HADOOP: A Solution to Big Data Problems using Partitioning Mechanism Map-Reduce
International Journal of Trend in Scientific Research and Development, 2 (4):
1296-1301 (июня 2018)Аннотация
With an increased usage of the internet, the data usage is also getting increased exponentially year on year. So obviously to handle such an enormous data we needed a better platform to process data. So a programming model was introduced called Map Reduce, which process big amounts of data in-parallel on large clusters (thousands of nodes) of commodity hardware in a reliable, fault-tolerant manner. Since HADOOP has been emerged as a popular tool for BIG DATA implementation, the paper deals with the overall architecture of HADOOP along with the details of its various components. Jagjit Kaur | Heena Girdher"HADOOP: A Solution to Big Data Problems using Partitioning Mechanism Map-Reduce" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14374.pdf http://www.ijtsrd.com/computer-science/database/14374/hadoop-a-solution-to-big-data-problems-using-partitioning-mechanism-map-reduce/jagjit-kaur