Big Data and Distributed Computing MCQ Questions and Answers

31.
What is the primary advantage of using data compression techniques in big data storage and processing?

A. Increased data variety

B. Reduced data storage and transmission costs

C. Enhanced data visualization

D. Improved data velocity

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32.
In the context of big data, what does the term "data skew" refer to?

A. The uneven distribution of data across nodes

B. The encryption of data

C. The replication of data

D. The loss of data during transmission

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33.
Which Apache project provides a real-time stream processing framework for handling and analyzing data streams in real-time?

A. Apache Kafka

B. Apache HBase

C. Apache Spark Streaming

D. Apache Hive

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34.
What is the primary benefit of using a columnar storage format like Parquet in big data analytics?

A. Real-time data processing

B. Reduced storage space and improved query performance

C. Simplified data variety and velocity

D. Enhanced data visualization

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35.
In the context of big data, what is the purpose of "data sampling"?

A. To increase data volume

B. To reduce data variety

C. To decrease data velocity

D. To obtain a representative subset of data

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36.
Which distributed computing framework is commonly used for batch processing of large datasets and is often associated with Hadoop?

A. Apache Kafka

B. Apache HBase

C. Apache Spark

D. Apache Hive

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37.
What is the primary purpose of "data replication" in a distributed computing environment?

A. To increase data variety

B. To improve data visualization

C. To enhance fault tolerance

D. To reduce data velocity

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38.
In big data analytics, what is the term for the process of transforming and preparing raw data for analysis, often involving cleaning and structuring the data?

A. Data sampling

B. Data siloing

C. Data preprocessing

D. Data encryption

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39.
What does the term "YARN" stand for in the context of Hadoop and distributed computing?

A. Yet Another Resource Negotiator

B. Yet Another Real-time Network

C. Yield and Return Notation

D. Your Advanced Resource Node

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40.
Which technology is commonly used for streamlining the data velocity aspect of big data, allowing for real-time data collection and analysis?

A. Data lakes

B. Data warehouses

C. Internet of Things (IoT)

D. Apache Kafka

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

31. What is the primary advantage of using data compression techniques in big data storage and processing?

Answer & Solution

32. In the context of big data, what does the term "data skew" refer to?

Answer & Solution

33. Which Apache project provides a real-time stream processing framework for handling and analyzing data streams in real-time?

Answer & Solution

34. What is the primary benefit of using a columnar storage format like Parquet in big data analytics?

Answer & Solution

35. In the context of big data, what is the purpose of "data sampling"?

Answer & Solution

36. Which distributed computing framework is commonly used for batch processing of large datasets and is often associated with Hadoop?

Answer & Solution

37. What is the primary purpose of "data replication" in a distributed computing environment?

Answer & Solution

38. In big data analytics, what is the term for the process of transforming and preparing raw data for analysis, often involving cleaning and structuring the data?

Answer & Solution

39. What does the term "YARN" stand for in the context of Hadoop and distributed computing?

Answer & Solution

40. Which technology is commonly used for streamlining the data velocity aspect of big data, allowing for real-time data collection and analysis?

Answer & Solution

31.
What is the primary advantage of using data compression techniques in big data storage and processing?

32.
In the context of big data, what does the term "data skew" refer to?

33.
Which Apache project provides a real-time stream processing framework for handling and analyzing data streams in real-time?

34.
What is the primary benefit of using a columnar storage format like Parquet in big data analytics?

35.
In the context of big data, what is the purpose of "data sampling"?

36.
Which distributed computing framework is commonly used for batch processing of large datasets and is often associated with Hadoop?

37.
What is the primary purpose of "data replication" in a distributed computing environment?

38.
In big data analytics, what is the term for the process of transforming and preparing raw data for analysis, often involving cleaning and structuring the data?

39.
What does the term "YARN" stand for in the context of Hadoop and distributed computing?

40.
Which technology is commonly used for streamlining the data velocity aspect of big data, allowing for real-time data collection and analysis?