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	GLog: A high level graph analysis system using MapReduce
	Gao, Jun ; Zhou, Jiashuai ; Zhou, Chang ; Yu, Jeffrey Xu
	2014
英文摘要	With the rapid growth of graphs in different applications, it is inevitable to leverage existing distributed data processing frameworks in managing large graphs. Although these frameworks ease the developing cost, it is still cumbersome and error-prone for developers to implement complex graph analysis tasks in distributed environments. Additionally, developers have to learn the details of these frameworks quite well, which is a key to improve the performance of distributed jobs. This paper introduces a high level query language called GLog and proposes its evaluation method to overcome these limitations. Specifically, we first design a RG (Relational-Graph) data model to mix relational data and graph data, and extend Datalog to GLog on RG tables to support various graph analysis tasks. Second, we define operations on RG tables, and show translation templates to convert a GLog query into a sequence of MapReduce jobs. Third, we propose two strategies, namely rule merging and iteration rewriting, to optimize the translated jobs. The final experiments show that GLog can not only express various graph analysis tasks in a more succinct way, but also achieve a better performance for most of the graph analysis tasks than Pig, another high level dataflow system. ? 2014 IEEE.; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/ICDE.2014.6816680
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/295559]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Gao, Jun,Zhou, Jiashuai,Zhou, Chang,et al. GLog: A high level graph analysis system using MapReduce. 2014-01-01.

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