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An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging
Jeongho Lee, Jonggyu Park, Young Ik Eom
http://doi.org/10.5626/JOK.2022.49.8.655
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.
An Efficient Cleaning Scheme for File Defragmentation on Log-Structured File System
Jonggyu Park, Dong Hyun Kang, Euiseong Seo, Young Ik Eom
When many processes issue write operations alternately on Log-structured File System (LFS), the created files can be fragmented on the file system layer although LFS sequentially allocates new blocks of each process. Unfortunately, this file fragmentation degrades read performance because it increases the number of block I/Os. Additionally, read-ahead operations which increase the number of data to request at a time exacerbates the performance degradation. In this paper, we suggest a new cleaning method on LFS that minimizes file fragmentation. During a cleaning process of LFS, our method sorts valid data blocks by inode numbers before copying the valid blocks to a new segment. This sorting re-locates fragmented blocks contiguously. Our cleaning method experimentally eliminates 60% of file fragmentation as compared to file fragmentation before cleaning. Consequently, our cleaning method improves sequential read throughput by 21% when read-ahead is applied.
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