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Optimal Genetic View Selection Algorithm for Data Warehouse

机译:数据仓库的最优遗传视图选择算法

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摘要

To efficiently solve the materialized view selection problem, an optimal genetic algorithm of how to select a set of views to be materialized is proposed so as to achieve both good query performance and low view maintenance cost under a storage space constraint. First, a pre-processing algorithm based on the maximum benefit per unit space is used to generate initial solutions. Then, the initial solutions are improved by the genetic algorithm having the mixture of optimal strategies. Furthermore, the generated infeasible solutions during the evolution process are repaired by loss function. The experimental results show that the proposed algorithm outperforms the heuristic algorithm and canonical genetic algorithm in finding optimal solutions.
机译:为了有效地解决物化视图选择问题,提出了一种如何选择一组待实现的视图的最优遗传算法,以在存储空间受限的情况下实现良好的查询性能和较低的视图维护成本。首先,基于每单位空间最大收益的预处理算法用于生成初始解。然后,通过混合最优策略的遗传算法对初始解进行改进。此外,通过损失函数来修复在演化过程中生成的不可行解。实验结果表明,该算法在寻找最优解方面优于启发式算法和规范遗传算法。

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