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Multi-Dimensional Database Allocation for Parallel Data Warehouses

Data allocation is a key performance factor for parallel database systems (PDBS). This holds especially for data warehousing environments where huge amounts of data and complex analytical queries have to be dealt with. While there are several studies on data allocation for relational PDBS, the specific requirements of data warehouses have not yet been sufficiently addressed. In this study, we consider the allocation of relational data warehouses based on a star schema and utilizing bitmap index structures. We investigate how a multi-dimensional hierarchical data fragmentation of the fact table supports queries referencing different subsets of the schema dimensions. Our analysis is based on realistic parameters derived from a decision support benchmark. The performance implications of different allocation choices are evaluated by means of a detailed simulation model.

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