Abstract
While a number of optimizing techniques have been developed to efficiently process increasing large Semantic Web databases, these optimization approaches have not fully leveraged the powerful computation capability of modern computers. Today's multi-core computers promise an enormous performance boost by providing a parallel computing platform. Although the parallel relational database systems have been well built, parallel query computing in Semantic Web databases have not extensively been studied. In this work, we develop the parallel algorithms for join computations of SPARQL queries. Our performance study shows that the parallel computation of SPARQL queries significantly speeds up querying large Semantic Web databases.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2011 ACM Symposium on Applied Computing |
| Number of pages | 6 |
| Place of Publication | New York, NY, USA |
| Publisher | ACM |
| Publication date | 21.03.2011 |
| Pages | 1681-1686 |
| ISBN (Print) | 978-1-4503-0113-8 |
| DOIs | |
| Publication status | Published - 21.03.2011 |
| Event | 26th Annual ACM Symposium on Applied Computing - TaiChung, Taiwan, Province of China Duration: 21.03.2011 → 24.03.2011 Conference number: 85134 |
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
- Research Area: Intelligent Systems
DFG Research Classification Scheme
- 409-04 Operating, Communication, Database and Distributed Systems
