At present, in smart city and other applications, message middleware Kafka is usually used to distribute massive image terminal data to business components such as data analysis. However, in practical business applications, it is found that the traditional Kafka message distribution mode is usually difficult to apply to high real-time massive data distribution scenarios. To solve this problem, the message distribution mode of the system is optimized, and a mode of separating normal real-time distribution from abnormal reissue is proposed. In this distribution mode, when the subscriber is normal, the message is directly distributed to the subscriber in real time. When the subscriber is abnormal, Kafka is responsible for reissuing the message after fault recovery. The experimental results show that the delay and resource consumption of the distribution mode are significantly reduced, the delay is reduced by 60% ~ 70%, and the CPU and memory utilization are reduced by 45% and 43% respectively.
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