复杂查询解相关

P. Seshadri, H. Pirahesh, T. Leung
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引用次数: 154

摘要

决策支持应用程序中使用的复杂查询使用多个相关子查询和表表达式,可能跨越多个嵌套层。直接执行相关查询通常效率低下;因此,提出了去关联查询的算法,即通过重写查询来消除相关性。本文阐述了去相关中涉及的问题,并对现有算法进行了综述。提出了一种高效、灵活的魔法去关联算法,该算法在应用的通用性和重写查询的效率方面都优于现有算法。介绍了该算法在Starburst可扩展数据库系统中的实现情况,并与其他去相关技术进行了性能比较。本文还解释了为什么魔术解关联不仅适用,而且在并行数据库系统中至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complex query decorrelation
Complex queries used in decision support applications use multiple correlated subqueries and table expressions, possibly across several levels of nesting. It is usually inefficient to directly execute a correlated query; consequently, algorithms have been proposed to decorrelate the query, i.e. to eliminate the correlation by rewriting the query. This paper explains the issues involved in decorrelation, and surveys existing algorithms. It presents an efficient and flexible algorithm called magic decorrelation which is superior to existing algorithms both in terms of the generality of application, and the efficiency of the rewritten query. The algorithm is described in the context of its implementation in the Starburst Extensible Database System, and its performance is compared with other decorrelation techniques. The paper also explains why magic decorrelation is not merely applicable, but crucial in a parallel database system.
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