HotRing: A Hotspot-Aware In-Memory Key-Value Store


Jiqiang Chen, Liang Chen, Sheng Wang, Guoyun Zhu, Yuanyuan Sun, Huan Liu, and Feifei Li, Alibaba Group


Due to travel restrictions, the authors could not attend the conference and their work was presented by Le Cai, Alibaba Group.

In-memory key-value stores (KVSes) are widely used to cache hot data, in order to solve the hotspot issue in disk-based storage or distributed systems. The hotspot issue inside in-memory KVSes is however being overlooked. Due to the recent trend that hotspot issue becomes more serious, the lack of hotspot-awareness in existing KVSes make them poorly performed and unreliable on highly skewed workloads. In this paper, we explore hotspot-aware designs for in-memory index structures in KVSes. We first analyze the potential benefits from ideal hotspot-aware indexes, and discuss challenges (i.e., hotspot shift and concurrent access issues) in effectively leveraging hotspot-awareness. Based on these insights, we propose a novel hotspot-aware KVS, named HotRing, that is optimized for massively concurrent accesses to a small portion of items. HotRing is based on an ordered-ring hash index structure, which provides fast access to hot items by moving head pointers closer to them. It also applies a lightweight strategy to detect hotspot shifts at run-time. HotRing comprehensively adopts lock-free structures in its design, for both common operations (i.e., read, update) and HotRing-specific operations (i.e., hotspot shift detection, head pointer movement and ordered-ring rehash), so that massively concurrent requests can better leverage multi-core architectures. The extensive experiments show that our approach is able to achieve 2.58× improvement compared to other in-memory KVSes on highly skewed workloads.

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@inproceedings {246162,
author = {Jiqiang Chen and Liang Chen and Sheng Wang and Guoyun Zhu and Yuanyuan Sun and Huan Liu and Feifei Li},
title = {{HotRing}: A {Hotspot-Aware} {In-Memory} {Key-Value} Store},
booktitle = {18th USENIX Conference on File and Storage Technologies (FAST 20)},
year = {2020},
isbn = {978-1-939133-12-0},
address = {Santa Clara, CA},
pages = {239--252},
url = {},
publisher = {USENIX Association},
month = feb

Presentation Video