Book Image

Mastering SQL Server 2017

By : Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah
Book Image

Mastering SQL Server 2017

By: Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah

Overview of this book

Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You’ll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you’ll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Miloš Radivojevi?, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al
Table of Contents (20 chapters)
Title Page
Free Chapter
1
Introduction to SQL Server 2017

Incremental package deployment

Prior to SSIS 2012, packages needed to be deployed one by one. We were usually downloading all packages from the source control software, such as Team Foundation Server (TFS), Visual Source Safe, SVN, and so on. Once downloaded, packages were moved to their destination. At that time, the person who deployed the packages had the choice to overwrite or skip existing packages. Usually, they overwrote all the packages since they were using the source control.

For those who didn't use the source control, they had all the necessary flexibility to deploy what needed to be deployed. Usually, they were keeping a backup somewhere on a file share of all packages. The reason why they chose what to deploy was mainly because they had doubts about the consistency of the packages in the file share. They were simply not sure of the state of the packages because...