Poster: Analyzing Patterns in Large-Scale Graphs Using MapReduce in Hadoop

摘要

Analyzing patterns in large-scale graphs, such as social networks (e.g. Facebook, Linkedin, Twitter) has many applications including community identification, blog analysis, intrusion and spamming detections. Currently, it is impossible to process information in large -- scale graphs with millions even billions of edges with a single computer. In this project, we take advantage of MapReduce, a programming model for processing large datasets, to detect important graph patterns using open source Hadoop on Amazon EC2. The aim of this poster is to show how MapReduce cloud computing with the application of graph pattern detection scales on real world data.