Hadoop MapReduce is processed for analysis large volume of data through multiple nodes in parallel. However MapReduce has two function Map and Reduce, large data is stored through HDFS. Lack of facility involve in MapReduce so Spark is designed to run for real time stream data and for fast queries. Spark jobs perform work on Resilient Distributed Datasets and directed acyclic graph execution engine. In this paper, we extend Hadoop MapReduce working and Spark architecture with supporting kind of operation to perform. We also show the differences between Hadoop MapReduce and Spark through Map and Reduce phase individually.
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Verma et al. (2016) studied this question.
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