When I Add-Migration, I get the appropriate DbMigration class with the Up / Down methods, where I am able to make schema changes and (with the use of the Sql() method) can make data/content changes as well.
I'd like to be able to make content changes per migration using the database context. I understand that I could use the Seed method in a Configuration class, but my understanding is that I can only wire up one Configuration with my initializer.
I'd prefer to have a UpCompleted()/DownCompleted() methods that would provide access to the db context after the migration completed. This would enable writing incremental data/context change "scripts" in a manner that would be less prone to errors than using the Sql() method.
Am I missing something? Is this possible?
Thanks!
That doesn't really work because the context only has your most recent model - which can only be used to access the database once the most recent migration has run (which is effectively what Seed achieves).
For an example of how this idea breaks, if you moved a property from one class to another then seed logic from older migrations would no longer compile. But you couldn't change it to use the new property because the corresponding column wouldn't exist in the database yet.
If you want to write this kind of seed/data-manipulation logic, you need to put it at the end of the Up/Down methods and use the Sql method to perform it using raw SQL.
~Rowan
My integration tests are use a live DB that's generated using the EF initalizers. When I run the tests individually they run as expected. However when I run them all at once, I get a lot of failed tests.
I appear to have some overlapping going on. For example, I have two tests that use the same setup method. This setup method builds & populates the DB. Both tests perform the same test ACT which adds a handful of items to the DB (the same items), but what's unique is each test is looking for different calculations (instead of one big test that does a lot of things).
One way I could solve this is to do some trickery in the setup that creates a unique DB for each test that's run, that way everything stays isolated. However the EF initilization stuff isn't working when I do that because it is creating a new DB rather than dropping & replacing it iwth a new one (the latter triggers the seeding).
Ideas on how to address this? Seems like an organization of my tests... just not show how to best go about it and was looking for input. Really don't want to have to manually run each test.
Use test setup and tear down methods provided by your test framework and start transaction in test setup and rollback the transaction in test tear down (example for NUnit). You can even put setup and tear down method to the base class for all tests and each test will after that run in its own transaction which will rollback at the end of the test and put the database to its initial state.
Next to what Ladislav mentioned you can also use what's called a Delta Assertion.
For example, suppose you test adding a new Order to the SUT.
You could create a test that Asserts that there is exactly 1 Order in the database at the end of the test.
But you can also create a Delta Assertion by first checking how many Orders there are in the database at the start of the test method. Then after adding an Order to the SUT you test that there are NumberOfOrdersAtStart + 1 in the database.
I am writing Web app. My program creates relations itself when it is needed, basically when the program is deployed and run first time. But I see that it is very common to create SQL script and run it to initialize data-base for the first time. Is it compulsory to do this?
No, it is not compulsory for the database initialization script to be part of the "first run" of your application; preparing the database can be a deployment step. In fact, depending how long it takes to initialize the database, you might specifically want to avoid initializing the database on the first run, and instead make sure it is deployed and initialized before the first time the application is accessed.
I'm looking into adding some unit tests for some classes in my data access layer and I'm looking at an update routine that has no return value. It simply updates a row based on the id you provide at whichever column name you provide.
Inside of this method, we collect the parameters and pass them to a helper routine which calls the stored procedure to update the table.
Is there a recommended approach for how to do unit testing in such a scenario? I'm having a hard time thinking of a test that wouldn't depend on other methods.
Test the method that reads the data from the database, first.
Then you can call the update function, and use the function that was tested above, to verify that the value that was updated is correct.
I tend to use other methods in my unit tests as long as I have tests that also test those that were called.
If your helper functions are in the database (stored procedures or functions) then just test those with a DatabaseUnitTest first, then test the visual basic code.
I would just use a lookup method to validate that the data was properly updated.
Yes, technically this would relay on the lookup method working properly, but I don't think you necessarily have to avoid that dependency. Just make sure the lookup method is tested as well.
I would use the method to get that data and check the return value to what you updated and Assert the expected value. This does assume the method used to retrieve the data has been tested and works correctly.
I use nhibernate and transactions and for unittests I don't commit to the database but I flush the session which gives the same errors if needed but doesn't write the data.
Of course if you have a build server you just run the unittests against a freshly made database which is freshly made on each build. Try using an filebased database like firebird or something.
I'm using SQL-Server 2008 with Visual Studio Database Edition.
With this setup, keeping your schema in sync is very easy. Basically, there's a 'compare schema' tool that allow me to sync the schema of two databases and/or a database schema with a source-controlled creation script folder.
However, the situation is less clear when it comes to data, which can be of three different kind :
static data referenced in the code. typical example : my users can change their setting, and their configuration is stored on the server. However, there's a system-wide default value for each setting that is used in case the user didn't override it. The table containing those default settings grows as more options are added to the program. This means that when a new feature/option is checked in, the system-wide default setting is usually created in the database as well.
static data. eg. a product list populating a dropdown list. The program doesn't rely on the existence of a specific product in the list to work. This can be for example a list of unicode-encoded products that should be deployed in production when the new "unicode version" of the program is deployed.
other data, ie everything else (logs, user accounts, user data, etc.)
It seems obvious to me that my third item shouldn't be source-controlled (of course, it should be backuped on a regular basis)
But regarding the static data, I'm wondering what to do.
Should I append the insert scripts to the creation scripts? or maybe use separate scripts?
How do I (as a developer) warn the people doing the deployment that they should execute an insert statement ?
Should I differentiate my two kind of data? (the first one being usually created by a dev, while the second one is usually created by a non-dev)
How do you manage your DB static data ?
I have explained the technique I used in my blog Version Control and Your Database. I use database metadata (in this case SQL Server extended properties) to store the deployed application version. I only have scripts that upgrade from version to version. At startup the application reads the deployed version from the database metadata (lack of metadata is interpreted as version 0, ie. nothing is yet deployed). For each version there is an application function that upgrades to the next version. Usually this function runs an internal resource T-SQL script that does the upgrade, but it can be something else, like deploying a CLR assembly in the database.
There is no script to deploy the 'current' database schema. New installments iterate trough all intermediate versions, from version 1 to current version.
There are several advantages I enjoy by this technique:
Is easy for me to test a new version. I have a backup of the previous version, I apply the upgrade script, then I can revert to the previous version, change the script, try again, until I'm happy with the result.
My application can be deployed on top of any previous version. Various clients have various deployed version. When they upgrade, my application supports upgrade from any previous version.
There is no difference between a fresh install and an upgrade, it runs the same code, so I have fewer code paths to maintain and test.
There is no difference between DML and DDL changes (your original question). they all treated the same way, as script run to change from one version to next. When I need to make a change like you describe (change a default), I actually increase the schema version even if no other DDL change occurs. So at version 5.1 the default was 'foo', in 5.2 the default is 'bar' and that is the only difference between the two versions, and the 'upgrade' step is simply an UPDATE statement (followed of course by the version metadata change, ie. sp_updateextendedproperty).
All changes are in source control, part of the application sources (T-SQL scripts mostly).
I can easily get to any previous schema version, eg. to repro a customer complaint, simply by running the upgrade sequence and stopping at the version I'm interested in.
This approach saved my skin a number of times and I'm a true believer now. There is only one disadvantage: there is no obvious place to look in source to find 'what is the current form of procedure foo?'. Because the latest version of foo might have been upgraded 2 or 3 versions ago and it wasn't changed since, I need to look at the upgrade script for that version. I usually resort to just looking into the database and see what's in there, rather than searching through the upgrade scripts.
One final note: this is actually not my invention. This is modeled exactly after how SQL Server itself upgrades the database metadata (mssqlsystemresource).
If you are changing the static data (adding a new item to the table that is used to generate a drop-down list) then the insert should be in source control and deployed with the rest of the code. This is especially true if the insert is needed for the rest of the code to work. Otherwise, this step may be forgotten when the code is deployed and not so nice things happen.
If static data comes from another source (such as an import of the current airport codes in the US), then you may simply need to run an already documented import process. The import process itself should be in source control (we do this with all our SSIS packages), but the data need not be.
Here at Red Gate we recently added a feature to SQL Data Compare allowing static data to be stored as DML (one .sql file for each table) alongside the schema DDL that is currently supported by SQL Compare.
To understand how this works, here is a diagram that explains how it works.
The idea is that when you want to push changes to your target server, you do a comparison using the scripts as the source data source, which generates the necessary DML synchronization script to update the target. This means you don't have to assume that the target is being recreated from scratch each time. In time we hope to support static data in our upcoming SQL Source Control tool.
David Atkinson, Product Manager, Red Gate Software
I have come across this when developing CMS systems.
I went with appending the static data (the stuff referenced in the code) to the database creation scripts, then a separate script to add in any 'initialisation data' (like countries, initial product population etc).
For the first two steps, you could consider using an intermediate format (ie XML) for the data, then using a home grown tool, or something like CodeSmith to generate the SQL, and possible source files as well, if (for example) you have lookup tables which relate to enumerations used in the code - this helps enforce consistency.
This has another benefit that if the schema changes, in many cases you don't have to regenerate all your INSERT statements - you just change the tool.
I really like your distinction of the three types of data.
I agree for the third.
In our application, we try to avoid putting in the database the first, because it is duplicated (as it has to be in the code, the database is a duplicate). A secondary benefice is that we need no join or query to get access to that value from the code, so this speed things up.
If there is additional information that we would like to have in the database, for example if it can be changed per customer site, we separate the two. Other tables can still reference that data (either by index ex: 0, 1, 2, 3 or by code ex: EMPTY, SIMPLE, DOUBLE, ALL).
For the second, the scripts should be in source-control. We separate them from the structure (I think they typically are replaced as time goes, while the structures keeps adding deltas).
How do I (as a developer) warn the people doing the deployment that they should execute an insert statement ?
We have a complete procedure for that, and a readme coming with each release, with scripts and so on...
First off, I have never used Visual Studio Database Edition. You are blessed (or cursed) with whatever tools this utility gives you. Hopefully that includes a lot of flexibility.
I don't know that I'd make that big a difference between your type 1 and type 2 static data. Both are sets of data that are defined once and then never updated, barring subsequent releases and updates, right? In which case the main difference is in how or why the data is as it is, and not so much in how it is stored or initialized. (Unless the data is environment-specific, as in "A" for development, "B" for Production. This would be "type 4" data, and I shall cheerfully ignore it in this post, because I've solved it useing SQLCMD variables and they give me a headache.)
First, I would make a script to create all the tables in the database--preferably only one script, otherwise you can have a LOT of scripts lying about (and find-and-replace when renaming columns becomes very awkward). Then, I would make a script to populate the static data in these tables. This script could be appended to the end of the table script, or made it's own script, or even made one script per table, a good idea if you have hundreds or thousands of rows to load. (Some folks make a csv file and then issue a BULK INSERT on it, but I'd avoid that is it just gives you two files and a complex process [configuring drive mappings on deployment] to manage.)
The key thing to remember is that data (as stored in databases) can and will change over time. Rarely (if ever!) will you have the luxury of deleting your Production database and replacing it with a fresh, shiny, new one devoid of all that crufty data from the past umpteen years. Databases are all about changes over time, and that's where scripts come into their own. You start with the scripts to create the database, and then over time you add scripts that modify the database as changes come along -- and this applies to your static data (of any type) as well.
(Ultimately, my methodology is analogous to accounting: you have accounts, and as changes come in you adjust the accounts with journal entries. If you find you made a mistake, you never go back and modify your entries, you just make a subsequent entries to reverse and fix them. It's only an analogy, but the logic is sound.)
The solution I use is to have create and change scripts in source control, coupled with version information stored in the database.
Then, I have an install wizard that can detect whether it needs to create or update the db - the update process is managed by picking appropriate scripts based on the stored version information in the database.
See this thread's answer. Static data from your first two points should be in source control, IMHO.
Edit: *new
all-in-one or a separate script? it does not really matter as long as you (dev team) agree with your deployment team. I prefer to separate files, but I still can always create all-in-one.sql from those in the proper order [Logins, Roles, Users; Tables; Views; Stored Procedures; UDFs; Static Data; (Audit Tables, Audit Triggers)]
how do you make sure they execute it: well, make it another step in your application/database deployment documentation. If you roll out application which really needs specific (new) static data in the database, then you might want to perform a DB version check in your application. and you update the DB_VERSION to your new release number as part of that script. Then your application on a start-up should check it and report an error if the new DB version is required.
dev and non-dev static data: I have never seen this case actually. More often there is real static data, which you might call "dev", which is major configuration, ISO static data etc. The other type is default lookup data, which is there for users to start with, but they might add more. The mechanism to INSERT these data might be different, because you need to ensure you do not destoy (power-)user-created data.