用于状态监测与诊断的Flink流式处理系统

FLINK STREAMING PROCESSING SYSTEM FOR CONDITION MONITORING AND DIAGNOSIS

  • 摘要: 为提升基于设备监测数据流开展故障诊断的能力,设计开发Flink流式处理系统。构建多通道传感器数据分布式并行处理的数据流处理流程,开发流程中包含各类算子,从而将监测数据流转化成诊断结果数据流。搭建Flink集群,开展系统功能和性能测试,结果表明:系统延迟时间<1 ms,数据处理完整率为100%,乱序数据恢复率为100%,job manager、task manager故障自动恢复时间分别为62 s、26 s。基于Flink的设备状态监测与诊断系统满足低延迟、精确一次一致性、可容错的要求。

     

    Abstract: In order to enhance the ability of fault diagnosis based on data streaming collected as equipment operating, Flink streaming processing systemis designed and developed. The distributed parallel processing flowgraph was designed for multi-channel sensory data. The operators of the flowgraph were developed. Therefore, Flink application transformed the input streaming into diagnosis output streaming. The Flink clusters were built to carry out functional and performance testing. The results indicate that the delay time is less than 1 ms, data integrity rate is 100%, disorderly data restoration rate is 100%, and the recovery time for job manager fault and task manager fault are 62 s and 26 s respectively. The Flink-based system satisfies the requirements of low latency, exactly-once consistency, and fault tolerance.

     

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