Olap Results, Distributed Caching

Panos Kalnis; Gabriel Ghinita

doi:10.1007/978-3-319-17885-1_909

Olap Results, Distributed Caching

Panos Kalnis, Gabriel Ghinita

National University of Singapore

Research output: Chapter in Book/Report/Conference proceeding › Entry for encyclopedia/dictionary › peer-review

Abstract

Spatial databases store information about the position of individual objects in space. In many applications, such as traffic supervision or mobile communications, only summarized data, like the number of cars in an area, or number of 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 nonspatial paradigm, spatial data warehouses (DW) can be constructed to accelerate spatial on-line analytical processing (OLAP) operations. Typically, DWs employ precomputation and caching of previous results (Kotidis and Roussopoulos 1999; Scheuermann et al. 1996); these methods are centralized.

Original language	English
Title of host publication	Encyclopedia of GIS
Publisher	Springer Science+Business Media
Pages	1473-1479
Number of pages	7
ISBN (Electronic)	9783319178851
ISBN (Print)	9783319178844
DOIs	https://doi.org/10.1007/978-3-319-17885-1_909
Publication status	Published - 1 Jan 2017
Externally published	Yes

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10.1007/978-3-319-17885-1_909

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AB - Spatial databases store information about the position of individual objects in space. In many applications, such as traffic supervision or mobile communications, only summarized data, like the number of cars in an area, or number of 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 nonspatial paradigm, spatial data warehouses (DW) can be constructed to accelerate spatial on-line analytical processing (OLAP) operations. Typically, DWs employ precomputation and caching of previous results (Kotidis and Roussopoulos 1999; Scheuermann et al. 1996); these methods are centralized.

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Olap Results, Distributed Caching

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