Benchmarking modern distributed streaming platforms

Shilei Qian, Gang Wu, Jie Huang, Tathagata Das
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引用次数: 31

Abstract

The prevalence of big data technology has generated increasing demands in large-scale streaming data processing. However, for certain tasks it is still challenging to appropriately select a platform due to the diversity of choices and the complexity of configurations. This paper focuses on benchmarking some principal streaming platforms. We achieve our goals on StreamBench, a streaming benchmark tool based on which we introduce proper modifications and extensions. We then accomplish performance comparisons among different big data platforms, including Apache Spark, Apache Storm and Apache Samza. In terms of performance criteria, we consider both computational capability and fault-tolerance ability. Finally, we give a summary on some key knobs for performance tuning as well as on hardware utilization.
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对现代分布式流媒体平台进行基准测试
随着大数据技术的普及,对大规模流数据处理的需求越来越大。然而,对于某些任务,由于选择的多样性和配置的复杂性,正确选择平台仍然是一项挑战。本文主要对一些主流流媒体平台进行了基准测试。我们在StreamBench上实现了我们的目标,这是一个流基准测试工具,我们在此基础上引入了适当的修改和扩展。然后,我们完成了不同大数据平台的性能比较,包括Apache Spark、Apache Storm和Apache Samza。在性能标准方面,我们考虑了计算能力和容错能力。最后,我们总结了性能调优的一些关键旋钮以及硬件利用率。
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