High-Performance Remote Data Persisting for Key-Value Stores via Persistent Memory Region

Key-value stores (KVStores), such as LevelDB and Redis, have been widely used in real-world production environments. To guarantee data durability and availability, traditional KVStores suffer from high write latency, mainly caused by the long network and data-persisting time. To solve this problem, this article presents a novel data-persisting path for KVStores, allowing remote clients to persist data to the KVStore server with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu s$ </tex-math></inline-formula> -level latency. The novelty of this study is threefold. First, we propose PMRDirect, which utilizes a persistent memory region (PMR) in the NVM express standard to construct a direct data-persisting path from the RDMA networking card (NIC) to the PMR region inside an SSD. Second, to showcase PMRDirect in KVStores, we developed a new accessing stack called PMRAccess, enabling remote clients to access existing KVStores and providing durability for each write request. Specifically, we present a low-latency RDMA-based messaging mode and a chunk-based PMR management in PMRAccess to reduce write latency and improve system throughput. Finally, we conducted extensive experiments to evaluate the performance of our proposals. We first compared PMRDirect with a few remote data-persisting paths to show its effectiveness. Then, we evaluated PMRAccess upon two KVStores, including LibCuckoo (an in-memory KVStore) and LevelDB (an in-storage KVStore). The results showed that PMRAccess outperformed the SSD-based accessing stack by up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.1\times $ </tex-math></inline-formula> in write throughput and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$36\times $ </tex-math></inline-formula> in write tail latency, and it achieved <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.7\times $ </tex-math></inline-formula> higher write throughput and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.59\times $ </tex-math></inline-formula> lower write tail latency over the PMEM-based accessing stack. Further, we conducted a system-to-system comparison between the PMRAccess-integrated LibCuckoo and Redis, and the results showed our proposal achieved up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$13\times $ </tex-math></inline-formula> higher throughputs and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$40\times $ </tex-math></inline-formula> lower write latency than Redis.