Abstract

Indexing of multi-dimensional data has been the focus of a considerable amount of research effort over many years but no generally agreed paradigm has emerged to compare with the impact of the B-Tree, for example, on the indexing of one-dimensional data. At the same time, the need for efficient methods is ever more important in an environment where databases become larger and more complex in their structures. Mapping multi-dimensional data to one dimension, thus enabling one-dimensional access methods to be exploited, has been suggested in the literature but for the most part interest has been confined to the Z-order curve. The possibility of using other curves, such as the Hilbert and Gray-code curves, whose characteristics differ from those of the Z-order curve, has also been suggested. In this thesis we design and implement a working le store which is underpinned by the principle of mapping multi-dimensional data to one of a variety of space-filling curves and their variants. Data is then indexed using a B+ Tree which remains compact, regardless of the volume and number of dimensions. The implementation has entailed developing

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