Abstract
Approximate range aggregate queries are one of the most frequent and useful kinds of queries for Decision Support Systems (DSS). Traditionally, sampling- based techniques have been proposed to tackle this problem. However, its effectiveness will degrade when the underlying data distribution is skewed. Another approach based on the outlier management can limit the effect of data skew but fails to address other requirements of approximate range aggregate queries, such as error guarantees and query processing efficiency. In this paper, we present a technique that provide approximate answers to range aggregate queries on OLAP data cubes efficiently with theoretical error guarantees. Our basic idea is to build different data structures for outliers and the rest of the data. Experimental results verified the effectiveness of our proposed methods.
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© 2004 Springer-Verlag Berlin Heidelberg
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Cuzzocrea, A., Wang, W., Matrangolo, U. (2004). Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2004. Lecture Notes in Computer Science, vol 3181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30076-2_10
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DOI: https://doi.org/10.1007/978-3-540-30076-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22937-7
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