  MapReduce is a popular programming model and an associated implementation for
parallel processing big data in the distributed environment. Since large scaled
MapReduce data centers usually provide services to many users, it is an
essential problem to preserve the privacy between different applications in the
same network. In this paper, we propose SDPMN, a framework that using
\textit{software defined network} (SDN) to distinguish the network between each
application, which is a manageable and scalable method. We design this
framework based on the existing SDN structure and Hadoop networks. Since the
rule space of each SDN device is limited, we also propose the rule placement
optimization for this framework to maximize the hardware supported isolated
application networks. We state this problem in a general MapReduce network and
design a heuristic algorithm to find the solution. From the simulation based
evaluation, with our algorithm, the given network can support more privacy
preserving application networks with SDN switches.
