X-RIME Chart (http://xrime.sourceforge.net/)

X-RIME: Hadoop based large scale social network analysis

Motivation

Today's Internet-based social network sites possess huge user communities. They hold large amount of data about their users and want to generate core competency from the data. A key enabler for this is a cost efficient solution for social data management and social network analysis (SNA).

Such a solution faces a few challenges. The most important one is that the solution should be able to handle massive and heterogeneous data sets. Facing this challenge, the traditional data warehouse based solutions are usually not cost efficient enough. On the other hand, existing SNA tools are mostly used in single workstation mode, and not scalable enough. To this end, low cost and highly scalable data management and processing technologies from cloud computing society should be brought in to help.

However, most of existing cloud based data analysis solutions are trying to provide SQL-like general purpose query languages, and do not directly support social network analysis. This makes them hard to optimize and hard to use for SNA users. So, we came up with X-RIME to fix this gap.

So, briefly speaking, X-RIME wants to provide a few value-added layers on top of existing cloud infrastructure, to support smart decision loops based on massive data sets and SNA. To end users, X-RIME is a library consists of Map-Reduce programs, which are used to do raw data pre-processing, transformation, SNA metrics and structures calculation, and graph / network visualization. The library could be integrated with other Hadoop based data warehouses (e.g., HIVE) to build more comprehensive solutions.

About the Project

This project is a join effort of Beijing University of Posts and Telecommunications (BUPT) and IBM China Research Lab, supported by IBM Open Collaboration Research program. The code is open source under Apache License V2.0.

Currently Supported SNA Metrics and Structures

• vertex degree statistics
• weakly connected components (WCC)
• strongly connected components (SCC)
• bi-connected components (BCC)
• ego-centric network density
• bread first search / single source shortest path (BFS/SSSP)
• K-core
• maximal cliques
• pagerank
• hyperlink-induced topic search (HITS)
• minimal spanning tree (MST)
• grid variant of Fruchterman-Reingold network layout algorithm

References

• Social Network Analysis: A Handbook,John P Scott ,Sage Publications Ltd; 2nd edition (March 25, 2000).
  
• "Finding Strongly Connected Components in Distributed Graphs",William McLendon III, Bruce Hendrickson, Steven J. Plimpton, Lawrence Rauchwerger, http://www.sandia.gov/~sjplimp/papers/jpdc05.pdf
• "An Experimental Study of Parallel Biconnected Components Algorithms on Symmetric Multiprocessors (SMPs)", Cong, Guojing, Bader, David A., http://smartech.gatech.edu/bitstream/1853/14382/1/GT-CSE-06-03.pdf
• "Graph Algorithms with MapReduce" .Jimmy Lin (2008).
• "An O(m) Algorithm for Cores Decomposition of Networks",V. Batagelj, M. Zaversnik, http://vlado.fmf.uni-lj.si/pub/networks/doc/cores/cores.pdf
• "Finding All Cliques of an Undirected Graph",Coen Bron, Joep Kerbosch, http://www.dfki.de/~neumann/ie-seminar/presentations/finding_cliques.pdf
  
• "On Computing All Maximal Cliques Distributedly",Fábio Protti, Felipe M. G. França, and Jayme Luiz Szwarcfiter, http://www.springerlink.com/content/g5km75g7u2l80446/fulltext.pdf
• "The PageRank citation ranking: Bringing order to the Web" . Page, Lawrence ; Brin, Sergey ; Motwani, Rajeev and Winograd, Terry (1999).
• "Algorithms for Estimating Relative Importance in Networks" . Scott White and Padhraic Smyth (2003).
• "Authoritative sources in a hyperlinked environment" .Kleinberg, Jon (1999).Journal of the ACM 46 (5): 604¨C632
• "Improvement of HITS-based Algorithms on Web Documents" . Li, L.; Shang, Y.; Zhang, W. (2002).Proceedings of the 11th International World Wide Web Conference (WWW 2002).
• "A Distributed Algorithm for Minimum-Weight Spanning Trees",R. G. Gallager, P. A. Humblet, P. M. Spira, http://www.cs.tau.ac.il/~afek/p66-gallager.pdf
•  "Graph Drawing by Force-directed Placement", Thomas M. J. Fruchterman, Edward M. Reingold, http://www.cs.ubc.ca/local/reading/proceedings/spe91-95/spe/vol21/issue11/spe060tf.pdf

History

Release V1.0.0        2009-09-04

Maintainers

1. Bin Cai, [email protected]
2. Wei Xue, [email protected]