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Using state modules for adaptive query processing

机译:使用状态模块进行自适应查询处理

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We present a query architecture in which join operators are decomposed into their constituent data structures (State Modules, or SteMs), and dataflow among these SteMs is managed adaptively by an eddy routing operator [R. Avnur et al., (2000)]. Breaking the encapsulation of joins serves two purposes. First, it allows the eddy to observe multiple physical operations embedded in a join algorithm, allowing for better calibration and control of these operations. Second, the SteM on a relation serves as a shared materialization point, enabling multiple competing access methods to share results, which can be leveraged by multiple competing join algorithms. Our architecture extends prior work significantly, allowing continuously adaptive decisions for most major aspects of traditional query optimization: choice of access methods and join algorithms, ordering of operators, and choice of a query spanning tree. SteMs introduce significant routing flexibility to the eddy, enabling more opportunities for adaptation, but also introducing the possibility of incorrect query results. We present constraints on eddy routing through SteMs that ensure correctness while preserving a great deal of flexibility. We also demonstrate the benefits of our architecture via experiments in the Telegraph dataflow system. We show that even a simple routing policy allows significant flexibility in adaptation, including novel effects like automatic "hybridization " of multiple algorithms for a single join.
机译:我们提出了一种查询体系结构,其中联接运算符被分解成它们的组成数据结构(状态模块或SteM),并且这些SteM之间的数据流由涡流路由运算符[R. Avnur et al。,(2000)]。打破联接的封装有两个目的。首先,它允许涡流观察连接算法中嵌入的多个物理操作,从而可以更好地校准和控制这些操作。其次,关系上的SteM充当共享的实现点,使多种竞争性访问方法可以共享结果,而这些结果可以被多种竞争性连接算法所利用。我们的体系结构极大地扩展了以前的工作,允许对传统查询优化的大多数主要方面进行连续的自适应决策:访问方法和联接算法的选择,运算符的排序以及查询生成树的选择。 SteM为涡流引入了显着的路由灵活性,从而为适应提供了更多机会,同时也引入了错误查询结果的可能性。我们提出了对通过SteM进行涡流路由的约束,这些约束在确保准确性的同时还保留了很大的灵活性。我们还通过在Telegraph数据流系统中进行的实验来证明我们的体系结构的好处。我们显示,即使是简单的路由策略,也可以在自适应方面具有显着的灵活性,包括新颖的效果,例如针对单个连接的多个算法的自动“杂交”。

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