Modeling Big Data Analytics with a Real-Time Executable Specification Language

Modeling Big Data Analytics with a Real-Time Executable Specification Language

Amir A. Khwaja (King Faisal University, Saudi Arabia)
Copyright: © 2016 |Pages: 23
DOI: 10.4018/978-1-4666-9840-6.ch021
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Abstract

Big data explosion has already happened and the situation is only going to exacerbate with such a high number of data sources and high-end technology prevalent everywhere, generating data at a frantic pace. One of the most important aspects of big data is being able to capture, process, and analyze data as it is happening in real-time to allow real-time business decisions. Alternate approaches must be investigated especially consisting of highly parallel and real-time computations for big data processing. The chapter presents RealSpec real-time specification language that may be used for the modeling of big data analytics due to the inherent language features needed for real-time big data processing such as concurrent processes, multi-threading, resource modeling, timing constraints, and exception handling. The chapter provides an overview of RealSpec and applies the language to a detailed big data event recognition case study to demonstrate language applicability to big data framework and analytics modeling.
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Background

This section provides an overview of the dataflow programming paradigm and introduces the RealSpec real-time specification language.

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