CAJ | 학술논문

针对现有数据挖掘软件不支持用户有序、动态地按需定制并行数据挖掘算法，且不能充分利用计算集群的能力，分析了 Hadoop技术及其多种数据处理组件，提出应用 Mahout分布式数据挖掘算法库和 Oozie 工作流技术在 Hadoop 中构建数据挖掘工作流的方法，并设计实现了一个聚类工作流实例。实验结果证明，该方法简单，且能有效地组织数据挖掘流程。
침대현유수거알굴연건불지지용호유서、동태지안수정제병행수거알굴산법，차불능충분이용계산집군적능력，분석료 Hadoop기술급기다충수거처리조건，제출응용 Mahout분포식수거알굴산법고화 Oozie 공작류기술재 Hadoop 중구건수거알굴공작류적방법，병설계실현료일개취류공작류실례。실험결과증명，해방법간단，차능유효지조직수거알굴류정。
The existing data mining applications do not allow users to create customized algorithm group on demand and can not support the usage of computing clusters well,an analysis of several components of Hadoop is made,especially focusing on Mahout which is a distributed data mining algorithm library.Then Mahout and Oozie are used to create data mining workflow in Hadoop.At last,a clustering workflow is defined and implemented.The experimental results show that the method is easy and effective for creating distributed data mining process.