随着大数据技术的发展和对海量数据存储、分析需求的提高,成熟的分布式存储系统越来越多。通过对不同分布式基础存储系统内部的存储策略、管理策略、架构思想等关键技术点的对比和分析,对当前流行的分布式存储系统在设计思想、创新性技...随着大数据技术的发展和对海量数据存储、分析需求的提高,成熟的分布式存储系统越来越多。通过对不同分布式基础存储系统内部的存储策略、管理策略、架构思想等关键技术点的对比和分析,对当前流行的分布式存储系统在设计思想、创新性技术上进行了追根溯源。对比传统数据存储与分布式数据存储的技术发展和应用实例,揭示了数据存储追求更大、更快、更安全的发展潮流,重点研究了大数据基础存储实例中基于文件、键值对和表格这三种分布式存储方式。正如网络技术的发展到SDN(Software Defined Network)一样,存储方式也在发生深刻变化—软件定义存储。通过对当前大数据主流基础存储系统技术的发展和应用实例所进行的对比研究,为分布式存储系统,特别是基础存储系统的开发,提供了一些在系统设计上的参考,也为在从事大数据方面有业务需求的工作人员在选择底层存储策略时提供了借鉴。展开更多
Aiming at the storage and management problems of massive remote sensing data,this paper gives a comprehensive analysis of the characteristics and advantages of thirteen data storage centers or systems at home and abro...Aiming at the storage and management problems of massive remote sensing data,this paper gives a comprehensive analysis of the characteristics and advantages of thirteen data storage centers or systems at home and abroad. They mainly include the NASA EOS,World Wind,Google Earth,Google Maps,Bing Maps,Microsoft TerraServer,ESA,Earth Simulator,GeoEye,Map World,China Centre for Resources Satellite Data and Application,National Satellite Meteorological Centre,and National Satellite Ocean Application Service. By summing up the practical data storage and management technologies in terms of remote sensing data storage organization and storage architecture,it will be helpful to seek more suitable techniques and methods for massive remote sensing data storage and management.展开更多
文摘随着大数据技术的发展和对海量数据存储、分析需求的提高,成熟的分布式存储系统越来越多。通过对不同分布式基础存储系统内部的存储策略、管理策略、架构思想等关键技术点的对比和分析,对当前流行的分布式存储系统在设计思想、创新性技术上进行了追根溯源。对比传统数据存储与分布式数据存储的技术发展和应用实例,揭示了数据存储追求更大、更快、更安全的发展潮流,重点研究了大数据基础存储实例中基于文件、键值对和表格这三种分布式存储方式。正如网络技术的发展到SDN(Software Defined Network)一样,存储方式也在发生深刻变化—软件定义存储。通过对当前大数据主流基础存储系统技术的发展和应用实例所进行的对比研究,为分布式存储系统,特别是基础存储系统的开发,提供了一些在系统设计上的参考,也为在从事大数据方面有业务需求的工作人员在选择底层存储策略时提供了借鉴。
基金supported by the National Basic Research Program of China ("973" Program) (Grant No.61399)
文摘Aiming at the storage and management problems of massive remote sensing data,this paper gives a comprehensive analysis of the characteristics and advantages of thirteen data storage centers or systems at home and abroad. They mainly include the NASA EOS,World Wind,Google Earth,Google Maps,Bing Maps,Microsoft TerraServer,ESA,Earth Simulator,GeoEye,Map World,China Centre for Resources Satellite Data and Application,National Satellite Meteorological Centre,and National Satellite Ocean Application Service. By summing up the practical data storage and management technologies in terms of remote sensing data storage organization and storage architecture,it will be helpful to seek more suitable techniques and methods for massive remote sensing data storage and management.
