Learning SQL Server Development on Linux

1h 55mBeginner2018-04-25

Authors

Joey D'Antoni

Consultant and Thought Leader

Course details

The release of Microsoft SQL Server 2017 introduces a wide range of new features for developers—including the ability to leverage the power of the SQL Server engine on Linux operating systems. In this course, get up to speed with all of the exciting new features available in this platform, and learn about SQL Server on Linux. Instructor Joey D'Antoni also covers adaptive query processing, discussing batch mode adaptive joins, interleaved execution, and automatic tuning. He wraps up the course with a discussion of SQL Operations Studio, an open-source tool that you can use to manage SQL Server and Azure SQL Database from any platform.

Learning objectives
Querying with SQL Graph
String functions in SQL 2017
Adaptive query processing
Docker containers and SQL
Deploying CLR code with SQL Server on Linux
Working with SQL Operations Studio
Using snippets
Code deployment using GIT

Skills covered

SQL ServerLinuxDatabase AdministrationDatabase ManagementNetwork AdministrationNetwork and System AdministrationOpen SourceMicrosoftDeep Dive (X:Y)

Concepts

0. Introduction

01 - Welcome
02 - Tools and techniques

1. New Features Overview

03 - New features - SQL Server 2017 overview
04 - Introduction to SQL Graph
05 - Querying with SQL Graph
06 - Tuning SQL Graph queries
07 - Temporal data enhancements
08 - String functions in SQL 2017
09 - Bulk insert using Azure Blob Storage

2. Adaptive Query Processing

10 - Introduction to adaptive query processing
11 - Batch mode adaptive joins
12 - Batch mode memory grant feedback
13 - Interleaved execution
14 - Parameter sniffing overview
15 - Automatic tuning

3. SQL Server on Linux

16 - Introduction to SQL Server on Linux
17 - Getting started with Docker containers and SQL
18 - SQL Server on Linux development
19 - Deploying CLR code with SQL Server on Linux
20 - Command-line tools on Linux
21 - SQL Server Agent on Linux

4. SQL Server Operations Studio

22 - Getting started with SQL Operations Studio
23 - Using snippets
24 - Code deployment using GIT

Conclusion

25 - Next steps