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@inproceedings{DBLP:conf/dasfaa/ZhangY99,
author = {Chuan Zhang and
Jian Yang},
editor = {Arbee L. P. Chen and
Frederick H. Lochovsky},
title = {Materialized View Evolution Support in Data Warehouse Environment},
booktitle = {Database Systems for Advanced Applications, Proceedings of the
Sixth International Conference on Database Systems for Advanced
Applications (DASFAA), April 19-21, Hsinchu, Taiwan},
publisher = {IEEE Computer Society},
year = {1999},
isbn = {0-7695-0084-6},
pages = {247-254},
ee = {db/conf/dasfaa/ZhangY99.html},
crossref = {DBLP:conf/dasfaa/99},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
As a sufficiently abstract level, the data in the data warehouse can be seen as a set of materialized views, where the base data resides at the information sources. These materialized views are designed based on the users requirements (e.g., frequently asked queries). However Data Warehouse is a dynamic environment, i.e., when user query requirement changes, the existing materialized views should evolve to meet the new requirement. These changes will demand schema changes at the warehouse and should be handled with as little disruption or modification to other components of the warehousing system as possible.
In this paper, we proposed a framework to determine if the existing materialized views will be affected by the requirement changes, and how they are affected. Algorithms are proposed to deal with the situation when a new query is added in. The aim of the algorithms are to efficiently get the new materialized views by analysing the relationships among queries using MVPP (a specification for query processing plan).
Copyright © 1999 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.