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- Publisher
- Association for Computing Machinery
- Copyright
- Copyright © 2011 by ACM Inc.
- ISSN
- 1556-4681
- DOI
- 10.1145/1921632.1921634
- Publisher site
- See Article on Publisher Site
Abstract
TKD00018 ACM (Typeset by SPi, Manila, Philippines) 1 of 24 February 23, 2011 HADI: Mining Radii of Large Graphs U. KANG and CHARALAMPOS E. TSOURAKAKIS, Carnegie Mellon University ANA PAULA APPEL, Universidade de Sao Paulo at Sao Carlos ˜ ˜ CHRISTOS FALOUTSOS, Carnegie Mellon University JURE LESKOVEC, Stanford University Given large, multimillion-node graphs (e.g., Facebook, Web-crawls, etc.), how do they evolve over time? How are they connected? What are the central nodes and the outliers? In this article we de ne the Radius plot of a graph and show how it can answer these questions. However, computing the Radius plot is prohibitively expensive for graphs reaching the planetary scale. There are two major contributions in this article: (a) We propose HADI (HAdoop DIameter and radii estimator), a carefully designed and ne-tuned algorithm to compute the radii and the diameter of massive graphs, that runs on the top of the H ADOOP/M AP R EDUCE system, with excellent scale-up on the number of available machines (b) We run HADI on several real world datasets including YahooWeb (6B edges, 1/8 of a Terabyte), one of the largest public graphs ever analyzed. Thanks to HADI, we report fascinating patterns on large
Journal
ACM Transactions on Knowledge Discovery from Data (TKDD) – Association for Computing Machinery
Published: Feb 1, 2011