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Shortest Path Computing in Relational DBMSs
Gao, Jun ; Zhou, Jiashuai ; Yu, Jeffrey Xu ; Wang, Tengjiao
刊名ieee知识与数据工程汇刊
2014
关键词Relational database graph shortest path QUERIES NETWORKS
DOI10.1109/TKDE.2013.43
英文摘要This paper takes the shortest path discovery to study efficient relational approaches to graph search queries. We first abstract three enhanced relational operators, based on which we introduce an FEM framework to bridge the gap between relational operations and graph operations. We show new features introduced by recent SQL standards, such as window function and merge statement, can improve the performance of the FEM framework. Second, we propose an edge weight aware graph partitioning schema and design a bi-directional restrictive BFS (breadth-first-search) over partitioned tables, which improves the scalability and performance without extra indexing overheads. The final extensive experimental results illustrate our relational approach with optimization strategies can achieve high scalability and performance.; Computer Science, Artificial Intelligence; Computer Science, Information Systems; Engineering, Electrical & Electronic; SCI(E); EI; 0; ARTICLE; gaojun@pku.edu.cn; zjiash@pku.edu.cn; yu@se.cuhk.edu.hk; tjwang@pku.edu.cn; 4; 997-1011; 26
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/215321]  
专题信息科学技术学院
推荐引用方式
GB/T 7714
Gao, Jun,Zhou, Jiashuai,Yu, Jeffrey Xu,et al. Shortest Path Computing in Relational DBMSs[J]. ieee知识与数据工程汇刊,2014.
APA Gao, Jun,Zhou, Jiashuai,Yu, Jeffrey Xu,&Wang, Tengjiao.(2014).Shortest Path Computing in Relational DBMSs.ieee知识与数据工程汇刊.
MLA Gao, Jun,et al."Shortest Path Computing in Relational DBMSs".ieee知识与数据工程汇刊 (2014).
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