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Implications of non-volatile memory as primary storage for database management systems

机译:非易失性存储器作为数据库管理系统的主要存储的含义

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Traditional Database Management System (DBMS) software relies on hard disks for storing relational data. Hard disks are cheap, persistent, and offer huge storage capacities. However, data retrieval latency for hard disks is extremely high. To hide this latency, DRAM is used as an intermediate storage. DRAM is significantly faster than disk, but deployed in smaller capacities due to cost and power constraints, and without the necessary persistency feature that disks have. Non-Volatile Memory (NVM) is an emerging storage class technology which promises the best of both worlds. It can offer large storage capacities, due to better scaling and cost metrics than DRAM, and is non-volatile (persistent) like hard disks. At the same time, its data retrieval time is much lower than that of hard disks and it is also byte-addressable like DRAM. In this paper, we explore the implications of employing NVM as primary storage for DBMS. In other words, we investigate the modifications necessary to be applied on a traditional relational DBMS to take advantage of NVM features. As a case study, we have modified the storage engine (SE) of PostgreSQL enabling efficient use of NVM hardware. We detail the necessary changes and challenges such modifications entail and evaluate them using a comprehensive emulation platform. Results indicate that our modified SE reduces query execution time by up to 40% and 14.4% when compared to disk and NVM storage, with average reductions of 20.5% and 4.5%, respectively.
机译:传统的数据库管理系统(DBMS)软件依赖于硬盘来存储关系数据。硬盘便宜,持久并且提供巨大的存储容量。但是,硬盘的数据检索延迟非常高。为了隐藏此延迟,将DRAM用作中间存储。 DRAM的速度明显快于磁盘,但由于成本和功耗的限制,并且没有磁盘所必需的持久性功能,因此以较小的容量部署。非易失性存储器(NVM)是一种新兴的存储类技术,可谓两全其美。它具有比DRAM更好的扩展性和成本指标,因此可以提供大容量的存储容量,并且像硬盘一样具有非易失性(持久性)。同时,它的数据检索时间比硬盘要少得多,并且像DRAM一样是字节寻址的。在本文中,我们探讨了将NVM用作DBMS的主要存储的含义。换句话说,我们研究了利用NVM功能必须在传统关系型DBMS上进行必要的修改。作为案例研究,我们修改了PostgreSQL的存储引擎(SE),从而可以有效地使用NVM硬件。我们详细介绍了必要的变更和此类修改带来的挑战,并使用一个综合的仿真平台对其进行了评估。结果表明,与磁盘和NVM存储相比,我们修改后的SE最多将查询执行时间减少了40%和14.4%,平均分别减少了20.5%和4.5%。

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