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ROBUST contributes to Apache Giraph

A key focus of ROBUST is the analysis of huge social graphs. For general-purpose big data computation, the map-reduce computing model has been well adopted and the most deployed map-reduce infrastructure is Apache Hadoop. However the map-reduce paradigm is not well suited for processing such large graphs. One of the core tasks of research in the ROBUST project is to identify more suitable and powerful paradigms for implementing large scale graph algorithms.

Apache Giraph is a graph-processing framework that is launched as a typical Hadoop job to leverage existing Hadoop infrastructure, such as Amazon's EC2. Giraph builds upon the graph-oriented nature of Google Pregel but additionally adds fault-tolerance to the coordinator process with the use of ZooKeeper as its centralized coordination service. Giraph follows the bulk-synchronous parallel model relative to graphs where vertices can send messages to other vertices during a given superstep.

Sebastian Schelter, PhD student in the ROBUST project, has recently joined the Giraph team as committer and PMC member and will work on the adaption of ROBUST's algorithms to this platform in the next year. He has already contributed to the 0.1 release of Apache Giraph that was announced this week.

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Apache Giraph reaches 0.1 milestone

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