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Holistic twig joins: optimal XML pattern matching
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| Venue: | in: Proceedings of ACM SIGMOD International Conference on Management of Data, 2002 |
| Citations: | 345 - 8 self |
BibTeX
@INPROCEEDINGS{Bruno_holistictwig,
author = {Nicolas Bruno and Nick Koudas and Divesh Srivastava},
title = {Holistic twig joins: optimal XML pattern matching},
booktitle = {in: Proceedings of ACM SIGMOD International Conference on Management of Data, 2002},
year = {},
pages = {310--321}
}
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Abstract
XML employs a tree-structured data model, and, naturally, XML queries specify patterns of selection predicates on multiple elements related by a tree structure. Finding all occurrences of such a twig pattern in an XML database is a core operation for XML query processing. Prior work has typically decomposed the twig pattern into binary structural (parent-child and ancestor-descendant) relationships, and twig matching is achieved by: (i) using structural join algorithms to match the binary relationships against the XML database, and (ii) stitching together these basic matches. A limitation of this approach for matching twig patterns is that intermediate result sizes can get large, even when the input and output sizes are more manageable. In this paper, we propose a novel holistic twig join algorithm, TwigStack, for matching an XML query twig pattern. Our technique uses a chain of linked stacks to compactly represent partial results to root-to-leaf query paths, which are then composed to obtain matches for the twig pattern. When the twig pattern uses only ancestor-descendant relationships between elements, TwigStack is I/O and CPU optimal among all sequential algorithms that read the entire input: it is linear in the sum of sizes of the input lists and the nal result list, but independent of the sizes of intermediate results. We then show how to use (a modication of) B-trees, along with TwigStack, to match query twig patterns in sub-linear time. Finally, we complement our analysis with experimental results on a range of real and synthetic data, and query twig patterns. 1
Keyphrases
twig pattern optimal xml pattern holistic twig join xml database entire input input list intermediate result size represent partial result structural join algorithm xml query processing twig matching output size root-to-leaf query path nal result list binary relationship intermediate result core operation selection predicate synthetic data sequential algorithm prior work basic match multiple element xml query twig pattern novel holistic twig join algorithm query twig pattern ancestor-descendant relationship tree structure sub-linear time experimental result tree-structured data model
