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Big Data Platforms And Applications Case Studies Methods Techniques And Performance Evaluation 1st Ed 2021 Florin Pop

  • SKU: BELL-34873462
Big Data Platforms And Applications Case Studies Methods Techniques And Performance Evaluation 1st Ed 2021 Florin Pop
$ 31.00 $ 45.00 (-31%)

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Big Data Platforms And Applications Case Studies Methods Techniques And Performance Evaluation 1st Ed 2021 Florin Pop instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 7.81 MB
Pages: 307
Author: Florin Pop, Gabriel Neagu, (eds.)
ISBN: 9783030388355, 3030388352
Language: English
Year: 2021
Edition: 1st ed. 2021

Product desciption

Big Data Platforms And Applications Case Studies Methods Techniques And Performance Evaluation 1st Ed 2021 Florin Pop by Florin Pop, Gabriel Neagu, (eds.) 9783030388355, 3030388352 instant download after payment.

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 needed for 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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