SparkRDF: In-Memory Distributed RDF Management Framework for Large-Scale Social Data | |
Xu, Zhichao ; Chen, Wei ; Gai, Lei ; Wang, Tengjiao | |
2015 | |
关键词 | RDF SPARQL Social networks Query processing |
英文摘要 | Considering the scalability and semantic requirements, Resource Description Framework (RDF) and the de-facto query language SPARQL are well suited for managing and querying online social network (OSN) data. Despite some existing works have introduced distributed framework for querying large-scale data, how to improve online query performance is still a challenging task. To address this problem, this paper proposes a scalable RDF data framework, which uses key-value store for offline RDF storage and pipelined in-memory based query strategy. The proposed framework efficiently supports SPARQL Basic Graph Pattern (BGP) queries on large-scale datasets. Experiments on the benchmark dataset demonstrate that the online SPARQL query performance of our framework outperforms existing distributed RDF solutions.; EI; CPCI-S(ISTP); xuzhichao@pku.edu.cn; pekingchenwei@pku.edu.cn; lei.gai@pku.edu.cn; tjwang@pku.edu.cn; 337-349; 9098 |
语种 | 英语 |
出处 | WEB-AGE INFORMATION MANAGEMENT (WAIM 2015) |
DOI标识 | 10.1007/978-3-319-21042-1_27 |
内容类型 | 其他 |
源URL | [http://ir.pku.edu.cn/handle/20.500.11897/423647] |
专题 | 信息科学技术学院 |
推荐引用方式 GB/T 7714 | Xu, Zhichao,Chen, Wei,Gai, Lei,et al. SparkRDF: In-Memory Distributed RDF Management Framework for Large-Scale Social Data. 2015-01-01. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论