Querying Semistructured Data Efficiently

In this paper, we address the issue of fast query processing of semistructured data. To this end, we propose a new index scheme, called the HQ-Index. The HQ-Index consists of two indexes, the H-Index and Q-Index. The H-Index is basically a hash table built upon the path expressions. It serves as a p...

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Bibliographic Details
Published inDatabase and Expert Systems Applications pp. 18 - 27
Main Authors Rho, Hongsik, Hou, Wen-Chi, Che, Dunren, Wang, Chih-Fang
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2003
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Author Data
Computer science; control theory; systems
Exact sciences and technology
Hash Table
Index Scheme
Information systems. Data bases
Memory organisation. Data processing
Query Processing
Software
Source Database
XML language
Information retrieval
Data processing
Database query
Query processing
Semistructured data
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Summary:In this paper, we address the issue of fast query processing of semistructured data. To this end, we propose a new index scheme, called the HQ-Index. The HQ-Index consists of two indexes, the H-Index and Q-Index. The H-Index is basically a hash table built upon the path expressions. It serves as a path index. The Q-Index facilitates fast traversal to the ancestor nodes in the graph and the retrieval of requested information. Not only the H-Index and Q-Index have very simple index structures, but also the combined use of them can effectively speed up the evaluation of ordinary path queries. The results of our experiments further confirm the advantage of our approach when compared with the Dataguide, one of the most referenced index schemes for XML and semistructured data.
ISBN:9783540408062
3540408061
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-45227-0_3