IP multicast is a technique to save bandwidth when sending multimedia traffic to multiple users. However, to provide end-to-end quality of service (QoS) for multicast applications is still a challenging problem. The recently emerging technique, software defined network(SDN), provides a flexible network management capability by decoupling the data plane and the control plane. The control plane can be programmable to intelligently allocate network resources based on the information collected from the data plane. In this paper, we propose an end-to-end QoS multicast mechanism in SDN environments. We design an algorithm which adaptively provides the bandwidth provision via a learning mechanism for the multimedia traffic. Thus, QoS of multimedia flows could be guaranteed effectively and efficiently even under heavy-loaded scenarios. In addition, the learning approach is to utilize the link bandwidth efficiently by predicting the required QoS bandwidth. Furthermore, low priority packets are forwarded statistically among N different routes to mitigate the congesting link problem. Such a design could prevent the oscillation problem which could exist in traditional approaches which are to reroute the multimedia traffic to other routes. Our design leverages the flexible functions provided by SDN protocols. The performance is evaluated in a real SDN environment. The experimental results show the effectiveness of the proposed algorithm.