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Multiple-View Self-Maintenance in Data Warehousing Environments

Huyn, N. (1997) Multiple-View Self-Maintenance in Data Warehousing Environments. In: 23rd International Conference on Very Large Data Bases (VLDB 1997), August 25-29, 1997, Athens, Greece.

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Abstract

A data warehouse materializes views derived from data that may not reside at the warehouse. Maintaining these views effciently in response to base updates is diffcult, since it may involve querying external sources where the base data reside. This paper considers the problem of view self-maintenance, where the views are maintained without using all the base data. Without full use of the base data, however, maintaining a view unambiguously is not always possible. Thus, the two critical questions that must be addressed are to determine, in a given situation, whether a view is maintainable, and how to maintain it. W e provide algorithms that answer these questions for a general class of views, and for an important subclass, generate SQL queries that test whether a view is self-maintainable and update the view if it is. We improve significantly on previous work by solving the view self-maintenance problem in the presence of multiple views, with optional access to a subset of the base data, and under arbitrary mixes of insertions and deletions. We provide better insight into the problem by showing that view self-maintainability can be reduced to the problem of deciding query containment. Work supported by ARO grant DAAH04{95{1{0192. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 23rd VLDB Athens, Greece, 1997

Item Type:Conference or Workshop Item (Paper)
Subjects:Computer Science > Data Warehousing
Projects:Information Integration
Related URLs:Project Homepagehttp://infolab.stanford.edu/serf/
ID Code:239
Deposited By:Import Account
Deposited On:25 Feb 2000 16:00
Last Modified:01 Jan 2009 12:03

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