Research on Real-time Log Data Processing And Monitoring Scheme of Printing Equipment Based on Flink Framework

With the arrival of the era of big data, machinery, information sensors and other equipment in the printing industry generate large-scale equipment log data through the running time. Mining and analyzing the real-time log data of these equipment can extract the potential value for detecting, warning, optimizing machinery and equipment and improving the efficiency of enterprises. However, these massive data have the characteristics of large-scale data, complex and changeable types and strong real-time, which are difficult to collect, detect and use effectively. In view of the above problems, this paper uses the distributed computing framework Flink, takes the real-time data of information sensors as the premise, combines Kafka message queue for real-time data caching, and uses the distributed open-source monitoring system ZABBIX and visualization tool Grafana for monitoring and early warning, effectively solving the real-time processing and analysis of equipment data.