Generating efficient plans for queries using views

Afrati, FN; Li, C; Ullman, JD

dc.contributor.author	Afrati, FN	en
dc.contributor.author	Li, C	en
dc.contributor.author	Ullman, JD	en
dc.date.accessioned	2014-03-01T02:41:53Z
dc.date.available	2014-03-01T02:41:53Z
dc.date.issued	2001	en
dc.identifier.issn	0163-5808	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30653
dc.subject	Cost Model	en
dc.subject	Efficient Algorithm	en
dc.subject	Query Optimization	en
dc.subject	Search Space	en
dc.subject	Closed World Assumption	en
dc.subject	Open World Assumption	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.title	Generating efficient plans for queries using views	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/376284.375705	en
heal.identifier.secondary	http://dx.doi.org/10.1145/376284.375705	en
heal.language	English	en
heal.publicationDate	2001	en
heal.abstract	We study the problem of generating efficient, equivalent rewritings using views to compute the answer to a query. We take the closed-world assumption, in which views are materialized from base relations, rather than views describing sources in terms of abstract predicates, as is common when the open-world assumption is used. In the closed-world model, there can be an infinite number of different rewritings that compute the same answer, yet have quite different performance. Query optimizers take a logical plan (a rewriting of the query) as an input, and generate efficient physical plans to compute the answer. Thus our goal is to generate a small subset of the possible logical plans without missing an optimal physical plan. We first consider a cost model that counts the number of subgoals in a physical plan, and show a search space that is guaranteed to include an optimal rewriting, if the query has a rewriting in terms of the views. We also develop an efficient algorithm for finding rewritings with the mi nimum number of subgoals. We then consider a cost model that counts the sizes of intermediate relations of a physical plan, without dropping any attributes, and give a search space for finding optimal rewritings. Our final cost model allows attributes to be dropped in intermediate relations. We show that, by careful variable renaming, it is possible to do better than the standard ""supplementary relation"" approach, by dropping attributes that the latter approach would retain. Experiments show that our algorithm of generating optimal rewritings has good efficiency and scalability.	en
heal.publisher	ASSOC COMPUTING MACHINERY	en
heal.journalName	Proceedings of the ACM SIGMOD International Conference on Management of Data	en
dc.identifier.doi	10.1145/376284.375705	en
dc.identifier.isi	ISI:000168887300029	en
dc.identifier.volume	30	en
dc.identifier.issue	2	en
dc.identifier.spage	319	en
dc.identifier.epage	330	en