Consistent query answering under key and exclusion dependencies: algorithms and experiments

Research in consistent query answering studies the definition and computation of "meaningful" answers to queries posed to inconsistent databases, i.e., databases whose data do not satisfy the integrity constraints (ICs) declared on their schema. Computing consistent answers to conjunctive queries is generally coNP-hard in data complexity, even in the presence of very restricted forms of ICs (single, unary keys). Recent studies on consistent query answering for database schemas containing only key dependencies have analyzed the possibility of identifying classes of queries whose consistent answers can be obtained by a first-order rewriting of the query, which in turn can be easily formulated in SQL and directly evaluated through any relational DBMS. In this paper we study consistent query answering in the presence of key dependencies and exclusion dependencies. We first prove that even in the presence of only exclusion dependencies the problem is coNP-hard in data complexity, and define a general method for consistent answering of conjunctive queries under key and exclusion dependencies, based on the rewriting of the query in Datalog with negation. Then, we identify a subclass of conjunctive queries that can be first-order rewritten in the presence of key and exclusion dependencies, and define an algorithm for computing the first-order rewriting of a query belonging to such a class of queries. Finally, we compare the relative efficiency of the two methods for processing queries in the subclass above mentioned. Experimental results, conducted on a real and large database of the computer science engineering degrees of the University of Rome "La Sapienza", clearly show the computational advantage of the first-order based technique.

[1]  Renée J. Miller,et al.  ConQuer: efficient management of inconsistent databases , 2005, SIGMOD '05.

[2]  Thomas Eiter,et al.  Efficient Evaluation of Logic Programs for Querying Data Integration Systems , 2003, ICLP.

[3]  Sergio Greco,et al.  A Logical Framework for Querying and Repairing Inconsistent Databases , 2003, IEEE Trans. Knowl. Data Eng..

[4]  Andrea Calì,et al.  On the decidability and complexity of query answering over inconsistent and incomplete databases , 2003, PODS.

[5]  Leopoldo E. Bertossi,et al.  Logic Programs for Consistently Querying Data Integration Systems , 2003, IJCAI.

[6]  Jan Chomicki,et al.  Consistent query answers in inconsistent databases , 1999, PODS '99.

[7]  Georg Gottlob,et al.  Disjunctive datalog , 1997, TODS.

[8]  Renée J. Miller,et al.  First-order query rewriting for inconsistent databases , 2005, J. Comput. Syst. Sci..

[9]  Jan Chomicki,et al.  On the Computational Complexity of Minimal-Change Integrity Maintenance in Relational Databases , 2005, Inconsistency Tolerance.

[10]  Wolfgang Faber,et al.  Magic Sets and their application to data integration , 2005, J. Comput. Syst. Sci..

[11]  Jan Chomicki,et al.  Computing consistent query answers using conflict hypergraphs , 2004, CIKM '04.

[12]  Wolfgang Faber,et al.  Enhancing the Magic-Set Method for Disjunctive Datalog Programs , 2004, ICLP.

[13]  Wolfgang Faber,et al.  The DLV system for knowledge representation and reasoning , 2002, TOCL.

[14]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[15]  Andrea Calì,et al.  Query rewriting and answering under constraints in data integration systems , 2003, IJCAI.