I think the basic gist of the article is that originally he was comparing movie X to every other movie, one at a time, and in any single such comparison he had to fetch all the users who had rated both movies to calculate the Pearson correlation. But later he realized it's much more efficient to just cycle through the users themselves who have rated movie X and check what other movies they have rated and to calculate the Pearson correlations from that data.