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Issue 5
Nov.  2014
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KANG Qiang-Qiang, JIN Che-Qing, ZHANG Zhao, HU Hua-Liang, ZHOU Ao-Ying. How to evaluate inmemory database objectively[J]. Journal of East China Normal University (Natural Sciences), 2014, (5): 320-329. doi: 10.3969/j.issn.1000-5641.2014.05.029
Citation: KANG Qiang-Qiang, JIN Che-Qing, ZHANG Zhao, HU Hua-Liang, ZHOU Ao-Ying. How to evaluate inmemory database objectively[J]. Journal of East China Normal University (Natural Sciences), 2014, (5): 320-329. doi: 10.3969/j.issn.1000-5641.2014.05.029

How to evaluate inmemory database objectively

doi: 10.3969/j.issn.1000-5641.2014.05.029
  • Publish Date: 2014-09-25
  • The hardware technology continues to develop in the past decade, and the price of memory gets lower so that many computer systems tend to deployhugesize memory. To fulfill this benefit, the researchers also developed several inmemory databases (IMDB) that execute workloads after preloading the whole data into memory. The bloom of various inmemory databases shows the necessity of testing and evaluating their performance objectively and fairly. Although the existing database benchmarks have shown great success during the development of the database technologies, including Wisconsin benchmark, TPCX series, and so on, such work cannot be applied straightforwardly due to the lack of consideration of several unique characteristics of inmemory databases. In this article, we propose a novel benchmark, called InMemBench, to test and evaluate the performance of an inmemory database objectively and fairly. Different from traditional database benchmarks, we take special consideration of startup, data organization, and data compression. Moreover, we conduct extensive experiments to illustrate the effectiveness and efficiency of our proposal.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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