The document describes how to implement PageRank, an algorithm for ranking the importance of web pages, using Hadoop MapReduce. PageRank is calculated iteratively by treating each web page as a "random surfer" that follows links with certain probabilities based on the page's own importance ranking. The MapReduce implementation involves multiple stages where mappers distribute PageRank values to outbound links and reducers calculate new PageRank values based on the formula. The process iterates until PageRank values converge within a set threshold.