Automated Physical Database Design and Tuning: 1st Edition (Paperback) book cover

Automated Physical Database Design and Tuning

1st Edition

By Nicolas Bruno

CRC Press

253 pages | 74 B/W Illus.

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Description

Due to the increasing complexity in application workloads and query engines, database administrators are turning to automated tuning tools that systematically explore the space of physical design alternatives. A critical element of such tuning is physical database design since the choice of physical structures has a significant impact on the performance of the database system. Automated Physical Database Design and Tuning presents a detailed overview of the fundamental ideas and algorithms for automatically recommending changes to the physical design of a database system.

The first part of the book introduces the necessary technical background. The author explains SQL, the space of execution plans for answering SQL queries, query optimization, how the choice of access paths (e.g., indexes) is crucial to performance, and the complexity of the physical design problem.

The second part extensively discusses automated physical design techniques, covering fundamental research ideas in the last 15 years that have resulted in a new generation of tuning tools. The text focuses on the search space of alternatives, the necessity of a cost model to compare such alternatives, different mechanisms to traverse and enumerate the search space, and practical aspects in real-world tuning tools.

In the third part, the author explores new advances in automated physical design. He applies previous approaches to other physical structures, such as materialized views, partitioning, and multidimensional clustering. He also analyzes workload models for new types of applications, generalizes the optimizing function of current physical design tools to cope with other application scenarios, and examines open-ended challenges in physical database design.

This book offers valuable insights on well-established principles and cutting-edge research results in automated physical design. It helps readers gain a deeper understanding of how automated tuning tools work in database installations as well as the challenges and opportunities involved in designing next-generation tuning tools.

Table of Contents

BACKGROUND

Declarative Query Processing in Relational Database Systems

An Exercise in Imperative Programming

SQL: Declarative Query Processing

Processing SQL Queries

Query Optimization in Relational Database Systems

Search Space

Cost Model

Enumeration Strategy

Physical Database Design

The Complexity of the Physical Design Problem

Toward Automated Physical Design

AUTOMATED PHYSICAL DATABASE DESIGN

Characterizing the Search Space

Candidate Indexes for a Single SELECT Query

Candidate Set for a Workload

Defining the Search Space Using Closures

Designing a Cost Model

What-If Optimization

Reducing the Overhead of What-If Optimization Calls

Index Usage Model (INUM)

Configuration-Parametric Query Optimization (CPQO)

Enumerating the Search Space

Bottom-Up Enumeration

Top-Down Enumeration

Practical Aspects in Physical Database Design

Workload Gathering

Workload Compression

Tuning Modes

Time-Bound Tuning

Production/Test Tuning

Reports

Deployment Scripts

A Case Study: Database Engine Tuning Advisor

ADVANCED TOPICS

Handling Materialized Views

Materialized View Definition Language

Search Space

Cost Model

Enumeration Strategies

Incorporating Other Physical Structures

Data Partitioning

Data Cube Selection

Multidimensional Clustering

Extensible Physical Design

Continuous Physical Database Design

An Alerting Mechanism

Continuous Physical Design Tuning

Constrained Physical Database Design

Constraint Language

Search Framework

Examples of Tuning Sessions with Constraints

New Challenges in Physical Database Design

Leveraging Richer Workloads

Other Aspects of Physical Database Design

Interactive Physical Design Tuning

Physical Database Design Benchmarks

Index

A Summary, Additional Reading, and References appear at the end of each chapter.

About the Author

Nicolas Bruno is a researcher in the Data Management, Exploration and Mining group at Microsoft Research. He earned his Ph.D. in computer science from Columbia University. Dr. Bruno’s research interests include physical database design, query processing and optimization, and database testing.

About the Series

Emerging Directions in Database Systems and Applications

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
COM021000
COMPUTERS / Database Management / General
COM021030
COMPUTERS / Database Management / Data Mining