Название: Analytics Optimization with Columnstore Indexes in Microsoft SQL Server: Optimizing OLAP Workloads
Автор: Edward Pollack
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 285
Размер: 18 Mb
Язык: English

Meet the challenge of storing and accessing analytic data in SQL Server in a fast and performant manner. This book illustrates how columnstore indexes can provide an ideal solution for storing analytic data that leads to faster performing analytic queries and the ability to ask and answer business intelligence questions with alacrity. The book provides a complete walk through of columnstore indexing that encompasses an introduction, best practices, hands-on demonstrations, explanations of common mistakes, and presents a detailed architecture that is suitable for professionals of all skill levels.
With little or no knowledge of columnstore indexing you can become proficient with columnstore indexes as used in SQL Server, and apply that knowledge in development, test, and production environments. This book serves as a comprehensive guide to the use of columnstore indexes and provides definitive guidelines. You will learn when columnstore indexes should be used, and the performance gains that you can expect. You will also become familiar with best practices around architecture, implementation, and maintenance. Finally, you will know the limitations and common pitfalls to be aware of and avoid.
As analytic data can become quite large, the expense to manage it or migrate it can be high. This book shows that columnstore indexing represents an effective storage solution that saves time, money, and improves performance for any applications that use it. You will see that columnstore indexes are an effective performance solution that is included in all versions of SQL Server, with no additional costs or licensing required.

What You Will Learn
Implement columnstore indexes in SQL Server
Know best practices for the use and maintenance of analytic data in SQL Server
Use metadata to fully understand the size and shape of data stored in columnstore indexes
Employ optimal ways to load, maintain, and delete data from large analytic tables
Know how columnstore compression saves storage, memory, and time
Understand when a columnstore index should be used instead of a rowstore index
Be familiar with advanced features and analytics