Efficient disk allocation for fast similarity searching
Proceedings of the tenth annual ACM symposium on Parallel algorithms and architectures
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As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that cyclic declustering techniques outperform previously proposed techniques.