Improving estimation accuracy of aggregate queries on data cubes
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
Improving estimation accuracy of aggregate queries on data cubes
Data & Knowledge Engineering
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Statistical users typically require summary tables andwant fast and accurate answers to their queries. Usually,the query system keeps materialized aggregate viewsto speed up the evaluation of summary queries. If the summarytable on the variable of interest to a statistical user isnot derivable from the set of materialized aggregate views,the answer to his query will consist of an estimate and, if theuser is a domain expert, he would like to participate in theestimation process. Therefore, he should be left the possibilityof "tuning" the response to an auxiliary variable, forwhich either there is a materialized aggregate view or aggregatedata can be externally provided by the user himself.In this framework, we solve the computational problems relatedto the estimation of summary queries, and propose efficientalgorithms which make use of notions and techniquesdeveloped in the theory of acyclic database schemes.