Intelligent MapReduce Assessment Test

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Intelligent MapReduce Assessment Test - Quiz

Testing knowledge on topics such as MapReduce Version 2 and Process MapReduce Job methods, the Intelligent MapReduce Assessment Test is a re-employment test designed to evaluate the application and practical skills of a MapReduce developer before an interview.


Questions and Answers
  • 1. 

    Which of the following is a topic covered in the test?

    • A.

      File System Counter

    • B.

      Data query

    • C.

      Absolute query

    • D.

      Database management

    Correct Answer
    A. File System Counter
    Explanation
    The correct answer is File System Counter. This suggests that the topic covered in the test is related to the File System Counter. It implies that the test will focus on understanding and assessing the knowledge and skills related to this particular subject matter.

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  • 2. 

    What is the duration of the Mapreduce Assessment Test?

    • A.

      30

    • B.

      40

    • C.

      60

    • D.

      20

    Correct Answer
    D. 20
    Explanation
    The correct answer is 20. This suggests that the duration of the Mapreduce Assessment Test is 20 minutes.

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  • 3. 

    The MapReduce programming model  is useful in?

    • A.

      Hardware modelling

    • B.

      Software input

    • C.

      Processing huge data

    • D.

      Coding

    Correct Answer
    C. Processing huge data
    Explanation
    The MapReduce programming model is useful in processing huge data. This model allows for parallel processing of large datasets by dividing them into smaller chunks and distributing the processing across multiple nodes or machines. This helps to improve the efficiency and speed of data processing, making it ideal for handling big data applications and tasks that require complex computations on large datasets.

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  • 4. 

    The MapReduce Assessment Test contains questions on?

    • A.

      UX/UI

    • B.

      Hadoop Supplied Interfaces

    • C.

      Interface System

    • D.

      Database System

    Correct Answer
    B. Hadoop Supplied Interfaces
    Explanation
    The correct answer is Hadoop Supplied Interfaces. The MapReduce Assessment Test contains questions on Hadoop Supplied Interfaces, which are the interfaces provided by the Hadoop framework for implementing MapReduce tasks. These interfaces include Mapper, Reducer, InputFormat, OutputFormat, and others. Understanding these interfaces is crucial for developing efficient and effective MapReduce programs in Hadoop.

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  • 5. 

    This pre-employment test is useful for hiring a?

    • A.

      Hadoop Developer - MapReduce

    • B.

      Hacker

    • C.

      Computer Engineer

    • D.

      Systems Informant

    Correct Answer
    A. Hadoop Developer - MapReduce
    Explanation
    This pre-employment test is useful for hiring a Hadoop Developer specializing in MapReduce. MapReduce is a programming model and software framework used for processing large sets of data in parallel across a distributed cluster. A Hadoop Developer with expertise in MapReduce would be responsible for designing and implementing MapReduce jobs to process and analyze big data efficiently.

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  • 6. 

    The test contains questions on?

    • A.

      Workload

    • B.

      Turner

    • C.

      Queries

    • D.

      Job methods

    Correct Answer
    D. Job methods
    Explanation
    The test contains questions on job methods. This suggests that the test is focused on assessing the knowledge and understanding of various methods and techniques used in job-related tasks and responsibilities. It is likely that the test will cover topics such as job analysis, job design, job evaluation, and job enrichment. Understanding and applying different job methods is crucial for effective and efficient job performance, making it a relevant topic for assessment in this test.

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  • 7. 

    The "MapReduce System" is also called?

    • A.

      Infrastructure

    • B.

      Development

    • C.

      Reduction

    • D.

      Coding

    Correct Answer
    A. Infrastructure
    Explanation
    The term "MapReduce System" refers to a framework used for processing and analyzing large data sets in a distributed computing environment. It is often referred to as an infrastructure because it provides the necessary resources and infrastructure for executing MapReduce tasks efficiently. The MapReduce system handles the distribution of data, manages the parallel processing of tasks, and ensures fault tolerance. Therefore, calling it an infrastructure accurately describes its role and functionality in the context of big data processing.

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  • 8. 

    If all nodes are on the same local network, they are collectively referred to as?

    • A.

      Cluster

    • B.

      Bunch

    • C.

      Key

    • D.

      Rim

    Correct Answer
    A. Cluster
    Explanation
    When all nodes are on the same local network, they are collectively referred to as a "cluster". A cluster is a group of interconnected computers or servers that work together to perform tasks and provide services. By being on the same local network, these nodes can communicate and share resources efficiently, allowing for improved performance and fault tolerance.

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  • 9. 

    If the nodes are shared across geographically distributed systems, they are called?

    • A.

      Line

    • B.

      Key

    • C.

      Grid

    • D.

      Press

    Correct Answer
    C. Grid
    Explanation
    When nodes are shared across geographically distributed systems, they are referred to as a grid. A grid is a network of interconnected nodes or computers that are spread across different locations but work together to perform a specific task or provide a service. This allows for distributed computing and enables efficient utilization of resources across multiple locations.

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  • 10. 

    MapReduce is useful in the application of? 

    • A.

      Infraction

    • B.

      Singular Value Decomposition

    • C.

      Multiple Documentation

    • D.

      Coded System

    Correct Answer
    B. Singular Value Decomposition
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