Search

Consistent query answering over a database that violates primary key constraints is a classical hard problem in database research that has been traditionally dealt with logic programming. However, the applicability of existing logic-based solutions is restricted to data sets of moderate size. This paper presents a novel decomposition and pruning strategy that reduces, in polynomial time, the problem of computing the consistent answer to a conjunctive query over a database subject to primary key constraints to a collection of smaller problems of the same sort that can be solved independently. The new strategy is naturally modeled and implemented using Answer Set Programming (ASP). An experiment run on benchmarks from the database world prove the effectiveness and efficiency of our ASP-based approach also on large data sets. [ABSTRACT FROM AUTHOR]

Linear Datalog programs are programs whose clauses have at most one intensional atom in their bodies. We explore syntactic classes of Datalog programs (syntactically non-linear) which turn out to express no more than the queries expressed by linear Datalog programs. In particular, we investigate linearisability of (database queries corresponding to) piecewise linear Datalog programs and chain queries:(a) We prove that piecewise linear Datalog programs can always be transformed into linear Datalog programs, by virtue of a procedure which performs the transformation automatically. The procedure relies upon conventional logic program transformation techniques.(b) We identify a new class of linearisable chain queries, referred to as pseudo-regular, and prove their linearisability constructively, by generating, for any given pseudo-regular chain query, the Datalog program corresponding to it. [Copyright &y& Elsevier]