Abstract
With the increasing development of platforms for massive users, the amount of data generated from these platforms is rapidly increasing. A large number of big data analysis frameworks have been designed to analyze data generated from these platforms. This however requires a specific benchmark to evaluate the system performance. Today, realtime analysis (or streaming analysis) becomes a hot research topic of big data research. However, there is no special benchmark designed for such streaming analysis systems. This paper introduces a tool for evaluating the performance of such streaming analysis systems. Based on the scenario of e-commerce platforms, the benchmark tool is designed using a data generator with certain user models based on the user’s habits in e-commerce platforms. A test suite is developed to be responsible for simulated mixed workloads for streaming analysis.
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References
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Acknowledgements
This work is supported by Science and Technology Project of the State Grid Corporation of China (SGBJDK00KJJS1500180) and the State Grid Information & Telecommunication Group CO., LTD. (SGITG-KJ-JSKF[2015]0010).
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Teng, M., Sun, Q., Deng, B., Sun, L., Qin, X. (2017). A Tool of Benchmarking Realtime Analysis for Massive Behavior Data. In: Chen, L., Jensen, C., Shahabi, C., Yang, X., Lian, X. (eds) Web and Big Data. APWeb-WAIM 2017. Lecture Notes in Computer Science(), vol 10367. Springer, Cham. https://doi.org/10.1007/978-3-319-63564-4_33
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DOI: https://doi.org/10.1007/978-3-319-63564-4_33
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