Dhcache: a dual-hash cache for optimizing the read performance in key-value store

被引:0
|
作者
Lu, Jinkang [1 ,2 ,3 ]
Lv, Meng [4 ]
Li, Peixuan [1 ,2 ,3 ]
Yuan, Zhu [5 ]
Xie, Ping [1 ,2 ,3 ]
机构
[1] Qinghai Normal Univ, Sch Comp, Xining 810016, Peoples R China
[2] Key Lab Internet Things Qinghai Prov, Xining 810016, Peoples R China
[3] State Key Lab Tibetan Intelligent Informat Proc &, Xining 810016, Peoples R China
[4] Qingdao Tech Coll, Informat & Technol Ctr, Qingdao 266555, Peoples R China
[5] Natl Police Univ Criminal Justice, Dept Informat Management, Baoding 071000, Peoples R China
来源
JOURNAL OF SUPERCOMPUTING | 2025年 / 81卷 / 02期
基金
中国国家自然科学基金;
关键词
Key-value store; Cache; Hash table; Cache replacement policy;
D O I
10.1007/s11227-024-06828-w
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Key-value (KV) stores are widely utilized in data-intensive applications to obtain exceptional storage performance. However, its caching mechanism often suffers read and write pauses. Especially when accessing old data periodically, it results in cache hit ratios and system throughput decline. To address the performance degradation issue, we propose an innovative dual-hash caching mechanism called DHCache. Firstly, we introduce a dual-hash structure in DHCache. It alleviates read and write pauses by reducing the frequency of rehash operations on the hash table. Secondly, we employ a Most Recently Used (MRU) cache replacement policy on DHCache to retain old data. This enhances the cache hit ratios and throughput when periodically accessing old data. DHCache is deployed within LevelDB, demonstrating significant performance advantages. Experimental results indicate that DHCache improves throughput by 11.89-21.92% in various read workloads compared to traditional LRUCache. Significantly, read performance improvement does not come at the cost of write performance degradation.
引用
收藏
页数:26
相关论文
共 50 条
  • [1] GHStore: A High Performance Global Hash Based Key-Value Store
    Li, Jiaoyang
    Yue, Yinliang
    Wang, Weiping
    DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2022, PT I, 2022, : 493 - 508
  • [2] 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
  • [3] Analysis of SSD Internal Cache Problem in a Key-Value Store System
    Jeong, Won Seob
    Won, Yongseok
    Ro, Won Woo
    PROCEEDINGS OF THE 2019 2ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND INFORMATION MANAGEMENT (ICSIM 2019) / 2019 2ND INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (ICBDSC 2019), 2019, : 59 - 62
  • [4] ZDB-High performance key-value store
    Thanh Nguyen Trung
    Minh Nguyen Hieu
    2013 THIRD WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES (WICT), 2013, : 311 - 316
  • [5] High-Performance Key-Value Store On OpenSHMEM
    Fu, Huansong
    Venkata, Manjunath Gorentla
    Choudhury, Ahana Roy
    Imam, Neena
    Yu, Weikuan
    2017 17TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), 2017, : 559 - 568
  • [6] Cache-Conscious Data Placement in an In-Memory Key-Value Store
    Tinnefeld, Christian
    Zeier, Alexander
    Plattner, Hasso
    PROCEEDINGS OF THE 15TH INTERNATIONAL DATABASE ENGINEERING & APPLICATIONS SYMPOSIUM (IDEAS '11), 2011, : 134 - 142
  • [7] InnerCache: A Tactful Cache Mechanism for RDMA-Based Key-Value Store
    Yang, Min
    Yu, Songping
    Yu, Rujie
    Xiao, Nong
    Liu, Fang
    Chen, Wei
    2016 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS), 2016, : 646 - 649
  • [8] PRISM: Optimizing Key-Value Store for Modern Heterogeneous Storage Devices
    Song, Yongju
    Kim, Wook-Hee
    Monga, Sumit Kumar
    Min, Changwoo
    Eom, Young Ik
    PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, VOL 2, ASPLOS 2023, 2023, : 588 - 602
  • [9] FoundationDB: A Distributed Key-Value Store
    Zhou, Jingyu
    Xu, Meng
    Shraer, Alexander
    Namasivayam, Bala
    Miller, Alex
    Tschannen, Evan
    Atherton, Steve
    Beamon, Andrew J.
    Sears, Rusty
    Leach, John
    Rosenthal, Dave
    Dong, Xin
    Wilson, Will
    Collins, Ben
    Scherer, David
    Grieser, Alec
    Liu, Yang
    Moore, Alvin
    Muppana, Bhaskar
    Su, Xiaoge
    Yadav, Vishesh
    COMMUNICATIONS OF THE ACM, 2023, 66 (06) : 97 - 105
  • [10] Catalyst: Optimizing Cache Management for Large In-memory Key-value Systems
    Wang, Kefei
    Chen, Feng
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2023, 16 (13): : 4339 - 4352