物理独立流合并

B. Chandramouli, D. Maier, J. Goldstein
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引用次数: 1

摘要

用于合并等效数据流的工具可以支持数据流管理系统(DSMS)中的多种功能,例如查询计划切换和高可用性。可以从逻辑上将数据流视为事件的时态表,每个事件都与一个生命周期(时间间隔)相关联,在此期间事件将贡献输出。在许多应用中,“相同”的逻辑流可以在物理上以多种物理形式呈现自己,例如,由于传输中产生的混乱或来自多个源的组合,以及先前事件的修改。当这些流在时间、顺序和组成上可能存在物理差异时,正确合并这些流是具有挑战性的。本文介绍了一种新的流操作符,称为逻辑合并(LMerge),它将多个逻辑上一致的流作为输入,并输出与所有流兼容的单个流。LMerge可以处理输入流的动态附加和分离。我们提出了一系列LMerge算法,这些算法可以利用编译时流属性来提高效率。Stream Insight(一款商业数据管理系统)的实验表明,LMerge有时比在输入上强制执行确定性要高效几个数量级,而且当流可变性有限时,使用专门的算法是有好处的。我们还展示了LMerge及其扩展可以在几个实际应用程序中提供性能优势。
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Physically Independent Stream Merging
A facility for merging equivalent data streams can support multiple capabilities in a data stream management system (DSMS), such as query-plan switching and high availability. One can logically view a data stream as a temporal table of events, each associated with a lifetime (time interval) over which the event contributes to output. In many applications, the "same" logical stream may present itself physically in multiple physical forms, for example, due to disorder arising in transmission or from combining multiple sources, and modifications of earlier events. Merging such streams correctly is challenging when the streams may differ physically in timing, order, and composition. This paper introduces a new stream operator called Logical Merge (LMerge) that takes multiple logically consistent streams as input and outputs a single stream that is compatible with all of them. LMerge can handle the dynamic attachment and detachment of input streams. We present a range of algorithms for LMerge that can exploit compile-time stream properties for efficiency. Experiments with Stream Insight, a commercial DSMS, show that LMerge is sometimes orders-of-magnitude more efficient than enforcing determinism on inputs, and that there is benefit to using specialized algorithms when stream variability is limited. We also show that LMerge and its extensions can provide performance benefits in several real-world applications.
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