Parallel PageRank Algorithm Using MapReduce

摘要

PageRank algorithm is used to determine the relevance of a web page based on the user query. It is among one of the most effective algorithms for working out on the relevance of website pages across the globe. In the world of computation, the web is a large dataset represented in the structure as a graph with billions of hubs and links that represent various features of the web page. It is difficult to find the relevance of pages and takes a large amount of time as it uses a huge number of calculations. Using basic PageRank algorithm, causes the main problem to measure the PageRank of the web page, to evaluate this problem the algorithm can be parallelized to achieve higher efficiency in terms of time, speed and accuracy. This basic algorithm of PageRank can be implemented using MapReduce in Hadoop Framework, which results in the Parallel PageRank algorithm using MapReduce works efficiently in terms of time, speed and accuracy. Our experimental results performed on different clusters deliveries higher efficiency.