基于MapReduce模型的间歇性能源海量数据处理技术

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基于MapReduce模型的间歇性能源海量数据处理技术

更新时间：2025-08-13

- 基于MapReduce模型的间歇性能源海量数据处理技术
- Automation of Electric Power Systems Vol. 38, Issue 15, Pages: 76-80(2014)
- 作者机构：
  
  华北电力大学电气与电子工程学院,河北省,保定市,071003
- 作者简介：
- 基金信息：
- DOI：
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- Published：2014
- 稿件说明：
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MEI Huawei. [J]. Automation of electric power systems, 2014, 38(15): 76-80.
DOI：

MEI Huawei. [J]. Automation of electric power systems, 2014, 38(15): 76-80. DOI：

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。

Abstract

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.

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