BonsaiKV: Towards Fast, Scalable, and Persistent Key-Value Stores with Tiered, Heterogeneous Memory System

被引:0
|
作者
Cai, Miao [1 ]
Shen, Junru [2 ]
Yuan, Yifan [3 ]
Qu, Zhihao [1 ]
Ye, Baoliu [1 ,4 ]
机构
[1] Hohai Univ, Sch Comp & Informat, Minist Water Resources, Key Lab Water Big Data Technol, Nanjing, Peoples R China
[2] Hohai Univ, Sch Comp & Informat, Nanjing, Peoples R China
[3] Intel Labs, Hillsboro, OR 97124 USA
[4] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing, Peoples R China
来源
PROCEEDINGS OF THE VLDB ENDOWMENT | 2023年 / 17卷 / 04期
基金
中国国家自然科学基金;
关键词
PERFORMANCE; TREE;
D O I
10.14778/3636218.3636228
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Emerging NUMA/CXL-based tiered memory systems with heterogeneous memory devices such as DRAM and NVMM deliver ultrafast speed, large capacity, and data persistence all at once, offering great promise to high-performance in-memory key-value stores. To fully unleash the performance potential of such memory systems, this paper presents BonsaiKV, a key-value store that makes the best use of different components in a tiered memory system. The core of BonsaiKV is a tri-layer hierarchical storage architecture that separates data indexing, persistence, and scalability from each other and realizes each of them within a specialized software-hardware layer. We design BonsaiKV with a set of novel techniques, including collaborative tiered indexing, NVMM congestion control mechanisms, fine-grained data striping, and NUMA-aware data management, to leverage hardware strengths and tackle device deficiencies. We compare BonsaiKV with state-of-the-art NVMM-optimized key-value stores and persistent index structures using a variety of YCSB workloads. Evaluation results demonstrate that BonsaiKV outperforms others by up to 7.69x, 19.59x, and 12.86x in read-, write- and scan-intensive scenarios, respectively.
引用
收藏
页码:726 / 739
页数:14
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