An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging 


Vol. 49,  No. 8, pp. 655-662, Aug.  2022
10.5626/JOK.2022.49.8.655


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  Abstract

RocksDB has been considered one of the most representative LSM-tree based key-value stores, and it is actively used in high-performance database systems. However, because of the nature of such database systems, which run for an extended period of time and frequently write to the underlying storage devices, the systems may incur file system-level fragmentation. Additionally, various optimizations in RocksDB may accelerate the file system-level fragmentation under aged systems, which hinders the maintenance of long-term superior performance of flash-based storage devices such as SSDs. In this paper, we first analyze the fragmentation problem of RocksDB on F2FS and propose a new RocksDB leveling technique that exploits F2FS multi-head logging. The experimental results using an SSD confirm that the proposed method improves the throughput by 7% and reduces tail latency by 18%, compared with the conventional F2FS file system, and improves the throughput by 56% and reduces tail latency by 19%, compared with the EXT4 file system.


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  Cite this article

[IEEE Style]

J. Lee, J. Park, Y. I. Eom, "An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging," Journal of KIISE, JOK, vol. 49, no. 8, pp. 655-662, 2022. DOI: 10.5626/JOK.2022.49.8.655.


[ACM Style]

Jeongho Lee, Jonggyu Park, and Young Ik Eom. 2022. An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging. Journal of KIISE, JOK, 49, 8, (2022), 655-662. DOI: 10.5626/JOK.2022.49.8.655.


[KCI Style]

이정호, 박종규, 엄영익, "F2FS 멀티-헤드 로깅을 이용한 효율적인 RocksDB 레벨링 기법," 한국정보과학회 논문지, 제49권, 제8호, 655~662쪽, 2022. DOI: 10.5626/JOK.2022.49.8.655.


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