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- W4242945714 abstract "Data declustering is an important issue for reducing query response times in multi-disk database systems. In this paper, we propose a declustering method that utilizes the available information on query distribution, data distribution, data-item sizes, and disk capacity constraints. The proposed method exploits the natural correspondence between a data set with a given query distribution and a hypergraph. We define an objective function that exactly represents the aggregate parallel query-response time for the declustering problem and adapt the iterative-improvement-based heuristics successfully used in hypergraph partitioning to this objective function. We propose a two-phase algorithm that first obtains an initial K-way declustering by recursively bipartitioning the data set, then applies multi-way refinement on this declustering. We provide effective gain models and efficient implementation schemes for both phases. The experimental results on a wide range of realistic data sets show that the proposed method provides a significant performance improvement compared with the state-of-the-art declustering strategy based on similarity-graph partitioning." @default.
- W4242945714 created "2022-05-12" @default.
- W4242945714 date "1998-01-01" @default.
- W4242945714 modified "2023-09-26" @default.
- W4242945714 title "5614684 Superplastic Mg-based composite material and method for production thereof" @default.
- W4242945714 doi "https://doi.org/10.1016/s1359-835x(98)90130-0" @default.
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