Semantic query optimization in datalog programs

Alon Y. Levy*, Yehoshua Sagiv

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

34 Scopus citations

Abstract

Semantic query optimization refers to the process of using integrity constraints (ic's) in order to optimize the evaluation of queries. The process is well understood in the case of unions of select-project-join queries (i.e., nonrecursive datalog). For arbitrary datalog programs, however, the issue has largely remained an unsolved problem. This paper studies this problem and shows when semantic query optimization can be completely done in recursive rules provided that order constraints and negated EDB subgoals appear only in the recursive rules, but not in the ic's. If either order constraints or negated EDB subgoals are introduced in ic's, then the problem of semantic query optimization becomes undecidable. Since semantic query optimization is closely related to the containment problem of a datalog program in a union of conjunctive queries, our results also imply new decidability and undecidability results for that problem when order constraints and negated EDB subgoals are used.

Original languageEnglish
Pages163-173
Number of pages11
StatePublished - 1995
Externally publishedYes
EventProceedings of the 14th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems - San Jose, CA, USA
Duration: 22 May 199525 May 1995

Conference

ConferenceProceedings of the 14th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems
CitySan Jose, CA, USA
Period22/05/9525/05/95

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