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Selection of Bitmap Join Index: Approach Based on Minimal Transversals

机译:位图连接索引的选择:基于最小横向的方法

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Decision systems handle a large volume of data usually stored in a data warehouse. The latter is modeled by a star schema that typically has a central fact table and a set of dimension tables. The queries corresponding to this type of model are very complex. In order to reduce the cost of running these queries, one common solution would be to ensure a good physical design of data warehouses. In this respect, the binary join indexes (BJI) are very suitable for reducing the cost of running these joins. In this paper, we introduce a BJI selection approach based on a key notion of the theory of hypergraphs, namely minimal transversal. The final configuration obtained is composed of several indexes that optimize the cost of executing of the set of queries. The carried out experiments prove the relevance of our approach versus those of the literature.
机译:决策系统处理通常存储在数据仓库中的大量数据。后者由星型模式建模,该星型模式通常具有中央事实表和一组维度表。与此类型的模型相对应的查询非常复杂。为了降低运行这些查询的成本,一种常见的解决方案是确保数据仓库的物理设计良好。在这方面,二进制联接索引(BJI)非常适合降低运行这些联接的成本。在本文中,我们介绍了一种基于超图理论的关键概念(即最小横向)的BJI选择方法。获得的最终配置由几个索引组成,这些索引优化了查询集的执行成本。进行的实验证明了我们的方法与文献的相关性。

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