【摘 要】
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Many key-value stores use RDMA to optimize the messaging and data transmission between application layer and the storage layer,most of which only provide point-wise op-erations.Skiplist-based store can support both point operations and range queries,but i
【机 构】
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School of Data Science and Engineering,East China Normal University,Shanghai 200062,China
论文部分内容阅读
Many key-value stores use RDMA to optimize the messaging and data transmission between application layer and the storage layer,most of which only provide point-wise op-erations.Skiplist-based store can support both point operations and range queries,but its CPU-intensive access operations com-bined with the high-speed network will easily lead to the stor-age layer reaches CPU bottlenecks.The common solution to this problem is offloading some operations into the application layer and using RDMA bypassing CPU to directly perform re-mote access,but this method is only used in the hash table-based store.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 mech-anism to ensure all the concurrency during two access modes.RS-store also supports client-active range query which can re-duce the storage layer\'s CPU consumption.At last,we eval-uate RS-store on an RDMA-capable cluster.Experimental re-sults show that RS-store achieves up to 2x improvements over RDMA-enabled RocksDB on the throughput and application\'s scalability.
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