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The Complexity of Transformation-Based Join Enumeration

机译:基于转换的联接枚举的复杂性

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Query optimizers that explore a search space exhaustively using transformation rules usually apply all possible rules on each alternative, and stop when no new information is produced. A memoizing structure was proposed in [McK93] to improve the re-use of common subexpression, thus improving the efficiency of the search considerably. However, a question that remained open is, what is the complexity of the transformation-based enumeration process? In particular, with n the number of relations, does it achieve the O(3~n) lower bound established by [OL90]?rnIn this paper we examine the problem of duplicates, in transformation-based enumeration. In general, different sequences of transformation rules may end up deriving the same element, and the optimizer must detect and discard these duplicate elements generated by multiple paths. We show that the usual commutativity/associativity rules for joins generate O(4~n) duplicate opera-rntors. We then propose a scheme-within the generic transformation-based framework- to avoid the generation of duplicates, which does achieve the O(3~n) lower bound on join enumeration. Our experiments show an improvement of up to a factor of 5 in the optimization of a query with 8 tables, when duplicates are avoided rather than detected.
机译:使用转换规则详尽地探索搜索空间的查询优化器通常将所有可能的规则应用于每个替代项,并在没有新信息产生时停止。 [McK93]中提出了一种记忆结构,以改善通用子表达式的重用,从而大大提高了搜索效率。但是,仍然存在一个问题,即基于转换的枚举过程的复杂性是什么?特别是,在n个关系的情况下,它是否达到了[OL90]确定的O(3〜n)下界?在本文中,我们研究了基于变换的枚举中的重复项问题。通常,转换规则的不同序列最终可能派生相同的元素,优化器必须检测并丢弃由多个路径生成的这些重复元素。我们表明,通常的联接可交换性/缔合性规则会生成O(4〜n)个重复算子。然后,我们在基于通用转换的框架内提出了一种避免重复的方案,该方案确实实现了连接枚举的O(3〜n)下界。我们的实验表明,在避免重复而不是检测到重复的情况下,对具有8个表的查询的优化最多可提高5倍。

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