Benchmarking modern distributed streaming platforms
Shilei Qian, Gang Wu, Jie Huang, Tathagata Das · 2016
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.