Bulk-Loading the ND-Tree in Non-ordered Discrete Data Spaces

Applications demanding multidimensional index structures for performing efficient similarity queries often involve a large amount of data. The conventional tuple-loading approach to building such an index structure for a large data set is inefficient. To overcome the problem, a number of algorithms to bulk-load the index structures, like the Rtree, from scratch for large data sets in continuous data spaces have been proposed. However, many of them cannot be directly applied to a non-ordered discrete data space (NDDS) where data values on each dimension are discrete and have no natural ordering. No bulk-loading algorithm has been developed specifically for an index structure, such as the ND-tree, in an NDDS. In this paper, we present a bulk-loading algorithm, called the NDTBL, for the ND-tree in NDDSs. It adopts a special in-memory structure to efficiently construct the target ND-tree. It utilizes and extends some operations in the original ND-tree tupleloading algorithm to exploit the...

• Type: Conference
• Year: 2008
• Where: DASFAA
• Authors: Hyun-Jeong Seok, Gang Qian, Qiang Zhu, Alexander R. Oswald, Sakti Pramanik
• Keywords: DASFAA 2008, Data Space, Database, Index Structure, Large Data Sets