Actual ranking at the time of your search does not involve too much computation, because a lot has been precomputed and stored in those Google indexes. In theo

Actual ranking at the time of your search does not involve too much computation, because a lot has been precomputed and stored in those Google indexes. In theory, you can view every search as a function of your query and all the web documents out there. This function is partially evaluated for a fixed universe of documents and super optimized. Evaluating hundreds of parameters is common sense for machine learning tasks. If you look at the papers explaining how the top Netflix prize competitors achieve their score, this is again what they do: they run literally hundreds of algorithms over the dataset and then blend the results. And this is for a domain where their data is only (user, movie, rating, date) quadriplets.