Rucio: Scientific Data Management

被引:79
|
作者
Barisits M. [1 ]
Beermann T. [2 ]
Berghaus F. [3 ]
Bockelman B. [4 ]
Bogado J. [5 ]
Cameron D. [6 ]
Christidis D. [7 ]
Ciangottini D. [8 ]
Dimitrov G. [1 ]
Elsing M. [1 ]
Garonne V. [6 ]
di Girolamo A. [1 ]
Goossens L. [1 ]
Guan W. [9 ]
Guenther J. [1 ]
Javurek T. [1 ]
Kuhn D. [10 ]
Lassnig M. [1 ]
Lopez F. [5 ]
Magini N. [11 ]
Molfetas A. [1 ]
Nairz A. [1 ]
Ould-Saada F. [6 ]
Prenner S. [10 ]
Serfon C. [10 ]
Stewart G. [1 ]
Vaandering E. [12 ]
Vasileva P. [1 ]
Vigne R. [13 ]
Wegner T. [1 ]
机构
[1] CERN, Meyrin
[2] University of Wuppertal, Wuppertal
[3] University of Victoria, Victoria
[4] Morgridge Institute, Madison, WI
[5] Universidad Nacional de La Plata, La Plata
[6] University of Oslo, Oslo
[7] University of Texas at Arlington, Arlington, TX
[8] INFN, Perugia
[9] University of Wisconsin-Madison, Madison, WI
[10] University of Innsbruck, Innsbruck
[11] Iowa State University, Ames, IA
[12] Fermi National Accelerator Laboratory, Batavia, IL
[13] University of Vienna, Vienna
关键词
Data access; Data management; Data organization; Distributed computing; Exascale;
D O I
10.1007/s41781-019-0026-3
中图分类号
学科分类号
摘要
Rucio is an open-source software framework that provides scientific collaborations with the functionality to organize, manage, and access their data at scale. The data can be distributed across heterogeneous data centers at widely distributed locations. Rucio was originally developed to meet the requirements of the high-energy physics experiment ATLAS, and now is continuously extended to support the LHC experiments and other diverse scientific communities. In this article, we detail the fundamental concepts of Rucio, describe the architecture along with implementation details, and report operational experience from production usage. © 2019, The Author(s).
引用
收藏
相关论文
共 50 条
  • [31] A Holistic Framework for Big Scientific Data Management
    Kantere, Verena
    2014 IEEE INTERNATIONAL CONGRESS ON BIG DATA (BIGDATA CONGRESS), 2014, : 220 - 226
  • [32] Data Management for the RedisDG Scientific Workflow Engine
    Abidi, Leila
    Bejaoui, Souha
    Cerin, Christophe
    Lejeune, Jonathan
    Ngoko, Yanik
    Saad, Walid
    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT), 2016, : 599 - 606
  • [33] A Performance Evaluation of Hive for Scientific Data Management
    Liu, Taoying
    Liu, Jing
    Liu, Hong
    Li, Wei
    2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2013,
  • [34] Special issue on scientific and statistical data management
    Kesheng Wu
    Florin Rusu
    Distributed and Parallel Databases, 2019, 37 : 1 - 3
  • [35] A data management strategy for scientific research.
    Roberts, AM
    ENVIRONMENTAL SOFTWARE SYSTEMS, VOL 2, 1997, : 121 - 127
  • [36] HYDROLOGICAL DATA IN SCIENTIFIC RESEARCH AND WATER MANAGEMENT
    Ostojski, Mieczyslaw S.
    Radczuk, Laura
    Takarczyk, Tamara
    II KRAJOWY KONGRES HYDROLOGICZNY - HYDROLOGIA W INZYNIERII I GOSPODARCE WODNEJ, TOM I, 2014, 20 : 221 - 235
  • [37] Special issue on scientific and statistical data management
    Wu, Kesheng
    Rusu, Florin
    DISTRIBUTED AND PARALLEL DATABASES, 2019, 37 (01) : 1 - 3
  • [38] Integrated data and task management for scientific applications
    Nieplocha, Jarek
    Krishamoorthy, Sriram
    Valiev, Marat
    Krishnan, Manoj
    Palmer, Bruce
    Sadayappan, P.
    COMPUTATIONAL SCIENCE - ICCS 2008, PT 1, 2008, 5101 : 20 - +
  • [39] Zenith: Scientific Data Management on a Large Scale
    Pacitti, Esther
    Valduriez, Patrick
    ERCIM NEWS, 2012, (89): : 17 - 18
  • [40] TECHNOLOGIES FOR LARGE DATA MANAGEMENT IN SCIENTIFIC COMPUTING
    Pace, Alberto
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2014, 25 (02):