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SPARQL Query Optimization For Structural Indexed RDF Data
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Sangyoon Oh | - |
| dc.contributor.author | Nguyen Minh Duc | - |
| dc.date.accessioned | 2018-11-08T08:04:57Z | - |
| dc.date.available | 2018-11-08T08:04:57Z | - |
| dc.date.issued | 2013-08 | - |
| dc.identifier.other | 15062 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/10250 | - |
| dc.description | 학위논문(석사)아주대학교 일반대학원 :컴퓨터공학과,2013. 8 | - |
| dc.description.tableofcontents | 1. Introduction 1 2. Background and related works 4 2.1 RDF and SPARQL 4 2.1.1 RDF 4 2.1.2 SPARQL 5 2.2 Related works of RDF data management 7 2.2.1 Relational DB system perspective 7 2.2.2 RDF graph-based perspective 10 3. SPARQL query evaluation with execution plan 14 3.1 System overview 14 3.2 Structural indexed RDF data with key-value based storage 16 3.3 Query Optimization with execution plan 19 3.4 Query processing 22 4. Experiment 26 4.1 Environment and data setup 26 4.2 Preparing queries 27 4.3 Experiment result 30 5. Conclusion and future work 33 5.1 Conclusion 33 5.2 Future work 34 REFERENCES 36 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | SPARQL Query Optimization For Structural Indexed RDF Data | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.department | 일반대학원 컴퓨터공학과 | - |
| dc.date.awarded | 2013. 8 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 571068 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000015062 | - |
| dc.description.alternativeAbstract | Resource Description Framework (RDF), a standard language model for representing semantic data, becomes more important to retrieve and exchange information as the Semantic Web gets more viable. Because efficient management of RDF data is one of the key research issues in Semantic Web, there are many RDF management system proposals with data storage architectures and query processing algorithms to retrieve data. However, most of approaches require many join operations based on the complexity of the queries and produce a lot of unnecessary intermediate results to processing SPARQL queries. The problem gets more serious with a huge amount of RDF data source. In this thesis, we propose a new structural index in an efficient manner with a query optimizer for processing query for a large scale RDF data without any join operations using structural indexing approach. In this approach, we process the query with it execution plan to reduce the useless intermediate data, hence improve performance of querying RDF data. The empirical experiment results show that our proposed system outperforms a system such as Jena that uses conventional approach by reducing unnecessary intermediate results in query processing. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Computer Engineering > 3. Theses(Master)
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