%0 Conference Proceedings
%T A Fine-Grained Performance Bottleneck Analysis Method for HDFS
%+ School of Computer Science and Engineering [Beijing]
%+ School of Instrumentation Science and Opto-electronics Engineering [Beijing]
%A Liu, Yi
%A Li, Yunchun
%A Zhou, Honggang
%A Zhang, Jingyi
%A Yang, Hailong
%A Li, Wei
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Network and Parallel Computing (NPC)
%C Muroran, Japan
%Y Feng Zhang
%Y Jidong Zhai
%Y Marc Snir
%Y Hai Jin
%Y Hironori Kasahara
%Y Mateo Valero
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-11276
%P 159-163
%8 2018-11-29
%D 2018
%R 10.1007/978-3-030-05677-3_17
%K HDFS
%K Instrumentation
%K Bottleneck analysis
%K Performance optimization
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-02279548/document
%2 https://inria.hal.science/hal-02279548/file/477597_1_En_17_Chapter.pdf
%L hal-02279548
%U https://inria.hal.science/hal-02279548
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-11276