Search results matching tag 'Continuous Integration'

Continuous deployment of SSDT database projects to Windows Azure using Team Foundation Service

jamiet — Sun, 27 Jan 2013 20:07:00 GMT

Continuous deployment is described by Wikipedia as:

Most CI systems allow the running of scripts after a build finishes. In most situations, it is possible to write a script to deploy the application to a live test server that everyone can look at. A further advance in this way of thinking is Continuous Deployment, which calls for the software to be deployed directly into production
http://en.wikipedia.org/wiki/Continuous_Integration

I think of Continuous Deployment as a natural extension of Continuous Integration where not only do we build the source code, we deploy it as well. As I continue to put together my SSDT Database Projects from the ground-up seminar it occurred to me that demonstrating Continuous Deployment for SSDT database projects would be very useful. It then occurred to me that the recently released Team Foundation Service (TFS) includes a facility to build source code so I wondered, could one perhaps use TFS to build an SSDT database project and deploy it to a Windows Azure SQL Database (aka SQL Azure)? It turns out that the answer is “yes” and this blog provides a step-by-step guide to doing just that.

Its worth noting that Team Foundation Service is free for up to five users. SSDT is also free. Windows Azure SQL Databases, however, are not free so you may have to pay a small amount to get one or alternatively adapt the steps herein to use Team Foundation Server to deploy to an on-premises SQL Server instance. Note that a MSDN subscription does include some small usage of Windows Azure SQL Database and that allowance will be more than enough to go through the steps herein.

We can break our process down into the following high-level steps:

Create a Windows Azure SQL Database
Sign up for Team Foundation Service (TFS)
Create an SSDT database project
Add the SSDT project to TFS Source Control
Setup your Publish Profile file
Create a Build Definition

Let’s dive into all of those steps.

Create a new Windows Azure SQL Database

Visit https://manage.windowsazure.com/ and sign up for a new Windows Azure SQL Database:

Your new database will be viewable in the portal immediately:

Windows Azure SQL Databases are, by default, closed to the outside world so you must edit the list of IP addresses that are allowed to access the server. Setting this up is outside the scope of this blog post however simply go to How to: Configure the Server-Level Firewall Settings (Windows Azure SQL Database) to learn how to do this (its very easy).

Sign up for Team Foundation Service

Visit https://tfs.visualstudio.com/ to sign up to use Team Foundation Service using your Microsoft Account (aka Windows Live ID). Once you have signed-up you will have a dedicated service URL (mine, for example, is https://jamiet.visualstudio.com/). Visit that URL and click “New Team Project”:

Fill in the pertinent details and hit “Create Project”:

Creating the Team Project will take a minute or so but will be ready for you when you need it shortly.

Create an SSDT database project

For this you’re going to need SSDT for Visual Studio 2010 or Visual Studio 2012. They are both free and can be downloaded from here; I am using SSDT for Visual Studio 2012.

You will need to create a new SQL Server Database Project:

Once the project is created it will appear in Solution Explorer and be empty at this point. We are going to be deploying to Windows Azure SQL Database therefore we must tell the project that that will be the case. To do that right-click on the project and select Properties:

In Project Settings select Windows Azure SQL Database as the Target platform:

You’ll need to add a database object to your project otherwise this is all rather pointless. Given that this is simply for demo purposes we shall simply create a table called [Table1].

OK, we now have a Windows Azure SQL Database, a TFS service (is that Team Foundation Service service???) and a SSDT database project with a simple table in it. Let’s now hook them all together.

Add the SSDT project to TFS Source Control

Interaction with TFS from within Visual Studio is done using the Team Explorer pane.

From Team Explorer you will need to connect to your new TFS. Click on the address bar in Team Explorer and point to “Connect to Team Projects…”

Choose your project and click Connect. Your server is simply the name of the server that was setup earlier; remember that mine was jamiet.visualstudio.com (note that it uses an https connection, not http):

You should now be connected to your Team Foundation Service. Add your source code to TFS Source Control from inside Solution Explorer:

And check in your SSDT database project (or “commit” if you prefer that terminology):

You will now be able to browse to your TFS home page (mine is https://jamiet.visualstudio.com), click on your project and browse through your checked in code:

Setup your Publish Profile file

You need to tell SSDT where to deploy the project to, that information is stored in a Publish Profile file. In Solution Explorer right-click and select “Publish…”

Enter the details of the Windows Azure SQL Database that you prepared earlier:

Once the Publish Profile file has been saved it will be saved in your project:

At the time of writing Windows Azure SQL Database only supports SQL authentication so we have to edit the Publish Profile file to include the password for the account that will be used for deployment. Right-click on the Publish Profile file, select “Open with…” and from the resultant dialog select “XML (Text) Editor:

Edit the Connection String to include your password:

NOW you can check in:

Create a Build Definition

A Build Definition defines how and when the source code in the project should get built. Create a new Build Definition by selecting “Builds” in the Team Explorer address bar and choosing New Build Definition:

Follow the steps shown in the screenshots below to setup your Build Definition:

(Credit for informing me about the MSBuild arguments goes entirely to Jakob Ehn and his blog post Deploying SSDT Projects with TFS Build)

And you’re done!

If you have set everything up correctly then any future check in should trigger a build and thus a Publish of the SSDT project to your Windows Azure SQL Database. Here is my first build report:

and back in SSDT I can use SQL Server Object Explorer to browse my newly deployed table:

That’s Continuous Deployment for SSDT projects to Windows Azure SQL Database using Team Foundation Service. Awesome!

@Jamiet

Implementing SQL Server solutions using Visual Studio 2010 Database Projects – a compendium of project experiences

jamiet — Sun, 01 Jan 2012 18:13:00 GMT

Over the past eighteen months I have worked on four separate projects for customers that wanted to make use of Visual Studio 2010 Database projects to manage their database schema.* All the while I have been trying to take lots of notes in order that I can write the blog post that you are reading right now – a compendium of experiences and tips from those eighteen months. I should note that this blog post should not necessarily be taken as a recommendation to actually use database projects in Visual Studio 2010 – it is intended to be useful for those of you that have already made the decision to use them; having said that, I do make recommendations as to actions I think you should take if you have made that decision.

First let’s be clear what we’re talking about here. Visual Studio Database Projects have been known by a few different names down the years, some of which you may be familiar with. If you have ever heard the terms datadude, DBPro, teamdata, TSData or Visual Studio Team System for Database Professionals then just know that all of these terms refer to the same thing, namely the project type highlighted below when starting a new project in Visual Studio:

From here onwards I am going to refer to Visual Studio Database projects and all the features therein simply as datadude because that’s a popular colloquial name (and is also much quicker to type). Know also that at the time of writing the features that I am talking about here are currently undergoing some changes ahead of the next release of SQL Server (i.e. SQL Server 2012) in which these features are mooted to be delivered under a new moniker - SQL Server Developer Tools (SSDT).

OK, with all those preliminaries out of the way let’s dig in.

Continuous Integration

Continuous Integration (CI) is a development practise that has existed for many years but in my experience has not been wholly embraced by the database community. The idea behind CI for databases is that every time a developer checks-in a piece of code be it a stored procedure, a table definition or whatever, the entire database project is built and then deployed to a database instance. Microsoft provide a useful article An Overview of Database Build and Deployment that goes some way to explaining how to setup your CI deployment.

CI is one of the fundamental tenets that underpins a lot of the things I talk about later in this blog post and hence gives rise to my first recommendation when using datadude:

Recommendation #1: Use Source Control and implement a Continuous Integration deployment

In an earlier draft of this blog post I outlined in detail the CI configuration from one of the aforementioned projects. Its not suitable for inclusion at this point in the current draft but I still think there is some useful information to be gleaned so I have included it below in “Appendix – An example CI configuration”.

Composite Projects

Each of the four aforementioned projects were brownfield projects meaning that each already encompassed some established, deployed, databases and they wanted to bring those databases under the control of datadude. Each project had thousands of objects across multiple databases and in this situation it is very likely that some of the stored procedures, views or functions will refer to objects in one of the other databases. The way to resolve those references is to use database references however once you have applied all of your database references it is still very possible that you will run into a situation where code in database A refers to an object in database B while at the same time database B refers to an object in database A. This is depicted in the following figure:

Here we have a view [DB1]..[View2] that selects data from [DB2]..[Table1] and a view [DB2]..[View1] that selects data from [DB1]..[Table1]. Datadude does not allow a database reference from [DB2] to [DB1] if there is already a database reference from [DB2] to [DB1] and hence will return an error akin to:

SQL03006: View: [dbo].[View1] has an unresolved reference to object [DB1].[dbo].[Table1].

We have the proverbial chicken-and-egg problem, [DB1] can’t be created before [DB2] and vice versa. This problem is solved by using Composite Projects (not to be confused with Partial Projects) which allow you to split objects that are intended to be in the same database over multiple datadude projects. I could go over how you set one of these things up but there’s really no need because there is a rather excellent walkthrough on MSDN at Walkthrough: Partition a Database Project by Using Composite Projects; the reason for me mentioning it here is to make you aware that composite projects exist and of the problem that they solve. If you are introducing datadude into a brownfield project then it is highly likely that you are going to require composite projects so learn them and learn them good.

One important last note about composite projects is to answer the question “How does the tool know that the multiple projects refer to the same database?” The answer is given at the walkthrough that I linked to above; namely, it says:

“Do not specify server variables and values or database variables and values when you define references in a composite project. Because no variables are defined, the referenced project is assumed to share the target server and database of the current project.”

So now you know! To put it another way, if you reference one project from another and don’t tell datadude that the two projects refer to different databases then it assumes they refer to the same database.

Code Analysis

Datadude provides the ability to analyse your code projects for code in stored procedures and functions that it considers to be inferior and highlight it – this feature is called Code Analysis. Note that Code Analysis will not highlight code that is syntactically incorrect (datadude does that already, which may well be considered its core feature), it highlights code that is syntactically correct but may be considered defective when executed. Specifically Code Analysis will highlight the following perceived code defects (click through on the links for explanations of why these are considered code defects):

Use of SELECT *
Use of @@IDENTITY rather than SCOPE_IDENTITY()
NCHAR & NVARCHAR fields whose maximum length is 1 or 2
Deprecated join syntax
An output parameter that might not be assigned to
Casts that could result in data loss (in my experience this is the one that shows up most often – particularly in inherited code)
Use of special characters in object names
Use of reserved words
Use of sp_ prefix for stored procedures
Use of unindexed columns in IN predicates
Use of patterns beginning with a wildcard in a LIKE predicate
Code that would not use an existing index that might actually be beneficial
Use of ISNULL() on nullable columns
Deterministic function calls in a WHERE predicate

In my opinion the best aspect of Code Analysis is that it can be run as part of your Continuous Integration deployment meaning that if anyone checks in some deficient code, BOOM, your CI deployment fails and the developer is left red-faced. Nothing else has increased the code quality on my projects quite like running Code Analysis as part of a CI deployment.

Hopefully I have convinced you that turning on Code Analysis is a good idea. If you agree then head to the project properties and check the box labelled Enable Code Analysis on Build. I also recommend checking the Treat warnings as errors boxes otherwise you’ll find that undisciplined developers will simply ignore the warnings.

N.B. Incidentally if you have time I highly recommend that you go and read the blog post I linked to there – Discipline Makes Strong Developers by Jeff Atwood. I’ve read many thousands of blog posts in my time and that is the one that has influenced me more than any other.

Turning on Code Analysis on a greenfield project is a no-brainer. On a brownfield project its not quite so easy – on a recent engagement I moved a single database into datadude and turned on Code Analysis which immediately found over two thousand perceived code defects. I generally abhor the use of that famous maxim if it aint broke, don’t fix it in our industry but on occasions like this you may be well advised to heed that advice and leave well alone for fear of breaking code that does what it is supposed to (no matter how inefficiently it does it). Instead you do have the option to suppress Code Analysis warnings/errors:

I advise using Code Analysis suppression sparingly. Recently I discovered that one of the developers on my team had decided it was OK to simply suppress every error that was thrown by Code Analysis without first investigating the cause. I was not amused!

Recommendation #2: Turn on Code Analysis

Realising the value of idempotency

An operation is considered idempotent if it produces the same result no matter how many times that operation is applied; for example, multiplication by a factor of one is an idempotent operation – no matter how many times you multiple a number by one the result will always be the same.

Idempotency is a vital facet of database deployment using datadude. Datadude tries to ensure that no matter how many times you deploy the same project the state of your database should be the same after each deployment. The implication here is that during a deployment datadude will examine the target database to see what changes (if any) need to be made rather than simply attempting to create lots of objects; if all the objects already exist nothing will be done. In my opinion this is the single biggest benefit of using datadude – you don’t have to determine what needs to be done to change your database schema to the desired state, datadude does it for you.

If I have convinced you about the value of idempotency within datadude then you should also realise that the same rigour should be applied to data as well. Datadude provides Post-Deployment scripts that allow you to deploy data to your schema however there is no inbuilt magic here – datadude will simply go and run those scripts as-is, it will not try and comprehend the contents of those scripts. What this means is that you, the developer, are responsible for making your Post-Deployment scripts idempotent and the easiest way to do that is to employ the T-SQL MERGE statement.

T-SQL’s INSERT is not sufficient as it will work once and thereafter fail as it will be attempting to insert already inserted data; this gives rise to my third recommendation:

Recommendation #3: When running your deployment in a test environment, run it more than once.

No-brainer Recommendations

I consider Code Analysis and Idempotency to be so important that I called them out as dedicated headlines. In this section I’ll outline some additional simple measures that you can undertake and which will, if employed correctly, have a profound effect on the success of your datadude projects.

Putting a build number into the DB

I find it is very useful to maintain a log of deployments that have been made to a database and my chosen method is to use a Post-Deployment script to insert a value into some table. Here’s the definition of the table I use for this:

CREATE TABLE [dbo].[DeployLog] ( [BuildId] NVARCHAR(50) , [DeployDatetime] SMALLDATETIME , CONSTRAINT PK_dboDeployLog PRIMARY KEY ([DeployDatetime]) )

In my Post-Deployment script I will use:

INSERT [dbo].[DeployLog]([BuildId],[DeployDatetime]) VALUES ('$(BuildId)',GETDATE());

to insert a row into that table during every deployment. $(BuildId) is a variable defined in the .sqlcmdvars file of my project:

Here is what we see inside that file:

The $(BuildId) variable has been defined with a default value of UNKNOWN and hence subsequent deployments from Visual Studio will result in the following:

On first glance that might not seem particularly useful however it comes into its own if you are doing CI deployments (see recommendation #1) because each build in a CI environment will result in a new build identifier. The following command-line call to vsdbcmd.exe is how deployments are generally done using datadude, note the presence of the /p:BuildId switch:

..\Tools\VSDBCMD\vsdbcmd.exe /Action:Deploy /ConnectionString:"Data Source=.;Integrated Security=True;Pooling=False" /p:BuildId="some-value" /DeployToDatabase:+ /ManifestFile:.\FinanceDB\sql\release\FinanceDB.deploymanifest

Your CI tool should be able to replace “some-value” with an identifier for the current build (that’s outside the scope of this blog post but any CI tool worth its salt will be able to do this) – when the deployment executes that value will then make its way into your [dbo].[DeployLog] table and you will have a self-maintaining history of all the deployments (datetime & build identifier) that have been made to your database.

Recommendation #4: Maintain an automated history of your deployments

Use Schema View

It is natural to navigate through all of the objects in your database project using Solution Explorer however datadude provides a better mechanism for doing just that – the Schema View window.

Schema View provides a logical view of all the objects defined in your database project regardless of which file they may be defined in. That is very useful for many reasons, not least because it makes it easy to locate whichever object you are after – that’s advantageous if multiple objects are defined in the same file. Moreover if some files have property BuildAction=”Not In Build” (see later) they won’t show up in Schema View (this is a good thing by the way). Schema View is also the place that operations such as refactoring and dependency analysis are launched from.

Some people think that it is important that the name of each file in a datadude project should accurately reflect the object defined within. I disagree; object renames mean that maintaining the filenames becomes laborious and having the Schema View means you never have to use the filenames to navigate your project anyway.

One final reason to use Schema View is the External Elements button:

Toggling this button on means that objects in referenced projects show up in the project that they are referenced from (this is particularly useful if you are using Composite Projects). Note in the following screenshot how the object [dbo].[t1] in project Database2 appears in the [dbo] schema of Database3 – that’s because Database3 has a reference to Database2.

For those reasons my fifth recommendation is:

Recommendation #5: Use Schema View in preference to Solution Explorer

You will still need Solution Explorer to navigate files that do not contain database objects (e.g. Post-Deployment scripts) but ordinarily you should spend most of your time interacting with Schema View.

Make liberal use of PRINT statements in Pre/Post-Deployment Scripts

When you deploy a datadude project datadude will take care of telling you what it is up to. For example, the following screenshot shows the output from deploying the already discussed [dbo].[DeplogLog]:

Of course it only does this for objects that it knows about and that doesn’t include anything in your Pre or Post \deployment scripts so you need to take responsibility for outputting pertinent information from those scripts. Here I have amended the script that inserts into [dbo].[DeployLog]:

SET NOCOUNT ON; INSERT [dbo].[DeployLog]([BuildId],[DeployDatetime]) VALUES ('$(BuildId)',GETDATE()); PRINT CAST(@@ROWCOUNT as NVARCHAR(5)) + N'rows inserted into [dbo].[DeployLog], BuildId=$(BuildId)';

This gives us much more useful output:

Adding PRINT statements to your Pre & Post Deployment scripts is so easy it really is a no-brainer and hence my next recommendation is:

Recommendation #6: Any action in a Pre or Post-Deployment Script should use PRINT to state what has been done

Output variable values in your Pre-Deployment script

This is in the same vein as the previous bullet-point – output as much information as is possible. In this case we’re talking about outputting the values of all variables that are stored in the .sqlcmdvars file; first, a reminder of what’s in that file:

Here is the contents of my amended Pre-Deployment Script:

PRINT 'DefaultDataPath=$(DefaultDataPath)'; PRINT 'DatabaseName=$(DatabaseName)'; PRINT 'DefaultLogPath=$(DefaultLogPath)'; PRINT 'BuildId=$(BuildId)';

And the resultant output:

This is the sort of simple amendment that will pay off in spades later in your project (especially if you are supplying many values from the command-line) and again, its so easy to do it there really is no reason not to. Just remember to update your Pre-Deployment script whenever you add new variables to .sqlcmdvars.

Recommendation #7: Output the value of all variables in your Pre-Deployment script

One Object Per File

Datadude doesn’t restrict what can go in a file, for example the following file, “t.table.sql”, defines three objects; a table, a primary key and a view:

Even though they’re all defined in the same file they show up in Schema View separately (one of the aforementioned benefits of using Schema View):

That said, just because you can doesn’t mean that you should. I prefer to go for one object per file for the simple reason that its easier to track the history of an object via Source Control. Moreover, if an object is no longer required then it is a simple change to just remove the file containing that object from the build (see “Don’t delete anything from your project” later) as opposed to editing a file to remove all traces of an object.

Recommendation #8: Each database object should be defined in a dedicated file

Time your Pre and Post Deployment Scripts

Its always useful to know where time is spent when doing deployments, in my experience the majority of time spent is in the Post-Deployment script (your mileage may vary of course). An easy win is to output the time taken to run your Pre and Post Deployment scripts. Adapt your Pre-Deployment script so that it looks something like this:

DECLARE @vPreDeploymentStartTime DATETIME = GETDATE(); PRINT '****************Begin Pre-Deployment script at ' +CONVERT(VARCHAR(30),GETDATE(),120) + '***********************'; /*Call other scripts from here using SQLCMD's :r syntax Example: :r .\myfile.sql */ PRINT 'Pre-Deployment duration = ' + CONVERT(VARCHAR(5),DATEDIFF(ss,@vPreDeploymentStartTime,GETDATE())) + ' seconds'; PRINT '****************End Pre-Deployment script at ' +CONVERT(VARCHAR(30),GETDATE(),120) + '***********************';

then do similar for your Post-Deployment script. When you deploy your output will include the following:

Note the lines:

    ****************Begin Pre-Deployment script at 2011-12-31 20:00:34***********************
    Pre-Deployment duration = 0 seconds
    ****************End Pre-Deployment script at 2011-12-31 20:00:34***********************


    ****************Begin Post-Deployment script at 2011-12-31 20:00:34***********************
    Post-Deployment duration = 0 seconds
    ****************End Post-Deployment script at 2011-12-31 20:00:34***********************

In this particular case its not all that useful to know that the deployment took 0 seconds but if and when your deployments snowball to many minutes it will be useful to know how long your scripts are taking at which point you can investigate further by timing each individual step in your Pre and Post Deployment scripts.

Recommendation #9: Time your deployments and output the timings

Use sqlcmdvars and the command-line as much as possible

Hardcoding any value into a piece of code is a fraught practise; you should assume that values previously thought to be constant may not be so in the future. You can protect yourself from future changes by storing all literal values as variables in your .sqlcmdvars file. Sure, you can supply default values for those variables but you have the added advantage that they can be overridden from the command-line when deploying using vsdbcmd.exe. Moreover, if you have values that are hardcoded in multiple places in your code then specifying those values in .sqlcmdvars ensures that your code adheres to the principle of DRY. Lastly, if values are stored in the .sqlcmdvars file then you can output them at deploy time (see recommendation #7).

Recommendation #10: All literal values should be stored in your .sqlcmdvars file

Every developer gets their own development database

In most SQL Server development shops that I’ve been on all developers work against a single centralised development database. To me this is an antiquated way of working because its possible that work one person is doing can conflict with that of someone else, I find it much better for every developer to work in isolation and then use the CI deployment to check that one’s code is not in conflict with anyone else’s. Datadude supports (nay encourages) this way of working with the notion of an Isolated Development Environment:

Every developer should configure their isolated development environment which, typically, would be their local instance. And so to my next recommendation:

Recommendation #11: Every developer should use the Isolated Dev Environment settings in order to author their code

Incidentally, if every developer has their own development database and you are following my earlier recommendation to use a [DeployLog] table then you can track how often a developer is bothering to deploy and test their code. On a recent project we used this evidence in a (ahem) discussion with a developer who tried to convince us that he was testing his code sufficiently even though he was repeatedly causing the CI deployment to fail.

Don’t delete anything from your project

When projects are no longer required in your database then intuitively it makes sense to remove the file containing that object from the datadude project, I would however like to suggest a different approach. Rather than removing a file just change the Build property to “Not in Build”:

This has the advantage that your project maintains some semblance of history of what objects have been removed from your database – that can be useful to anyone inheriting your code in the future.

Recommendation #12: Use “Not in Build” to remove an object from your database

Build and Deploy your datadude projects outside of Visual Studio

Building and deploying your datadude projects within Visual Studio can become a real time hog; in my experience its not unusual for deployments to take many minutes and your Visual Studio environment will be unavailable for further development work during that time. For that reason I recommend investing some time in writing some msbuild scripts that will build and deploy your project(s) from the command-line. Here are some examples that you can adapt for your own use, firstly a script to build a solution:

<?xml version="1.0" encoding="utf-8"?>

<Project xmlns="http://schemas.microsoft.com/developer/msbuild/2003"
          DefaultTargets="Build">

< ItemGroup >
    
    <Config Include="Debug" />
    <Config Include="Release" />
</ ItemGroup >
<Target Name="Build">
    <Message Text="Building %(Config.Identity) configuration..."/>
    <MSBuild Projects=".\Lloyds.UKTax.DB.sln" Properties="Configuration=%(Config.Identity)" />
</ Target >
</ Project >

and secondly a script that will deploy a datadude project:

<?xml version="1.0" encoding="utf-8"?>

<Project xmlns="http://schemas.microsoft.com/developer/msbuild/2003"
          DefaultTargets="Build;Deploy">
< PropertyGroup >
    
    <Configuration>Debug</Configuration>
    <DevServer>Data Source=GBS0039182\GLDDEV01;Integrated Security=True;Pooling=False</DevServer>
</ PropertyGroup >

< ItemGroup >
    <ProjectToBuild Include="SolutionBuild.proj" />
</ ItemGroup >


< ItemGroup >
    <DbProj Include="username">
      <DbName>MyDB</DbName>
      <ProjectName>MySoln.MyDB</ProjectName>
      <OutputPath>\%(ProjectName)\sql\$(Configuration)\\cf1 </OutputPath>
      <DeployConnStr>Data Source=localhost;Integrated Security=True;Pooling=False</DeployConnStr>
    </ DbProj >
</ ItemGroup >

<Target Name="Build">
    <MSBuild Projects="@(ProjectToBuild)" />
</ Target >

<Target Name="Deploy">
    
    <Message Text="USERNAME=$(USERNAME)" />
    <Message Condition="'%(DbProj.Identity)'==$(USERNAME)" Text="Deploying:
     Project%09%09%09: %(DbProj.ProjectName)
     DbName%09%09%09: %(DbProj.DbName)
     From OutputPath%09%09: %(DbProj.OutputPath)
     To ConnStr%09%09: %(DbProj.DeployConnStr)
     By%09%09%09: %(DbProj.Identity)"
     />
    <Exec Condition="'%(DbProj.Identity)'==$(USERNAME)" Command=""$(VSINSTALLDIR)\vstsdb\deploy\vsdbcmd.exe"
            /Action:Deploy /ConnectionString:"%(DbProj.DeployConnStr)" /DeployToDatabase+
            /manifest:".%(DbProj.OutputPath)%(DbProj.ProjectName).deploymanifest" /p:TargetDatabase=%(DbProj.DbName)
            /p:Build="from cmd line"" />
</ Target >
</ Project >

Writing these scripts may appear to be laborious but they’ll save you heaps of time in the long run.

Recommendation #13: Build and deploy to your development sandbox using scripts

UPDATE: Upon reading this blog post Mordechai Danielov wrote a follow-up in which he published a useful script that builds a series of projects using Powershell. Its at building your database solutions outside of Visual Studio.

Useful links

Over the years I’ve collected some links to MSDN articles that have proved invaluable:

Datadude bugs

Like any substantial piece of software datadude is not without bugs. Many of the issues I have found are concerned with the datadude interpreter not correctly parsing T-SQL code, here’s a list of some bugs that I have found down the years:

Some of these bugs were reported a long time ago and may well have been fixed in later service packs.

Previous datadude blog posts

I have blogged on datadude quite a bit in the past:

Summing up

This has been an inordinately large blog post so if you’ve read this far – well done. For easy reference, here are all the recommendations that I have made:

Use Source Control and implement a Continuous Integration deployment
Turn on Code Analysis
When running your deployment in a test environment, run it more than once
Maintain an automated history of your deployments
Use Schema View in preference to Solution Explorer
Any action in a Pre or Post-Deployment Script should use PRINT to state what has been done
Output the value of all variables in your Pre-Deployment script
Each database object should be defined in a dedicated file
Time your deployments and output the timings
All literal values should be stored in your .sqlcmdvars file
Every developer should use the Isolated Dev Environment settings in order to author their code
Use “Not in Build” to remove an object from your database
Build and deploy to your development sandbox using scripts

I really hope this proves useful because its taken a good long while to get it published If you have any feedback then please let me know in the comments.

Thanks for reading!

@jamiet

* When I started writing this blog post the first sentence was “Over the past six months I have worked on two separate projects for customers that wanted to make use of Visual Studio 2010 Database projects to manage their database schema.” as opposed to what it is now: “Over the past eighteen months I have worked on four separate projects…” Yes, that’s how long its taken to write it!

Appendix – An example CI configuration

As stated above, an earlier draft of this blog post included full details of the CI configuration from one of the projects that I have worked on. Although it may repeat some of what has already been said I have included that text below.

==============================================================

Introduction

This project has invested heavily in using a Continuous Integration (CI) approach to development. What that means, succinctly, is that whenever someone checks-in some code to our source control system an automated build process is kicked off that constructs our entire system from scratch on a dedicated server. CI is not a new concept but it is fairly rare that anyone applies the same rigour to their database objects as they do to so-called “application code” (e.g. the stuff written in .Net code) and on this project we have made a conscious decision to properly build our databases as part of the CI build.

Datadude employs a declarative approach to database development. In other words you define what you want database schema to look like and datadude will work out what it needs to do to your target in order to turn it into what you have defined. What this means in practice is that you only ever write CREATE … DDL statements rather than IF <object-exists> THEN ALTER …ELSE CREATE … statements which is what you may have done in the past.

Here’s our CI environment setup:

SubVersion (SVN) is being used for source control
Hudson, an open source CI server, is being used to orchestrate our whole CI environment. It basically monitors our SVN repository and when it spots a checked-in file, kicks off the CI build
Our CI scripts (the stuff that actually does the work) are written using msbuild
We have 2 msbuild scripts:
- Build.proj which is responsible for:
  - Compiling all our .Net website code
  - Building/Compiling our datadude projects (every datadude project file is a msbuild-compliant script)
- Deploy.proj which is responsible for:
  - Restoring latest database backups from our production environment into our CI environment
  - Deploying our built datadude projects on top of those restored backups
  - Build a folder structure to hold all the artefacts that get deployed
  - Creating folder shares
  - Moving SSIS packages into folder structure
  - Deploying SSRS reports to our SSRS server
  - Deploy our Analysis Services cube definitions to our Analysis Server
Both Build.proj and Deploy.proj get executed by our CI build

Building datadude projects

Datadude makes it very easy to build datadude projects in a CI environment because they are already msbuild-compliant; its simply a call to the MSBuild task, passing in the location of the solution file as an argument. We use the Release configuration (although there is no particular reason for you to do the same – purely your choice):

That’s it! The output from a datadude build includes a number of files but the most important one is a .dbschema file which is an XML representation of all the objects in your database.

Deploying the output from a built datadude project

This is a little more difficult. We *could* simply use the MSBuild task to call our deployment script as we do for build script (see above) but the problem with that is that there are many pre-requisites (including datadude itself) and we don’t want to install Visual Studio and all the assorted paraphernalia onto our various environments. Instead we chose to make use of a command-line tool called VSDBCMD.exe to deploy datadude projects. VSDBCMD does basically the same job as what happens if you were to right-click on a datadude project in Visual Studio and select “Deploy” i.e. It compares the output of a build (A) to the target database (B) and works out what it needs to do to make B look like A. It then produces a .sql script that will actually make those requisite changes, then goes and executes it.

The difficulty comes in VSDBCMD.exe having its own list of file dependencies that are listed at MSDN article How to: Prepare a Database for Deployment From a Command Prompt by Using VSDBCMD.EXE, thankfully a much smaller list then if we were using the MSBuild task.

Some of those files, namely:

Sqlceer35en.dll
Sqlceme35.dll
Sqlceqp35.dll
Sqlcese35.dll
System.Data.SqlServerCe.dll

get installed with SQL Server CE. We bundle along the x86 & x64 installers for SQL Server CE along with all the rest of our deployment artefacts and then, as part of Deploy.proj, install them like so:

That takes care of some of the dependencies but we still have to take care of:

DatabaseSchemaProviders.Extensions.xml
Microsoft.Data.Schema.dll
Microsoft.Data.Schema.ScriptDom.dll
Microsoft.Data.Schema.ScriptDom.Sql.dll
Microsoft.Data.Schema.Sql.dll
Microsoft.SqlServer.BatchParser.dll

as well as the actual VSDBCMD.exe file itself. Quite simply we keep those files in SVN and then bundle them along with all our deployment artefacts (I won’t show you how we do that because its out of the scope of this post and besides if you’re at all proficient with msbuild then you’ll know how to do that and if you’re not, well, why are you reading this?)

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SSIS MSBuild task now included in MSBuild Extension Pack

jamiet — Tue, 14 Sep 2010 21:11:55 GMT

The information in this blog post may be of interest to anyone out there that is using Continuous Integration with msbuild in order to build/deploy a project that includes SSIS packages.

The MSBuild Extension Pack at http://msbuildextensionpack.codeplex.com/ now includes an MSBuild task that will build an SSIS project, the output from which is a .deploymentmanifest file that can be used in concert with the SSIS deployment utility.

Building a SSIS project using the SSIS MSBuild Task essentially has the same effect as right-clicking on a SSIS project and selecting Build with CreateDeploymentUtility=True (i.e. produces a .deploymentmanifest file):

The advantage of using the MSBuild task is of course that you can now do it in an MSBuild script, none of this manual mouse-clicking required thank you very much!

The SSIS MSBuild task was previously available in the SSIS community samples project at http://sqlsrvintegrationsrv.codeplex.com but having it as part of the MSBuild Extension Pack is definitely advantageous as this is a very widely used set of utilities. The source code has been available in the MSBuild Extension pack since changeset 54481 which was checked-in on 26th August 2010 and was included in the August 2010 Release.

Note that in order to deploy your packages after using the SSIS MSBuild task you will need to call the SSIS deployment utility and pass in the outputted .deploymentmanifest file. Information on doing that is decidedly thin on the ground so I’ll try and elucidate. The SSIS Deployment Utility is an executable that gets installed with SQL Server Integration Services workstation tools and is called dtsinstall.exe. You can call it on the command-line and pass in the path to a .deploymentmanifest file but as far as I can determine there is no way to do an unattended install (i.e. there is no way to tell dtsinstall.exe where to install the packages to, it simply opens up a GUI and prompts you for this information). This is a horribly antiquated method of deployment and I’m hunting around to see if there’s anything I’ve missed here – if you know any better please let me know.

Hope this helps!

@Jamiet

Setting up database unit testing as part of a Continuous Integration build process [VS2010 DB Tools - Datadude]

jamiet — Fri, 20 Aug 2010 18:41:00 GMT

[This blog post assumes a familiarity with the terms Continuous Integration (CI), MSBuild & MSTest. If you don’t have a good appreciation of those terms then this blog post probably isn’t for you anyway so don’t worry about it!]

Over the past few days I have been working to get database unit tests executing as part of our Continuous Integration (CI) build and in this blog post I’ll explain how I went about it because it is decidedly not straightforward.

We are using the DB Tools in Visual Studio 2010 (aka DBPro or Datadude - I will refer to it as Datadude from here on in) which includes unit testing functionality. The rest of this blog post also assumes a familiarity with database unit testing in Datadude although if you want to do some background reading an excellent place to start is Jamie Laflen’s whitepaper Apply Test-Driven Development to your Database Projects on MSDN.

We got to the point where we had a C# test project containing database unit tests that executed successfully inside Visual Studio. For demonstration purposes I have put together a solution that contains a simple database project and a test project containing a database unit test:

And just to prove that the test executes successfully in Visual Studio:

N.B. The code for the database object(s) and the unit test itself are not important, that is outside the scope of this blog post.

At this point we have some tests that run in our development sandbox, the configuration for which is done using the Database Test Configuration dialog:

Those config settings are stored in the app.config file which exists as part of our test project (screenshot of which is at the top of this blog post). If we take a look inside that file we can see the ConnectionString that we defined in the Database Test Configuration dialog:

Note the <DatabaseUnitTesting> element, we’re going to be coming back to that a little later!!

Once we have the tests running in Visual Studio the next step is to get them running inside a CI build and for that we call out to MSTest.exe from inside an MSBuild script:

When we execute that script we get some positive results and all looks peachy:

OK, we now have a test that runs successfully both in Visual Studio and by calling MSTest.exe directly from MSBuild. The problem I have to solve now though (and this is the real crux of this blog post) is that the test is still running against the server I specified in app.config; I don’t want this, I want the test to run against a server of my choosing, namely my build server. For this I had to call on the help of the aforementioned Jamie Laflen (who, luckily, I have met in the past) and he gave me guidance on how to achieve it. Below are the steps that you need to take.

Firstly you need to tell Datadude that you want to specify some different credentials and that is done by adding an attribute AllowConfigurationOverride="true" to the <DatabaseUnitTesting> element of app.config like so:

Don’t forget to build your test project after changing the app.config file!!!

This will cause datadude unit testing framework to go and search for a file called *.dbunittest.config where the * indicates either:

The name of machine upon which the tests are being run or
The name of the user running the tests

According to Jamie L datadude runs the following precedence checks:

Is an override specified in app.config? If not, use app.config
Does an override file exist called <machinename>.dbunittest.config? If so, use it, if not…
Does an override file exist called <username>.dbunittest.config? If so, use it, if not…
Fail!

“So”, you may be asking, “what goes in this *.dbunittest.config file then?”. Fair question, that’s where the <DatabaseUnitTesting> element that I mentioned earlier comes in. Copy that element from the app.config file into your *.dbunittest.config file, remove the AllowConfigurationOverride="true" attribute and change the ConnectionString property accordingly:

The next step is to tell MSTest.exe that there is another file that it needs to be aware of when it runs the tests and to do that we need to create a custom testsettings file that will be used instead of the default Local.testsettings. To create a new testsettings file use the Add New Item dialog:

In the Test Settings dialog go to ‘Deployment’, click ‘Enable deployment’, then ‘Add File…’. Browse to your *.dbunittest.config file and add it to the project:

At this point you’re good to go and all you need to do edit your call to MSTest.exe and tell it to use your new testsettings file:

Notice the extra information in the output:

You’ll have to trust me that it used the new config file and therefore the new ConnectionString, although having said that you do get some useful information in the test results file (*.trx) that MSTest.exe creates:

I think its fair to say that this process is a little fiddly to say the least so I’m hoping that Microsoft come up with a better solution in the future, one that integrates better into the whole testing infrastructure. Meanwhile you can download the demo that I put together for this blog post from my SkyDrive.

Hope that helps! Comments are welcome.

Jamiet

UPDATE: Atul Verma has written a 3-part blog series on how to write your database unit tests so if Jamie Laflen's whitepaper (linked to above) doesn't tickle your fancy try reading Atul's series instead: