Multiple-View Self-Maintenance in Data Warehousing Environments.

@inproceedings{DBLP:conf/vldb/Huyn97,
  author    = {Nam Huyn},
  editor    = {Matthias Jarke and
               Michael J. Carey and
               Klaus R. Dittrich and
               Frederick H. Lochovsky and
               Pericles Loucopoulos and
               Manfred A. Jeusfeld},
  title     = {Multiple-View Self-Maintenance in Data Warehousing Environments},
  booktitle = {VLDB'97, Proceedings of 23rd International Conference on Very
               Large Data Bases, August 25-29, 1997, Athens, Greece},
  publisher = {Morgan Kaufmann},
  year      = {1997},
  isbn      = {1-55860-470-7},
  pages     = {26-35},
  ee        = {db/conf/vldb/Huyn97.html},
  crossref  = {DBLP:conf/vldb/97},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

A data warehouse materializes views derived from data that may not reside at the warehouse. Maintaining these views efficiently in response to base updates is difficult, 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.

We 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.

Copyright © 1997 by the VLDB Endowment. 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 the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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