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H13-831_V2.0 · Question #3807

Both the Spark framework and the MapReduce framework are distributed computing frameworks in Hadoop clusters. Which of the following descriptions of the differences between these two frameworks are…

The correct answer is A. The iterative calculation process performed by Spark mainly relies on memory. Intermediate data is B. MapReduce has diverse algorithms and supports the combined application of multiple algorithms C. Spark has rich operation types and supports various data conversion operations D. MapReduce needs to put data on disk for each iteration and read it from disk for the next iteration. See the full explanation below for the reasoning.

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Question

Both the Spark framework and the MapReduce framework are distributed computing frameworks in Hadoop clusters. Which of the following descriptions of the differences between these two frameworks are correct? (Multiple choice)

Options

  • AThe iterative calculation process performed by Spark mainly relies on memory. Intermediate data is
  • BMapReduce has diverse algorithms and supports the combined application of multiple algorithms
  • CSpark has rich operation types and supports various data conversion operations
  • DMapReduce needs to put data on disk for each iteration and read it from disk for the next iteration,

How the community answered

(19 responses)
  • A
    100% (19)

Topics

#Spark vs MapReduce#in-memory computing#iterative computation#distributed frameworks

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