电网技术Issue(11)：3221-3227,7.DOI:10.13335/j.1000-3673.pst.2015.11.031
容错存储的电力系统监测数据查询优化技术
Query Optimization for Power System Monitoring Data With Fault-Tolerant Storage
摘要
Abstract
In order to solve massive time series data storage and query problem in power system monitoring, a new classified partition query optimization method of fault tolerant storage is proposed using cloud computing framework and HQL query engine. Fault tolerant storage model of power system monitoring data is designed through redundancy replication mechanism, and loading test and query optimization test of monitoring data are carried out by coordinating HQL query plan generation, conversion from HQL to Map/Reduce and partition pruning process. Results show that HQL performance is better than SQL when amounts of loading data exceed two millions or amounts of query data exceed three hundred and eighty thousand, and the bigger the data volume is, the more obvious the performance advantage will be. Classified partition query results show that amounts of data for partition query can be expanded to two orders of magnitude under similar time conditions, and second-level partition is better than first-level partition. It is verified that query optimization can improve query effectiveness, and provide a query optimization method for power monitoring data processing.关键词
电力监测/云计算/容错/查询优化Key words
power monitoring/cloud computing/fault- tolerance/query optimization分类
信息技术与安全科学引用本文复制引用
屈志坚,陈阁..容错存储的电力系统监测数据查询优化技术[J].电网技术,2015,(11):3221-3227,7.基金项目
国家自然科学基金项目(51267005)。Project Supported by National Natural Science Foundation of China (51267005) （51267005）
