NOC-NOC: Towards Performance-optimal Distributed Transactions

Author:

Liu Si1ORCID,Multazzu Luca1ORCID,Wei Hengfeng2ORCID,Basin David A.1ORCID

Affiliation:

1. ETH Zurich, Zurich, Switzerland

2. Nanjing University, Nanjing, China

Abstract

Substantial research efforts have been devoted to studying the performance optimality problem for distributed database transactions. However, they focus just on optimizing transactional reads, and thus overlook crucial factors, such as the efficiency of writes, which also impact the overall system performance. Motivated by a recent study on Twitter's workloads showing the prominence of write-heavy workloads in practice, we make a substantial step towards performance-optimal distributed transactions by also aiming to optimize writes, a fundamentally new dimension to this problem. We propose a new design objective and establish impossibility results with respect to the achievable isolation levels. Guided by these results, we present two new transaction algorithms with different isolation guarantees that fulfill this design objective. Our evaluation demonstrates that these algorithms outperform the state of the art.

Publisher

Association for Computing Machinery (ACM)

Reference54 articles.

1. Causal memory: definitions, implementation, and programming

2. Deepthi Devaki Akkoorath, Alejandro Z. Tomsic, Manuel Bravo, Zhongmiao Li, Tyler Crain, Annette Bieniusa, Nuno M. Preguicc a, and Marc Shapiro. 2016. Cure: Strong Semantics Meets High Availability and Low Latency. In ICDCS 2016. IEEE Computer Society, 405--414.

3. Karolos Antoniadis, Diego Didona, Rachid Guerraoui, and Willy Zwaenepoel. 2020. The Impossibility of Fast Transactions. In IPDPS'20. IEEE, 1143--1154.

4. Masoud Saeida Ardekani Pierre Sutra Nuno Preguiça and Marc Shapiro. 2013. Non-Monotonic Snapshot Isolation. arxiv: 1306.3906 [cs.DC]

5. Scalable Atomic Visibility with RAMP Transactions

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. NOC-NOC: Towards Performance-optimal Distributed Transactions;Proceedings of the ACM on Management of Data;2024-03-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3