基于Hadoop平台的K均值算法的分析与实现

L. Wei
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引用次数: 1

摘要

当今社会已经进入了大数据时代,数据的多样性和数据量的增加给数据的存储和处理带来了巨大的挑战,Hadoop HDFS和MapReduce较好的解决了这两个问题。经典K-means算法是目前应用最广泛的一种基于分割的聚类算法。在完成集群配置的基础上,对k-means算法在集群模式下的工作原理和在集群模式下实现的k-means算法进行了研究和分析,并对实验结果进行了研究和分析,总结了k-means算法在Hadoop平台上运行的优势和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Analysis and Implementation of the K - Means Algorithm Based on Hadoop Platform
In today's society has entered the era of big data, data of the diversity and the amount of data increases to the data storage and processing brought great challenges, Hadoop HDFS and MapReduce better solves the these two problems. Classical K-means algorithm is the most widely used one based on the partition of the clustering algorithm. At the completion of the cluster configuration based on, the k-means algorithm in cluster mode of operation principle and in the cluster mode realized kmeans algorithm, and the experimental results are research and analysis, summarized the k-means algorithm is run on the Hadoop platform's strengths and limitations.
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