Efficient top-(k,l)range query processing for uncertaindata based onmulticore architectures
Efficient top-(k,l)range query processing for uncertaindata based onmulticore architectures
复制标题
基于多核架构的不确定数据高效top(k,l)范围查询处理
DOI：
10.1007/s10619-014-7156-8
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发表时间：
2015
影响因子：
1.2
通讯作者：
Yantao Zhou
中科院分区：
文献类型：
--
作者：
Guoqing Xiao;Kenli Li;Keqin Li;Xu Zhou;Yantao Zhou
由于现实世界数据中存在不确定性，因此对不确定数据的查询处理在许多应用中都是非常重要的。本文首先阐述了不确定数据库环境下的一种新的重要查询，即不确定Top-(k，L)区间查询，它检索期望满足得分区间约束[，]且具有最大top-k概率但不低于用户指定的概率阈值的不确定元组。为了能够更快地响应UTR查询，我们提出了一些有效的剪枝规则来减少UTR查询空间，并将这些剪枝规则集成到一个高效的UTR查询过程中。此外，为了提高UTR查询的效率和效果，提出了一种并行UTR(PUTR)查询过程。大量实验验证了该算法的有效性和有效性。值得注意的是，与Utr查询过程相比，putr查询过程的执行效率和效率要高得多。
Query processing over uncertain data is very important in many applications due to the existence of uncertainty in real-world data. In this paper, we first elaborate a new and important query in the context of an uncertain database, namely uncertain top-(k,l) range (UTR) query, which retrievesuncertain tuples that are expected to meet score range constraint [,] and have the maximum top-kprobabilities but no less than a user-specified probability threshold. In order to enable the UTR query answer faster, we put forward some effective pruning rules to reduce the UTR query space, which are integrated into an efficient UTR query procedure. What’s more, to improve the efficiency and effectiveness of the UTR query, a parallel UTR (PUTR) query procedure is presented. Extensive experiments have verified the efficiency and effectiveness of our proposed algorithms. It is worth to notice that, comparing to the UTR query procedure, the PUTR query procedure performs much more efficiently and effectively.