Improving Small File I/O Performance for Massive Digital Archives

被引:4
|
作者
Kim, Hwajung [1 ,2 ]
Yeom, Heonyoung [1 ]
机构
[1] Seoul Natl Univ, Dept Comp Sci & Engn, Seoul, South Korea
[2] Samsung Elect Co, Software R&D Ctr, Suwon, South Korea
基金
新加坡国家研究基金会;
关键词
D O I
10.1109/eScience.2017.39
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the growth of online services, a large amount of files have been generated by users or by the service itself. To make it easier to service users with different network environments and devices, online services usually keep different versions of the same file with various sizes. For users with high speed network and top of the line displays, a large size file with high precision can be supplied while users with mobile devices typically receive a smaller file with less precision. In some cases, a large file can be divided into small files to make it easier to transmit over the wide area networks. As a result, underlying filesystem should efficiently maintain a large number of small files. Providing such a huge number of files to applications is one of new challenges of existing filesystems. In this paper, we propose techniques to efficiently manage a large number of files in digital archives using data characteristics and access patterns of the application. Based on the knowledge we have of the upper layer applications, we have modified both in-memory and on-disk inode structure of the existing filesystem and were able to dramatically reduce the number of storage I/O operations to service the same files. Our experimental results show that the proposed methods significantly reduce the number of storage I/O operations both for reading and writing files, especially for small-sized ones. Moreover, we demonstrated that proposed techniques reduce the application-level latency as well as improve file operation throughput, using several synthetic-and micro-benchmarks.
引用
收藏
页码:256 / 265
页数:10
相关论文
共 50 条
  • [1] Implementing WebGIS on Hadoop: A Case Study of Improving Small File I/O Performance on HDFS
    Liu, Xuhui
    Han, Jizhong
    Zhong, Yunqin
    Han, Chengde
    He, Xubin
    2009 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING AND WORKSHOPS, 2009, : 429 - +
  • [2] Massive stripe cache and prefetching for massive file I/O
    Baek, Sung Hoon
    Park, Kyu Ho
    ICCE: 2007 DIGEST OF TECHNICAL PAPERS INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, 2007, : 203 - +
  • [3] Performance Optimization of Small File I/O with Adaptive Migration Strategy in Cluster File System
    Li, Xiuqiao
    Dong, Bin
    Xiao, Limin
    Ruan, Li
    HIGH PERFORMANCE COMPUTING AND APPLICATIONS, 2010, 5938 : 242 - 249
  • [4] File Placing Control for Improving the I/O Performance of Hadoop in Virtualized Environment
    Nakashima, Kenji
    Fujishima, Eita
    Yamaguchi, Saneyasu
    2016 FOURTH INTERNATIONAL SYMPOSIUM ON COMPUTING AND NETWORKING (CANDAR), 2016, : 402 - 407
  • [5] Improving File Tree Traversal Performance by Scheduling I/O Operations in User space
    Lunde, Carl Henrik
    Espeland, Havard
    Stensland, Hakon Kvale
    Halvorsen, Pal
    2009 IEEE 28TH INTERNATIONAL PERFORMANCE COMPUTING AND COMMUNICATIONS CONFERENCE (IPCC 2009), 2009, : 145 - +
  • [6] Improving Performance of Small-File Accessing in Hadoop
    Vorapongkitipun, Chatuporn
    Nupairoj, Natawut
    2014 11TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE), 2014, : 200 - 205
  • [7] Improving the Small File Synchronous Write Performance for Parallel Filesystem
    Huang, Jian
    Lu, Jun
    MEMS, NANO AND SMART SYSTEMS, PTS 1-6, 2012, 403-408 : 2432 - 2436
  • [8] An Architecture for High Performance File System I/O
    Patocka, Mikulas
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 23, 2007, 23 : 250 - 255
  • [9] Improving File System Performance and Reliability of Car Digital Video Recorders
    Kim, Younghun
    Shin, Dongkun
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2015, 61 (02) : 222 - 229
  • [10] FlatLFS: A lightweight file system for optimizing the performance of accessing massive small files
    Fu, Songling
    Liao, Xiangke
    Huang, Chenlin
    Wang, Lei
    Li, Shanshan
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2013, 35 (02): : 120 - 126