期刊文献+

从数据库视角解读大数据的研究进展与趋势 被引量:53

Research progress and trends of big data from a database perspective
在线阅读 下载PDF
导出
摘要 "大数据"是2012年排名第二的热词,本文试图从数据库研究者的视角来解读大数据,说明"大数据"这个概念的诞生、内涵和外延以及它和传统数据库的关系。将在现今语境下重新审视"数据库研究",即如何理解"数据库"这个概念以及数据库研究的本质问题。还将讨论Hadoop与大数据的关系,"数据库研究"和"大数据研究"的关系。通过回顾Hadoop的起源和发展,从数据处理的角度说明Hadoop发展的偶然性和必然性,以及它所处的地位。基本观点是:"大数据"是个笼统的概念,对其进行分类有助于深入理解;大数据研究的显著特征是它与应用密切相关;Hadoop是数据管理研究回到文件系统这一原点后的一个有益探索;"大数据"和传统的数据库在研究理念和方法学上是一脉相承的。 "Big Data" is one of the hottest topics in 2012.We try to detangle Big Data from the view of database researcher,and describe the concept of Big Data and the relationship between Big Data and traditional databases.Revisiting database research in the Big Data scene includes reinvestigating the concept of database and essential issues of database research,discussing the relationship between Hadoop and Big Data,database research and Big Data research as well.Through tracking the inspiration and development of Hadoop,we try to explain why it has been such a big deal in Big Data.The basic ideas of the report are:(1) Big Data is a general concept.Classification of Big Data is helpful to have a deep understanding of it; (2) Big Data research closely correlates to its applications; (3) Hadoop is an enlightening exploration for database research going back to file system; (4) the philosophy and methodology of Big Data is consistent with those of traditional databases.
出处 《计算机工程与科学》 CSCD 北大核心 2013年第10期1-11,共11页 Computer Engineering & Science
关键词 大数据 数据库 HADOOP big data data base Hadoop
  • 相关文献

参考文献24

  • 1http://epaper.gmw.cn/gmrb/htmI/2012-12/14/nw. D1100- 00gmrb_20121214_2-05. htm.
  • 2http://www.ycwb.com/ePaper/ycwb/htmI/2012-12/15/co- ntent_36546. htm? div=-1.
  • 3Apache官方主页[DB/OL].http://Hadoop.apache.org/.
  • 4White T. Hadoop , The definitive guide[M]. Zhou Min-qi , Wang Xiao-ling ,J in Che-qing , et al , translation. Beijing: Tsinghua University Press. 2011. (in Chinese).
  • 5http://www.nature.com/news/specials/bigdata/index.ht- ml.
  • 6Segaran T. Hammerbacher 1. Beautiful data:The stories be?hind elegant data solutions[M]. California: OReilly Media. 2009.
  • 7Hey T. Tansley S. Tolle K. The fourth paradigm: Data-in?tensive scientic discovery[M]. Washington: Microsoft Re?search. 2009.
  • 8http://news. sohu. com/20070202/n247993796. shtrnl.
  • 9http://www.sciencemag. org/site/special/data/.
  • 10http://product. ccidnet. com/art/27243/20110224/231S095 1. htrnl.

共引文献3

同被引文献537

引证文献53

二级引证文献351

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部