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ABSTRACT
In a previous paper we proposed a novel method for generating alternative query plans that uses chasing (and back-chasing) with logical constraints. The method brings together use of indexes, use of materialized views, semantic optimization and join elimination (minimization). Each of these techniques is known separately to be beneficial to query optimization. The novelty of our approach is in allowing these techniques to interact systematically, eg. non-trivial use of indexes and materialized views may be enabled only by semantic constraints.
We have implemented our method for a variety of schemas and queries. We examine how far we can push the method in term of complexity of both schemas and queries. We propose a technique for reducing the size of the search space by “stratifying” the sets of constraints used in the (back)chase. The experimental results demonstrate that our method is practical (i.e., feasible and worthwhile).
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 10
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Yi Chen , Susan Davidson , Carmem Hara , Yifeng Zheng, RRXS: redundancy reducing XML storage in relations, Proceedings of the 29th international conference on Very large data bases, p.189-200, September 09-12, 2003, Berlin, Germany
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