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Nowadays data analytics applications are accessing more and more data from distributed data stores, creating a large amount of data traffic on the network. Therefore, distributed analytic queries are prone to suffer from poor performance when they encounter network contention, which can be quite common in a shared network. Typical distributed query optimizers do not have a way to solve this problem because they treat the network as a black-box: they are unable to monitor it, let alone control it. With the new era of software-defined networking (SDN), we show how SDN can be effectively exploited for performance management for analytical queries in distributed data store environments. More specifically, we present a group of methods to leverage SDN's visibility into and control of the network's state that enable distributed query processors to achieve performance improvements and differentiation for analytical …