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Materialised view construction in data warehouse for decision making

机译:数据仓库中用于实例化的物化视图构建

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摘要

A data warehouse contains historical and summarised data that grows, almost, exponentially with time. It provides a uniform platform for posing decision support queries. These queries are usually analytical and complex in nature and, when processed against a large data warehouse, consume a lot of processing time resulting in an increased query response time. This time can be reduced by using materialised views, which pre-compute the most frequently accessed information and stores them in a data warehouse. In this paper, an algorithm to construct materialised views using previously posed, optimal, user queries on the data warehouse, is proposed. This algorithm defines a heuristic that maximally merges the optimal queries to construct a single materialised view. These materialised views are capable of providing meaningful information for a given future query. Further, experiments are performed to evaluate the effectiveness of the materialised views with respect to the query response time. The experimental results show that materialised views so constructed are capable of answering future user queries in a reduced response time. This would enable effective and efficient decision-making.
机译:数据仓库包含历史数据和摘要数据,这些数据几乎随时间呈指数增长。它提供了一个统一的平台来提出决策支持查询。这些查询通常是分析性的,本质上很复杂,并且在针对大型数据仓库进行处理时,会消耗大量的处理时间,从而导致查询响应时间增加。可以通过使用物化视图来减少此时间,该物化视图可预先计算最常访问的信息并将其存储在数据仓库中。本文提出了一种在数据仓库上使用先前提出的最佳用户查询构造物化视图的算法。该算法定义了一种试探法,该试探法可最大程度地合并最佳查询以构建单个实例化视图。这些物化视图能够为给定的将来查询提供有意义的信息。此外,进行实验以评估物化视图相对于查询响应时间的有效性。实验结果表明,如此构造的物化视图能够在减少的响应时间内回答未来的用户查询。这将使有效和高效的决策成为可能。

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