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Expiring Data in a Warehouse |
Full Paper (PDF)
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Data warehouses collect data into materialized views for analysis.
After some time, some of the data may no longer be needed or may not be ofinterest.
In this paper, we handle this by expiring or removing unneeded materialized view tuples.
A framework supporting such expiration is presented.
Within it, a user or administrator can declaratively request expirations and can specify what type of modifications are expected from external sources.
The latter can significantly increase the amount of data that can be expired.
We present efficient algorithms for determining what data can be expired (data not needed for maintenance of other views), taking into account the types of updates that may occur.
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References, where available, link to the DBLP on the World Wide Web.
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@inproceedings{DBLP:conf/vldb/Garcia-MolinaLY98,
author = {Hector Garcia-Molina and
Wilburt Labio and
Jun Yang},
editor = {Ashish Gupta and
Oded Shmueli and
Jennifer Widom},
title = {Expiring Data in a Warehouse},
booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
Large Data Bases, August 24-27, 1998, New York City, New York,
USA},
publisher = {Morgan Kaufmann},
year = {1998},
isbn = {1-55860-566-5},
pages = {500-511},
crossref = {DBLP:conf/vldb/98},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
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DBLP: Copyright ©1999 by Michael Ley (ley@uni-trier.de).
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