Efficient Query Evaluation on Probabilistic Databases Nilesh Dalvi and Dan Suciu   View Paper (PDF)   Return to RESEARCH SESSION 22:QUERY PROCESSING Abstract We describe a system that supports arbitrarily complex SQL queries on probabilistic databases. The query semantics is based on a probabilistic model and the results are ranked, much like in Information Retrieval. Our main focus is efficient query evaluation, a problem that has not received attention in the past. We describe an optimization algorithm that can compute efficiently most queries. We show, however, that the data complexity of some queries is #P-complete, which implies that these queries do not admit any efficient evaluation methods. For these queries we describe both an approximation algorithm and a Monte-Carlo simulation algorithm. ©2005 Association for Computing Machinery