The fairness of multi-resource allocation is one of the most important indicators in the resource scheduling subsystem, Dominant Resource Fairness (DRF), as a general resource allocation algorithm for multi-resources scenarios, it may be unfair in heterogeneous cluster environment. On the basis of the research on the DRF multi-resource fair allocation algorithm under Mesos framework environment, meDRF allocation algorithm was designed and implemented to evaluate the influence factors of the performance of the server. The machine performance scores of computing nodes, as the dominant factor of DRF share calculation, made computing tasks have equal chance to obtain high quality computing resources and poor computing resources. Experiments were conducted by using K-means, Bayes and PageRank jobs under Hadoop. The experimental results show that, compared with DRF allocation algorithm, the meDRF algorithm can reflect more fairness of the allocation of resources, and the allocation of resources has better stability, which effectively improves the utilization of system resources.