Abstract
In this paper, we present a novel ordered xpath evaluation in tree-unaware rdbms. The novelties of our approach lies in the followings. (a) We propose a novel xml storage scheme which comprises only leaf nodes, their corresponding data values, order encodings and their root-to-leaf paths. (b) We propose an algorithm for mapping ordered xpath queries into sql queries over the storage scheme. (c) We propose an optimization technique that enforces all mapped sql queries to be evaluated in a “left-to-right” join order. By employing these techniques, we show, through a comprehensive experiment, that our approach not only scales well but also performs better than some representative tree-unaware approaches on more than 65% of our benchmark queries with the highest observed gain factor being 1939. In addition, our approach reduces significantly the performance gap between tree-aware and tree-unaware approaches and even outperforms a state-of-the-art tree-aware approach for certain benchmark queries.
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Seah, BS., Widjanarko, K.G., Bhowmick, S.S., Choi, B., Leonardi, E. (2007). Efficient Support for Ordered XPath Processing in Tree-Unaware Commercial Relational Databases. In: Kotagiri, R., Krishna, P.R., Mohania, M., Nantajeewarawat, E. (eds) Advances in Databases: Concepts, Systems and Applications. DASFAA 2007. Lecture Notes in Computer Science, vol 4443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71703-4_66
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DOI: https://doi.org/10.1007/978-3-540-71703-4_66
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