Optimizing Performance of Hadoop with Parameter Tuning

被引:3
|
作者
Chen, Xiang [1 ]
Liang, Yi [1 ]
Li, Guang-Rui [2 ]
Chen, Cheng [1 ]
Liu, Si-Yu [1 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
[2] China Mobile Software Technol Co Ltd, 10 Bldg,Suzhou Software Pk,78, Suzhou, Peoples R China
关键词
D O I
10.1051/itmconf/20171203040
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Optimizing Hadoop with the parameter tuning is an effective way to greatly improve the performance, but it usually costs too much time to identify the optimal parameters configuration because there are many parameters. Users are always blindly adjust too many parameters and are sometimes confused about which one could be changed at a higher-priority. To make optimization easier, classifying the parameter based on different applications will be helpful. In this paper, we will introduce a method that can classify these parameters in order that users can optimize performance more quickly and effectively for different applications.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Customized Parameter Configuration Framework for Performance Tuning in Apache Hadoop
    Mathiya, Bhavin J.
    Desai, Vinodkumar L.
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ICT FOR SUSTAINABLE DEVELOPMENT ICT4SD 2015, VOL 2, 2016, 409 : 511 - 521
  • [2] Parameter based tuning model for optimizing performance on GPU
    Nhat-Phuong Tran
    Lee, Myungho
    Choi, Jaeyoung
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2017, 20 (03): : 2133 - 2142
  • [3] Parameter Tuning Model for Optimizing Application Performance on GPU
    Nhat-Phuong Tran
    Lee, Myungho
    2016 IEEE 1ST INTERNATIONAL WORKSHOPS ON FOUNDATIONS AND APPLICATIONS OF SELF* SYSTEMS (FAS*W), 2016, : 78 - 83
  • [4] Parameter based tuning model for optimizing performance on GPU
    Nhat-Phuong Tran
    Myungho Lee
    Jaeyoung Choi
    Cluster Computing, 2017, 20 : 2133 - 2142
  • [5] Analyzing & Optimizing Hadoop Performance
    Jain, Ankita
    Choudhary, Monika
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS AND COMPUTATIONAL INTELLIGENCE (ICBDAC), 2017, : 116 - 121
  • [6] Toward an Automatic Parameter Tuning Method for Hadoop
    Nakashita, Kazunori
    Koita, Takahiro
    IMCIC'11: THE 2ND INTERNATIONAL MULTI-CONFERENCE ON COMPLEXITY, INFORMATICS AND CYBERNETICS, VOL II, 2011, : 52 - 52
  • [7] A recommendation-based parameter tuning approach for Hadoop
    Cai, Lin
    Qi, Yong
    Li, Jingwei
    2017 IEEE 7TH INTERNATIONAL SYMPOSIUM ON CLOUD AND SERVICE COMPUTING (SC2 2017), 2017, : 223 - 230
  • [8] Investigating Automatic Parameter Tuning for SQL-on-Hadoop Systems
    Lucas Filho, Edson Ramiro
    de Almeida, Eduardo Cunha
    Scherzinger, Stefanie
    Herodotou, Herodotos
    BIG DATA RESEARCH, 2021, 25
  • [9] Lessons Learned: Performance Tuning for Hadoop Systems
    Trivedi, Manan
    Nambiar, Raghunath
    PERFORMANCE EVALUATION AND BENCHMARKING: TRADITIONAL - BIG DATA - INTERNET OF THINGS, TPCTC 2016, 2017, 10080 : 121 - 141
  • [10] Statistical analysis of an improved tuning method for optimizing performances of Hadoop applications
    Singh, Prabhdeep
    Prasad, M. S. Guru
    Taneja, Harsh
    Pai, H. Aditya
    Sharonchrista
    JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 2022, 43 (03): : 533 - 541