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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2020, Vol. 14 Issue (5) : 145204    https://doi.org/10.1007/s11704-019-8438-0
RESEARCH ARTICLE
Benchmarking on intensive transaction processing
Chunxi ZHANG, Yuming LI, Rong ZHANG(), Weining QIAN, Aoying ZHOU
1School of Data Science and Engineering, East China Normal University, Shanghai 200062, China
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Abstract

Benchmarks play a crucial role in database performance evaluation, and have been effectively promoting the development of database management systems.With critical transaction processing requirements of new applications, we see an explosion of innovative database technologies for dealing with highly intensive transaction workloads (OLTP) with the obvious characteristics of sharp dynamics, terrific skewness, high contention, or high concurrency (abbr. DSC2), which can not be well described or evaluated by current standard benchmarks. In this paper, based on the representative SecKill applications, we define a pacakge of workloads simulating intensive transactional processing requirements. And we create a general and flexible benchmark framework PeakBench for evaluating intensive OLTP workloads on databases. We are the first work to have full control on simulating DSC2, especially for the fine granularity control for contention generation. With a comprehensive set of experiments conducted on popular open sourced DBMSs compared with the other representative OLTP benchmarks, we completely demonstrate the usefulness of PeakBench.

Keywords benchmark      transaction processing      intensiveworkloads      evaluation     
Corresponding Author(s): Rong ZHANG   
Just Accepted Date: 08 July 2019   Issue Date: 10 March 2020
 Cite this article:   
Chunxi ZHANG,Yuming LI,Rong ZHANG, et al. Benchmarking on intensive transaction processing[J]. Front. Comput. Sci., 2020, 14(5): 145204.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-019-8438-0
https://academic.hep.com.cn/fcs/EN/Y2020/V14/I5/145204
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