Title: Keigo: Co-designing Log-Structured Merge Key-Value Stores with a Non-Volatile, Concurrency-aware Storage Hierarchy (Extended Version) Show Chinese title

Title: 北广吾：与非易失性、并发感知的存储层次结构协同设计日志结构合并键值存储（扩展版本）

Abstract: We present Keigo, a concurrency- and workload-aware storage middleware that enhances the performance of log-structured merge key-value stores (LSM KVS) when they are deployed on a hierarchy of storage devices. The key observation behind Keigo is that there is no one-size-fits-all placement of data across the storage hierarchy that optimizes for all workloads. Hence, to leverage the benefits of combining different storage devices, Keigo places files across different devices based on their parallelism, I/O bandwidth, and capacity. We introduce three techniques - concurrency-aware data placement, persistent read-only caching, and context-based I/O differentiation. Keigo is portable across different LSMs, is adaptable to dynamic workloads, and does not require extensive profiling. Our system enables established production KVS such as RocksDB, LevelDB, and Speedb to benefit from heterogeneous storage setups. We evaluate Keigo using synthetic and realistic workloads, showing that it improves the throughput of production-grade LSMs up to 4x for write- and 18x for read-heavy workloads when compared to general-purpose storage systems and specialized LSM KVS. Show Chinese abstract

Abstract: 我们提出了Keigo，这是一种具备并发和工作负载感知能力的存储中间件，当部署在存储设备层次结构上时，它可以提升日志结构合并键值存储（LSM KVS）的性能。 Keigo背后的关键观察是，在存储层次结构中不存在一种能够适用于所有工作负载的“一刀切”的数据放置方式。 因此，为了利用结合不同存储设备的优势，Keigo根据文件的并行性、I/O带宽和容量，在不同的设备之间放置文件。 我们引入了三种技术——并发感知的数据放置、持久只读缓存和基于上下文的I/O区分。 Keigo可以跨不同的LSM移植，能够适应动态工作负载，并且不需要广泛的配置分析。 我们的系统使已有的生产级KVS（如RocksDB、LevelDB和Speedb）能够从异构存储设置中受益。 我们使用合成和实际工作负载对Keigo进行了评估，结果显示，与通用存储系统和专门的LSM KVS相比，对于写密集型工作负载，Keigo可将生产级LSM的吞吐量提高多达4倍；对于读密集型工作负载，可提高多达18倍。