Abstract
Many key-value stores use RDMA to optimize the messaging and data transmission between application layer and storage layer, most of which only provide point-wise operations. Skiplist-based store can support both point operations and range queries, but its CPU-intensive access operations combined with the high-speed network will easily lead to the storage layer reaches CPU bottlenecks. In this paper, we present RS-store, a skiplist-based key-value store with RDMA, which can overcome the cpu handle of the storage layer by enabling two access modes: local access and remote access. In RS-store, we redesign a novel data structure R-skiplist to save the communication cost in remote access, and implement a latch-free concurrency control mechanism to ensure all the concurrency during two access modes. At last, our evaluation on a RDMA-capable cluster shows that the performance of RS-store over R-skiplist is 0.6 –1 higher than the existing skiplist, and it supports application layer’s high scalability.
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CITATION STYLE
Huang, C., Hu, H., Qi, X., Zhou, X., & Zhou, A. (2020). RS-store: A SkipList-Based Key-Value Store with Remote Direct Memory Access. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12112 LNCS, pp. 314–323). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59410-7_22
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