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Big Data Platforms and Applications
Case Studies, Methods, Techniques, and Performance Evaluation
von Gabriel Neagu, Florin Pop
Verlag: Springer International Publishing
Reihe: Computer Communications and Networks
Hardcover
ISBN: 978-3-030-38838-6
Auflage: 1st ed. 2021
Erschienen am 30.09.2022
Sprache: Englisch
Format: 235 mm [H] x 155 mm [B] x 17 mm [T]
Gewicht: 470 Gramm
Umfang: 308 Seiten

Preis: 181,89 €
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Biografische Anmerkung
Inhaltsverzeichnis
Klappentext

Dr. Florin Pop is a Professor at the Department of Computer Science and Engineering at the University Politehnica of Bucharest, Romania and a Senior Researcher (1st Degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania.


Dr. Gabriel Neagu is a Senior Researcher (1st Degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania.



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This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation.
The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.
The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.


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