@article{M68724AB3,
title = "An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging",
journal = "Journal of KIISE, JOK",
year = "2022",
issn = "2383-630X",
doi = "10.5626/JOK.2022.49.8.655",
author = "Jeongho Lee,Jonggyu Park,Young Ik Eom",
keywords = "F2FS,multi-head logging,fragmentation",
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."
}