利用内置透明压缩的存储硬件改进关系数据库

Yifan Qiao, Xubin Chen, Jingpeng Hao, Jiangpeng Li, Qi Wu, Jingqiang Wang, Yang Liu, Tong Zhang
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引用次数: 2

摘要

本文提出了一种通过内置透明压缩使关系数据库充分利用现代存储硬件的方法。先进的存储设备(例如,全闪存阵列)和一些最新的ssd(固态硬盘)可以执行基于硬件的数据压缩,透明地从操作系统和应用程序。此外,云存储基础设施中基于硬件的压缩能力的部署不断增长,导致内置透明压缩的基于云存储硬件即将到来。为了使关系数据库更好地利用现代存储硬件,我们建议部署内存内与存储上的双重页面格式:数据库缓存中的页面保留传统的基于行的格式,而存储设备上的每个页面都具有基于列的格式,以便存储硬件可以更好地压缩它。我们提出的设计技术可以通过额外的轻量级列数据转换进一步提高存储页面数据的可压缩性。我们讨论了压缩算法对列数据转换技术选择的影响。我们将设计技术集成到MySQL/InnoDB中,只增加了大约600行代码,并在内置透明压缩的商用SSD上运行Sysbench OLTP工作负载。结果表明,所提出的解决方案可以在只有几个百分比的性能下降的情况下,将存储成本额外降低45%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Relational Database Upon the Arrival of Storage Hardware with Built-in Transparent Compression
This paper presents an approach to enable relational database take full advantage of modern storage hardware with built-in transparent compression. Advanced storage appliances (e.g., all-flash array) and some latest SSDs (solid-state drives) can perform hardware-based data compression, transparently from OS and applications. Moreover, the growing deployment of hardware-based compression capability in Cloud storage infrastructure leads to the imminent arrival of cloud-based storage hardware with built-in transparent compression. To make relational database better leverage modern storage hardware, we propose to deploy a dual in-memory vs. on-storage page format: While pages in database cache memory retain the conventional row-based format, each page on storage devices has a column-based format so that it can be better compressed by storage hardware. We present design techniques that can further improve the on-storage page data compressibility through additional light-weight column data transformation. We the impact of compression algorithms on the selection of column data transformation techniques. We integrated the design techniques into MySQL/InnoDB by adding only about 600 lines of code, and ran Sysbench OLTP workloads on a commercial SSD with built-in transparent compression. The results show that the proposed solution can bring up to 45% additional reduction on the storage cost at only a few percentage of performance degradation.
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