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Implementation of the CoreCover Algorithm Chen Li ([email protected]) Generating Efficient Plans for Queries Using Views. Foto Afrati, Chen Li, and Jeff Ullman. In the Proc. of the 30th ACM SIGMOD Conference, Santa Barbara, CA, May, 2001 Experiments: 1. Probability of having rewritings: - random (small) - chain (small) - star (large) --> time consuming o no variables dropped o 1 variable dropped o 2 variables dropped Choose small number of query/view subgoals to make sure there is a rewriting. Setting: relationNum = 6; // # of relations relAttrNum = 3; // # of rel attrs querySubgoalNum = 6; // # of subgoals in a query viewSubgoalNum = 2; // # of subgoals in a view dropHeadArgNum = 0; // # of args dropped a head queryArgDomSize = 5; // size of arg domain in a query simQueryNum = 10; // # of queries Files: - prob-random.data: random - prob-chain.data: chain // all vars are distinguished - prob-star.data: star The files with a ".conf" extension has more detailed info. 2. number/time of GMRs, chain queries (also comment on other queries): 3. Effects of shrinking views and view tuples, star queries (also comment on other queries): - # of views; - # of view tuples Increase the number of query/view subgoals to show the scalability.
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CoreCover algorithm as described in our ALU01 SIGMOD paper: Generating Efficient Plans for Queries Using Views. Foto Afrati, Chen Li, and Jeff Ullman. SIGMOD 2001
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