Application of HADOOP to Store and Process Big Data Gathered from an Urban Water Distribution System
Tomasz Jach, Ewa Magiera, Wojciech Froelich
Abstract
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Tomasz Jach, Ewa Magiera, Wojciech Froelich
Abstract
Open-access reader
Information technology has become an integral part of municipal water distribution systems (WDS). Various types of sensors, e.g., smart water meters, usually work in real-time mode delivering a huge amount of data. Big data must be stored in appropriate databases. Along with the development of data mining tools, the analysis of big data is very important for the management of WDS. Valuation of NoSQL databases for water data is currently in its very early stages. In this paper, the Apache Hadoop platform is investigated with respect to a possible database solution based on NoSQL. We present comparative experiments evaluating the performance of the Hadoop and MySQL databases.
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Information technology has become an integral part of municipal water distribution systems (WDS). Various types of sensors, e.g., smart water meters, usually work in real-time mode delivering a huge amount of data. Big data must be stored in appropriate databases. Along with the development of data mining tools, the analysis of big data is very important for the management of WDS. Valuation of NoSQL databases for water data is currently in its very early stages. In this paper, the Apache Hadoop platform is investigated with respect to a possible database solution based on NoSQL. We present comparative experiments evaluating the performance of the Hadoop and MySQL databases.
Key concepts: NoSQL, Big data, Database, Computer science, Work (physics), Process (computing), Data mining, Operating system