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dc.contributor.authorLiu, DRen_US
dc.contributor.authorShekhar, Sen_US
dc.date.accessioned2014-12-08T15:02:23Z-
dc.date.available2014-12-08T15:02:23Z-
dc.date.issued1996-09-01en_US
dc.identifier.issn0306-4379en_US
dc.identifier.urihttp://dx.doi.org/10.1016/0306-4379(96)00024-5en_US
dc.identifier.urihttp://hdl.handle.net/11536/1068-
dc.description.abstractDeclustering 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 Ltden_US
dc.language.isoen_USen_US
dc.subjectsimilarity graphen_US
dc.subjectgeographic databasesen_US
dc.subjectdeclusteringen_US
dc.subjectgrid fileen_US
dc.subjectparallel databasesen_US
dc.titlePartitioning similarity graphs: A framework for declustering problemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/0306-4379(96)00024-5en_US
dc.identifier.journalINFORMATION SYSTEMSen_US
dc.citation.volume21en_US
dc.citation.issue6en_US
dc.citation.spage475en_US
dc.citation.epage496en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
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