摘要
针对传统间歇性能源海量数据处理技术的局限性,提出了基于MapReduce模型的间歇性能源海量数据处理技术,利用廉价的商用计算机组成集群,对海量数据进行并行处理,确保了海量数据处理的可靠性、低成本、高效能和扩展性,并对该技术的平台实现进行了论述。最后通过实验对比不同数据平台下海量数据处理的效率,验证了基于MapReduce模型的间歇性能源海量数据处理技术的高效性。
To overcome the limitations of the traditional massive data processing technology of intermittent energy,this paper introduces a massive data processing technology of intermittent energy based on a MapReduce model.This is a method for processing large-scale data in-parallel on large clusters of cheap commercial computers to ensure the reliability,low cost,high efficiency and scalability of massive data processing.Then the technology platform of massive data processing is discussed. Finally,by a comparison of processing efficiency via different platforms,the high efficiency of the massive data processing technology of intermittent energy based on MapReduce model is proved.
出处
《电力系统自动化》
EI
CSCD
北大核心
2014年第15期76-80,99,共6页
Automation of Electric Power Systems
基金
中央高校基本科研业务费专项资金资助项目(12MS111)~~
