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A Proposal of CS-index Approach for SPARQL Queries Considering Chain and Star Shaped Subgraphs

Published: 10 December 2018 Publication History

Abstract

The interlinking nature of web-scale RDF data makes a challenge on storage and retrieving of these data efficiently. Even though different storage and query processing techniques have been proposed, query processing on complex linking structured (RDF) data requires many join operations when the input query is large (with respect to number of triple patterns). One solution to this problem is to reduce the number of joins by indexing. Indexing is an effective technique to reduce data searching space and retrieve data as fast as possible. In this paper, we propose an indexing scheme of chain and star (CS-index) and querying approach for SPARQL queries. The proposed approach could support both chain and star shaped queries. It employs graph pattern based technology: the RDF data graph is firstly decomposed into chain and star shaped subgraphs based on the structural information of each vertex. These subgraphs are stored as index, called CS-index. When a SPARQL query is given, it is decomposed into query subgraphs based on common join variable among all triple patterns. And the query results are retrieved by matching these query subgraphs against with CS-index. The proposed approach tends to minimize the query execution time by reducing the number of join operations as well as reduce memory usage for storing data.

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Cited By

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  • (2020)Enhancement of Query Execution Time in SPARQL Query Processing2020 International Conference on Advanced Information Technologies (ICAIT)10.1109/ICAIT51105.2020.9261805(153-158)Online publication date: 4-Nov-2020

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        cover image ACM Other conferences
        IAIT '18: Proceedings of the 10th International Conference on Advances in Information Technology
        December 2018
        145 pages
        ISBN:9781450365680
        DOI:10.1145/3291280
        © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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        • KMUTT: King Mongkut's University of Technology Thonburi

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        New York, NY, United States

        Publication History

        Published: 10 December 2018

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        Author Tags

        1. RDF
        2. SPARQL query
        3. graph-based index

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        IAIT '18 Paper Acceptance Rate 20 of 47 submissions, 43%;
        Overall Acceptance Rate 20 of 47 submissions, 43%

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        • (2020)Enhancement of Query Execution Time in SPARQL Query Processing2020 International Conference on Advanced Information Technologies (ICAIT)10.1109/ICAIT51105.2020.9261805(153-158)Online publication date: 4-Nov-2020

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