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	SparkRDF: In-Memory Distributed RDF Management Framework for Large-Scale Social Data
	Zhichao Xu ; Wei Chen ; Lei Gai ; Tengjiao Wang
	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 inmemory 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.; 337-349
语种	英语
出处	International Conference on Web-Age Information Management
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/451317]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhichao Xu,Wei Chen,Lei Gai,et al. SparkRDF: In-Memory Distributed RDF Management Framework for Large-Scale Social Data. 2015-01-01.

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