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Aggregation in Probabilistic Databases via Knowledge Compilation by Robert Fink; Larisa Han; Dan Olteanu is a Computer Science article available to read on EtoBox.
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This paper presents a query evaluation technique for positive relational algebra queries with aggregates on a representation system for probabilistic data based on the algebraic structures of semiring and semimodule. The core of our evaluation technique is a procedure that compiles semimodule and semiring expressions into so-called decomposition trees, for which the computation of the probability distribution can be done in time linear in the product of the sizes of the probability distributions represented by its nodes. We give syntactic characterisations of tractable queries with aggregates by exploiting the connection between query tractability and polynomial-time decomposition trees. A prototype of the technique is incorporated in the probabilistic database engine SPROUT. We report on performance experiments with custom datasets and TPC-H data.
Who reads Aggregation in Probabilistic Databases via Knowledge Compilation?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Robert Fink; Larisa Han; Dan Olteanu
- Publisher
- ACM
- Published
- 2012
- Language
- EN
- Field
- Computer Science (Physical Sciences)