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Title:
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BD4NRG QUERY ENGINE - INTUITIVE, EFFICIENT
AND FEDERATED QUERYING ON BIG DATA |
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Author(s):
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Konstantinos Touloumis, Evangelos Karakolis, Panagiotis Kapsalis, Vangelis Marinakis and John Psarras |
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ISBN:
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978-989-8704-47-4 |
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Editors:
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Piet Kommers, Inmaculada Arnedillo Sánchez and Pedro Isaías |
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Year:
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2023 |
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Edition:
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Single |
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Keywords:
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Big Data Querying, Big Data Analytics, Energy Sector, Federated Querying |
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Type:
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Full Paper |
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First Page:
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111 |
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Last Page:
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118 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Due to the rapid development of Internet of Things (IoT) technology during the last decade, there has been recorded a
significant growth in the size of data collected by data warehouses, especially on the ones connected to sensors and meters
on the energy sector. Querying such data, gathered by heterogeneous data sources is a complicated task in terms of space
allocation, scalability, and integration. Big data analytics methods try to address the problem of querying big data by
bringing together different data sources of different formats with a high level of abstraction. This paper presents a query
engine that, on the one hand addresses the problem of querying big data stored on different and heterogeneous databases
and on the other hand, simplifies the steps needed by the user for defining and executing queries on the aforementioned
databases through an intuitive and easy to use interface, so as to facilitate high level analytical services. Particular attention
is given to securing the tool by employing access resource management thus preventing unauthorized users from accessing
the requested resources. |
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