PageRank Matrix Partitioned Algorithm Using Hadoop-MapReduce

PageRank is the classical algorithm of Web structure mining,already has been a huge success in Google search engine.But the more iterative times,the more space-time consumption,execution speed and convergence speed are slower.Put forward a kind of parallel MapReduce framework,realize matrix partition using PageRank algorithm,as a matter of fact substance is the iterations of reducing MapReduce frame structure in Map and Reduce phase,thus reducing space-time overhead.Finally build Hadoop-MapReduce open-source platform,simulate Web structure climb taking,the performance in traditional algorithm and improved algorithm is compared.Results show the improved algorithm has lower iteration times,higher parallel efficiency,using PageRank identification shows its superiority in the simulation environment.