Authors:
Stefan Böttcher
;
Matthias Feldotto
and
Rita Hartel
Affiliation:
University of Paderborn, Germany
Keyword(s):
XML, XML Compression, Parallelization.
Related
Ontology
Subjects/Areas/Topics:
Distributed and Parallel Applications
;
Internet Technology
;
Web Information Systems and Technologies
;
XML and Data Management
Abstract:
Whenever huge amounts of XML data have to be transferred from a web server to multiple clients, the transferred data volumes can be reduced significantly by sending compressed XML instead of plain XML. Whenever applications require querying a compressed XML format and XML compression or decompression time is a bottleneck, parallel XML compression and parallel decompression may be of significant advantage. We choose the XML compressor XSDS as starting point for our new approach to parallel compression and parallel decompression of XML documents for the following reasons. First, XSDS generally reaches stronger compression ratios than other compressors like gzip, bzip2, and XMill. Second, in contrast to these compressors, XSDS not only supports XPath queries on compressed XML data, but also XPath queries can be evaluated on XSDS compressed data even faster than on uncompressed XML. We propose a String-search-based parsing approach to parallelize XML compression with XSDS, and we show th
at we can speed-up the compression of XML documents by a factor of 1.4 and that we can speed-up the decompression time even by a factor of up to 7 on a quad-core processor.
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