Investigating the Effects of Spatial Data Redundancy in Query Performance over Geographical Data Warehouses

1 This work has been supported by the following Brazilian research agencies: CAPES, CNPq, FAPESP, FINEP and INEP. The first two authors also thank the support of the Web-PIDE Project in the context of the Observatory of the Education of the Brazilian Government. Abstract. Geographical Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis. For these, several conceptual and logical data models have been proposed in the literature. However, little attention has been devoted to the study of how spatial data redundancy affects query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. Further, we analyze the indexing issue, aiming at improving query performance on a redundant GDW. Comparisons among the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST showed that SB-index significantly improves the elapsed time on query processing from 25% up to 95%.