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Traditionally, distributed databases assume that the (small) set of nodes participating in a query is known apriori, the data is well placed, and the statistics are readily available. However, these assumptions are no longer valid in a peer-based database management system (PDBMS). As such, it is a challenge to process and optimize queries in a PDBMS. In this paper, we present our distributed solution to this problem for multi-way join queries. Our approach first processes a multi-way join query based on an initial query evaluation plan (generated using statistical data that may be obsolete or inaccurate); as the query is being processed, statistics obtained on-the-fly are used to (continuously) refine the current plan dynamically into a more effective one. We have conducted an extensive performance study which shows that our adaptive query processing strategy can reduce the network traffic significantly.