• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2013, Vol. 35 ›› Issue (10): 12-24.

• • 上一篇    下一篇

面向新型存储的大数据存储架构与核心算法综述

金培权,郝行军,岳丽华   

  1. (中国科学技术大学计算机科学与技术学院,安徽 合肥 230027)
  • 收稿日期:2013-08-02 修回日期:2013-09-27 出版日期:2013-10-25 发布日期:2013-10-25
  • 基金资助:

    国家自然科学基金重点项目(60833005);国家自然科学基金面上项目(61073039)

A survey on storage architectures and core #br# algorithms for big data management on new storages 

JIN Pei quan,HAO Xing jun,YUE Li hua   

  1. (School of Computer Science and Technology,University of Science and Technology of China,Hefei 230027,China)
  • Received:2013-08-02 Revised:2013-09-27 Online:2013-10-25 Published:2013-10-25

摘要:

大数据已成为目前学术界和工业界共同关注的热点问题,同时,闪存、相变存储器等新型存储技术也正在极大地影响着计算机系统的软硬件设计与应用。大数据管理面临着诸多的挑战,例如能耗、性能等,而新型存储介质则在I/O延迟、能耗等方面优于传统磁盘存储介质。面向新型存储技术的大数据管理旨在通过利用新型存储技术来解决大数据管理中的关键问题,但目前尚有许多问题还有待于进一步探讨。试图对面向新型存储技术的大数据管理的研究现状做一个梳理,理清几个问题,例如新型存储技术的快速发展对于大数据管理而言带来了哪些新的机遇和问题?引入新型存储后是否能够部分解决大数据管理中的挑战性问题?论文首先讨论了目前新型存储器的器件特点,总结了面向新型存储技术的大数据存储架构研究现状,对已经提出的主要核心算法进行了概述。最后,给出了基于新型存储技术的大数据管理的若干未来发展方向,以期能够对新型存储技术和大数据管理的未来研究提供新的线索。

关键词: 新型存储, 大数据管理, 研究进展, 发展趋势

Abstract:

Big data has been a hot topic both in academia and industries. At the same time, new storages, such as flash memory and phase changing memory, are greatly changing the design and applications of both software and hardware in modern computer systems. Basically, big data management has to deal with a lot of challenges, such as energy and performance, whereas new storages are superior to traditional magnetic disks in many aspects including I/O latency and energy consumption. Therefore, researchers conduct big data management study on new storages and expect to solve the critical issues in big data management. However, so far lots of issues are still to be further explored. We summarize the stateoftheart studies in big data management over new storages, and try to answer some key questions, e.g., “What new challenges and issues are brought by introducing new storages to big data management?”, “Can we solve or partially solve the key issues in big data management by using new storages?”. Particularly, we first discuss the special features of new storages, and then present the recent research advances in storage architectures and core algorithms for big data management over new storages. Finally, some future research directions in this area are proposed, which are expected to provide useful references for the future study in big data management and newstoragebased data management.

Key words: new storage, big data management, research advances, future trend