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by Amy J. Lee, Andreas Koeller, Anisoara Nica, Elke A. Rundensteiner
In International Database Conference, Hong Kong
http://www.eecs.umich.edu/~anica/papers/IDC99-submit.ps
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Abstract:
Previous work in query rewriting has made the restricting assumption that the rewritten query must be equivalent to the initially given query. We now propose to relax this assumption to allow for query rewriting in situations where equivalent rewritings may not exist-- yet alternate not necessarily equivalent query rewritings may still be preferable to users over not receiving any answers at all. In this paper, we apply this concept of non-equivalent query rewriting to the problem of maintaining view definitions (data warehouses), where it now allows us to handle a much larger class of changes of the underlying information sources, namely not only data but also schema changes. This relaxed query notion allows for more diversity in acceptable query answers, but also raises a new issue of the evaluation of such queries. For this purpose, we introduce an analytical model of query rewritings that incorporates measures of information preservation (quality) of a query in addition to the commonly studied measures of view maintenance performance (query cost). Quality is modeled as a function of the divergence from the intended view extent, both in terms of the preservation of the information amount and the information type. Both quality and cost are integrated into one uniform model, called the Quality-CostModel or QC-Model, to allow for a trade-off among these two measures. This model can be used to compare two alternate (even if not equivalent) rewritings, and thus to automatically select a good view maintenance solution from among numerous non-equivalent rewritings. We also report on an experimental evaluation of our
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