A MapReduce iteration framework in local parallel and message synchronization

With the development of large-scale distributed computing, Stand-alone operating environment to meet the demand of the time and space overhead of massive data based on. There is more attention to how to design the distributed algorithm for efficient cloud computing environment. The MapReduce model cannot solve the issue. In this paper, the redesign of the computing model of MapReduce, ensure the existing calculation models compatible with the old MapReduce operation. At the same time, the framework used the message synchronization mechanism to implement state data changing interaction tasks in Parallel Layer. Compared to the original MapReduce operation, greatly reduces the processing time of the MapReduce iterative algorithm. © (2013) Trans Tech Publications, Switzerland