Results 81 to 90 of about 12,223 (205)
Research on application of Hadoop in personnel positioning software system
Gong-kuang zidonghua, 2017 In order to solve the problem that existing personnel locating system can not meet large data access requirement of large-scale coal mines, Hadoop was proposed to be used in personnel positioning software system, and parallel computing model MapReduce ...
WANG Wei
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Verifica Sperimentale di un modello per MapReduce [PDF]
, 2022 Proposto nel 2005 a partire dall'esperienza implementativa di Google, MapReduce rappresenta a tutt'oggi uno dei più utilizzati paradigmi per il calcolo parallelo.
Rodeghiero, Paolo
core
Zhejiang Daxue xuebao. Lixue ban, 2017 地理国情统计分析是深度研究地理国情普查数据的首要前提.针对现有单机集中式数据存储与处理方式存在耗时长、效率低甚至不支持的问题，设计了“格网索引+MapReduce”策略，基于规则格网设计普查数据文件的分块组织与分布式存储方式，研制了格网索引与空间分析相结合的双层过滤机制，构建基于MapReduce的地理国情并行统计算法.最后，与无索引MapReduce、ArcGIS平台进行性能对比测试，结果表明：“格网索引+ MapReduce”方法的统计效率远高于ArcGIS平台 ...
LINYaping(林雅萍) +3 more
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An Improved Algorithm for Optimizing MapReduce Based on Locality and Overlapping
Tsinghua Science and Technology, 2018 MapReduce is currently the most popular programming model for big data processing, and Hadoop is a well-known MapReduce implementation platform. However, Hadoop jobs suffer from imbalanced workloads during the reduce phase and inefficiently utilize the ...
Jianjiang Li +4 more
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Efficient Computation of the Well-Founded Semantics over Big Data [PDF]
, 2014 Data originating from theWeb, sensor readings and social media result in increasingly huge datasets. The so called Big Data comes with new scientific and technological challenges while creating new opportunities, hence the increasing interest in academia
Faber, Wolfgang +2 more
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Fast Matrix Multiplication with Big Sparse Data
Cybernetics and Information Technologies, 2017 Big Data becameabuzz word nowadays due to the evolution of huge volumes of data beyond peta bytes. This article focuses on matrix multiplication with big sparse data.
Somasekhar G., Karthikeyan K.
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MAPSkew: Metaheuristic Approaches for Partitioning Skew in MapReduce
Algorithms, 2018 MapReduce is a parallel computing model in which a large dataset is split into smaller parts and executed on multiple machines. Due to its simplicity, MapReduce has been widely used in various applications domains.
Matheus H. M. Pericini +4 more
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Hadoop Çatısının Bulut Ortamında Gerçeklenmesi Ve Terabyte Sort Deneyleri
MANAS: Journal of Engineering, 2015 Hadoop framework employs MapReduce programming paradigm to process big data by distributing data across a cluster and aggregating. MapReduce is one of the methods used to process big data hosted on large clusters.
G. Ozen, R. Sultanov
doaj
CES Transactions on Electrical Machines and Systems, 2019 Effective storage, processing and analyzing of power device condition monitoring data faces enormous challenges. A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun ...
Hongtao Shen, Peng Tao, Pei Zhao, Hao Ma
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Implementing and Optimizing Multiple Group by Query in a MapReduce Approach
Journal of Algorithms & Computational Technology, 2010 MapReduce model is a new parallel programming model initially developed for large-scale web content processing. Data analysis meets the issue of how to do calculation over extremely large dataset.
Jie Pan +2 more
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