We study the problem of evaluating conjunctive queries composed of triple patterns over RDF data stored in distributed hash tables. Our goal is to develop algorithms that scale to large amounts of RDF data, distribute the query processing load evenly and incur little network traffic. We present and evaluate two novel query processing algorithms with these possibly conflicting goals in mind. We discuss the various tradeoffs that occur in our setting through a detailed experimental evaluation of the proposed algorithms.