Data Analysis of Weather Data Using Hadoop Technology

  • Diallo Thierno Mamadou Oury
  • Archana SinghEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 77)


In the present age, all the real business forms comprise of colossal or huge information. As per the reports in the most recent 3 years, 90% of information was made from the utilitarian modules. The information is advancing exponentially, and the IT databases are moving to the capacity in terabytes along with these lines venturing into the period of huge information. The paper, investigates the progressions in different parameters of climate conditions like temperature, precipitation, snowfall, and so forth in the Pannonian Basin (focal Europe) and other comparative districts, from 1900 to 2014 with a base dataset containing day by day estimations by the climate stations arranged close to our purpose of examination. We have utilized the Hadoop innovation to actualize the weather data. For map reduction, we have utilized Apache PIG, and information is pictured by utilizing Python technology. The data results show the visualization Flot of weather data.


Big Data Hadoop Weather data Map reduction 


  1. 1.
    Lin, J.: Mapreduce is good enough? if all you have is a hammer, throw away everything that’s not a nail! Big Data 1(1), 28–37 (2012). CoRR, abs/1209.2191CrossRefGoogle Scholar
  2. 2.
    Miller, T.W.: Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R, Revised and Expanded 1st edn. Pearson FT Press (2013)Google Scholar
  3. 3.
    Kang, U., Chau, D.H., Faloutsos, C.: Pegasus: mining billion-scale graphs in the cloud. In: ICASSP, pp. 5341–5344 (2012)Google Scholar
  4. 4.
    Fayyad, U.: Big data analytics: applications and opportunities in on-line predictive modeling (2012).
  5. 5.
    Mayer-Schonberger, V.: Big data: a revolution that will transform how we live, work and think paperbackGoogle Scholar
  6. 6.
  7. 7.
    Weather data analysis and visualization—big data tutorial part 1/9—fundamentals. file:///C:/Open-BigData/Upload/Weather-analysis.htmGoogle Scholar
  8. 8.
  9. 9.

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Amity UniversityNoidaIndia

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