Partial Selection Query in Peer-to-Peer Databases

F. Kashani, C. Shahabi
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引用次数: 4

Abstract

In this paper, we propose DBSampler, a query execution mechanism to answer "partial selection" queries in peerto- peer databases. A partial selection query is an arbitrary selection query that is satisfied with a fraction \in of the results; a universal operation with applications in database tuning, query optimization and approximate query processing in peer-to-peer databases. DBSampler is based on an epidemic dissemination algorithm. We model the epidemic dissemination as a percolation problem and by rigorous percolation analysis tune DBSampler per-query and on-thefly to answer partial queries correctly and efficiently. We verify the efficiency of DBSampler in terms of query cost and query time via extensive simulation.
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点对点数据库中的部分选择查询
在本文中,我们提出了DBSampler,一个查询执行机制来回答点对点数据库中的“部分选择”查询。部分选择查询是一种任意选择查询,它满足于结果的一小部分\in;一种通用操作,应用于对等数据库的数据库调优、查询优化和近似查询处理。DBSampler基于流行病传播算法。我们将流行病传播建模为一个渗透问题,并通过严格的渗透分析,对DBSampler进行每查询和动态调整,以正确有效地回答部分查询。我们通过大量的仿真验证了DBSampler在查询成本和查询时间方面的效率。
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