Poster: AutoThermKV: An Efficient User-Transparent In-Memory Management of Hot Data for Key-Value Stores

Abstract

Log-structured merge-tree (LSM-tree) key-value stores rely on caching to mitigate multi-component lookups and long tails, yet block and KP caches are prone to compactioninduced expiry, and all three cache types suffer from scan pollution under LRU eviction. We present AutoThermKV, a two-level in-memory architecture that decouples fast admission from hot-item protection. The front tier (HotFilter) uses a 64 Baligned bitmap/key/value page layout with Quick Space Reservation for near-constant admission cost; the back tier (HotCommitted) retains proven hot items via a lightweight LRU and a secondtouch promotion rule. Implemented atop RocksDB and evaluated on YCSB-like workloads with controllable temporal locality, AutoThermKV achieves up to 2.58 × throughput speedup, 2.60 × average-latency reduction, and tail-latency improvements of up to 20 × (p99) and 36 (p999) under modest memory budgets.