Book Image

SQL Server 2017 Developer???s Guide

Book Image

SQL Server 2017 Developer???s Guide

Overview of this book

Microsoft SQL Server 2017 is a milestone in Microsoft's data platform timeline, as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. This book prepares you for advanced topics by starting with a quick introduction to SQL Server 2017's new features. Then, it introduces you to enhancements in the Transact-SQL language and new database engine capabilities before switching to a different technology: JSON support. You will take a look at the security enhancements and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Toward the end of the book, you'll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You'll also learn to integrate Python code into SQL Server and graph database implementations as well as the deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will be armed to design efficient, high-performance database applications without any hassle.
Table of Contents (25 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
1
Introduction to SQL Server 2017
Index

Improvements in the In-Memory OLTP engine


Further to the previously mentioned size limitation removal, there have been a number of improvements of the In-Memory OLTP engine that may not be immediately apparent, but can still drastically improve performance and scalability.

First up is a range of improvements to the storage subsystem; not only was the checkpoint file pair limit removed, but there was also the introduction of multi-threaded checkpointing. In SQL Server 2014, the offline checkpoint process was a single-threaded system. This thread would scan the transaction log for changes to memory-optimized tables and write those changes to the checkpoint file pairs. This meant that a potentially multi-core system would have a busy core for the checkpointing process. With SQL Server 2016, this checkpointing system was redesigned to run on multiple threads, therefore increasing throughput to the checkpoint file pairs and thus increasing overall performance and the scalability of the In-Memory...