Frameworks for management, storage and preparation of large data volumes Big Data
DOI:
https://doi.org/10.51302/tce.2015.26Keywords:
Big Data, Hadoop, HDFS, World Meteorological Organization, Global Observing System, Internet of ThingsAbstract
Weather systems like the World Meteorological Organization´s Global Information System need to store different kinds of images, data and files. Big Data and its 3V paradigm can provide a suitable solution to solve this problem. This tutorial presents some concepts around the Hadoop framework, de facto standard implementation of Big Data, and how to store semi-estructured data generated by automatic weather stations using this framework. Finally, a formal method to generate weather reports using Hadoop´s ecosystem frameworks is presented.
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References
Capriolo, E.; Wampler, D. y Rutherglen, J. [2012]: Programming hive, Sebastopol, California, EE. UU.,O’Reilly Media.
Gates, A. [2011]: Programming Pig,1. a ed., Sebastopol, California,EE. UU., O’Reilly Media.
Holmes, A. [2014]: Hadoop in practice, 2. a ed., Shelter Island, Nueva York, EE. UU., Manning Publications Co.
Lam, C. [2011]: Hadoop in action,Stamford, Connecticut, EE. UU., Manning Publication Co.
Nathan, M. y Warren, J. [2014]: Big Data: principles and best practices of scalable realtime data systems, Manning Publications.
Prajapati, V. [2013]: Big Data analytics with R and Hadoop, Bimingham, Reino Unido, Packt Publishing Ltd.
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Copyright (c) 2015 Marco Antonio Almeida Pazmiño, Juan Alfonso Lara Torralbo, David Lizcano Casas
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.