Research on stream processing engine and benchmarking framework

Qionghua Le, Mingang Chen, Wenjie Chen
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Abstract

Stream computing engine is an important part of big data system, and benchmarking is one of the main means to measure the engine's performance. In this paper, we compare the differences between two engines, Spark Streaming and Flink, in stream processing technologies. Then the open source benchmarking frameworks supporting stream processing and their respective characteristics are studied, and the HiBench testing framework is selected to test the two stream processing engines. The test results show that Flink is better than Spark Streaming in terms of performance in shuffle, stateful computation and windowed computation.
流处理引擎和基准框架的研究
流计算引擎是大数据系统的重要组成部分,对标测试是衡量流计算引擎性能的主要手段之一。在本文中,我们比较了Spark Streaming和Flink这两个引擎在流处理技术上的差异。然后研究了支持流处理的开源基准测试框架及其各自的特点,并选择HiBench测试框架对两种流处理引擎进行测试。测试结果表明,Flink在shuffle、有状态计算和有窗口计算方面的性能都优于Spark Streaming。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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