论文标题
评估持续记忆范围索引：第二部分[扩展版本]
Evaluating Persistent Memory Range Indexes: Part Two [Extended Version]
论文作者
论文摘要
可扩展的持续内存（PM）为构建直接在内存总线上操作和持久数据的索引开辟了新的机会，有可能即时恢复，低潜伏期和高吞吐量。当真正的PM硬件（Intel Optane DCPMM）首先可用时，先前的工作评估了PES前时代提出的PM索引。从那时起，基于真实PM的较新索引就出现了，但目前尚不清楚它们如何相互比较以及以前的建议，以及还有什么进一步的挑战。本文通过分析和实验评估为真实PM构建的最新PM系列索引来解决这些问题。我们发现较新的设计继承了过去的新技术，但它们并不一定要超过前最佳时代的建议。此外，PM索引通常也非常有竞争力，甚至均匀的表现索引量身定制为DRAM，这突出了对PM和DRAM都使用统一设计的潜力。从功能上讲，这些索引仍然缺乏对可变长度键和处理NUMA效应的良好支持。根据我们的发现，我们提炼了新的设计原理并突出未来的方向。
Scalable persistent memory (PM) has opened up new opportunities for building indexes that operate and persist data directly on the memory bus, potentially enabling instant recovery, low latency and high throughput. When real PM hardware (Intel Optane DCPMM) first became available, previous work evaluated PM indexes proposed in the pre-Optane era. Since then, newer indexes based on real PM have appeared, but it is unclear how they compare to each other and to previous proposals, and what further challenges remain. This paper addresses these issues by analyzing and experimentally evaluating state-of-the-art PM range indexes built for real PM. We find newer designs inherited past techniques with new improvements, but they do not necessarily outperform pre-Optane era proposals. Moreover, PM indexes are often also very competitive or even outperform indexes tailored for DRAM, highlighting the potential of using a unified design for both PM and DRAM. Functionalitywise, these indexes still lack good support for variable-length keys and handling NUMA effect. Based on our findings, we distill new design principles and highlight future directions.
