• DocumentCode
    166619
  • Title

    SCALER: Scalable parallel file write in HDFS

  • Author

    Xi Yang ; Yanlong Yin ; Hui Jin ; Xian-He Sun

  • Author_Institution
    Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL, USA
  • fYear
    2014
  • fDate
    22-26 Sept. 2014
  • Firstpage
    203
  • Lastpage
    211
  • Abstract
    Two camps of file systems exist: parallel file systems designed for conventional high performance computing (HPC) and distributed file systems designed for newly emerged data-intensive applications. Addressing the big data challenge requires an approach that utilizes both high performance computing and data-intensive computing power. Thus, HPC applications may need to interact with distributed file systems, such as HDFS. The N-1 (N-to-1) parallel file write is a critical technical challenge, because it is very common for HPC applications but HDFS does not allow it. This study introduces a system solution, named SCALER, which allows MPI based applications to directly access HDFS without extra data movement. SCALER supports N-1 file write at both the inter-block level and intra-block level. Experimental results confirm that SCALER achieves the design goal efficiently.
  • Keywords
    message passing; parallel databases; parallel processing; HDFS; HPC; MPI based applications; N-1 parallel file write; SCALER; data-intensive applications; data-intensive computing power; design goal; distributed file systems; high performance computing; interblock level; intrablock level; parallel file systems; scalable parallel file write; Algorithm design and analysis; Computational modeling; Computer architecture; Message systems; Parallel processing; Time factors; Writing; Distributed file systems; HDFS; Optimization; Parallel I/O;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing (CLUSTER), 2014 IEEE International Conference on
  • Conference_Location
    Madrid
  • Type

    conf

  • DOI
    10.1109/CLUSTER.2014.6968736
  • Filename
    6968736