The latest increasing popularity of high-speed railways (HSR) has stimulated growing demands for wireless Internet services in HSR networks, especially for video streaming. However, due to the high variability and unpredictability of wireless communications in HSR networks, it is still difficult for the existing solutions to provide high-quality video streaming services to HSR passengers. This paper addresses this crucial problem first by reporting on field experiments performed to investigate the characteristics of HSR networks. Then the paper formulates an intractable optimization problem for dynamic adaptive streaming over HTTP (DASH)-enabling service in HSR networks considering various factors, including packet loss, energy consumption, video service quality, etc. By leveraging Lyapunov optimization approaches, the formulated optimization problem is transformed into a queue stability problem which is of high scalability and generality. Moreover, in order to overcome the intractability of the initial optimization problem, the queue stability problem is further decomposed into three subproblems which can be easily solved individually. Finally, a novel joint stochastic DASH optimization (JSDO) mechanism consisting of three algorithms for the derived subproblems is proposed. Rigorous theoretical analyses and realistic dataset-based simulations demonstrate the effectiveness of the proposed JSDO mechanism.