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Semantic query optimization for tree and chain queries

机译:树和链查询的语义查询优化

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摘要

Semantic query optimization, or knowledge-based query optimization, has received increasing interest in recent years. The authors provide an effective and systematic approach to optimizing queries by appropriately choosing semantically equivalent transformations. Basically, there are two different types of transformations: transformations by eliminating unnecessary joins, and transformations by adding/eliminating redundant beneficialonbeneficial selection operations (restrictions). A necessary and sufficient condition to eliminate a single unnecessary join is provided. We prove that it is /spl Nscr//spl Pscr/-/spl Cscr/omplete to eliminate as many unnecessary joins as possible for various types of acyclic queries with the exception of the closure chain queries whose query graphs are chains and all equi-join attributes are distinct. An algorithm is provided to minimize the number of joins in tree queries. This algorithm has an important property that, when applied to a closure chain query, it will yield an optimal solution with the time complexity O(n*m), where n is the number of relations referenced in the chain query, and m is the time complexity of a restriction closure computation.
机译:近年来,语义查询优化或基于知识的查询优化受到越来越多的关注。作者提供了一种有效且系统的方法,通过适当选择语义上等效的转换来优化查询。基本上,有两种不同类型的转换:通过消除不必要的联接进行转换,以及通过添加/消除冗余的有益/非有益选择操作(限制)进行转换。提供消除单个不必要连接的必要和充分条件。我们证明/ spl Nscr // spl Pscr /-/ spl Cscr / omplete可以消除各种类型的非循环查询的尽可能多的不必要联接,但闭包链查询的查询图是链且所有等价的除外。连接属性是不同的。提供了一种算法来最小化树查询中的联接数。该算法具有重要的性质,当应用于闭环查询时,它将产生时间复杂度为O(n * m)的最优解,其中n是链查询中引用的关系数,m是限制关闭计算的时间复杂度。

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