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Making Aggregation Work in Uncertain and Probabilistic Databases

Murthy, Raghotham and Ikeda, Robert and Widom, Jennifer (2007) Making Aggregation Work in Uncertain and Probabilistic Databases.


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We describe how aggregation is handled in the \emph{Trio} system for uncertain and probabilistic data. Because ``exact'' aggregation in uncertain databases can produce exponentially-sized results, we provide three alternatives: a {\em low} bound on the aggregate value, a {\em high} bound on the value, and the {\em expected} value. These variants return a single result instead of a set of possible results, and they are generally efficient to compute for both full-table and grouped aggregation queries. We provide formal definitions and semantics and a description of our implementation for single-table aggregation queries. We study the performance and scalability of our algorithms through experiments over a large synthetic data set. We also provide some preliminary results on aggregations over joins.

Item Type:Article
Uncontrolled Keywords:Trio, Aggregations, TriQL, Probabilistic Databases, Uncertain Databases
Subjects:Computer Science
Related URLs:Project Homepage
ID Code:826
Deposited By:Raghotham Murthy
Deposited On:31 May 2007 17:00
Last Modified:15 Apr 2010 04:53

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