Discard-Based Garbage Collection for Distributed Log-Structured Storage Systems in ByteDance
Runhua Bian, Liqiang Zhang, Jinxin Liu, Jiacheng Zhang, Jianong Zhong, Jiahao Gu, Hao Guo, Zhihong Guo, Yunhao Li, Fenghao Zhang, Jiangkun Zhao, Yangming Chen
Abstract
ByteStore is a distributed append-only storage system that serves as the foundational storage layer of the ByteDance infrastructure. Initially, storage services on ByteStore use compaction for garbage collection (GC). Additional writes induced by compaction and the SSD space occupied by stale data result in millions of dollars in extra Total Cost of Ownership (TCO) per month. Aggressive compaction releases the SSD space, but at the cost of more write operations and faster SSD wear, thus failing to reduce TCO.
Based on our analysis of the traces from the block storage service (ByteDrive) deployed on ByteStore, we propose DisCoGC, a Discard-and-Compaction combined Garbage Collection scheme, which employs a discard mechanism to reclaim the space occupied by stale data without moving valid data. Production cluster metrics monitor and offline experiments demonstrate that DisCoGC achieves approximately 20% reduction in TCO, without sacrificing performance.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on6
- FlatStore: An Efficient Log-Structured Key-Value Storage Engine for Persistent MemoryYoumin Chen, Youyou Lu, Fan Yang, Qing Wang et al.ASPLOS 2020 · 166 citations
- SpanDB: A Fast, Cost-Effective LSM-tree Based KV Store on Hybrid StorageHao Chen, Chaoyi Ruan, Cheng Li, Xiaosong Ma et al.FAST 2021 · 120 citations
- Pacman: An Efficient Compaction Approach for Log-Structured Key-Value Store on Persistent MemoryJing Wang, Youyou Lu, Qing Wang, Minhui Xie et al.USENIX ATC 2022 · 44 citations
- AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC OffloadingZhuohui Duan, Hao Feng, Haikun Liu, Xiaofei Liao et al.FAST 2025 · 11 citations
- MaxEmbed: Maximizing SSD bandwidth utilization for huge embedding models servingRuwen Fan, Minhui Xie, Haodi Jiang, Youyou LuASPLOS 2024 · 1 citation
Related papers
- TierScape: Harnessing Multiple Compressed Tiers to Tame Server Memory TCOSandeep Kumar, Aravinda Prasad, Sreenivas SubramoneyEuroSys 2026 · 1 citation
- Terark-DS: A High-Performance and Storage-Efficient Key-Value Separation Storage Engine on Disaggregated StorageJianshun Zhang, Xun Deng, Fang Wang, Jiaxin Ou et al.VLDB 2026
- How to Cut Out Expired Data with Nearly Zero Overhead for Solid-State DrivesWei-Lin Wang, Tseng-Yi Chen, Yuan-Hao Chang, Hsin-Wen Wei et al.DAC 2020 · 2 citations
- Scavenger: Better Space-Time Trade-Offs for Key-Value Separated LSM-treesJianshun Zhang, Fang Wang, Sheng Qiu, Yi Wang et al.ICDE 2024 · 5 citations
- PolarStore: High-Performance Data Compression for Large-Scale Cloud-Native DatabasesQingda Hu, Xinjun Yang, Feifei Li, Junru Li et al.FAST 2026 · 4 citations
