计算机工程与应用Issue(12)：123-132,10.DOI:10.3778/j.issn.1002-8331.1410-0261
迭代式MapReduce研究进展
Advances in iterative MapReduce
摘要
Abstract
Iterative computations are pervasive among big data processing, but the traditional MapReduce cannot explicitly support iterative computation. In recent years, researchers have extended and improved the original MapReduce, and have developed a number of iterative MapReduce to better support iterative computation for big data processing. A comprehen-sive review of iterative MapReduce programming framework is provided. These research achievements are described in detail. Their basic ideas are given. Their characteristics, advantages and disadvantages are analyzed for each framework, and some technologies that have been adopted in these frameworks are compared. Some promising development trends for future research of iterative MapReduce are pointed out.关键词
MapReduce/迭代计算/迭代式MapReduce/并行编程模型/大数据处理Key words
MapReduce/iterative computation/iterative MapReduce/parallel programming model/big data processing分类
信息技术与安全科学引用本文复制引用
李金忠,汤鹏杰,夏洁武,谭云兰..迭代式MapReduce研究进展[J].计算机工程与应用,2015,(12):123-132,10.基金项目
国家自然科学基金（No.61163062）；江西省教育厅科技计划项目（No.GJJ14561）；江西省科技支撑计划项目（No.20122BBG70161）；江西省自然科学基金项目（No.2012BAB201038）。 （）
