Deriving Highly Efficient Implementations of Parallel PageRank

摘要

In 1999, Page et al. described their algorithm - PageRank - for scoring pages in their web search engine, Google. Already from the start it was clear that due to the large number of pages to be ranked, the PageRank algorithm's efficiency and optimal performance was and is a critical feature. One method of increasing the efficiency of calculations is based on MapReduce, also originally published by Google. In this paper, we use the forelem framework to go from an initial specification of PageRank to a much more performant implementation.