Automatically Indexing Millions of Databases in Microsoft Azure SQL Database

被引：50

作者：

Das, Sudipto ^{[1
]}

Grbic, Miroslav ^{[1
]}

Ilic, Igor ^{[1
]}

Jovandic, Isidora ^{[1
]}

Jovanovic, Andrija ^{[1
]}

Narasayya, Vivek R. ^{[1
]}

Radulovic, Miodrag ^{[1
]}

Stikic, Maja ^{[1
]}

Xu, Gaoxiang ^{[1
]}

Chaudhuri, Surajit ^{[1
]}

机构：

[1] Microsoft Corp, Redmond, WA 98052 USA

来源：

SIGMOD '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA | 2019年

关键词：

Automated indexing; autonomous database management; performance tuning; relational database-as-a-service;

D O I：

10.1145/3299869.3314035

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An appropriate set of indexes can result in orders of magnitude better query performance. Index management is a challenging task even for expert human administrators. Fully automating this process is of significant value. We describe the challenges, architecture, design choices, implementation, and learnings from building an industrial-strength auto-indexing service for Microsoft Azure SQL Database, a relational database service. Our service has been generally available for more than two years, generating index recommendations for every database in Azure SQL Database, automatically implementing them for a large fraction, and significantly improving performance of hundreds of thousands of databases. We also share our experience from experimentation at scale with production databases which gives us confidence in our index recommendation quality for complex real applications.

引用

页码：666 / 679

页数：14

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