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The Heterogeneity Paradigm in Big Data Architectures

The Heterogeneity Paradigm in Big Data Architectures
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Author(s): Todor Ivanov (Goethe University Frankfurt, Germany), Sead Izberovic (Goethe University Frankfurt, Germany)and Nikolaos Korfiatis (University of East Anglia, UK)
Copyright: 2017
Pages: 27
Source title: Artificial Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1759-7.ch021

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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.

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