDFS) in a Hadoop ecosystem?

5.
In distributed computing, what is the term for a group of computers connected over a network that work together to solve a problem or perform a task?

6.
Which technology is commonly used for distributed data processing and can handle both batch and stream data processing?

7.
What is the primary advantage of using distributed computing frameworks like Hadoop and Spark for big data processing?

8.
Which distributed computing framework is known for its in-memory processing capabilities and is often used for iterative machine learning algorithms?

9.
What is the main goal of data partitioning in distributed computing?

10.
Which technology is commonly used for real-time stream processing of big data and is part of the Apache ecosystem?