The Internet community has recently become interested in distributed query processing. Not surprisingly, they approach this problem from a very different angle than the traditional database literature. The fundamental goal of Internet systems is to operate at very large scale (thousands if not millions of nodes). To achieve this degrees of scale, these system sacrifice transparency and/or flexibility.

This thesis develops a system called PIER (which stands for "Peer-to-Peer Information Exchange and Retrieval") which provides a rich query language that provides location transparency and scalability with relaxed semantics. We explore the architecture of PIER, develop techniques for query processing (with specific focus on aggregation and join operations), and finally examine an optimization problem with multiple simultaneous aggregation queries.