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To reduce the energy consumption and optimize the allocation of resources in big data cloud center, a virtual machine resource allocation strategy is proposed. The proposed method defines the clustering of the selected features with similar task grouping, and maps the tasks of each group to the customized efficient virtual machine type. And this efficiency is the successful implementation of tasks with minimal resource depletion. The parameters of virtual machine are the number of cores, memory and storage. The virtual machine is based on the historical data extracted from the log trace, and it is based on the usage pattern of the task. The proposed resource allocation strategy is based on the actual resource usage of the task, and the energy consumption is reduced. The experimental results show that the proposed virtual machine resource allocation strategy can save energy consumption and reduce the average number of tasks in different cases of clustering.