A NUMA-aware Key-Value Store for Hybrid Memory Architecture

Abstract

Key-value (KV) store, which regards data as key-value pairs, has been widely deployed in the cloud while demanding highly responsive query operations. A novel persistent memory device, Intel Optane DC Persistent Memory Module (DCPMM), provides the opportunity for boosting the performance. In this paper, we propose a KV store based on LSM tree, called PMDB, which is tailor-made for a hybrid memory architecture, namely the traditional DRAM device alongside the DCPMM. PMDB stores data on DCPMM for persistence and establishes an auxiliary index in the DRAM for improving the read performance. To improve write amplification which is caused by the physical characteristic of DCPMM, PMDB performs both the operations of flush and compaction at a performance-friendly granularity (256Bytes). In addition, by using the local thread of the CPU node, PMDB is able to improve the NUMA latency of DCPMM effectively. We implement PMDB in a realistic DCPMM environment. The experimental results show that, compared to the state-of-art LSM-based KV stores, PMDB improves the throughput of random read by up to 2.72×.