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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1783.1/2519
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| Title: | Efficient OLAP operations in spatial data warehouses |
| Authors: | Papadias, Dimitris
Kalnis, Panagiotis
Zhang, Jun
Tao, Yufei |
| Keywords: | Spatial data warehouses
Traffic supervision
Mobile communications
Summarized data
Star schema |
| Issue Date: | Jul-2001 |
| Citation: | 7th International symposium, SSTD 2001 (LNCS 2121) p. 443-459 |
| Abstract: | Spatial databases store information about the position of individual objects in space. In many applications however, such as traffic supervision or mobile communications, only summarized data, like the number of cars in an area or phones serviced by a cell, is required. Although this information can be obtained from transactional spatial databases, its computation is expensive, rendering online processing inapplicable. Driven by the non-spatial paradigm, spatial data warehouses can be constructed to accelerate spatial OLAP operations. In this paper we consider the star-schema and we focus on the spatial dimensions. Unlike the non-spatial case, the groupings and the hierarchies can be numerous and unknown at design time, therefore the well-known materialization techniques are not directly applicable. In order to address this problem, we construct an ad-hoc grouping hierarchy based on the spatial index at the finest spatial granularity. We incorporate this hierarchy in the lattice model and present efficient methods to process arbitrary aggregations. We finally extend our technique to moving objects by employing incremental update methods. |
| Rights: | The original publication is available at http://www.springerlink.com/. Please use the appropriate URL and/or DOI for the article. |
| URI: | http://hdl.handle.net/1783.1/2519 |
| Appears in Collections: | CSE Conference Papers
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Size | Format |
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| effi.pdf | pre-published version | 143Kb | Adobe PDF | View/Open |
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