摘要
针对大规模电力设备监测数据存储和批量计算问题,基于云计算平台,应用大数据计算服务(MaxCompute)实现了电力设备监测数据的高效分区存储和并行化的批量特征分析,并将分析过程组织为工作流,实现了数据加载、分析任务的自动化周期调度。所设计的存储和并行分析算法可以有效应对TB/PB级海量电力设备监测数据分析和计算场景。
Aiming at the problem of large-scale power equipment monitoring data storage and batch calculation, based on the cloud computing platform and the application of advanced big data computing service design, an efficient partition storage method and parallel batch feature analysis method of electric equipment monitoring data are achieved. The analysis process is organized as a work flow, the automatic periodic scheduling of data loading and analysis task is realized. The designed storage and parallel analysis algorithms can effectively deal with the TB/PB level of mass power equipment monitoring data analysis and calculation scenarios.
出处
《电力信息与通信技术》
2018年第1期26-32,共7页
Electric Power Information and Communication Technology
关键词
电力设备监测
大数据
云计算
特征提取
数据存储
power equipment monitoring
big data
cloud computing
feature extraction
data storage
