標題: Partitioning similarity graphs: A framework for declustering problems
作者: Liu, DR
Shekhar, S
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: similarity graph;geographic databases;declustering;grid file;parallel databases
公開日期: 1-九月-1996
摘要: Declustering problems are well-known in the databases for parallel computing environments. In this paper, we propose a new similarity-based technique for declustering data. The proposed method can adapt to the available information about query distribution (e.g. size,shape and frequency) and can work with alternative atomic data-types. Furthermore, the proposed method is flexible and can work with alternative data distributions, data sizes and partition-size constraints. The method is based on max-cut partitioning of a similarity graph defined over the given set of data, under constraints on the partition sizes. It maximizes the chances that a pair of atomic data-items that are frequently accessed together by queries are allocated to distinct disks. We describe the application of the proposed method to parallelizing Grid Files at the data page level. Detailed experiments in this context show that the proposed method adapts to query distribution and data distribution, and that it outperforms traditional mapping-function-based methods for many interesting query distributions as well for several non-uniform data distributions. Copyright (C) 1996 Elsevier Science Ltd
URI: http://dx.doi.org/10.1016/0306-4379(96)00024-5
http://hdl.handle.net/11536/1068
ISSN: 0306-4379
DOI: 10.1016/0306-4379(96)00024-5
期刊: INFORMATION SYSTEMS
Volume: 21
Issue: 6
起始頁: 475
結束頁: 496
顯示於類別:期刊論文


文件中的檔案:

  1. A1996VP66400002.pdf