Analysis of the workload running on the file system is helpful to optimize the performance of the distributed file system and is crucial to the construction of new storage system. Due to the complexity of workload and the increase of scale diversity, it is incomplete to explicitly capture the characteristics of workload traces by intuition-based analysis. To solve this problem, a distributed log analysis and workload characteristic extraction model was proposed. First, reading and writing related information was extracted from distributed file system logs according to the keywords. Second, the workload characteristics were described from two aspects: statistics and timing. Finally, the possibility of system optimization based on workload characteristics was analyzed. Experimental results show that the proposed model has certain feasibility and accuracy, and can give workload statistics and timing characteristics in detail. It has the advantages of low overhead, high timeliness and being easy to analyze, and can be used to guide the synthesis of workloads with the same characteristics, hot spot data monitoring, and cache prefetching optimization of the system.