Abstract
Query optimization that involves expensive predicates have received considerable attention in the database community. Typically, the output to a database query is a set of tuples that satisfy certain conditions, and, with expensive predicates, these conditions may be computationally costly to verify. In the simplest case, when the query looks for the set of tuples that simultaneously satisfy k expensive predicates, the problem reduces to ordering the evaluation of the predicates so as to minimize the time to output the set of tuples comprising the answer to the query.
Here, we give a simple and fast deterministic k-approximation algorithm for this problem, and prove that k is the best possible approximation ratio for a deterministic algorithm, even if exponential time algorithms are allowed. We also propose a randomized, polynomial time algorithm with expected approximation ratio \(1+\sqrt{2}/2\approx1.707\) for k=2, and prove that 3/2 is the best possible expected approximation ratio for randomized algorithms.
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Laber, S., Carmo, R., Kohayakawa, Y. (2004). Querying Priced Information in Databases: The Conjunctive Case. In: Farach-Colton, M. (eds) LATIN 2004: Theoretical Informatics. LATIN 2004. Lecture Notes in Computer Science, vol 2976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24698-5_5
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DOI: https://doi.org/10.1007/978-3-540-24698-5_5
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