The Heterogeneity Paradigm in Big Data Architectures

Ivanov, Todor, Izberovic, Sead and Korfiatis, Nikolaos (2016) The Heterogeneity Paradigm in Big Data Architectures. In: Managing and Processing Big Data in Cloud Computing. Advances in Data Mining and Database Management (ADMDM) . Idea Group Publishing, pp. 218-245. ISBN 9781466697676

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Abstract

This chapter introduces the concept of heterogeneity as a perspective in the architecture of big data systems targeted to both vertical and generic workloads and discusses how this can be linked with the existing Hadoop ecosystem (as of 2015). The case of the cost factor of a big data solution and its characteristics can influence its architectural patterns and capabilities and as such an extended model based on the 3V paradigm is introduced (Extended 3V). This is examined on a hierarchical set of four layers (Hardware, Management, Platform and Application). A list of components is provided on each layer as well as a classification of their role in a big data solution.

Item Type: Book Section
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Related URLs:
Depositing User: Pure Connector
Date Deposited: 24 Sep 2016 01:01
Last Modified: 25 Jul 2019 04:15
URI: https://ueaeprints.uea.ac.uk/id/eprint/60356
DOI: 10.4018/978-1-4666-9767-6.ch015

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