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基于新型存储的大数据存储管理 被引量:3

Big data storage management based on new storage
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摘要 如何高效地存储大数据并支持实时大数据处理与分析是大数据技术发展面临的首要问题。近年来,以相变存储器、闪存等为代表的新型存储为实现高效的大数据存储和管理提供了新思路。以相变存储器为代表的存储级主存技术为切入点,针对大数据存储与管理中的高效存储、实时处理等存在的挑战,讨论了面向新型存储的大数据存储管理研究现状,并对未来基于新型存储的大数据研究进行了展望。 How to efficiently store big data and support real-time big data processing and analysis has been the most critical issue in the development of big data technologies. Recently, new storage media such as phase change memory and flash memory provides new opportunities for developing an efficient framework for big data storage and management. Based on the challenges of efficient storage and real-time processing in big data storage and management, storage class memories were focused, which were represented by phase change memory, and the state of the art of new-storage-based big data storage management was discussed. Finally, some future research directions for new-storage-based big data storage management were proposed.
作者 金培权 JIN Peiquan(School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei 230027, China)
出处 《大数据》 2017年第5期70-82,共13页 Big Data Research
基金 国家自然科学基金资助项目(No.61672479)~~
关键词 相变存储器 大数据管理 新型存储 存储管理 phase change memor big data management, new storage, storage management
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  • 1刘金垒,李琼.新型非易失相变存储器PCM应用研究[J].计算机研究与发展,2012,49(S1):90-93. 被引量:5
  • 2陈卓,熊劲,马灿.基于SSD的机群文件系统元数据存储系统[J].计算机研究与发展,2012,49(S1):269-275. 被引量:8
  • 3邓志欣,甘学温.相变存储器简介与展望[J].中国集成电路,2005,14(4):48-51. 被引量:4
  • 4刘波,宋志棠,封松林.我国相变存储器的研究现状与发展前景[J].微纳电子技术,2007,44(2):55-61. 被引量:14
  • 5Codd E E A relational model of data for large shared data banks[J]. Communications of the ACM, 1970, 13(6): 377-387.
  • 6Danga Interactive, Memcached[EB/OL]. [2011-03-19], http://rnemcached.org.
  • 7Salvatore Sanfilippo. Redis [EB/OL]. [2011-03-19 ]. http:// redis.io.
  • 8Sleepycat Software. BerkeleyDB[EB/OL]. [2011-03-21].http://www.oracle.com/technetwork/database/berkeleydb/ overview/index.html.
  • 9Debnath B, Sengupta S, Li Jin. FlashStore: high through- hput persistent key-value store[J]. Proceedings of the VLDB Endowment, 2010, 3(1/2): 1414-1425.
  • 10Debnath B, Sengupta S, Li Jin. SkimpyStash: RAM space skimpy key-value store on flash-based storage[C]//Pro-ceedings of the 2011 International Conference on Man-agement of Data (SIGMOD '11). New York, NY, USA:ACM, 2011: 25-36.

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