Abstract
XML filtering applications are gaining increasing popularity recently. Automata are generally adopted to construct query indexes for evaluating large numbers of XPath queries over XML streams. Usually only shallow data are observed in existing approaches. How to process deep and recursive XML data with low memory limitation efficiently is still a challenging issue. In this paper, we propose HFilter, a Hybrid Finite Automaton (HFA) based stream filtering approach, to solve this problem. We introduce the basic two-tier HFA (lazy DFA tier and NFA tier) first, which realizes data prefix sharing and memory overflow control to improve the filtering throughput. Then an optimized three-tier HFA with an extra pre-expanded DFA tier is put forward, which significantly reduces the restarting cost of HFA after memory overflow. Experiments show that our approaches work more efficiently than existing ones.
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Sun, W., Qin, Y., Yu, P., Zhang, Z., He, Z. (2008). HFilter: Hybrid Finite Automaton Based Stream Filtering for Deep and Recursive XML Data. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2008. Lecture Notes in Computer Science, vol 5181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85654-2_48
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DOI: https://doi.org/10.1007/978-3-540-85654-2_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85653-5
Online ISBN: 978-3-540-85654-2
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