基于流处理引擎和数据库集成的流数据管理

H. Kitagawa, Y. Watanabe
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引用次数: 2

摘要

网络和传感器设备技术的发展使我们能够轻松获取现实世界的信息,如移动物体的位置、天气信息、新闻和股票价格。这些数据是连续提供的,它们被视为数据流。由于流数据量的急剧增加,流数据的管理和利用变得越来越重要。本文介绍了一个名为Harmonica的数据流管理系统。Harmonica采用了一种将流处理引擎(名为stream-spinner)和关系dbms结合在一起的体系结构。基于该体系结构,系统既可以处理连续查询,也可以处理传统的单次查询。此外,Harmonica支持流数据的持续持久性需求,以及数据流上的查询,包括选择、连接、投影和用户定义函数。用户还可以指定集成流数据和存储在数据库中的持久数据的连续查询。使用Harmonica API,用户可以开发各种应用程序来应对不同的连续蒸数据和存储在数据库中的数据。该系统可以部署在网络环境中,实现高效、可靠的分布式流处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stream Data Management Based on Integration of a Stream Processing Engine and Databases
Developments in network and sensor device technologies enable us to easily obtain real-world information, such as locations of moving objects, weather information, news, and stock prices. These data are continuously supplied, and they are regarded as data streams. Because of the dramatical increase of streaming data, their management and utilization has become more and more important. This paper describes a data stream management system named Harmonica. Harmonica employs an architecture combining our stream processing engine named stream-spinner and relational DBMSs. Based on the architecture, the system processes both continuous queries and traditional one-shot queries. Moreover, Harmonica supports continuous persistence requirements for streaming data as well as queries including selection, join, projection, and user-defined functions over data streams. Users can also specify continuous queries that integrate streaming data and persistent data stored in databases. Using the Harmonica API, users can develop a variety of applications coping with different continuous steaming data and data stored in databases. Our system can be deployed in network environments to achieve efficient and dependable distributed stream processing.
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