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There are two broad approaches to query evaluation over probabilistic databases: Intensional Methods proceed by manipulating expressions over symbolic events associated with uncertain tuples. This approach is very general and can be applied to any query, but requires an expensive post-processing phase, which involves some general-purpose probabilistic inference. Extensional Methods, on the other hand, evaluate the query by translating operations over symbolic events to a query plan; extensional methods scale well, but they are restricted to safe queries. In this paper, the authors bridge this gap by proposing an approach that can translate the evaluation of any query into extensional operators, followed by some post-processing that requires probabilistic inference.
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