Bounded conjunctive queries

Abstract

A query Q is said to be effectively bounded if for all datasets D , there exists a subset D Q of D such that Q ( D ) = Q ( D Q ), and the size of DQ and time for fetching D Q are independent of the size of D . The need for studying such queries is evident, since it allows us to compute Q ( D ) by accessing a bounded dataset D Q , regardless of how big D is. This paper investigates effectively bounded conjunctive queries (SPC) under an access schema A , which specifies indices and cardinality constraints commonly used. We provide characterizations (sufficient and necessary conditions) for determining whether an SPC query Q is effectively bounded under A . We study several problems for deciding whether Q is bounded, and if not, for identifying a minimum set of parameters of Q to instantiate and make Q bounded. We show that these problems range from quadratic-time to NP-complete, and develop efficient (heuristic) algorithms for them. We also provide an algorithm that, given an effectively bounded SPC query Q and an access schema A , generates a query plan for evaluating Q by accessing a bounded amount of data in any (possibly big) dataset. We experimentally verify that our algorithms substantially reduce the cost of query evaluation.