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Scalability Analysis of Declustering Methods for Multidimensional Range Queries
March/April 1998 (vol. 10 no. 2)
pp. 310-327

Abstract—Efficient storage and retrieval of multiattribute data sets has become one of the essential requirements for many data-intensive applications. The Cartesian product file has been known as an effective multiattribute file structure for partial-match and best-match queries. Several heuristic methods have been developed to decluster Cartesian product files across multiple disks to obtain high performance for disk accesses. Although the scalability of the declustering methods becomes increasingly important for systems equipped with a large number of disks, no analytic studies have been done so far. In this paper, we derive formulas describing the scalability of two popular declustering methods—Disk Modulo and Fieldwise Xor—for range queries, which are the most common type of queries. These formulas disclose the limited scalability of the declustering methods, and this is corroborated by extensive simulation experiments. From the practical point of view, the formulas given in this paper provide a simple measure that can be used to predict the response time of a given range query and to guide the selection of a declustering method under various conditions.

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Index Terms:
Multiattribute access methods, range query, file declustering, scalability, Disk Modulo, Fieldwise Xor, Hilbert curve-allocation method.
Bongki Moon, Joel H. Saltz, "Scalability Analysis of Declustering Methods for Multidimensional Range Queries," IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 2, pp. 310-327, March-April 1998, doi:10.1109/69.683759
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