Data Stream Management Systems

Sandra Geisler
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引用次数: 15

Abstract

In many application fields, such as production lines or stock analysis, it is substantial to create and process high amounts of data at high rates. Such continuous data flows with unknown size and end are also called data streams. The processing and analysis of data streams are a challenge for common data management systems as they have to operate and deliver results in real time. Data Stream Management Systems (DSMS), as an advancement of database management systems, have been implemented to deal with these issues. DSMS have to adapt to the notion of data streams on various levels, such as query languages, processing or optimization. In this chapter we give an overview of the basics of data streams, architecture principles of DSMS and the used query languages. Furthermore, we specifically detail data quality aspects in DSMS as these play an important role for various applications based on data streams. Finally, the chapter also includes a list of research and commercial DSMS and their key properties.
数据流管理系统
在许多应用领域中,例如生产线或库存分析,以高速率创建和处理大量数据是非常重要的。这种大小和终点未知的连续数据流也称为数据流。数据流的处理和分析对普通数据管理系统来说是一个挑战,因为它们必须实时操作和交付结果。数据流管理系统(Data Stream Management system, DSMS)作为数据库管理系统的一种进步,已经被用于解决这些问题。DSMS必须适应不同层次的数据流概念,例如查询语言、处理或优化。在这一章中,我们概述了数据流的基础,DSMS的架构原则和使用的查询语言。此外,我们特别详细介绍了DSMS中的数据质量方面,因为这些方面在基于数据流的各种应用中起着重要作用。最后,本章还列出了研究和商业DSMS及其关键特性。
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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