发表机构
Carnegie Mellon University; Sepuluh Nopember Institute of Technology; Harvard University（卡内基梅隆大学; 十十一月理工学院; 哈佛大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究针对缓存淘汰的惰性提升机制，通过真实系统轨迹测试多种策略，提出D-FR和AGE两种新方案，可减少20%-60%的提升次数且保持低缺失率。
AI 中文摘要
缓存淘汰算法对现代数据系统的性能至关重要，但它们的可扩展性常受限于对象提升带来的高计算开销。惰性提升（Lazy Promotion）技术作为传统最近最少使用（LRU）方法的松弛方案应运而生，旨在缓解锁竞争并提升吞吐量。本研究采用真实系统的生产轨迹对五种惰性提升策略进行基准测试：概率LRU（Probabilistic-LRU）、批量LRU（Batch-LRU）、延迟LRU（Delay-LRU）、先进先出重插入（FIFO-reinsertion）及随机LRU（Random-LRU）。我们从缺失率、可扩展性、提升次数，以及衡量每次提升对应命中数的新指标——提升效率这四个维度评估这些技术。结果显示，延迟LRU和先进先出重插入可显著提升提升效率，而批量LRU和概率LRU在不显著增加缺失率的前提下难以减少提升次数。我们进一步探究了惰性提升在ARC和2Q等高级算法中的影响，得到相似结论。此外，我们发现了巨大的优化潜力，表明若具备先验知识，多数缓存提升是不必要的。为进一步减少LRU中的提升次数，我们提出两种新型增强方案：延迟先进先出重插入（Delayed FIFO-reinsertion, D-FR）和年龄引导淘汰（Age-Guided Eviction, AGE），这两种方案可减少20%-60%的提升次数，同时实现相近或更低的缺失率。
英文摘要
Cache eviction algorithms play a critical role in the performance of modern data systems, yet their scalability is often limited by the high computational overhead associated with object promotions. Lazy Promotion techniques have emerged as relaxations of traditional Least-Recently-Used (LRU) methods, designed to alleviate lock contention and increase throughput. This work uses production traces from real-world systems to benchmark five Lazy Promotion strategies: Probabilistic-LRU, Batch-LRU, Delay-LRU, FIFO-reinsertion, and Random-LRU. We evaluate these techniques across miss ratio, scalability, promotion count, and a novel metric called promotion efficiency, which measures the number of hits per promotion. Our results reveal that Delay-LRU and FIFO-reinsertion significantly improve promotion efficiency, whereas Batch-LRU and Probabilistic-LRU struggle to reduce promotions without significantly increasing miss ratio. We further explore the impact of lazy promotion in advanced algorithms such as ARC and 2Q and make a similar observation. Moreover, we uncover substantial optimization potential, showing that most cache promotions are unnecessary when equipped with oracle knowledge. To further reduce promotions in LRU, we propose two novel enhancements-Delayed FIFO-reinsertion (D-FR) and Age-Guided Eviction (AGE)-that reduce promotions by 20-60% while achieving a similar or lower miss ratio.
Comments14 pages, 13 figures, and 3 tables. Published in PVLDB 19(4); VLDB 2026 conference paper
Journal refProceedings of the VLDB Endowment, 19(4): 549-562, 2025
