Physical design refinement

Author:

Bruno Nicolas1,Chaudhuri Surajit1

Affiliation:

1. Microsoft Research, Redmond, WA

Abstract

Physical database design tools rely on a DBA-provided workload to pick an “optimal” set of indexes and materialized views. Such tools allow either creating a new such configuration or adding new structures to existing ones. However, these tools do not provide adequate support for the incremental and flexible refinement of existing physical structures. Although such refinements are often very valuable for DBAs, a completely manual approach to refinement can lead to infeasible solutions (e.g., excessive use of space). In this article, we focus on the important problem of physical design refinement and propose a transformational architecture that is based upon two novel primitive operations, called merging and reduction . These operators help refine a configuration, treating indexes and materialized views in a unified way, as well as succinctly explain the refinement process to DBAs.

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems

Reference27 articles.

1. Database tuning advisor for microsoft SQL server 2005

2. Automatic physical design tuning

3. Brassard G. and Bratley P. 1996. Fundamental of Algorithmics. Prentice Hall Englewood Cliffs NJ. Brassard G. and Bratley P. 1996. Fundamental of Algorithmics. Prentice Hall Englewood Cliffs NJ.

4. Automatic physical database tuning

Cited by 14 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. Pando: Enhanced Data Skipping with Logical Data Partitioning;Proceedings of the VLDB Endowment;2023-05

2. Budget-aware Index Tuning with Reinforcement Learning;Proceedings of the 2022 International Conference on Management of Data;2022-06-10

3. DISTILL;Proceedings of the VLDB Endowment;2022-06

4. Replicated layout for in-memory database systems;Proceedings of the VLDB Endowment;2021-12

5. Streaming statistical models via Merge & Reduce;International Journal of Data Science and Analytics;2020-06-12

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