• DocumentCode
    125635
  • Title

    Enhancing Throughput of Hadoop Distributed File System for Interaction-Intensive Tasks

  • Author

    Xiayu Hua ; Hao Wu ; Shangping Ren

  • Author_Institution
    Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL, USA
  • fYear
    2014
  • fDate
    12-14 Feb. 2014
  • Firstpage
    508
  • Lastpage
    511
  • Abstract
    The performance of the Hadoop Distributed File System (HDFS)decreases dramatically when handling interaction-intensive files, i.e., files that have relatively small size but are accessed frequently. The paper analyzes the cause of throughput degradation issue when accessing interaction-intensive files and presents an enhanced HDFS architecture along with an associated storage allocation algorithm that overcomes the performance degradation problem. Experiments have shown that with the proposed architecture together with the associated storage allocation algorithm, the HDFS throughput for interaction-intensive files increase 300% in average with only a negligible performance decrease for large data set tasks.
  • Keywords
    cache storage; distributed databases; memory architecture; network operating systems; software performance evaluation; storage allocation; HDFS architecture; Hadoop distributed file system throughput enhancement; interaction-intensive file handling; performance degradation problem; storage allocation algorithm; throughput degradation issue; Arrays; Multi-layer neural network; Periodic structures; Resource management; Throughput; Vectors; Cache; HDFS; Hierarchical structure; PSO; Storage Allocation Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel, Distributed and Network-Based Processing (PDP), 2014 22nd Euromicro International Conference on
  • Conference_Location
    Torino
  • ISSN
    1066-6192
  • Type

    conf

  • DOI
    10.1109/PDP.2014.110
  • Filename
    6787322