Solving Mean-Shift Clustering Using MapReduce Hadoop

被引：0

作者：

Kalimoldayev, Maksat N. ^{[1
]}

Siladi, Vladimir ^{[2
]}

Satymbekov, Maksat N. ^{[1
]}

Naizabayeva, Lyazat ^{[1
]}

机构：

[1] Inst Informat & Computat Technol, Alma Ata, Kazakhstan

[2] Matej Bel Univ, Fac Nat Sci, Banska Bystrica, Slovakia

来源：

2017 IEEE 14TH INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATICS | 2017年

关键词：

Hadoop; MapReduce; Mean-Shift; MPI; HDFS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Paper presents results of a practical experiment that was conducted in order to pursuit main objective - design and implement novel iterative MapReduce framework based on Hadoop technology. To study the effects of implementation parallel scientific applications, we deployed. Despite the fact that they did not show better performance than the same algorithm implemented in MPI, we conducted experiments to solve problems iterative computations using the Hadoop architecture. As a result of the experiments, the fail-safe behavior of Hadoop technology was revealed in the solutions of complex hadacies.

引用

页码：164 / 167

页数：4

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