CategoryValue
Available viahttp://dbpubs.stanford.edu/pub/2007-7
Submitted on 1st of June 2007
Author Murthy, Raghotham; Widom, Jennifer
Title Making Aggregation Work in Uncertain and Probabilistic Databases
Date of publication June 2007
Citation Murthy, Raghotham; Widom, Jennifer. Making Aggregation Work in Uncertain and Probabilistic Databases,
Number of pages 13
Language English
Project Database Group
Type Technical Report
Subject group Computer Science
Abstract We describe how aggregation is handled in the Trio system for uncertain and probabilistic data. Because ýexactý aggregation in uncertain databases can produce exponentially-sized results, we provide three alternatives: a low bound on the aggregate value, a high bound on the value, and the expected value. These variants return a single result instead of a set of possible results, and they are generally very efficient to compute for both full-table and grouped aggregation queries. We provide formal definitions and semantics, a description of our implementation, and some preliminary analytical and experimental results for the one aggregate (expected-average) for which we compute an approximation.
Keywords Trio, Aggregations, TriQL, Probabilistic Databases, Uncertain Databases
Contact address rsm@cs.stanford.edu
Sponsored by This work was supported by the National Science Foundation
under grants IIS-0324431 and IIS-0414762, and by grants from the
Boeing and Hewlett-Packard Corporations.
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