{"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.
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.