Data mining-based materialized view and index selection in data warehouses
Data mining-based materialized view and index selection in data warehouses
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DOI：
10.1007/s10844-009-0080-0
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发表时间：
2009-08-01
影响因子：
3.4
通讯作者：
Darmont, Jerome
中科院分区：
文献类型：
--
作者：
Aouiche, Kamel;Darmont, Jerome
物化视图和索引是用于加速数据访问的物理结构，在数据仓库中偶尔使用。然而，这些数据结构会产生一些维护开销。它们也共享相同的存储空间。现有的关于物化视图和索引选择的研究大多是分别考虑这两种结构。本文采取相反的立场，将物化视图和索引选择结合起来，考虑视图和索引的交互，实现高效的存储空间共享。通过数据挖掘过程选择候选物化视图和索引。我们还利用成本模型，评估索引和视图物化各自的好处，并帮助选择一个相关的配置的索引和物化视图之间的候选人。实验结果表明，我们的策略性能优于独立选择物化视图和索引。
Materialized views and indexes are physical structures for accelerating data access that are casually used in data warehouses. However, these data structures generate some maintenance overhead. They also share the same storage space. Most existing studies about materialized view and index selection consider these structures separately. In this paper, we adopt the opposite stance and couple materialized view and index selection to take view-index interactions into account and achieve efficient storage space sharing. Candidate materialized views and indexes are selected through a data mining process. We also exploit cost models that evaluate the respective benefit of indexing and view materialization, and help select a relevant configuration of indexes and materialized views among the candidates. Experimental results show that our strategy performs better than an independent selection of materialized views and indexes.