Survey on MapReduce and Hadoop
Patel Ahad
, Kapratwar Abhishek , Khandagale Nikita , Helwade Rishikesh , Kamble A.S
Hadoop, Map Reduce, Big Data, HDFS.
The word Big Data indicates to catch, regulate, process and analyze large amount of data that is structured, unstructured or semi-structured which has varying speed and growth. Analyzing such large and varying size of data is challenging using traditional structural databases. One of the important patterns in Big Data processing is HDFS which is better than the traditional structural databases. Hadoop is freely available software program. Hadoop being classified as a pivot platform for structuring Big Data and provides facility for analyzing the stored data. Hadoop can expand from a single machine to n number of machines depending on the demand of the users. This paper helps users to understand how Hadoop is better than the traditional structural databases for processing of Big Data and also gives a summary about how Map Reduce is used alongside with HDFS to do analysis on large datasets.
"Survey on MapReduce and Hadoop", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.422 - 424, November-2018, Available :https://ijsdr.org/papers/IJSDR1811074.pdf
Volume 3
Issue 11,
November-2018
Pages : 422 - 424
Paper Reg. ID: IJSDR_180858
Published Paper Id: IJSDR1811074
Downloads: 000347190
Research Area: Engineering
Country: Pune, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
