Scalable XSLT Evaluation

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dc.creatorGuo, Zhimao
dc.creatorLi, Min
dc.creatorWang, Xiaoling
dc.creatorZhou, Aoying
dc.date2004-08-22
dc.date.accessioned2026-07-07T03:21:42Z
dc.date.available2026-07-07T03:21:42Z
dc.descriptionXSLT is an increasingly popular language for processing XML data. It is widely supported by application platform software. However, little optimization effort has been made inside the current XSLT processing engines. Evaluating a very simple XSLT program on a large XML document with a simple schema may result in extensive usage of memory. In this paper, we present a novel notion of \emph{Streaming Processing Model} (\emph{SPM}) to evaluate a subset of XSLT programs on XML documents, especially large ones. With SPM, an XSLT processor can transform an XML source document to other formats without extra memory buffers required. Therefore, our approach can not only tackle large source documents, but also produce large results. We demonstrate with a performance study the advantages of the SPM approach. Experimental results clearly confirm that SPM improves XSLT evaluation typically 2 to 10 times better than the existing approaches. Moreover, the SPM approach also features high scalability.
dc.descriptionIt appeared on the international conference of APWeb 04. And it includes 10 pages
dc.identifierhttps://arxiv.org/abs/cs/0408051
dc.identifierhttp://arxiv.org/abs/cs/0408051
dc.identifierIn Proc. of APWeb, 2004
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32306
dc.subjectDatabases
dc.titleScalable XSLT Evaluation
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