Why can it be more beneficial to use Spark than MapReduce when creating a big data solution?

IT Questions BankCategory: IoT Big Data & AnalyticsWhy can it be more beneficial to use Spark than MapReduce when creating a big data solution?

Why can it be more beneficial to use Spark than MapReduce when creating a big data solution?

  • batch processing
  • built-in machine learning library
  • data stored on disk
  • parallelizing algorithms

Explanation: Spark is gaining popularity because of its performance, ease of administration, simplicity and the fact that applications can be created more quickly using it. Some of the differentiating features are as follows:

  • It is capable of dealing with enormous amounts of real-time data.
  • It can transcend different silos of data.
  • It supports many different languages, which means there is less code that needs to be written and maintained.
  • It is easier to learn to develop and less intimidating than MapReduce.

More Questions: Big data & Analytics Chapter 6 Quiz Answers – Architecture for Big Data and Data Engineering


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