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Big Data And Distributed Computing MCQs

Practice Big Data And Distributed Computing MCQs for competitive exams.

Big Data And Distributed Computing MCQs

Practice questions from this topic.

In the context of big data, what does the term "data ingestion" refer to?

  1. A. The process of extracting insights from data
  2. B. The process of collecting and importing data
  3. C. The process of visualizing data
  4. D. The process of reducing data volume
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What is the primary role of a "Data Scientist" in the context of big data analytics?

  1. A. Managing job scheduling
  2. B. Data visualization
  3. C. Analyzing and extracting insights from data
  4. D. Data encryption
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In distributed computing, what is the primary advantage of using a "Reducer" in the MapReduce programming model?

  1. A. To split data into smaller chunks
  2. B. To process and aggregate data from Mapper tasks
  3. C. To store data in the HDFS
  4. D. To visualize data relationships
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What is the main purpose of a "Combiner" in the Hadoop MapReduce programming model?

  1. A. To split data into smaller chunks
  2. B. To process and aggregate data from Mapper tasks
  3. C. To optimize data storage in HDFS
  4. D. To visualize data relationships
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In the context of big data analytics, what is the term for the process of combining data from multiple sources and formats into a single, unified dataset?

  1. A. Data sampling
  2. B. Data integration
  3. C. Data deduplication
  4. D. Data preprocessing
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What is the primary advantage of using distributed data processing frameworks like Hadoop and Spark for big data analytics?

  1. A. Increased data variety
  2. B. Scalability and parallel processing capabilities
  3. C. Reduced data storage and transmission costs
  4. D. Real-time data collection and analysis
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In big data analytics, what does the term "data transformation" involve?

  1. A. Reducing data volume
  2. B. Shuffling data across nodes
  3. C. Preparing data for analysis
  4. D. Encrypting data
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Which distributed computing framework is commonly used for interactive data analytics and SQL-like querying of large datasets in real-time?

  1. A. Apache Kafka
  2. B. Apache HBase
  3. C. Apache Spark
  4. D. Apache Drill
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In distributed computing, what is the primary purpose of a "Job Tracker" in the Hadoop MapReduce framework?

  1. A. Storing metadata
  2. B. Managing job scheduling
  3. C. Storing and managing data blocks
  4. D. Managing data visualization
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What is the primary goal of "data deduplication" in big data storage and processing?

  1. A. To increase data variety
  2. B. To reduce storage space and data redundancy
  3. C. To improve data visualization
  4. D. To slow down data velocity
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Which distributed computing framework is known for its high-speed, low-latency data processing capabilities and is suitable for real-time analytics?

  1. A. Apache Kafka
  2. B. Apache HBase
  3. C. Apache Spark
  4. D. Apache Hive
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What does the term "batch processing" typically refer to in the context of big data analytics?

  1. A. Real-time data processing
  2. B. Processing data in small increments
  3. C. Processing data in fixed-size batches
  4. D. Real-time data collection and analysis
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