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With the increase of glass detection speed, some defects of MapReduce distributed computing framework are exposed, and the processing speed and timeliness cannot meet the requirements of industrial glass defect detection technology. Based on the MapReduce parallel computing framework, the paper designs a threshold segmentation method to complete the segmentation of glass defect images. By adding a streaming data processing module and a data partitioning module, the computing and storage are localized, and the timeliness of data processing is accelerated. The experiment results show that the improved MapReduce computing framework has an average processing speed increase of 14.1%. It can detect the glass ribbon running at 600m/h and detect the number, position and type of defects on the glass ribbon.