FAST '22 - Closing the B+-tree vs. LSM-tree Write Amplification Gap on Modern Storage Hardware with Built-in Transparent Compression
Yifan Qiao, Rensselaer Polytechnic Institute; Xubin Chen, Google Inc.; Ning Zheng, Jiangpeng Li, and Yang Liu, ScaleFlux Inc.; Tong Zhang, Rensselaer Polytechnic Institute and ScaleFlux Inc.
This paper studies how B+-tree could take full advantage of modern storage hardware with built-in transparent compression. Recent years witnessed significant interest in applying log-structured merge tree (LSM-tree) as an alternative to B+-tree, driven by the widely accepted belief that LSM-tree has distinct advantages in terms of storage cost and write amplification. This paper aims to revisit this belief upon the arrival of storage hardware with built-in transparent compression. Advanced storage appliances and emerging computational storage drives perform hardware-based lossless data compression, transparent to OS and user applications. Beyond straightforwardly reducing the storage cost gap between B+-tree and LSM-tree, such storage hardware creates new opportunities to re-think the implementation of B+-tree. This paper presents three simple design techniques that can leverage such modern storage hardware to significantly reduce the B+-tree write amplification. Experiments on a commercial storage drive with built-in transparent compression show that the proposed design techniques can reduce the B+-tree write amplification by over 10× . Compared with RocksDB (a key-value store built upon LSM-tree), the enhanced B+-tree implementation can achieve similar or even smaller write amplification.
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