制造行业机械日志高吞吐量数据采集系统的实现

Jaehui Park, Su-Young Chi
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引用次数: 8

摘要

本文旨在介绍一个为制造商设计和实现数据摄取系统的案例研究。在我们的实现中,提出了用于高吞吐量数据摄取的集群服务器架构,考虑了以下因素:从一组铣床接收流数据,即机器日志,将它们存储在集中的消息队列中,并轻松地下沉到外部系统。特别是,我们利用开源框架、Apache Kafka、Apache Hadoop File System和Apache Flume的强大功能来处理来自工厂车间大量机器的数据流。由于这是一项正在进行的研究,我们仅用结构图说明我们的实现细节,而不包括本文的理论研究和性能评估结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An implementation of a high throughput data ingestion system for machine logs in manufacturing industry
This paper aims at presenting a case study of designing and implementing a data ingestion system for manufacturers. In our implementation, clustered server architecture for high throughput data ingestion is proposed with regard to following factors: receiving stream data, i.e., machine logs, from a set of milling machines, storing them in a centralized messaging queue, and sinking to external systems with ease. Especially, we leverage the power of the open sources frameworks, Apache Kafka, Apache Hadoop File System and Apache Flume to cope with the data streams from a large number of machines in the factory floors. As this is an on-going study, we only illustrate our implementation details with structural diagrams, but exclude the theoretical study and the performance evaluation results in this paper.
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