基于流计算的电力调度网络流量监测平台

由于电力调度网出现任何网络故障都可能发生极度严重的事故，因此具有的极高可靠性及安全性的要求.而当前传统的网络监测系统在面对大数据量时，其实时处理能力和扩展能力都无法满足需求.因此对实时产生的大规模各类型数据的分析处理则需要一种专门的实时数据分析平台完成.本文结合电力调度信息网络的特点以及监测准确性及实时性的需求，构建出一个基于流计算的数据处理分析平台，以Apache Spark中的Spark Streaming为代表的开源流计算框架，加入如Kafka分布式消息队列、Redis内存数据库等组件，为数据分析平台提供稳定高效的数据来源和数据服务接口，从而实现适用于电力调度网的各类海量数据的实时分析处理完成流量异常监测场景.

Power Dispatch Network Flow Monitoring Platform Based on Flow Calculation

Due to any network failure of the power dispatching network may lead to serious accidents, it is required to have high reliability and safety. Faced the large amount of data, the traditional network monitoring system cannot meet the demand at present in terms of the actual processing capacity and expansion capacity. Therefore, a special real-time data analysis platform is needed for the real-time analysis and processing of large amount of data. This study constructed a platform based on flow calculation. Spark Streaming in Apache Spark of the open source stream computing framework, adding Kafka message queue and Redis memory database components, provides stable data sources and efficient interface for data analysis and data service platform, so as to realize the real-time analysis and processing of all kinds of massive data, thus to complete the flow anomaly monitoring of power dispatching network.