@inproceedings{d6235d29799245dfabdca11e9fc04bb4,
title = "PM-Blade: A Persistent Memory Augmented LSM-tree Storage for Database",
abstract = "In this paper, we present PM-Blade, an LSM-tree structured storage augmented with persistent memory (or non-volatile memory). PM-Blade utilizes persistent memory to optimize read performance and reduce write amplification, which are essential to Meituan's online retail applications. Distinguished from existing designs, PM-Blade leverages persistent memory to drastically increase the capacity of the level-0 layer of LSM-tree. An enlarged level-0 layer allows a large amount of hot or warm data to be retained in persistent memory, enabling high read performance. At the same time, it works as a large write buffer that absorbs write amplification. To make the best of the design, we devised an internal compaction method and used a cost-based compaction strategy to maximize the utility of the level-0 layer. We implemented the compaction method using coroutines to improve its efficiency and resource utilization. We evaluated PM-Blade through extensive experiments, in which PM-Blade outperformed several open-source alternatives on standard benchmarks and a real-world workload of Meituan.",
keywords = "Database storage, LSM-tree, Persistent memory",
author = "Yinan Zhang and Huiqi Hu and Xuan Zhou and Enlong Xie and Hongdi Ren and Le Jin",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 39th IEEE International Conference on Data Engineering, ICDE 2023 ; Conference date: 03-04-2023 Through 07-04-2023",
year = "2023",
doi = "10.1109/ICDE55515.2023.00258",
language = "英语",
series = "Proceedings - International Conference on Data Engineering",
publisher = "IEEE Computer Society",
pages = "3363--3375",
booktitle = "Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023",
address = "美国",
}