Big Data Mining on Rainfall Data

  • Keshani VyasEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 52)


India is a country with leading economy driven by agriculture, which is majorly depended on the climatic changes. Rainfall events in India have diversified irregular pattern across the country, which makes it more complex and challenging to mine. Rainfall data comes under the meteorological data which is spatiotemporal in nature. The meteorological data is increasing day by day, to handle that huge amount of data imposing a wide range of challenges for storage and analysis. Big data technologies, like Hadoop Distributed File System (HDFS), Hbase, and many query processing tools for processing data like Hive and Pig are popularly known to handle such type of data. But these tools and techniques individually are inadequate for mining data efficiently. We have reviewed the research in the area of mining rainfall data and identified the gaps in the existing approaches.


Spatiotemporal data Rainfall Big data mining 


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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.L. D. College of EngineeringAhmedabadIndia

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