Book Image

SQL Server on Linux

Book Image

SQL Server on Linux

Overview of this book

Microsoft's launch of SQL Server on Linux has made SQL Server a truly versatile platform across different operating systems and data-types, both on-premise and on-cloud. This book is your handy guide to setting up and implementing your SQL Server solution on the open source Linux platform. You will start by understanding how SQL Server can be installed on supported and unsupported Linux distributions. Then you will brush up your SQL Server skills by creating and querying database objects and implementing basic administration tasks to support business continuity, including security and performance optimization. This book will also take you beyond the basics and highlight some advanced topics such as in-memory OLTP and temporal tables. By the end of this book, you will be able to recognize and utilize the full potential of setting up an efficient SQL Server database solution in your Linux environment.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

What is a heap


Imagine a library where every book is just placed in any available space. To find a particular book, you need to scan through all the bookshelves. From the database perspective, there is a structure with the same properties called a heap. A heap is the simplest table structure available in SQL Server.

A heap is a table without a clustered index. The data rows are not stored in any specific order, and there is no specific order to quickly find a particular data page. Data rows are added to the first available location within the table's pages that have sufficient space. If no space is available, additional pages are added to the table and the rows placed in those pages.

Consider using a heap for tables that:

  • Contain volatile data where rows are added, deleted, and updated frequently: The overhead of index maintenance can be costlier than the benefits
  • Contain small amounts of data: Using a table scan to find data can be quicker than maintaining and using an index
  • Contain data that...