Resumable online index rebuild in SQL server

Author:

Antonopoulos Panagiotis1,Kodavalla Hanuma1,Tran Alex1,Upreti Nitish1,Shah Chaitali1,Sztajno Mirek1

Affiliation:

1. Microsoft

Abstract

Azure SQL Database and the upcoming release of SQL Server enhance Online Index Rebuild to provide fault-tolerance and allow index rebuild operations to resume after a system failure or a user-initiated pause. SQL Server is the first commercial DBMS to support pause and resume functionality for index rebuilds. This is achieved by splitting the operation into incremental units of work and persisting the required state so that it can be resumed later with minimal loss of progress. At the same time, the proposed technology minimizes the log space required for the operation to succeed, making it possible to rebuild large indexes using only a small, constant amount of log space. These capabilities are critical to guarantee the reliability of these operations in an environment where a) the database sizes are increasing at a much faster pace compared to the available hardware, b) system failures are frequent in Cloud architectures using commodity hardware, c) software upgrades and other maintenance tasks are automatically handled by the Cloud platforms, introducing further unexpected failures for the users and d) most modern applications need to be available 24/7 and have very tight maintenance windows. This paper describes the design of "Resumable Online Index Rebuild" and discusses how this technology can be extended to cover more schema management operations in the future.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 10 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. Riveter: Adaptive Query Suspension and Resumption Framework for Cloud Native Databases;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. Efficiently Learning Spatial Indices;2023 IEEE 39th International Conference on Data Engineering (ICDE);2023-04

3. Automatic modelling of networked innovation outsourcing-oriented talent competency in the era of artificial intelligence;International Journal of System Assurance Engineering and Management;2022-12-08

4. Automatic Database Index Defragmentation Using Machine Learning;Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications;2022

5. Multimedia Teaching in Teaching of College English Reading;Journal of Testing and Evaluation;2020-12-18

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