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Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.6 P.758-769

http://doi.org/10.1631/jzus.A0720103


Adaptive XML to relational mapping: an integrated approach


Author(s):  Tian-lei HU, Gang CHEN

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   htl@zju.edu.cn

Key Words:  XML, XML to relational (X2R) mapping, Autonomic computing


Tian-lei HU, Gang CHEN. Adaptive XML to relational mapping: an integrated approach[J]. Journal of Zhejiang University Science A, 2008, 9(6): 758-769.

@article{title="Adaptive XML to relational mapping: an integrated approach",
author="Tian-lei HU, Gang CHEN",
journal="Journal of Zhejiang University Science A",
volume="9",
number="6",
pages="758-769",
year="2008",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0720103"
}

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%T Adaptive XML to relational mapping: an integrated approach
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%A Gang CHEN
%J Journal of Zhejiang University SCIENCE A
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%@ 1673-565X
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0720103

TY - JOUR
T1 - Adaptive XML to relational mapping: an integrated approach
A1 - Tian-lei HU
A1 - Gang CHEN
J0 - Journal of Zhejiang University Science A
VL - 9
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SP - 758
EP - 769
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0720103


Abstract: 
Storing and querying XML (eXtensible Markup Language) data in relational form can exploit various services offered by modern relational database management systems (RDBMSs). Due to structural complexity of XML, there are many equivalent relational mapping schemes for the same XML data and queries. In this paper, we propose the adaptive XML to relational mapping (AX2RM) system, which considers finding optimal XML to relational (X2R) mapping as four separate but correlated procedures: logical database design, data scale estimation, workload transformation, and physical database design. We view the whole process as an autonomic computing problem and formalize the adaptive X2R mapping problem. Search spaces for each procedure are investigated individually, and five approaches for finding the optimal mapping are studied. We propose an integrated approach with greedy pruning (IT-GP), which views the mapping procedures as a whole and exploits heuristic rules in each procedure to prune impossible mappings as early as possible. Evaluation of these approaches shows the validity and high efficiency of IT-GP.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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