HADOOP A Solution to Big Data Problems using Partitioning Mechanism Map Reduce

Main Authors: Jagjit Kaur, Heena Girdher
Format: Article eJournal
Bahasa: eng
Terbitan: , 2018
Subjects:
Online Access: https://zenodo.org/record/3583543
Daftar Isi:
  • 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: https://www.ijtsrd.com/papers/ijtsrd14374.pdf