In response to the ever increasing scale, distribution, and complexity of data processing, database research in the past few years has focused on adaptive query processing. However, many of these solutions, although aimed at processing wide-area data, remain centralized solutions. In this paper, we present FREddies, an extension of the centralized Eddy operator for use in a P2P query processing system. FREddies operate within the framework of PIER, a DHT-based P2P query processor. FREddies optimize the query during runtime and require no global knowledge. We show that FREddies using rudimentary routing policies can perform competitively with a traditional static query optimization approach. Furthermore, we validate our simulation results in the real world environment of PlanetLab.