NVDIMM-N Persistent Memory and its Impact on Two Relational Databases

Netanel Katzburg, Amit Golander, S. Weiss
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引用次数: 4

Abstract

The architecture of Database Management Systems (DBMS) is closely related to the characteristics of the storage hierarchy, because durability and response time are highly dependent on the physical properties of the target storage. Main memory volatility requires a DBMS to provide durability by software means as data continuously moves between volatile memory buffers and input/output persistent media. In traditional storage systems applications use complex concurrency control schemes to reduce latency and increase throughput and in order to utilize multicore hardware and shared system resources. New persistent memory (PM) devices emerging in the last decade, such as PCM, RRAM and MRAM, exhibit near-DRAM speed and characteristics, provide data persistence, and could be game changing for storage bound applications. In this paper we focus on benefits of persistent memory and their impact on database management systems. We consider methods for application speedup that are applicable to DBMSs that use PM. These optimization methods depend on the characteristics of PM storage. We consider concurrency and mutual resource contention, explore and rethink major application components, and finally combine static code optimization. Running the on-line transaction processing (OLTP) workload, the DBMSs explored here show performance gains relative to traditional storage systems by a factor of 3.17 and 1.79 for PostgreSQL and SQLite respectively.
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NVDIMM-N Persistent Memory及其对两个关系数据库的影响
数据库管理系统(DBMS)的体系结构与存储层次结构的特征密切相关,因为持久性和响应时间高度依赖于目标存储的物理属性。当数据在易失性存储器缓冲区和输入/输出持久介质之间连续移动时,主存易失性要求DBMS通过软件手段提供持久性。在传统的存储系统中,应用程序使用复杂的并发控制方案来减少延迟和提高吞吐量,并利用多核硬件和共享系统资源。在过去十年中出现的新的持久性存储器(PM)设备,如PCM、RRAM和MRAM,表现出接近dram的速度和特性,提供数据持久性,并可能改变存储绑定应用程序的游戏规则。在本文中,我们关注持久内存的好处及其对数据库管理系统的影响。我们考虑了适用于使用PM的dbms的应用程序加速方法。这些优化方法取决于PM存储的特性。我们考虑并发性和相互资源争用,探索和重新思考主要应用组件,最后结合静态代码优化。在运行联机事务处理(OLTP)工作负载时,本文所研究的dbms相对于传统存储系统的性能分别提高了3.17倍和1.79倍(PostgreSQL和SQLite)。
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