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Scheduling for shared window joins over data streams

机译:共享窗口的计划加入数据流

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Continuous Query (CQ) systems typically exploit commonality among query expressions to achieve improved efficiency through shared processing. Recently proposed CQ systems have introduced window specifications in order to support unbounded data streams. There has been, however, little investigation of sharing for windowed query operators. In this paper, we address the shared execution of windowed joins, a core operator for CQ systems. We show that the strategy used in systems to date has a previously unreported performance flaw that can negatively impact queries with relatively small windows. We then propose two new execution strategies for shared joins. We evaluate the alternatives using both analytical models and implementation in a DBMS. The results show that one strategy, called MQT, provides the best performance over a range of workload settings.
机译:连续查询(CQ)系统通常通过共享处理来实现查询表达式中的共性,以实现提高的效率。最近提出的CQ系统推出了窗口规范,以支持无限的数据流。但是,已经很少调查窗口查询运营商的共享。在本文中,我们解决了CQ系统的核心运算符的窗口连接的共享执行。我们表明,系统中使用的策略有一个以前未报告的性能缺陷,可以使用相对较小的窗口对查询产生负面影响。然后,我们为共享加入提出了两个新的执行策略。我们在DBMS中使用分析模型和实现评估替代方案。结果表明,一种策略称为MQT,提供了一系列工作负载设置的最佳性能。

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