Abstract
According to increase of spatial data, many decision support systems require the fast spatio-temporal analysis. This paper proposes the improved index for efficient OLAP in a spatial data warehouse. The main idea is to use the hybrid index of the extended aggregation R-tree and the sorted hash table. The extended R-tree supports the spatial hierarchy with the level of R-tree. Also, it provides pre-aggregation for fast retrieval of the aggregated value. The sorted hash table is the transformed hash table for supporting the temporal hierarchy. So, it provides pre-aggregation of each temporal unit, year, month and etc. By the proposed hybrid index, an efficient spatio-temporal analysis can be sup-ported since it provides the spatio-temporal hierarchy and the pre-aggregated value.
This research was supported by the MIC(Ministry of Information and Communication), Ko-rea, under the ITRC(Information Technology Research Center) support program supervised by the IITA(Institute of Information Technology Assessment) .
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You, BS., Lee, DW., Eo, SH., Lee, JD., Bae, HY. (2006). Hybrid Index for Spatio-temporal OLAP Operations. In: Yakhno, T., Neuhold, E.J. (eds) Advances in Information Systems. ADVIS 2006. Lecture Notes in Computer Science, vol 4243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11890393_12
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DOI: https://doi.org/10.1007/11890393_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46291-0
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