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An Ant Colony based algorithm for optimal selection of Materialized view

机译:基于蚁群的物化视图最优选择算法

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The problem of Materialized view selection is one key issue in improving response time of complex queries in data warehouse. In this paper we proposed an Ant Colony based algorithm which is efficient compared with Genetic Algorithm (GA), a popular algorithm for materialized view selection. Given space limitation, our algorithm could minimize total query cost as much as possible. Based on evaporation mechanism and positive feedback of Ant Colony Algorithm, our approach could achieve sub-optimal selection in global search area. Experimental results show that our algorithm is much more efficient than GA algorithm with varying space limitations.
机译:物化视图选择问题是改善数据仓库中复杂查询响应时间的关键问题之一。在本文中,我们提出了一种基于蚁群的算法,该算法与流行的用于物化视图选择的遗传算法(GA)相比,效率更高。给定空间限制,我们的算法可以最大程度地降低总查询成本。基于蒸发机制和蚁群算法的正反馈,我们的方法可以实现全局搜索区域的次优选择。实验结果表明,在空间受限的情况下,我们的算法比遗传算法更有效。

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