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| 支持实时流计算应用的关键技术研究进展 |
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徐志榛1,2, 徐辰1,2,3, 丁光耀1,2, 陈梓浩1,2, 周傲英1,2
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1.华东师范大学 数据科学与工程学院, 上海 200062;2.上海市大数据管理系统工程研究中心, 上海 200062;3.广西可信软件重点实验室(桂林电子科技大学), 广西 桂林 541004
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| 摘要: |
| 信息系统在进行知识的挖掘和管理时, 需要处理各种形式的数据, 流数据便是其中之一. 流数据具有数据规模大、产生速度快且蕴含的知识具有较强时效性等特点, 因而发展支持实时处理应用的流计算技术对于信息系统的知识管理十分重要. 流计算系统可以追溯到29世纪90年代, 至今已经经历了长足的发展. 然而, 当前多样化的知识管理需求和新一代的硬件架构为流计算系统带来了全新的挑战和机遇, 催生出了一系列流计算领域的技术研究. 首先介绍流计算系统的基本需求以及发展脉络, 再按照编程接口、执行计划、资源调度和故障容错4个层次分别分析流计算系统领域的相关技术; 最后, 展望流计算技术在未来可能的研究方向和发展趋势. |
| 关键词: 实时处理 流计算 数据处理系统 |
| DOI：10.13328/j.cnki.jos.006917 |
| 分类号: |
| 基金项目:国家自然科学基金(61902128); 广西可信软件重点实验室研究课题 |
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| Research Progress on Key Technologies Towards Real-time Stream Processing Applications |
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XU Zhi-Zhen1,2, XU Chen1,2,3, DING Guang-Yao1,2, CHEN Zi-Hao1,2, ZHOU Ao-Ying1,2
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1.School of Data Science and Engineering, East China Normal University, Shanghai 200062, China;2.Shanghai Engineering Research Center of Big Data Management, Shanghai 200062, China;3.Guangxi Key Laboratory of Trusted Software (Guilin University of Electronic Technology), Guilin 541004, China
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| Abstract: |
| In order to perform knowledge mining and management, information systems need to process various forms of data, including stream data. Stream data have the characteristics of large data scale, fast generation speed, and strong timeliness of the knowledge contained in them. Therefore, it is very important for knowledge management of information systems to develop stream processing technology that supports real-time stream processing applications. Stream processing systems (SPSs) can be traced back to the 1990s, and they have undergone significant development since then. However, current diverse knowledge management needs and the new generation of hardware architectures have brought new challenges and opportunities for SPSs, and a series of technical research on stream processing ensues. This study introduces the basic requirements and development history of SPSs and then analyzes relevant technologies in the SPS field in terms of four aspects: programming interface, execution plan, resource scheduling, and fault tolerance. Finally, this study predicts the research directions and development trends of stream processing technology in the future. |
| Key words: real-time processing stream processing data processing system |
