CRAST: Crash-resilient data management for a key-value store in persistent memory

被引:3
|
作者
Han, Youil [1 ]
Lee, Eunji [1 ]
机构
[1] Chungbuk Natl Univ, Dept Comp Sci, 1 Chungdaer Ro, Cheongju, Chungbuk, South Korea
来源
IEICE ELECTRONICS EXPRESS | 2018年 / 15卷 / 23期
基金
新加坡国家研究基金会;
关键词
phase-change memory; non-volatile memory; key-value store; storage systems;
D O I
10.1587/eIex.15.20180919
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The rapid pace of innovation in non-volatile memory technologies such as 3D Xpoint [1], NVDIMM [2], and zSSD [3] is set to transform how we build, deploy, and manage data service platforms. In particular, the emergence of a byte-addressable and persistent type of memory changes the landscape of the current storage architecture, consolidating different functionalities of memory and storage into a single layer [4]. To take full advantage of this advanced technology, this letter presents a crash-resilient skip list (CRAST) which serves as an in-memory data management module in a key-value store to support crash-consistency from a system failure when running on non-volatile memory. By maintaining the persistent in-memory data in a consistent manner, the proposed skip list provides strong reliability and high performance simultaneously in modern data service platforms. We demonstrate the efficacy of CRAST by implementing its prototype in LevelDB. We experimentally show that CRAST provides excellent performance across various workloads, compared to the original key-value store without any compromise on reliability.
引用
下载
收藏
页数:9
相关论文
共 50 条
  • [1] LibreKV: A Persistent in-Memory Key-Value Store
    Liu, Hao
    Huang, Linpeng
    Zhu, Yanmin
    Shen, Yanyan
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, 2020, 8 (04) : 916 - 927
  • [2] ChameleonDB: a Key-value Store for Optane Persistent Memory
    Zhang, Wenhui
    Zhao, Xingsheng
    Jiang, Song
    Jiang, Hong
    PROCEEDINGS OF THE SIXTEENTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS '21), 2021, : 194 - 209
  • [3] A Multicore-Friendly Persistent Memory Key-Value Store
    Wang Q.
    Zhu B.
    Shu J.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2021, 58 (02): : 397 - 405
  • [4] TurboHash: A Hash Table for Key-value Store on Persistent Memory
    Zhao, Xingsheng
    Zhong, Chen
    Jiang, Song
    PROCEEDINGS OF THE 16TH ACM INTERNATIONAL SYSTEMS AND STORAGE CONFERENCE, SYSTOR 2023, 2023, : 35 - 48
  • [5] HyperKV: A High Performance Concurrent Key-Value Store for Persistent Memory
    Sun, Penghao
    Xue, Dongliang
    You, Litong
    Yan, Yan
    Huang, Linpeng
    19TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS (ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM 2021), 2021, : 125 - 134
  • [6] Rethinking Key-Value Store for Byte-Addressable Optane Persistent Memory
    Wu, Sung-Ming
    Chang, Li-Pin
    PROCEEDINGS OF THE 59TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC 2022, 2022, : 805 - 810
  • [7] A Scalable and Persistent Key-Value Store Using Non-Volatile Memory
    Kim, Doyoung
    Choi, Won Gi
    Sung, Hanseung
    Park, Sanghyun
    SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING, 2019, : 464 - 467
  • [8] FlashStore: High Throughput Persistent Key-Value Store
    Debnath, Biplob
    Sengupta, Sudipta
    Li, Jin
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2010, 3 (02): : 1414 - 1425
  • [9] Implementing efficient data compression and encryption in a persistent key-value store for HPC
    Kim, Jungwon
    Vetter, Jeffrey S.
    INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2019, 33 (06): : 1098 - 1112
  • [10] PetaKV: Building Efficient Key-Value Store for File System Metadata on Persistent Memory
    Zhang, Yiwen
    Zhou, Jian
    Min, Xinhao
    Ge, Song
    Wan, Jiguang
    Yao, Ting
    Wang, Daohui
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2023, 34 (03) : 843 - 855