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首页> 外文会议>Twenty-Seventh International Conference on Very Large Data Bases, 27th, Sep 11-14th, 2001, Roma, Italy >Estimating the Selectivity of XML Path Expressions for Internet Scale Applications
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Estimating the Selectivity of XML Path Expressions for Internet Scale Applications

机译：估计Internet规模应用程序的XML路径表达式的选择性

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摘要

Data on the Internet is increasingly presented in XML format. This enables novel applications that pose queries over "all the XML data on the Internet." Queries over XML data use path expressions to navigate through the structure of the data, and optimizing these queries requires estimating the selectivity of these path expressions. In this paper, we propose two techniques for estimating the selectivity of simple XML path expressions over complex large-scale XML data as would be handled by Internet-scale applications: path trees and Markov tables. Both techniques work by summarizing the structure of the XML data in a small amount of memory and using this summary for selectivity estimation. We experimentally demonstrate the accuracy of our proposed techniques, and explore the different situations that would favor one technique over the other. We also demonstrate that our proposed techniques are more accurate than the best previously known alternative.
机译：互联网上的数据越来越多地以XML格式呈现。这使新颖的应用程序可以对“ Internet上的所有XML数据”进行查询。对XML数据的查询使用路径表达式来导航数据的结构，而优化这些查询需要估计这些路径表达式的选择性。在本文中，我们提出了两种用于估计简单XML路径表达式对复杂大规模XML数据的选择性的技术，它们是由Internet规模的应用程序处理的：路径树和马尔可夫表。两种技术都通过总结少量内存中XML数据的结构并将此摘要用于选择性估计而起作用。我们通过实验证明了我们提出的技术的准确性，并探索了将一种技术优于另一种技术的不同情况。我们还证明了我们提出的技术比以前最好的替代技术更为准确。

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