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引用次数: 11

摘要

集群技术通过在多个设备之间分布数据,从而通过并行I/O减少查询响应时间。大多数关于聚类的研究都是针对空间距离查询,并研究具有低加性误差的方案。最近,为了减少附加开销,提出了使用复制进行集群分离。复制显著降低了任意查询的检索成本。本文提出了一种基于设计理论的任意查询磁盘分配和检索机制。使用所提出的c-copy复制集群方案,(c - 1)k/sup 2/ + ck桶可以使用最多k次磁盘访问来检索。检索算法效率高,对于查询Q具有/spl Theta/(|Q|)复杂度的渐近最优,除具有确定性的最坏情况界和高效检索外,该算法还能处理非均匀数据、高维数据、支持增量聚类和良好的容错性能。
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Design theoretic approach to replicated declustering
Declustering techniques reduce query response times through parallel I/O by distributing data among multiple devices. Most of the research on declustering is targeted at spatial range queries and investigates schemes with low additive error. Recently, declustering using replication is proposed to reduce the additive overhead. Replication significantly reduces retrieval cost of arbitrary queries. In this paper, we propose a disk allocation and retrieval mechanism for arbitrary queries based on design theory. Using proposed c-copy replicated declustering scheme, (c - 1)k/sup 2/ + ck buckets can be retrieved using at most k disk accesses. Retrieval algorithm is very efficient and is asymptotically optimal with /spl Theta/(|Q|) complexity for a query Q. In addition to the deterministic worst-case bound and efficient retrieval, proposed algorithm handles nonuniform data, high dimensions, supports incremental declustering and has good fault-tolerance property.
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