Benchmarking Spatial Data Warehouses

Author(s)

Lopes Siqueira, Thiago Luis ; Ciferri, Ricardo Rodrigues ; Times, Valeria Cesano ; de Aguiar Ciferri, Cristina Dutra ; Pedersen, TB ; Mohania, MK ; Tjoa, AM

• Document type: Journal article
• Source: Lecture Notes in Computer Science; v. 6263, p. 2-pg., 2010-01-01.

Abstract

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 (in) 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 http //gbd dc ufscar br/spadawan (AU)

• FAPESP's process: 09/06052-7 - Access methods for improving query performance of non-conventional databases
• Grantee: Cristina Dutra de Aguiar
• Support Opportunities: Regular Research Grants