ACM Home Page
Please provide us with feedback. Feedback
ViST: a dynamic index method for querying XML data by tree structures
Full text PdfPdf (244 KB)
Source International Conference on Management of Data archive
Proceedings of the 2003 ACM SIGMOD international conference on Management of data table of contents
San Diego, California
SESSION: XML indexing and compression table of contents
Pages: 110 - 121  
Year of Publication: 2003
ISBN:1-58113-634-X
Authors
Haixun Wang  IBM Thomas J. Watson Research Center, Hawthorne, NY
Sanghyun Park  POSTECH, Pohang, Korea
Wei Fan  IBM Thomas J. Watson Research Center, Hawthorne, NY
Philip S. Yu  IBM Thomas J. Watson Research Center, Hawthorne, NY
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 13,   Downloads (12 Months): 92,   Citation Count: 59
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/872757.872774
What is a DOI?

ABSTRACT

With the growing importance of XML in data exchange, much research has been done in providing flexible query facilities to extract data from structured XML documents. In this paper, we propose ViST, a novel index structure for searching XML documents. By representing both XML documents and XML queries in structure-encoded sequences, we show that querying XML data is equivalent to finding subsequence matches. Unlike index methods that disassemble a query into multiple sub-queries, and then join the results of these sub-queries to provide the final answers, ViST uses tree structures as the basic unit of query to avoid expensive join operations. Furthermore, ViST provides a unified index on both content and structure of the XML documents, hence it has a performance advantage over methods indexing either just content or structure. ViST supports dynamic index update, and it relies solely on B+ Trees without using any specialized data structures that are not well supported by DBMSs. Our experiments show that ViST is effective, scalable, and efficient in supporting structural queries.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
 
4
D. Chamberlin, D. Florescu, J. Robie, J. Simon, and M. Stefanescu. XQuery: A query language for XML W3C working draft. Technical Report WD-xquery-20010215, World Wide Web Consortium, 2001.
 
5
6
 
7
J. Clark and S. DeRose. XML path language (XPath) version 1.0 w3c recommendation. Technical Report REC-xpath-19991116, World Wide Web Consortium, 1999.
8
 
9
 
10
 
11
 
12
Dan Gus eld. Algorithms on Strings, Trees, and Sequences. Cambridge University Press, 1997.
 
13
14
 
15
Michael Ley. DBLP database web site. http://www.informatik.uni-trier.de/ ley/db, 2000.
 
16
17
 
18
 
19
 
20
Sleepycat Software, http://www.sleepycat.com. The Berkeley Database (Berkeley DB).
 
21
Haixun Wang, Chang shing Perng, Wei Fan, Sanghyun Park, and Philip S. Yu. Indexing weighted sequences in large databases. In ICDE, 2003.
 
22
The internet movie database. http://www.imdb.com, 2000.
 
23
XMARK: The XML-benchmark project. http://monetdb.cwi.nl/ xml, 2002.

CITED BY  60

Collaborative Colleagues:
Haixun Wang: colleagues
Sanghyun Park: colleagues
Wei Fan: colleagues
Philip S. Yu: colleagues