The ability to process data up to 100 times faster than MapReduce makes which of these an attractive option to businesses looking to process large amounts of unstructured data?

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21 August, 14:15

The ability to process data up to 100 times faster than MapReduce makes which of these an attractive option to businesses looking to process large amounts of unstructured data?

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Marcus Fuentes · Answer 1

Answer: Spark

Explanation: Spark is a unified analytics engine for large scale data processing suitable for use in a wide range of circumstances. It was first developed at the AMPLab (Algorithms, Machines, and People Lab) at UC Berkeley, but is now part of the Apache Software Foundation. It is useful both in data processing and data analysis.

Using Spark, organizations can get a lot of valuable information and inferences from a huge pile of unstructured data. Spark has demonstrated to be highly efficient, running programs 100 times faster than Mapreduce and Hadoop. It is also very useful with algorithms of machine learning