Concerning the problems of resource allocation about uneven distribution, low efficiency, dislocation and so on, a new algorithm named Global Dominant Resource Fair (GDRF) allocation algorithm which adopts several rounds of allocation was proposed to meet the needs of different users, achieve multiple types of resource fairness, and get high resource utilization. First, a qualification queue was determined by allocated resource amount of the users, then the specific user was determined to allocate resource through the global dominant resource share and the global dominant resource weight. The matching condition of resources was took into account in allocation process and the progressive filling of Max-Min strategy was used. In addition, the universal fairness evaluation model of multi-resource allocation was applied to the specific algorithm. Comparison experiments were conducted based on a Google's cluster. Experimental results show that compared with maximizing multi-resource fairness based on dominant resource, the amount of allocated virtual machine is increased by 12%, the resource utilization is increased by 0.5 percentage points, and fairness evaluation value is increased by about 15%. The proposed algorithm has a high degree of adaptation of resources combination allocation, allowing the supply to better match users' demand.