Semantic connection set-based massive RDF data query processing in Spark environment
Abstract Resource Description Framework (RDF) is a data representation of the Semantic Web, and its data volume is growing rapidly. Cloud-based systems provide a rich platform for managing RDF data. However, there is a performance challenge in the distributed environment when RDF queries, which cont...
Main Authors: | Jiuyun Xu, Chao Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2019-11-01
|
Series: | EURASIP Journal on Wireless Communications and Networking |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13638-019-1588-9 |
Similar Items
-
Design and evaluation of a NoSQL database for storing and querying RDF data
by: Kanda Runapongsa Saikaew, et al.
Published: (2014-12-01) -
Temporal Data Representation and Querying Based on RDF
by: Fu Zhang, et al.
Published: (2019-01-01) -
Path Index Based Keywords to SPARQL Query Transformation for Semantic Data Federations
by: Thilini Cooray, et al.
Published: (2016-06-01) -
An Efficient Distributed SPARQL Query Processing Scheme Considering Communication Costs in Spark Environments
by: Jongtae Lim, et al.
Published: (2021-12-01) -
Adaptive and Optimized RDF Query Interface for Distributed WFS Data
by: Tian Zhao, et al.
Published: (2017-04-01)