Hippo a System for Computing Consistent Query Answers to a Class of SQL Queries Jan Chomicki University at Buffalo Jerzy Marcinkowski Wroclaw University Slawomir Staworko University at Buffalo

Motivation - Inconsistent data Enforcing data consistency no longer applicable: Data Integration – Consistent data sources, but inconsistent global view. Long-running transactions. Efficiency reasons.

Consistent Query Answers Repair Instance satisfying the constraint. The set of changes is minimal. There can be an exponential number of repairs. Tuple t is a consistent answer to Q if t is an answer to Q in every repair.

Computing CQA Query rewriting For query Q construct Q’ which evaluation returns consistent answers of Q. Logic programming Use disjunctive program to specify repairs and query result. Condensed representations of repairs

Conflict Hypergraphs Vertex – database tuple Edge – conflicting tuples NameTown J. SmithBuffalo J. SmithChicago D. GibsBuffalo M. AdamsBuffalo M. AdamsChicago M. AdamsNew York (J.S.,BUF) (D.G.,BUF) (M.A.,BUF) (M.A.,CHO) (M.A.,NYC) (J.S.,CHO) Repair – Maximal Independent Set

Hippo – System Description Conflict hypergraph – stored in RAM Denial integrity constraints Queries: SQL frontend – RDMBS independent Platform independent (Java2)

Hippo is fast Selection and Join – as fast as underlying database system. (QR takes approx. twice the time) Union and Difference – takes approx. Twice the time of simple query evaluation. (QR the same for difference).

Future Work Projection – In general problem is co-NP-data-complete. – Find an efficient heuristic. – Characterize hypergraphs where projection is easy Preferences – User provides preferences on resolving conflicts. – Computing Preferred CQA still easy.

References 1. M. Arenas, L. Bertossi, J. Chomicki. Consistent Query Answers in Inconsistent Databases. PODS’99 2. J. Chomicki, J. Marcinkowski. Minimal Change Integrity Maintenance using Tuple Deletions. Under revision for Information and Computation. 3. J. Chomicki, J. Marcinkowski, S. Staworko. Computing Consistent Query Answers using Conflict Hypergraphs. Under conference submission. 4.