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Reducing the Size of Auxiliary Data Needed to Support Materialized View Maintenance in a Data Warehouse Environment
Abstract
A data warehouse consists of a set of materialized views that contain derived data from several data sources. Materialized views are beneficial because they allow efficient re-trieval of summary data. However, materialized views need to be refreshed periodically in order to avoid staleness. During a materialized view refresh, only changes to the base tables are transmitted from the data sources to the data warehouse, where the data ware-house should contain the data from the base tables that is relevant to the refresh. In this paper we explore how this additional data, which is commonly referred to as auxiliary views, can be reduced in size. Novel algorithms that exploit non-trivial integrity con-straints and that can handle materialized views defined over queries with grouping and aggregation are presented in the paper.
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