Practicals - Data Science

Tuesday, June 29, 2010

Design Patterns for Efficient Graph Algorithms in MapReduce


Abstract
1. Introduction
2. MapReduce
3. Graph Algorithms
4. Basic Implementation
4.1 Message Passing
4.2 Local Aggregation
5. Algorithm Optimizations
5.1 In-Mapper Combining
5.2 Schimmy
5.3 Range Partitioning
6. Results
7. Future Works and Conclusions
8. Acknowledgements
9. References
Posted by Simplicio Gamboa III at 2:08 PM
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  • ▼  2010 (36)
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      • Handbook of Statistical Analysis and Data Mining
      • Data Mining: Practical Machine Learning Tools and ...
      • Programming Collective Intelligence
      • Efficient Parallel Set-Similarity Joins Using MapRe...
      • EigenSpokes: Surprising Patterns and Scalable Comm...
      • Design Patterns for Efficient Graph Algorithms in M...
      • Hadoop Summit 2010 - Presentation Slides & Videos
      • Some activities in a data science team
      • MapReduce: Simplified Data Processing on Large Clu...
      • The Unreasonable Effectiveness of Data
      • Experiences Evolving a New Analytical Platform: Wh...
      • Pregel: A System for Large-Scale Graph Processing
      • FlumeJava: Easy, Efficient Data-Parallel Pipelines
      • Hadoop: The Definitive Guide

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