research-article

Building Efficient Key-Value Stores via a Lightweight Compaction Tree

Authors:

Changsheng XieAuthors Info & Claims

ACM Transactions on Storage (TOS), Volume 13, Issue 4

Article No.: 29, Pages 1 - 28

https://doi.org/10.1145/3139922

Published: 24 November 2017 Publication History

Abstract

Log-Structure Merge tree (LSM-tree) has been one of the mainstream indexes in key-value systems supporting a variety of write-intensive Internet applications in today’s data centers. However, the performance of LSM-tree is seriously hampered by constantly occurring compaction procedures, which incur significant write amplification and degrade the write throughput. To alleviate the performance degradation caused by compactions, we introduce a lightweight compaction tree (LWC-tree), a variant of LSM-tree index optimized for minimizing the write amplification and maximizing the system throughput. The lightweight compaction drastically decreases write amplification by appending data in a table and only merging the metadata that have much smaller size. Using our proposed LWC-tree, we have implemented three key-value LWC-stores on different storage mediums including Shingled Magnetic Recording (SMR) drives, Solid State Drives (SSD), and conventional Hard Disk Drives (HDDs). The LWC-store is particularly optimized for SMR drives, as it eliminates the multiplicative I/O amplification from both LSM-trees and SMR drives. Due to the lightweight compaction procedure, LWC-store reduces the write amplification by a factor of up to 5× compared to the popular LevelDB key-value store. Moreover, the random write throughput of the LWC-tree on SMR drives is significantly improved by up to 467% even compared with LevelDB on conventional HDDs. Furthermore, LWC-tree has wide applicability and delivers impressive performance improvement in various conditions, including different storage mediums (i.e., SMR, HDD, SSD) and various value sizes and access patterns (i.e., uniform and Zipfian).

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Cited By

Shin JZhou LWang JAref W(2025)An update-intensive LSM-based R-tree indexThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-024-00876-734:1Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1007/s00778-024-00876-7
Zhou RZhang YLi CZhou KWang PZhang GZhang JZhang G(2024)HyperDB: a Novel Key Value Store for Reducing Background Traffic in Heterogeneous SSD StorageProceedings of the 53rd International Conference on Parallel Processing10.1145/3673038.3673153(453-463)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3673038.3673153
Yu QGuo CZhuang JThakkar VWang JCao Z(2024)CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated InfrastructureProceedings of the ACM on Management of Data10.1145/36549272:3(1-28)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654927
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Index Terms

Building Efficient Key-Value Stores via a Lightweight Compaction Tree
1. General and reference
  1. Cross-computing tools and techniques
    1. Performance
2. Information systems
  1. Data management systems
    1. Database management system engines
      1. Parallel and distributed DBMSs
        Key-value stores
  2. Information storage systems
    1. Information storage technologies
      1. Magnetic disks

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Published In

cover image ACM Transactions on Storage

ACM Transactions on Storage Volume 13, Issue 4

Special Issue on MSST 2017 and Regular Papers

November 2017

329 pages

ISSN:1553-3077

EISSN:1553-3093

DOI:10.1145/3160863

Editor:
Sam H. Noh
Ulsan National Institute of Science and Technology, Ulsan, Korea

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Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 November 2017

Accepted: 01 September 2017

Received: 01 August 2017

Published in TOS Volume 13, Issue 4

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U.S. National Science Foundation (NSF)
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China
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Cited By

Shin JZhou LWang JAref W(2025)An update-intensive LSM-based R-tree indexThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-024-00876-734:1Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1007/s00778-024-00876-7
Zhou RZhang YLi CZhou KWang PZhang GZhang JZhang G(2024)HyperDB: a Novel Key Value Store for Reducing Background Traffic in Heterogeneous SSD StorageProceedings of the 53rd International Conference on Parallel Processing10.1145/3673038.3673153(453-463)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3673038.3673153
Yu QGuo CZhuang JThakkar VWang JCao Z(2024)CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated InfrastructureProceedings of the ACM on Management of Data10.1145/36549272:3(1-28)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654927
Sun HXu JJiang XChen GYue YQin X(2024)gLSM: Using GPGPU to Accelerate Compactions in LSM-tree-based Key-value StoresACM Transactions on Storage10.1145/363378220:1(1-41)Online publication date: 30-Jan-2024
https://dl.acm.org/doi/10.1145/3633782
Kim DLee JLim KHeo JHam TLee J(2024)An LSM Tree Augmented with B+ Tree on Nonvolatile MemoryACM Transactions on Storage10.1145/363347520:1(1-24)Online publication date: 30-Jan-2024
https://dl.acm.org/doi/10.1145/3633475
Cai MJiang XShen JYe B(2024)SplitDB: Closing the Performance Gap for LSM-Tree-Based Key-Value StoresIEEE Transactions on Computers10.1109/TC.2023.332698273:1(206-220)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TC.2023.3326982
Wang XLi HTan HWang XLu PWang H(2024)HIndex-FLSM: Fragmented Log-Structured Merge Trees Integrated with Heat and Index2024 3rd International Joint Conference on Information and Communication Engineering (JCICE)10.1109/JCICE61382.2024.00024(71-76)Online publication date: 10-May-2024
https://doi.org/10.1109/JCICE61382.2024.00024
Yang CYang FXu QZhang YLiang J(2024)SolsDBFuture Generation Computer Systems10.1016/j.future.2024.05.050160:C(295-304)Online publication date: 1-Nov-2024
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Lin XPan YFeng WZhang HLin M(2024)MTDB: an LSM-tree-based key-value store using a multi-tree structure to improve read performanceThe Journal of Supercomputing10.1007/s11227-024-06382-580:16(23995-24025)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s11227-024-06382-5
Li XShao ZWang YLiu B(2024)Minimum Resonant Current Control for Detuned WPT System with LCC-LCC CompensationThe Proceedings of the 11th Frontier Academic Forum of Electrical Engineering (FAFEE2024)10.1007/978-981-97-8824-8_33(296-304)Online publication date: 30-Nov-2024
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