The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A dynamic load balancing strategy for parallel datacube computation
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Parallel Star Join + DataIndexes: Efficient Query Processing in Data Warehouses and OLAP
IEEE Transactions on Knowledge and Data Engineering
Selective Materialization: An Efficient Method for Spatial Data Cube Construction
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Dynamic Query Scheduling in Parallel Data Warehouses
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Efficient OLAP Operations in Spatial Data Warehouses
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Parallel Multi-Dimensional ROLAP Indexing
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Parallel ROLAP Data Cube Construction On Shared-Nothing Multiprocessors
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Spatial hierarchy and OLAP-favored search in spatial data warehouse
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Range Aggregate Processing in Spatial Databases
IEEE Transactions on Knowledge and Data Engineering
Modified R-MVB tree and BTV algorithm used in a distributed spatio-temporal data warehouse
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Extended cascaded star schema and ECOLAP operations for spatial data warehouse
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Extended cascaded star schema for distributed spatial data warehouse
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
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In this paper we present a Spatial Data Warehouse system that we use for aggregation and analysis of huge amounts of spatial data. The data is generated by utilities meters communicating via radio. In order to provide sufficient efficiency for our system we propose data and workload distribution as well as advanced indexing techniques. The system is based on a cascaded star model, which is a spatial development of a standard star schema and contains interconnected and often nested star schemas. The cascaded star allows efficient storage and analysis of spatial data, whose range extends from meter measurement values to weather information. The indexing tree structure and operation is tightly integrated with the spatial character of the data. Thanks to an available memory evaluating mechanism the system is very flexible in the field of aggregates accuracy. We also implemented indexing structure updating mechanism. The system is written in Java; for the data base we use Oracle 9i. Basing on the wide variety of tests results, we prove that a distributed system significantly surpasses the centralized version in terms of efficiency. We also show that a selective materialization of indexing structure fragments strongly increases system efficiency.