Automobile production action data collection method, system and device and storage medium

Abstract

The invention discloses an automobile production action data collection method, system and device and a storage medium. The method comprises the following steps: acquiring action data of automobile production equipment; uploading the action data to a Kafka message queue; consuming the action data of the Kafka message queue through an Flink cluster; and processing the action data in a distributed manner, wherein the action data is streaming data. According to the invention, the architecture advantage of distributed streaming real-time data processing of the Flink platform assembly is utilized;a traditional single-thread Cycle calculation algorithm is correspondingly improved, and then a single-thread Cycle calculation algorithm is obtained. The method is applied to a calculation algorithmwhich is provided by Flink and used for processing Cycle in a distributed mode, the performance of real-time data monitoring processing is improved through a new architecture application mode, currentdata accumulation and performance bottlenecks are solved, and real-time monitoring of action data of automobile production is achieved. The method is widely applied to the technical field of automobile production.

Description

technical field [0001] The invention relates to the technical field of automobile production, in particular to a method, system, device and storage medium for collecting automobile production action data. Background technique [0002] Data storage and data analysis and mining in the automobile production process are in their infancy. Most of the current data storage is stand-alone storage, so the current application of data analysis and mining is relatively small, and the performance of data analysis and mining has a greater impact on production efficiency. , so that in the process of automobile production, the production cost remains high. On the other hand, in the daily automobile production process, the real-time monitoring delay in operation and maintenance is relatively long. This is because after collecting data from production, most of the data will be stored in the time series database or mysql database first, and then Unified calculation and output, which leads to ...

AI Technical Summary

Problems solved by technology

When calculating Cycle currently, the performance of single-threaded processing of Cycle data is very slow, and the accumulation of Cycle data in the cache queue is very serious. When it is particularly serious, the delay of accumulating data in the cache queue reaches 2 hours, which seriously affects the performance of the car. Production action data monitoring

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