2011 GBASEAScalableandGeneralGraphMa

• (Kang et al., 2011) ⇒ U. Kang, Hanghang Tong, Jimeng Sun, Ching-Yung Lin, and Christos Faloutsos. (2011). “GBASE: A Scalable and General Graph Management System.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011) Journal. ISBN:978-1-4503-0813-7 doi:10.1145/2020408.2020580

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222011%22+GBASE%3A+A+Scalable+and+General+Graph+Management+System
• http://dl.acm.org/citation.cfm?id=2020408.2020580&preflayout=flat#citedby

Quotes

Author Keywords

• Algorithms; compression; data mining; design; distributed computing; experimentation; graph; indexing

Abstract

Graphs appear in numerous applications including cyber-security, the Internet, social networks, protein networks, recommendation systems, and many more. Graphs with millions or even billions of nodes and edges are common-place. How to store such large graphs efficiently? What are the core operations / queries on those graph? How to answer the graph queries quickly? We propose GBASE, a scalable and general graph management and mining system. The key novelties lie in 1) our storage and compression scheme for a parallel setting and 2) the carefully chosen graph operations and their efficient implementation. We designed and implemented an instance of GBASE using MapReduce / Hadoop. GBASE provides a parallel indexing mechanism for graph mining operations that both saves storage space, as well as accelerates queries. We ran numerous experiments on real graphs, spanning billions of nodes and edges, and we show that our proposed GBASE is indeed fast, scalable and nimble, with significant savings in space and time.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 GBASEAScalableandGeneralGraphMa	Christos Faloutsos U. Kang Jimeng Sun Hanghang Tong Ching-Yung Lin			GBASE: A Scalable and General Graph Management System				10.1145/2020408.2020580		2011