Join processing for flash SSDs: remembering past lessons

Jaeyoung Do, J. Patel
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引用次数: 38

Abstract

Flash solid state drives (SSDs) provide an attractive alternative to traditional magnetic hard disk drives (HDDs) for DBMS applications. Naturally there is substantial interest in redesigning critical database internals, such as join algorithms, for flash SSDs. However, we must carefully consider the lessons that we have learnt from over three decades of designing and tuning algorithms for magnetic HDD-based systems, so that we continue to reuse techniques that worked for magnetic HDDs and also work with flash SSDs. The focus of this paper is on recalling some of these lessons in the context of ad hoc join algorithms. Based on an actual implementation of four common ad hoc join algorithms on both a magnetic HDD and a flash SSD, we show that many of the "surprising" results from magnetic HDD-based join methods also hold for flash SSDs. These results include the superiority of block nested loops join over sort-merge join and Grace hash join in many cases, and the benefits of blocked I/Os. In addition, we find that simply looking at the I/O costs when designing new flash SSD join algorithms can be problematic, as the CPU cost is often a bigger component of the total join cost with SSDs. We hope that these results provide insights and better starting points for researchers designing new join algorithms for flash SSDs.
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加入闪存ssd的处理:记住过去的教训
闪存固态驱动器(ssd)为DBMS应用程序提供了传统磁性硬盘驱动器(hdd)的有吸引力的替代方案。当然,对于为闪存ssd重新设计关键的数据库内部,例如连接算法,有很大的兴趣。然而,我们必须仔细考虑我们从30多年来为基于磁性hdd的系统设计和调整算法中学到的经验教训,以便我们继续重用适用于磁性hdd和闪存ssd的技术。本文的重点是回顾在特设连接算法上下文中的一些经验教训。通过在磁性HDD和闪存SSD上实际实现四种常见的临时连接算法,我们发现,基于磁性HDD的连接方法的许多“令人惊讶”的结果也适用于闪存SSD。这些结果包括在许多情况下块嵌套循环连接优于排序合并连接和Grace散列连接,以及阻塞I/ o的好处。此外,我们发现,在设计新的闪存SSD连接算法时,仅仅考虑I/O成本可能会有问题,因为CPU成本通常是SSD总连接成本中较大的组成部分。我们希望这些结果为研究人员设计闪存固态硬盘的新连接算法提供见解和更好的起点。
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