摘要
电力能源是现今人们生产、生活使用最为广泛的能源之一,处于持续短缺状态;电力能源产生的数据量级较大,如何在电力能源大数据中精确查询并采集需求数据,对电力能源合理管理与应用至关重要。提出一种基于多级索引集群均衡的电力能源大数据采集方法。深入分析电力能源大数据存储情况(电力能源数据表与元数据表),构建多级索引集群;采用定向任务分配算法均衡处理多级索引集群,确定每个集群节点的任务分配结果;以集群节点任务分配结果为依据,配置并启动多级索引集群;结合电力能源大数据查询需求,对查询数据进行缓存,最终实现电力能源大数据的采集。实验数据表明:相较于对比方法,应用所提方法获得的构建索引耗时和需求数据查询时延均更少,其最小值分别为3 s、12.03 s;数据采集质量参数更大,最大值为9.6,证实了提出方法具有可行性。
Electric energy is the most widely used energy in people’s production and life,but it is often in a continuous shortage.The data generated by electric power is very large,and the method to accurately query and collect the demand data in electric energy big data is very important for the rational management and application of electric energy.This paper proposes a electric energy big data acquisition method based on multi-level index cluster equilibrium.The storage situation of electric energy big data(electric power data table and metadata table)is thoroughly analyzed,and a multi-level index cluster;Using a targeted task allocation algorithm is built to balance multi-level index clusters and determine the task allocation results for each cluster node;Based on the task allocation results of cluster nodes,the multi-level index cluster is configured and started;Based on the demand for querying electric energy,the query data is cached and the collection of electric power big data is ultimately achieved.The experimental data show that compared with the comparison method,the index construction time and demand data query delay obtained by the proposed method are shorter,the shortest index construction time is 3 s,the shortest query delay is 12.03 s,and the data acquisition quality parameter is larger,with a maximum value of 9.6,which fully proves the feasibility of the proposed method.
作者
赵少东
王程斯
ZHAO Shaodong;WANG Chengsi(Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen 518001,Guangdong,China)
出处
《电网与清洁能源》
CSCD
北大核心
2024年第8期85-90,共6页
Power System and Clean Energy
基金
中国南方电网有限责任公司科技项目(090000KK52210128)。
关键词
索引集群
电力能源
多级索引
大数据
集群均衡
采集
index cluster
electric energy
multi level index
big data
cluster equilibrium
collection
