Optimizing In-network Caching for Key-Value Stores under Write-intensive Workloads
Yuanhang Gao, Yingwen Chen, Xiangrui Yang, Huan Zhou, Shihua Tang, Yuanfeng Chen, Ming Xu · 2024
Key-value stores are critical for modern data centers, yet they struggle with performance degradation under write-intensive workloads due to frequent cache invalidations. Traditional read-optimized caching mechanisms fail to maintain efficiency as frequent updates lead to obsolete cached data. As a result, queries sent by clients will suffer from long queuing delays or even be dropped and overall system performance will be degraded severely. This paper presents a novel key-value stores architecture, named Freq-absorb, which addresses this issue through a delayed-write mechanism delaying writes commitment to backend servers. By buffering write queries within the switch for a specific period, Freq-absorb reduces the impact of cache invalidations, improves switch hit rates, and enhances overall system performance. We implement a prototype using an FPGA-based switch that acts as the ToR (Top of Rack) switch to achieve cache and the appended write buffer. Our experimental results show that compared to the read cache mechanism, our approach can reduce switch miss from 99% to 48.4% when handling write-intensive workloads, significantly enhancing performance.