AnyKey: A Key-Value SSD for All Workload Types
- Authors
- Park, Chanyoung; Lee, Jungho; Liu, Chun-Yi; Kang, Kyungtae; Kandemir, Mahmut Taylan; Choi, Wonil
- Issue Date
- Mar-2025
- Publisher
- Association for Computing Machinery
- Keywords
- key-value solid-state drive; log-structured merge-tree; storage management software; tail latency
- Citation
- International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS, v.1, pp 47 - 63
- Pages
- 17
- Indexed
- SCOPUS
- Journal Title
- International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
- Volume
- 1
- Start Page
- 47
- End Page
- 63
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125379
- DOI
- 10.1145/3669940.3707279
- Abstract
- Key-value solid-state drives (KV-SSDs) are considered as a potential storage solution for large-scale key-value (KV) store applications. Unfortunately, the existing KV-SSD designs are tuned for a specific type of workload, namely, those in which the size of the values are much larger than the size of the keys. Interestingly, there also exists another type of workload, in practice, in which the sizes of keys are relatively large. We re-evaluate the current KV-SSD designs using such unexplored workloads and document their significantly-degraded performance. Observing that the performance problem stems from the increased size of the metadata, we subsequently propose a novel KV-SSD design, called AnyKey, which prevents the size of the metadata from increasing under varying sizes of keys. Our detailed evaluation using a wide range of real-life workloads indicates that AnyKey outperforms the state-of-the-art KV-SSD design under different types of workloads with varying sizes of keys and values. © 2025 ACM.
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