Removing Double-Logging with Passive Data Persistence in LSM-tree based Relational Databases

Authors: 

Kecheng Huang, Shandong University, The Chinese University of Hong Kong; Zhaoyan Shen and Zhiping Jia, Shandong University; Zili Shao, The Chinese University of Hong Kong; Feng Chen, Louisiana State University

Abstract: 

Storage engine is a crucial component in relational databases (RDBs). With the emergence of Internet services and applications, a recent technical trend is to deploy a Log-structured Merge Tree (LSM-tree) based storage engine. Although such an approach can achieve high performance and efficient storage space usage, it also brings a critical double-logging problem——In LSM-tree based RDBs, both the upper RDB layer and the lower storage engine layer implement redundant logging facilities, which perform synchronous and costly I/Os for data persistence. Unfortunately, such “double protection” does not provide extra benefits but only incurs heavy and unnecessary performance overhead.

In this paper, we propose a novel solution, called Passive Data Persistence Scheme (PASV), to address the double-logging problem in LSM-tree based RDBs. By completely removing Write-ahead Log (WAL) in the storage engine layer, we develop a set of mechanisms, including a passive memory buffer flushing policy, an epoch-based data persistence scheme, and an optimized partial data recovery process, to achieve reliable and low-cost data persistence during normal runs and also fast and efficient recovery upon system failures. We implement a fully functional, open-sourced prototype of PASV based on Facebook’s MyRocks. Evaluation results show that our solution can effectively improve system performance by increasing throughput by up to 49.9% and reducing latency by up to 89.3%, and it also saves disk I/Os by up to 42.9% and reduces recovery time by up to 4.8%.

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BibTeX
@inproceedings {277848,
title = {Removing {Double-Logging} with Passive Data Persistence in {LSM-tree} based Relational Databases},
booktitle = {20th USENIX Conference on File and Storage Technologies (FAST 22)},
year = {2022},
isbn = {978-1-939133-26-7},
address = {Santa Clara, CA},
pages = {101--116},
url = {https://www.usenix.org/conference/fast22/presentation/huang},
publisher = {USENIX Association},
month = feb,
}

Presentation Video