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Querying Priced Information in Databases: The Conjunctive Case

Extended Abstract
  • Sany Laber
  • Renato Carmo
  • Yoshiharu Kohayakawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2976)

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.

Keywords

Minimum Cover Deterministic Algorithm Complete Bipartite Graph Query Optimization Conjunctive Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Sany Laber
    • 1
  • Renato Carmo
    • 2
    • 3
  • Yoshiharu Kohayakawa
    • 2
  1. 1.Departamento de Informática da PontifíciaUniversidade Católica do Rio de JaneiroRio de JaneiroBrazil
  2. 2.Instituto de Matemática e Estatística daUniversidade de São Paulo Rua do MatãoSão PauloBrazil
  3. 3.Departamento de Informática daUniversidade Federal do Paraná Centro Politécnico da UFPRCuritibaBrazil

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