Abstract
A range-sum query computes aggregate information over a data cube in the query range specified by a user. Existing methods based on the prefix-sum approach use an additional cube called the prefix-sum cube (PC), to store the cumulative sums of data, causing a high space overhead. This space overhead not only leads to extra costs for storage devices, but also causes additional propagations of updates and longer access time on physical devices. In this paper, we propose a new cube called Partial Prefix-sum Cube (PPC) that drastically reduces the space of the PC in a large data warehouse. The PPC decreases the update propagation caused by the dependency between values in cells of the PC. We perform an extensive experiment with respect to various dimensions of the data cube and query sizes, and examine the effectiveness and performance of our proposed method. Experimental results show that the PPC drastically reduces the space requirements, while having reasonable query performances.
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Chun, SJ. (2003). Partial Prefix Sum Method for Large Data Warehouses. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_67
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DOI: https://doi.org/10.1007/978-3-540-39592-8_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20256-1
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