Elzein, Nahla Mohammed and Mazlina, Abdul Majid and Fakherldin, Mohammed and Hashem, Ibrahim Abaker Targio (2018) Distributed Join Query Processing for Big RDF Data. Advanced Science Letters, 24 (10). p. 96. ISSN 1936-6612. (Published)
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Abstract
The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to effectively store, retrieve, and analyze resource description framework (RDF) data in swarms. Moreover, efficient data storage and retrieval that can scale to large amounts of possibly schema-less data have proven to be quite difficult to achieve, specifically, RDF data storage with complex and large graph patterns for representing semantic data, and SPARQL query languages. In this paper, we provide comprehensive discussion about the proposed algorithms of Join.Query processing of RDF data by considering MapReduce Framework in a distributed environment. Moreover, we introduced a framework for RDF query processing and the benchmark that is used for the performance evaluation. Finally, we offer an evaluation discussion on distributed join query processing for big RDF data.
| Item Type: | Article |
|---|---|
| Additional Information: | JCR® Category: Multidisciplinary Sciences. Quartile: Q2 |
| Uncontrolled Keywords: | Semantic Web; Big data; Query processing |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Pn. Hazlinda Abd Rahman |
| Date Deposited: | 27 Mar 2018 02:53 |
| Last Modified: | 27 Nov 2018 01:55 |
| URI: | http://umpir.ump.edu.my/id/eprint/20172 |
| Download Statistic: | View Download Statistics |
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