Performance Comparison of Map Reduce and Apache Spark on Hadoop for Big Data Analysis
Keywords:
Big Data, Hadoop, HDFS, Map Reduce, Apache SparkAbstract
With the unremitting advancement of internet and IT, tremendous growth of data has been observed. Data creation occurring at very fast pace, referred as big data, is a trending term these days. Big Data has been the topic of fascination for Computer Science fanatic around the world, and has gained even more prominence in the last few years. This paper scrutinizes the comparison of Hadoop Map Reduce and the newly introduced Apache Spark – both of which are framework for analyzing big data. Although both of these resources are based on the idea of Big Data, their performance varies significantly based on the application under consideration. In this paper two frameworks are being compared along with providing the performance comparison using word count algorithm. In this paper, various datasets has been analyzed over Hadoop Map Reduce and Apache Spark environment for word count algorithm. The system that comes out to be better is further used to analyze the research dataset of a university.
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