ZARC: Re-inventing Zone Allocation for LSMs on ZNS SSD

Log-Structured Merge (LSM)-based storage engines offer high write throughput by storing the data on storage as immutable files that are opportunistically reorganized through compactions. Immutability of the files and their frequent garbage collection (GC), however, leads to a major performance bottleneck: high write amplification. This is further exacerbated by the device-level GC when LSM engines run on top of ZNS SSDs. While prior research has shown that compaction-aware file placement at the device level can reduce the overall write amplification, we point out that the proposed solutions are tuned exclusively for specific compaction strategies, SSD configurations, and workloads. In this early-stage work, we highlight that for LSM engines on ZNS SSDs, performance is governed by a critical four-way trade-off between the compaction file picking policy (LSM-side) and the file placement, GC, and new zone allocation policies (ZNS-side). To this end, we introduce ZARC, a novel framework for Zone Allocation & Reclamation after Compaction that offers a continuum of hybrid file placement policies to bring the overall write amplification closer to its theoretical lower bound and allows the user to navigate this vast design space for a given workload and configuration. ZARC’s hybrid file placement policies optimize performance for each LSM-level independently, leading to level-specific file placement, garbage collection, and zone allocation policies. Preliminary results from experimentation on ZenFS, a RocksDB file system for ZNS SSDs, show that ZARC’s hybrid file placement policies reduce data movement by up to 86% and ZARC-GC improves ZenFS garbage collection performance by (i) reclaiming sufficient free space and (ii) maintaining a small reserve of empty zones to prevent GC-induced stalls, and (iii) reducing GC-induced data movement by 8.6%.