Benchmarking Spatial Data Warehouses

Spatial data warehouses (SDW) enable analytical multidimensional queries together with spatial analysis. Mainly, three operations are related to SDW query processing performance: (i) joining large fact tables and large spatial and non-spatial dimension tables; (ii) computing one or more costly spatial predicates based on spatial ad hoc query windows; and (iii) aggregating data according to different spatial granularity levels. Several techniques to improve the query processing performance over SDW have been proposed in the literature. However, we identified the lack of a benchmark to carry out a controlled experimental evaluation of such techniques and, principally, to effectively measure the costs of the aforementioned three complex operations. In this paper, we propose a novel spatial data warehouse benchmark, called Spadawan, to provide performance evaluation environments for SDW and enable a further investigation on spatial data redundancy. The Spadawan benchmark is available at ht...

• Type: Conference
• Year: 2010
• Where: DAWAK
• Authors: Thiago Luís Lopes Siqueira, Ricardo Rodrigues Ciferri, Valéria Cesário Times, Cristina Dutra de Aguiar Ciferri
• Keywords: DAWAK 2010, Information Technology, Query Processing Performance, Spatial, Spatial Data Warehouse