1. A computer-implemented method for reducing an amount of ranking data analyzed at query time, the method comprising computer-implemented operations for: at index time, selecting a term from a master index, the term corresponding to a number of documents greater than a threshold; selecting a set of documents that includes the term based on the master index; determining a rank for each document in the set of documents that contains the term; assigning each document in the set of documents that contains the term to a top document list for the term or a bottom document list for the term based on the rank; storing predefined values of at least part of the rank in the top document list for documents in the top document list and not storing the predefined values of at least part of the rank in the bottom document list for documents in the bottom document list; at query time, determining whether each query term in a query is common; upon determining that each query term is common, populating a document result set with at least a subset of documents from the top document list and the bottom document list that satisfy the query, each of the subset of documents occurring in the top document list for at least one term in the query; upon populating the document result set, retrieving the predefined values from the top document list; ranking the document result set according to a linear model based on the predefined values for documents from the top document list and zero values for documents from the bottom document list; and transmitting a reduced subset of the document result set having the highest linear rank to a ranking function adapted to re-rank the documents in the reduced subset.
8. The computer-implemented method of claim 1 , wherein the document result set comprises documents that include every term in the query.