Implementation of Map Reduce Using Machine Learning

ABSTRACT

Cloud computing provides a distributed environment where data are stored in separated disks and processed in multiple servers in parallel. To witness a quick increase in the variety of data processed there is a rapid growth of applications such as social network analysis, semantic web analysis, and bioinformatics network analysis. Analysis of large-scale data and effective management are interesting but it’s a critical challenge. In recent days the big data gets a lot of attention from academia, industry as well as the government. This paper introduces several big data processing techniques from the aspect of system and application. From the view of cloud data management and big data processing mechanisms, this paper presents the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database, and data storage scheme. The MapReduce parallel processing framework introduces Map Reduce optimization strategies and applications that are in the literature. This paper tells about issues and challenges and explores research on big data processing in cloud computing environments.

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