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Efficient Evaluation of SUM Queries over Probabilistic Data
April 2013 (vol. 25 no. 4)
pp. 764-775
Reza Akbarinia, INRIA and LIRMM, Montpellier
Patrick Valduriez, INRIA and LIRMM, Montpellier
Guillaume Verger, INRIA and LIRMM, Montpellier
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 those applications. We implemented our solution and conducted an extensive experimental evaluation over synthetic and real-world data sets; the results show its effectiveness.
Index Terms:
Decision support systems,Complexity theory,Probabilistic logic,Indexes,Aggregates,Distribution functions,query processing,Database management,systems
Citation:
Reza Akbarinia, Patrick Valduriez, Guillaume Verger, "Efficient Evaluation of SUM Queries over Probabilistic Data," IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 4, pp. 764-775, April 2013, doi:10.1109/TKDE.2012.62
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