Hierarchical clustering has been proved an effective means for physically organizing large fact tables since it reduces significantly the I/O cost during ad hoc OLAP query evaluation. In this paper, we propose a novel multidimensional file structure for organizing the most detailed data of a cube, the CUBE File. The CUBE File achieves hierarchical clustering of the data, enabling fast access via hierarchical restrictions. Moreover, it imposes a low storage cost and adapts perfectly to the extensive sparseness of the data space achieving a high compression rate. Our results show that the CUBE File outperforms the most effective method proposed up to now for hierarchically clustering the cube, resulting in 7-9 times less I/Os on average for all workloads tested. Thus, it achieves a higher degree of hierarchical clustering. Moreover, the CUBE File imposes a 2-3 times lower storage cost.
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