Peer-to-peer file-sharing systems have hundreds of thousands of users sharing petabytes of data, however, their search functionality is limited. In general, query results contain many references to the same data object. These references are grouped, and the size of the group — the number of references it contains — is the typical ranking metric. Although group size is effective in finding popular data, it works poorly for rare, less popular data. Other ranking functions, such as precision and cosine similarity, are more appropriate in this case. We show the significant performance benefit in finding rare data using these ranking functions through extensive simulation.