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A Review of System Benchmark Standards and a Look Ahead Towards an Industry Standard for Benchmarking Big Data Workloads

A Review of System Benchmark Standards and a Look Ahead Towards an Industry Standard for Benchmarking Big Data Workloads
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Author(s): Raghunath Nambiar (Cisco Systems, Inc., USA)and Meikel Poess (Oracle Corp., USA)
Copyright: 2014
Pages: 18
Source title: Big Data Management, Technologies, and Applications
Source Author(s)/Editor(s): Wen-Chen Hu (University of North Dakota, USA)and Naima Kaabouch (University of North Dakota, USA)
DOI: 10.4018/978-1-4666-4699-5.ch017

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Abstract

Industry standard benchmarks have played, and continue to play, a crucial role in the advancement of the computing industry. Demands for them have existed since buyers were first confronted with the choice between purchasing one system over another. Over the years, industry standard benchmarks have proven critical to both buyers and vendors: buyers use benchmark results when evaluating new systems in terms of performance, price/performance, and energy efficiency; while vendors use benchmarks to demonstrate competitiveness of their products and to monitor release-to-release progress of their products under development. Historically, we have seen that industry standard benchmarks enable healthy competition that results in product improvements and the evolution of brand new technologies. Over the past quarter-century, industry standard bodies like the Transaction Processing Performance Council (TPC) and the Standard Performance Evaluation Corporation (SPEC) have developed several industry standards for performance benchmarking, which have been a significant driving force behind the development of faster, less expensive, and/or more energy efficient system configurations. The world has been in the midst of an extraordinary information explosion over the past decade, punctuated by rapid growth in the use of the Internet and the number of connected devices worldwide. Today, we’re seeing a rate of change faster than at any point throughout history, and both enterprise application data and machine generated data, known as Big Data, continue to grow exponentially, challenging industry experts and researchers to develop new innovative techniques to evaluate and benchmark hardware and software technologies and products. This chapter looks into techniques to measure the effectiveness of hardware and software platforms dealing with big data.

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