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As the uses of social media networking platforms increasing hence, huge volume of data is generated with that it required large amount of memory for storing the data. Since, there are some issues like storing the large data set, parallel and distributed large data set also including some challenges like critical path problem, reliability problem, equal split issues, single split issues and aggregation of issues. Hence, to overcome this problem we have MapReduce method which allows us to use parallel computations, distributed processing without considering issues like fault tolerance and reliability. For such reasons, this survey paper mentioned the various implementation methods of MapReduce and also, comparison between various implementation methods with respect to the volume and variety.
Keywords:
MapReduce, Big Data, Hadoop
Cite Article:
"Analysis of MapReduce Methods", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 3, page no.58 - 62, March-2020, Available :http://www.ijrti.org/papers/IJRTI2003011.pdf
Downloads:
000204834
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator