TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic

被引:0
|
作者
Zhan, Ling [1 ]
Lu, Kai [2 ]
Xiong, Yiqin [2 ]
Wan, Jiguang [2 ]
Yang, Zixuan [3 ]
机构
[1] Wenhua Coll, Fac Informat Sci & Technol, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China
[3] Fujian Normal Univ, Sch Big Data & Artificial Intelligence, Fuzhou 350007, Peoples R China
来源
IEEE ACCESS | 2024年 / 12卷
基金
中国国家自然科学基金;
关键词
Disaggregated storage; key-value store; NVMe over fabrics; remote direct memory access; NEURAL-NETWORKS; CLASSIFICATION; AREA;
D O I
10.1109/ACCESS.2024.3496880
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Disaggregated storage (DS) based on remote direct memory access (RDMA) network decouples compute and storage resources, thereby significantly improving resource utilization. While building key-value (KV) stores on DS benefits from these merits, existing fast KV stores suffer from network bandwidth contention and high latency under DS due to the non-negligible network amplification and high-overhead I/O stack. In this paper, we propose TrickleKV, a high-performance persistent KV store designed for DS. TrickleKV reduces network amplification and latency in three approaches: 1) TrickleKV proposes an efficient storage-side data filtering mechanism and a two-level cache structure with different granularities to reduce network traffic in the read process. 2) TrickleKV presents an efficient write buffer structure that includes asynchronous flushing and queue scheduling mechanisms to reduce network traffic in the write process. 3) TrickleKV designs a read-write decoupled user-space I/O stack and lightweight storage space management to reduce access latency. Evaluation results show that TrickleKV achieves 1.2x - 7x higher throughput and 30%- 7.4x lower latency compared to state-of-the-art KV stores under DS.
引用
收藏
页码:167596 / 167612
页数:17
相关论文
共 50 条
  • [41] TreeLine: An Update-In-Place Key-Value Store for Modern Storage
    Yu, Geoffrey X.
    Markakis, Markos
    Kipf, Andreas
    Larson, Per-Ake
    Minhas, Umar Farooq
    Kraska, Tim
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2022, 16 (01): : 99 - 112
  • [42] 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
  • [43] Design Considerations of A Novel Distributed Key-Value Store for New Storage
    Liu, Ruicheng
    Jin, Peiquan
    Wang, Xiaoliang
    Luo, Yongping
    Chu, Zhaole
    2022 IEEE 42ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2022), 2022, : 1276 - 1277
  • [44] Memory Efficient and High Performance Key-value Store on FPGA Using Cuckoo Hashing
    Liang, Wei
    Yin, Wenbo
    Kang, Ping
    Wang, Lingli
    2016 26TH INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS (FPL), 2016,
  • [45] Kreon: An Efficient Memory-Mapped Key-Value Store for Flash Storage
    Papagiannis, Anastasios
    Saloustros, Giorgos
    Xanthakis, Giorgos
    Kalaentzis, Giorgos
    Gonzalez-Ferez, Pilar
    Bilas, Angelos
    ACM TRANSACTIONS ON STORAGE, 2021, 17 (01)
  • [46] SLIK: Scalable Low-Latency Indexes for a Key-Value Store
    Kejriwal, Ankita
    Gopalan, Arjun
    Gupta, Ashish
    Jia, Zhihao
    Yang, Stephen
    Ousterhout, John
    PROCEEDINGS OF USENIX ATC '16: 2016 USENIX ANNUAL TECHNICAL CONFERENCE, 2016, : 57 - 70
  • [47] Improving Write Performance of LSMT-based Key-Value Store
    Zhang, WeiTao
    Xu, Yinlong
    Li, Yongkun
    Li, Dinglong
    2016 IEEE 22ND INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS), 2016, : 553 - 560
  • [48] Ultra-Low Latency and High Throughput Key-Value Store Systems Over Ethernet
    Ding, Li
    Yin, Wenbo
    Wang, Lingli
    2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2018,
  • [49] PHash: A memory-efficient, high-performance key-value store for large-scale data-intensive applications
    Shim, Hyotaek
    JOURNAL OF SYSTEMS AND SOFTWARE, 2017, 123 : 33 - 44
  • [50] Design of a High-Performance, High-Endurance Key-Value SSD for Large-Key Workloads
    Park, Chanyoung
    Liu, Chun-Yi
    Kang, Kyungtae
    Kandemir, Mahmut
    Choi, Wonil
    IEEE COMPUTER ARCHITECTURE LETTERS, 2023, 22 (02) : 149 - 152