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PM-Blade: A Persistent Memory Augmented LSM-tree Storage for Database

  • Yinan Zhang
  • , Huiqi Hu*
  • , Xuan Zhou
  • , Enlong Xie
  • , Hongdi Ren
  • , Le Jin
  • *此作品的通讯作者
  • East China Normal University
  • Meituan

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
出版商IEEE Computer Society
3363-3375
页数13
ISBN(电子版)9798350322279
DOI
出版状态已出版 - 2023
活动39th IEEE International Conference on Data Engineering, ICDE 2023 - Anaheim, 美国
期限: 3 4月 20237 4月 2023

出版系列

姓名Proceedings - International Conference on Data Engineering
2023-April
ISSN(印刷版)1084-4627

会议

会议39th IEEE International Conference on Data Engineering, ICDE 2023
国家/地区美国
Anaheim
时期3/04/237/04/23

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