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Big Data Analytics in Aquaculture Using Hive and Hadoop Platform

Big Data Analytics in Aquaculture Using Hive and Hadoop Platform
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Author(s): P. Venkateswara Rao (ASCET, India), A. Ramamohan Reddy (S. V. University, India)and V. Sucharita (K. L. University, India)
Copyright: 2018
Pages: 7
Source title: Exploring the Convergence of Big Data and the Internet of Things
Source Author(s)/Editor(s): A.V. Krishna Prasad (K.L. University, India)
DOI: 10.4018/978-1-5225-2947-7.ch002

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Abstract

In the field of Aquaculture with the help of digital advancements huge amount of data is constantly produced for which the data of the aquaculture has entered in the big data world. The requirement for data management and analytics model is increased as the development progresses. Therefore, all the data cannot be stored on single machine. There is need for solution that stores and analyzes huge amounts of data which is nothing but Big Data. In this chapter a framework is developed that provides a solution for shrimp disease by using historical data based on Hive and Hadoop. The data regarding shrimps is acquired from different sources like aquaculture websites, various reports of laboratory etc. The noise is removed after the collection of data from various sources. Data is to be uploaded on HDFS after normalization is done and is to be put in a file that supports Hive. Finally classified data will be located in particular place. Based on the features extracted from aquaculture data, HiveQL can be used to analyze shrimp diseases symptoms.

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