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Erschienen in:
2018 | OriginalPaper | Buchkapitel
A Fine-Grained Performance Bottleneck Analysis Method for HDFS
verfasst von : Yi Liu, Yunchun Li, Honggang Zhou, Jingyi Zhang, Hailong Yang, Wei Li
Erschienen in: Network and Parallel Computing
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Abstract
The performance issue of HDFS has always been a great concern due to its widely adoption in both production and research environments. However, a fine-grained performance analysis tool is missing to effectively identify the bottlenecks as well as to provide useful guidance for performance optimization. In this paper, we propose a fine-grained performance bottleneck analysis tool, which extends HTrace with fine-grained instrumentation points that are missing in Hadoop official distribution. In addition, we propose an effective trace merging method that improves the understandability of our analysis. We analyze the performance of HDFS under different kinds of workloads and get undiscovered insights.