就像它很热一样:持久内存作为NVMe ssd的直接替代品的分析

Maximilian Böther, Otto Kißig, Lawrence Benson, T. Rabl, H. Plattner
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引用次数: 9

摘要

固态硬盘(ssd)大大提高了数据库系统的性能,因为它们提供了比传统硬盘驱动器更高的带宽。持久内存(PMem)是一种新的存储技术,它提供类似dram的速度和类似ssd的容量。由于其字节可寻址性,研究主要将PMem视为DRAM的替代品或补充,例如,通过提出高度优化的DRAM-PMem混合数据结构和系统设计。但是,PMem也可以通过常规文件系统接口和标准Linux I/O操作来使用。在本文中,我们分析了PMem作为非易失性内存快速(NVMe) ssd的直接替代品,并评估了在不需要或只需要对现有应用程序进行微小更改的情况下可能获得的性能提升。这种插入式方法可以提高数据库系统(如Postgres)的速度,而不需要更改任何代码。我们在三个数据库微基准测试和Postgres上广泛使用的TPC-H基准测试中系统地评估了PMem和NVMe ssd。我们的实验表明,在读取密集型OLAP工作负载中,PMem在没有任何修改的情况下,比四个NVMe ssd的RAID性能高出4倍,同时在写密集型工作负载中达到类似的性能。最后,我们给出了四个实用的见解,以帮助决策何时使用PMem作为SSD的直接替代品以及如何对其进行优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Drop It In Like It's Hot: An Analysis of Persistent Memory as a Drop-in Replacement for NVMe SSDs
Solid-state drives (SSDs) have improved database system performance significantly due to the higher bandwidth that they provide over traditional hard disk drives. Persistent memory (PMem) is a new storage technology that offers DRAM-like speed at SSD-like capacity. Due to its byte-addressability, research has mainly treated PMem as a replacement of, or an addition to DRAM, e.g., by proposing highly-optimized, DRAM-PMem-hybrid data structures and system designs. However, PMem can also be used via a regular file system interface and standard Linux I/O operations. In this paper, we analyze PMem as a drop-in replacement for Non-Volatile Memory Express (NVMe) SSDs and evaluate possible performance gains while requiring no or only minor changes to existing applications. This drop-in approach speeds-up database systems like Postgres, without requiring any code changes. We systematically evaluate PMem and NVMe SSDs in three database microbenchmarks and the widely used TPC-H benchmark on Postgres. Our experiments show that PMem outperforms a RAID of four NVMe SSDs in read-intensive OLAP workloads by up to 4x without any modifications while achieving similar performance in write-intensive workloads. Finally, we give four practical insights to aid decision-making on when to use PMem as an SSD drop-in replacement and how to optimize for it.
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