From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees
Databases
2020-11-03 v2 Machine Learning
Abstract
We introduce BOURBON, a log-structured merge (LSM) tree that utilizes machine learning to provide fast lookups. We base the design and implementation of BOURBON on empirically-grounded principles that we derive through careful analysis of LSM design. BOURBON employs greedy piecewise linear regression to learn key distributions, enabling fast lookup with minimal computation, and applies a cost-benefit strategy to decide when learning will be worthwhile. Through a series of experiments on both synthetic and real-world datasets, we show that BOURBON improves lookup performance by 1.23x-1.78x as compared to state-of-the-art production LSMs.
Keywords
Cite
@article{arxiv.2005.14213,
title = {From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees},
author = {Yifan Dai and Yien Xu and Aishwarya Ganesan and Ramnatthan Alagappan and Brian Kroth and Andrea C. Arpaci-Dusseau and Remzi H. Arpaci-Dusseau},
journal= {arXiv preprint arXiv:2005.14213},
year = {2020}
}