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- W1523544086 abstract "Materialized summary tables and cached query results are frequently used for the optimization of aggregate queries in a data warehouse. Query rewriting techniques are incorporated into database systems to use those materialized views and thus avoid accessing the possibly huge raw data. A rewriting is only possible if the query is derivable from these views. Several approaches can be found in the literature to check the derivability and find query rewritings. However, most algorithms either find rewritings only in very restricted cases or in complex cases which rarely occur in data warehouse environments. The specific application scenario of a data warehouse with its multidimensional perspective allows the consideration of much more semantic information, e.g. structural dependencies within the dimension hierarchies and different characteristics of measures. The motivation of this article is to use this information to present simple conditions for derivability in a large number of relevant cases which go beyond previous approaches.KeywordsData WarehouseCategory AttributeData CubeFact TableQuery PlanThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1523544086 date "2001-01-01" @default.
- W1523544086 modified "2023-09-27" @default.
- W1523544086 title "Using Semantics for Query Derivability in Data Warehouse Applications" @default.
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- W1523544086 doi "https://doi.org/10.1007/978-3-7908-1834-5_1" @default.
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