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Ling Wen
Northwest Branch of PetroChina Research Institute of Petroleum Exploration and Development
Computer Science & IT

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MapReduce Integrated Multi-algorithm for HPC Running State Analysis ShuRen Liu; ChaoMin Feng; HongWu Luo; Ling Wen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3771

Abstract

High-performance computer clusters are major seismic processing platforms in the oil industry and have a frequent occurrence of failures. In this study, K-means and the Naive Bayes algorithm were programmed into MapReduce and run on Hadoop. The accumulated high-performance computer cluster running status data were first clustered by K-means, and then the results were used for Naive Bayes training. Finally, the test data were discriminated for the knowledge base and equipment failure. Experiments indicate that K-means returned good results, the Naive Bayes algorithm had a high rate of discrimination, and the multi-algorithm used in MapReduce achieved an intelligent prediction mechanism.
Co-Authors ChaoMin Feng HongWu Luo ShuRen Liu