在傳統的固態硬碟（SSDs）中，某些應用場景的性能受到硬體設計限制的制約。因此，出現了各種新的SSD架構，尤其是在需要頻繁寫操作的場景中，分區命名空間固態硬碟（Zoned Namespace SSDs）展現出優越的寫入性能並被廣泛採用。此外，在大規模數據庫中，基於日誌結構合併樹（LSM Trees）常被用作後端存儲，因為它們的數據結構特性使其能夠更有效地處理連續寫入數據。這些因素使得LSM Trees成為大規模數據庫或數據中心等應用的熱門選擇。

在我們的研究中，我們探索了LSM Tree與分區命名空間固態硬碟的整合，旨在充分利用它們各自的優勢，以實現增強的性能。我們提出了SplitLSM，它從數據放置和合併兩個方面對在ZNS SSDs上廣泛使用的RocksDB（一個基於LSM Tree的廣泛使用的數據庫）進行了優化。我們的實驗結果表明，SplitLSM通過利用ZNS的區域架構和LSM Tree的連續寫入特性，提高了RocksDB在ZNS SSDs上的寫入性能。

In traditional SSDs, performance in certain application scenarios has been limited by hardware design constraints. As a result, various new SSD architectures have been developed, especially in scenarios that require frequent write operations, where Zoned Namespace SSDs have demonstrated outstanding write performance and are widely adopted. Additionally, in large-scale databases, Log-Structured Merge Trees (LSM Trees) are commonly used as backend storage due to their data structure characteristics, which allow them to handle continuous write data more effectively. These factors make LSM Trees a popular choice for applications such as large-scale databases or data centers.

In our research, we explore the integration of LSM Tree with ZNS SSDs with the goal of leveraging their respective strengths to achieve enhanced performance. We propose SplitLSM, which optimizes RocksDB (a widely used LSM Tree-based database) on ZNS SSDs from two aspects: data placement and compaction. Our experimental results demonstrate that SplitLSM improves the write performance of RocksDB on ZNS SSDs by harnessing the benefits of ZNS's zone architecture and LSM Tree's sequential write characteristics.

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