DocumentCode
37682
Title
Multi-Core Processing of XML Twig Patterns
Author
Shnaiderman, Lila ; Shmueli, Oded
Author_Institution
Comput. Sci. Dept., Technion - Israel Inst. of Technol., Haifa, Israel
Volume
27
Issue
4
fYear
2015
fDate
April 1 2015
Firstpage
1057
Lastpage
1070
Abstract
XML is based on a tree-structured data model. Naturally, the most popular XML querying language (XPath) uses patterns of selection predicates, on multiple elements related by a tree structure, which often may be abstracted by twig patterns. Finding all occurrences of such a twig pattern in an XML database is a basic operation for XML query processing. We present the parallel path stack algorithm (PPS) and the parallel twig stack algorithm (PTS). PPS and PTS are novel and efficient algorithms for matching XML query twig patterns in a parallel multi-threaded computing platform. PPS and PTS are based on the PathStack and TwigStack algorithms [1]. These algorithms employ a sophisticated search technique for limiting processing to specific subtrees. We conducted extensive experimentation with PPS and PTS. We compared PPS and PTS to the standard (sequential) PathStack and TwigStack algorithms in terms of run time (to completion). We checked their performance for varying numbers of threads. Experimental results indicate that using PPS and PTS significantly reduces the running time of queries in comparison with the PathStack/TwigStack algorithm (up to 44 times faster for DBLP queries and up to 22 times faster for XMark queries).
Keywords
XML; data mining; parallel processing; query languages; tree data structures; PathStack algorithm; TwigStack algorithm; XML database; XML querying language; XML twig pattern; XPath; multicore processing; parallel multithreaded computing; parallel path stack algorithm; parallel twig stack algorithm; tree-structured data model; Databases; Instruction sets; Parallel algorithms; Partitioning algorithms; Pattern matching; Vegetation; XML; Query processing; concurrency;
fLanguage
English
Journal_Title
Knowledge and Data Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1041-4347
Type
jour
DOI
10.1109/TKDE.2014.2349907
Filename
6880848
Link To Document