首页> 外文会议>International Conference on Extending Database Technology(EDBT 2006); 20060326-31; Munich(DE) >A Decomposition-Based Probabilistic Framework for Estimating the Selectivity of XML Twig Queries
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A Decomposition-Based Probabilistic Framework for Estimating the Selectivity of XML Twig Queries

机译:基于分解的概率框架,用于估计XML树枝查询的选择性

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摘要

In this paper we present a novel approach for estimating the selectivity of XML twig queries. Such a technique is useful for answering approximate queries as well as for determining an optimal query plan for complex queries based on said estimates. Our approach relies on a summary structure that contains the occurrence statistics of small twigs. We rely on a novel probabilistic approach for decomposing larger twig queries into smaller ones. We then show how it can be used to estimate the selectivity of the larger query in conjunction with the summary information. We present and evaluate different strategies for decomposition and compare this work against a state-of-the-art selectivity estimation approach on synthetic and real datasets. The experimental results show that our proposed approach is very effective in estimating the selectivity of XML twig queries.
机译:在本文中,我们提出了一种新颖的方法来估计XML树枝查询的选择性。这种技术对于回答近似查询以及基于所述估计确定用于复杂查询的最优查询计划是有用的。我们的方法依赖于包含小树枝发生统计信息的摘要结构。我们依靠一种新颖的概率方法将较大的树枝查询分解为较小的查询。然后,我们展示如何结合摘要信息将其用于估计较大查询的选择性。我们提出并评估了不同的分解策略,并将此工作与合成和真实数据集上的最新选择性估计方法进行了比较。实验结果表明,我们提出的方法在估计XML树枝查询的选择性方面非常有效。

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