Frameworks for management, storage and preparation of large data volumes Big Data

Authors

  • Marco Antonio Almeida Pazmiño Desarrollador en Apache ServiceMix (ESB), Apache Camel, Hadoop, HBase y Pig y estudiante de la Universidad a Distancia de Madrid, UDIMA (España)
  • Juan Alfonso Lara Torralbo Profesor de la Universidad a Distancia de Madrid, UDIMA (España)
  • David Lizcano Casas Profesora de la Universidad a Distancia de Madrid, UDIMA (España)

DOI:

https://doi.org/10.51302/tce.2015.26

Keywords:

Big Data, Hadoop, HDFS, World Meteorological Organization, Global Observing System, Internet of Things

Abstract

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

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Holmes, A. [2014]: Hadoop in practice, 2. a ed., Shelter Island, Nueva York, EE. UU., Manning Publications Co.

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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.

Published

2015-06-01

How to Cite

Almeida Pazmiño, M. A., Lara Torralbo, J. A., & Lizcano Casas, D. (2015). Frameworks for management, storage and preparation of large data volumes Big Data. Technology, Science and Education Journal, (1), 99–115. https://doi.org/10.51302/tce.2015.26