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

Introduction

This chapter discusses SSIS customization - the built-in capability of the SSIS platform that allows you to extend the natively provided programmatic elements. In addition to the system-provided tasks and components, including the script task and the script component, the SSIS programming model allows you to implement your own programmatic logic by designing your own control flow tasks (custom tasks) or your own data flow components (custom components).

Typically, a custom task would be needed when none of the system-provided tasks facilitate the specific operation that you need to implement in your SSIS solution; for instance, the built-in File Transfer Protocol (FTP) task does not support Secure FTP, so if you need to access remote file locations using the Secure File Transfer Protocol (SSH FTP), you need to design a custom task.

The most frequent uses of the custom...