A comprehensive study on fault tolerance in stream processing systems

作     者：Xiaotong WANG Chunxi ZHANG Junhua FANG Rong ZHANG Weining QIAN Aoying ZHOU Xiaotong WANG;Chunxi ZHANG;Junhua FANG;Rong ZHANG;Weining QIAN;Aoying ZHOU

作者机构：School of Data Science and EngineeringEast China Normal UniversityShanghai 200062China Advanced Data Analytics Laboratory of Soochow UniversitySuzhou 215006China 

出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)

年 卷 期：2022年第16卷第2期

页      面：80-97页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The work was supported by the National Key Research and Development Plan Project(2018YFB1003404) 

主　　题：fault tolerance performance evaluation stream processing 

摘      要：Stream processing has emerged as a useful technology for applications which require continuous and low latency computation on infinite streaming *** stream processing systems(SPSs)usually require distributed deployment on clusters of servers in face of large-scale of data,it is especially common to meet with failures of processing nodes or communication networks,but should be handled seriously considering service quality.A failed system may produce wrong results or become unavailable,resulting in a decline in user experience or even significant financial ***,a large amount of fault tolerance approaches have been proposed for *** approaches often have their own priorities on specific performance concerns,e.g.,runtime overhead and recovery ***,there is a lack of a systematic overview and classification of the state-of-the-art fault tolerance approaches in SPSs,which will become an obstacle for the development of ***,we investigate the existing achievements and develop a taxonomy of the fault tolerance in ***,we propose an evaluation framework tailored for fault tolerance,demonstrate the experimental results on two representative open-sourced SPSs and exposit the possible disadvantages in current ***,we specify future research directions in this domain.