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Efficient Evaluation of SUM Queries Over Probabilistic Data

Reza Akbarinia 1 Patrick Valduriez 1, 2 Guillaume Verger 1, 2
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : SUM queries are crucial for many applications that need to deal with uncertain data. In this paper, we are interested in the queries, called ALL_SUM, that return all possible sum values and their probabilities. In general, there is no efficient solution for the problem of evaluating ALL_SUM queries. But, for many practical applications, where aggregate values are small integers or real numbers with small precision, it is possible to develop efficient solutions. In this paper, based on a recursive approach, we propose a new solution for this problem. We implemented our solution and conducted an extensive experimental evaluation over synthetic and real-world data sets; the results show its effectiveness.
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Submitted on : Tuesday, December 20, 2011 - 6:32:02 AM
Last modification on : Monday, December 14, 2020 - 3:33:13 PM
Long-term archiving on: : Wednesday, March 21, 2012 - 2:21:56 AM


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  • HAL Id : lirmm-00652293, version 1



Reza Akbarinia, Patrick Valduriez, Guillaume Verger. Efficient Evaluation of SUM Queries Over Probabilistic Data. IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2013, 25 (4), pp.764-775. ⟨lirmm-00652293⟩



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