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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 7, ISSUE 12, DECEMBER 2018

Big Data Load Management: A Survey

Aasheesh Raizada Manoj Rana, Pankaj Kumar Varshney

DOI: 10.17148/IJARCCE.2018.71216

Abstract: Big Data refers to huge volume of data which present everywhere, in human body as human protein and also present in our environment. Previous generations amassed vast collections of rocks, papers, photographs, punch cards, microfilm etc. But now it's becoming very difficult for industries to store, retrieve and processes the big data at real time. But now day, the high performance and reliable systems are required to subpart real time work. Map Reduce is a programming model for writing applications that can process Big Data in parallel on multiple nodes. Map Reduce provides analytical capabilities for analyzing huge volumes of complex data.



Keywords: Big Data, Map Reduce, HADOOP, YARN

How to Cite:

[1] Aasheesh Raizada Manoj Rana, Pankaj Kumar Varshney, “Big Data Load Management: A Survey,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2018.71216