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作者:

Chen, Cheng (Chen, Cheng.) | Liu, Fei (Liu, Fei.) | Li, Guangrui (Li, Guangrui.) | Chen, Xiang (Chen, Xiang.) | Hou, Ying (Hou, Ying.)

收录:

CPCI-S

摘要:

The existing coarse-grained monitoring mechanism in Spark has much difficulty in analyzing and locating the bottleneck during the execution of tasks. Aiming to solve this problem, we divide the execution process of Spark tasks into several subphases, and propose a fine-grained subphases-based monitoring mechanism. The fine-grained monitoring mechanism can help users to understand the detail execution status of Spark tasks and be beneficial to analyze and locate the performance bottleneck in Spark.

关键词:

Fine-grained In-memory Computing Spark Task monitoring

作者机构:

  • [ 1 ] [Chen, Cheng]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Liu, Fei]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Chen, Xiang]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Hou, Ying]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 5 ] [Li, Guangrui]10 Bldg,Suzhou Software Pk,78 Keling Rd, Suzhou, Peoples R China

通讯作者信息:

  • [Chen, Cheng]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China

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来源 :

PROCEEDINGS OF THE ADVANCES IN MATERIALS, MACHINERY, ELECTRICAL ENGINEERING (AMMEE 2017)

ISSN: 2352-5401

年份: 2017

卷: 114

页码: 395-399

语种: 英文

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