Improving database performance by leveraging network-assisted logging

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-03-17 DOI:10.1016/j.future.2025.107785
Hwajung Kim
{"title":"Improving database performance by leveraging network-assisted logging","authors":"Hwajung Kim","doi":"10.1016/j.future.2025.107785","DOIUrl":null,"url":null,"abstract":"<div><div>In mission-critical systems like databases and transaction processing systems, write-ahead logging (WAL) is commonly used to ensure fault tolerance against power failures and system malfunctions. However, WAL requires data to be logged before it is permanently stored in persistent storage, causing delays that can slow down the system, even when using advanced technologies like Optane persistent memory. Although seemingly small, such delays can accumulate and affect overall transaction performance. In this paper, we propose an in-transit logging (<em>ITLogging</em>) scheme that performs logging at the network layer by capturing important data upon its arrival at the destination system. Our scheme filters incoming packets and logs the necessary data from the payload before any processing occurs. In case of data loss, our scheme replays packet deliveries to the target system by mimicking the original client actions for recovery. We implement the proposed scheme by allocating a separate core for packet inspection, ensuring that logging operations are handled independently of the application layer’s data processing, thereby avoiding delays in the main processing flow. The experimental results demonstrate that our scheme improves database throughput by 16% for TPC-C and 15% for LinkBench on MySQL, compared with vanilla MySQL.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"169 ","pages":"Article 107785"},"PeriodicalIF":6.2000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X25000809","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

In mission-critical systems like databases and transaction processing systems, write-ahead logging (WAL) is commonly used to ensure fault tolerance against power failures and system malfunctions. However, WAL requires data to be logged before it is permanently stored in persistent storage, causing delays that can slow down the system, even when using advanced technologies like Optane persistent memory. Although seemingly small, such delays can accumulate and affect overall transaction performance. In this paper, we propose an in-transit logging (ITLogging) scheme that performs logging at the network layer by capturing important data upon its arrival at the destination system. Our scheme filters incoming packets and logs the necessary data from the payload before any processing occurs. In case of data loss, our scheme replays packet deliveries to the target system by mimicking the original client actions for recovery. We implement the proposed scheme by allocating a separate core for packet inspection, ensuring that logging operations are handled independently of the application layer’s data processing, thereby avoiding delays in the main processing flow. The experimental results demonstrate that our scheme improves database throughput by 16% for TPC-C and 15% for LinkBench on MySQL, compared with vanilla MySQL.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
期刊最新文献
A distributed identity management and cross-domain authentication scheme for the Internet of Things Causal invariant geographic network representations with feature and structural distribution shifts HS-GIoV: High-speed green internet of vehicles (IoV) edge-assisted model for low-latency inference in autonomous driving Prediction model of performance–energy trade-off for CFD codes on AMD-based cluster RAANMF: An adaptive sequence feature representation method for predictions of protein thermostability, PPI, and drug–target interaction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1