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Category: Source Control

Feature Branching for Database Projects

Olivier Van Steenlandt describes one branching strategy and applies it to database development:

Depending on how you have defined your branching strategy, you will start development differently. Below I’m defining a few different branching strategies:

1. No branching

2. Branching/environment

3. Branching/feature

4. …

In the past, I have used all of the above. I need to tell you that the Branching/feature strategy allows me to be the most flexible for database development. Why? Let’s dive into this method for now:

Read on to learn more.

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Database Projects and Version Control

Olivier van Steenlandt helps you get database code into source control:

In this blog post, we will focus on how to get started with Database Projects and how to get this into Source Control (Azure Repos). So together we will create our first Database Project, import our database into the project and push it to the Azure Repository.

Before we can start, we need to make sure that we have the required tools installed, in this blog post I will focus on Visual Studio. In order to create your first Database Project, you need to ensure that the SQL Server Data Tools extension for Visual Studio is installed.

This one I intended to post earlier in the week but it got away from me for a little bit. Do check it out.

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Adding an Existing Data Factory to GitHub

Andy Leonard has a three-parter for us. Part 1 shows you how to create a GitHub account and repo:

The unabridged topic of source control with github is beyond the scope of this post. There are a number of ways to accomplish the tasks described in this post and series. I welcome your suggestions in the comments.

This post is written to help Azure Data Factory developers get started using github.

Part 2 connects a Data Factory to the repository:

For the purposes of this demo, accept the defaults for “Publish branch” and “Root folder.” Check the “Import existing resources to repository” checkbox under the “Import existing resource” property, select the main branch in the “Import resource into this branch” property, and then click the “Apply” button:

Part 3 handles changes:

Applying what we’ve configured and learned thus far, let’s put this to work in a code-management workflow.

When it’s time to make a change, first create a new branch. I can hear some of you thinking, “Why, Andy? Why create a new branch?” That’s an excellent question. I am so glad you asked! Think of the new branch as a temporary copy of the current state of my Azure Data Factory. 

This series works from the assumption that you don’t have any real experience with Git (or GitHub) for source control, and maybe not much source control experience at all.

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Updates to AzureDevOps-AzureSQLDatabase Repo

Kevin Chant updates a repo:

In this post I want to cover some significant updates to an Azure SQL Database repository that I have been doing for one of the public GitHub repositories that I share.

Due to the fact that I have updated the AzureDevOps-AzureSQLDatabase repository. Which contains an example of a SQL Server database project that you can use to perform CI/CD on an Azure SQL Database using Azure DevOps.

It does this by using the popular state-based migration method of creating a dacpac file based on the contents of a database project. From there, the dacpac file can be used to update one or more databases.

Click through for those updates.

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Choosing Azure DevOps or GitHub Actions

Sarah Dutkiewicz compares and contrasts:

Every time I do an Azure DevOps talk, I get someone asking me about migrating from GitHub to Azure DevOps. Every time, I have to ask “Why do you want to migrate from GitHub to Azure DevOps?” Why would you choose between Azure DevOps and GitHub? Or better yet – do you have to choose between them? Let’s look at how they compare and the tooling available.

This is a really tough question and Sarah helps explain why.

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Sources of Data Structure Truth

Deb Melkin performs database epistomology:

The “source of truth” is my newly made up phrase for whatever you are using to say this is my database schema and initial data needed to start up the application. This can be your script directory; this can be a dacpac or bacpac; this can be your data model; this can be a combination of these things. My go-to “source of truth” right now is my source control repository. I’ve got both the schema and the default data needed in the same location. In the past, I would have probably included the data model as way to help me make sure whatever database table changes I have in my source control are there, especially for that one database which only had tables and views. (A different rant for a different time.) Whatever you use, it absolutely CANNOT be an actual database. There are two main reasons for this:

Read on for those reasons.

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Database Project Versioning and Identification

Eitan Blumin answers an important question:

“What is SSDT“, you ask? Oh, you didn’t? Well, let me tell you anyway! SSDT is the go-to solution from Microsoft for versioning SQL Server databases and performing state-based deployments (and it’s free!). It has many useful capabilities for developing and publishing changes from your SQL Database project to your SQL Database in production (or wherever).

One of the things that are not so clear about SSDT specifically and database versioning in general, is how should one identify which “version” of your database project was last deployed to your server?

Eitan includes several ways of tracking and controlling database versions.

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Databases, Applications, and Source Control Repos

Eitan Blumin asks and answers a question:

Following the rise in popularity of DevOps for Databases, many interesting questions are being asked on the topic.

One of these questions is: Should your SQL Database project be in the same source control repository and solution as the App code project? Or maybe they should be in the same repository but separate solutions? Or maybe they should be in completely separate repositories?

Pre-registering my answer here: for most organizations, databases should be in a separate repository. The deployment cadence is different, the deployment mechanism is different, and the people working on each likely differ. Read on for Eitan’s thoughts, which get into more of the nuance behind the answer.

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Filling in GitHub Repo Details

Kevin Chant practices GitHub hygeine:

To clarify, GitHub hygiene is a term that I use to describe the practice of keeping GitHub repositories healthy.

Some of you have probably noticed I have been doing this more recently. With this in mind, I thought I would share what I have been doing in this post for a couple of reasons.

First of all, to help raise awareness about some of the best practices I have been doing.

Secondly, because I am interested to get feedback from other members of the Microsoft Data Platform community about this. For example, do you also follow the same practices?

This is a reminder that there’s a lot you can include in a GitHub repo aside from the code itself.

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“Unsafe Repository” When using Git

Niels Berglund sees something odd:

Every 6 – 9 months (or so), I clean up my development PC just to keep it “lean and mean”. I do it by formatting the hard-drive partition the OS (in this case, Windows) is on, followed by a new install. Recently I had a four-day weekend here in SA. Four glorious days off, a perfect time to “nuke” my PC and re-install!

Off I go, everything goes to plan (Chocolatey is my friend), and after a while, I am done (or as done as one can be). At this stage, I needed to do my weekly roundup blog post for the week gone by, and as I had done some changes to the GitHub repo from my MacBook Pro, I wanted to do a git pull in the repo directory for my blog. Part of the story is that on my dev PC, I have all my repos on a separate partition from the system partition, so the non-system partition was un-affected by the reformat (or so I thought). Imagine my surprise when doing the git pull I got:

Click through to see the error and root cause.

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