Results 71 to 80 of about 2,055 (161)
MASSIVE SIMULATIONS USING MAPREDUCE MODEL
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2015 In the last few years cloud computing is growing as a dominant solution for large scale numerical problems. It is based on MapReduce programming model, which provides high scalability and flexibility, but also optimizes costs of computing infrastructure.
Artur Krupa, Bartosz Sawicki
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Procedia Computer Science, 2015 AbstractDespite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era.
Vineyard, Craig M. +4 more
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MapReduce-Based D_ELT Framework to Address the Challenges of Geospatial Big Data
ISPRS International Journal of Geo-Information, 2019 The conventional extracting−transforming−loading (ETL) system is typically operated on a single machine not capable of handling huge volumes of geospatial big data.
Junghee Jo, Kang-Woo Lee
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A Parallel ETL Tool Based on an Improved Chain-MapReduce Framework
Dianxin kexue, 2013 The related work in parallel ETL and common methods to deal with multiple MapReduce jobs were introduced. Then an improved chain-MapReduce framework was presented, based on this framework,a parallel ETL tool was designed.
Bin Wu, Xinguang Liu
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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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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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A distributed computing model for big data anonymization in the networks. [PDF]
PLoS One, 2023 Ashkouti F, Khamforoosh K.
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Data stream treatment using sliding windows with MapReduce
Journal of Computer Science and Technology, 2016 Knowledge Discovery in Databases (KDD) techniques present limitations when the volume of data to process is very large. Any KDD algorithm needs to do several iterations on the complete set of data in order to carry out its work.
María José Basgall +2 more
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Design and analysis of management platform based on financial big data. [PDF]
PeerJ Comput Sci, 2023 Chen Y, Mustafa H, Zhang X, Liu J.
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Graph partitioning MapReduce-based algorithms for counting triangles in large-scale graphs. [PDF]
Sci Rep, 2023 Sharafeldeen A, Alrahmawy M, Elmougy S.
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