What happens in Grails, when you update your model, and deploy it to your web server? Does the existing data get overwritten?
If your model is changed you need to upgrade your db, you can use this plugin.
Make sure you change you setting from create-drop to update.
There are a couple of good guides you can look at, here is a good one.
Good luck!
The behavior is defined in the GORM configuration
Basically, the default for development is drop-create, which erase all the content, and recreate tables.
On more stable releases, update might be a good setting knowing that Hibernate prefer to fails that conflict.
As always, I would recommend making a backup of the DB before performing such operation on pre-production and production systems.
Related
I'm in the research phase trying to adopt 2012 Database Projects on an existing small project. I'm a C# developer, not a DBA, so I'm not particularly fluent with best practices. I've been searching google and stackoverflow for a few hours now but I still don't know how to handle some key deployment scenarios properly.
1) Over the course of several development cycles, how do I manage multiple versions of my database? If I have a client on v3 of my database and I want to upgrade them to v8, how do I manage this? We currently manage hand-crafted schema and data migration scripts for every version of our product. Do we still need to do this separately or is there something in the new paradigm that supports or replaces this?
2) If the schema changes in such a way that requires data to be moved around, what is the best way to handle this? I assume some work goes in the Pre-Deployment script to preserve the data and then the Post-Deploy script puts it back in the right place. Is that the way of it or is there something better?
3) Any other advice or guidance on how best to work with these new technologies is also greately appreciated!
UPDATE: My understanding of the problem has grown a little since I originally asked this question and while I came up with a workable solution, it wasn't quite the solution I was hoping for. Here's a rewording of my problem:
The problem I'm having is purely data related. If I have a client on version 1 of my application and I want to upgrade them to version 5 of my application, I would have no problems doing so if their database had no data. I'd simply let SSDT intelligently compare schemas and migrate the database in one shot. Unfortunately clients have data so it's not that simple. Schema changes from version 1 of my application to version 2 to version 3 (etc) all impact data. My current strategy for managing data requires I maintain a script for each version upgrade (1 to 2, 2 to 3, etc). This prevents me from going straight from version 1 of my application to version 5 because I have no data migration script to go straight there. The prospect creating custom upgrade scripts for every client or managing upgrade scripts to go from every version to every greater version is exponentially unmanageable. What I was hoping was that there was some sort of strategy SSDT enables that makes managing the data side of things easier, maybe even as easy as the schema side of things. My recent experience with SSDT has not given me any hope of such a strategy existing but I would love to find out differently.
I've been working on this myself, and I can tell you it's not easy.
First, to address the reply by JT - you cannot dismiss "versions", even with declarative updating mechanics that SSDT has. SSDT does a "pretty decent" job (provided you know all the switches and gotchas) of moving any source schema to any target schema, and it's true that this doesn't require verioning per se, but it has no idea how to manage "data motion" (at least not that i can see!). So, just like DBProj, you left to your own devices in Pre/Post scripts. Because the data motion scripts depend on a known start and end schema state, you cannot avoid versioning the DB. The "data motion" scripts, therefore, must be applied to a versioned snapshot of the schema, which means you cannot arbitrarily update a DB from v1 to v8 and expect the data motion scripts v2 to v8 to work (presumably, you wouldn't need a v1 data motion script).
Sadly, I can't see any mechanism in SSDT publishing that allows me to handle this scenario in an integrated way. That means you'll have to add your own scafolding.
The first trick is to track versions within the database (and SSDT project). I started using a trick in DBProj, and brought it over to SSDT, and after doing some research, it turns out that others are using this too. You can apply a DB Extended Property to the database itself (call it "BuildVersion" or "AppVersion" or something like that), and apply the version value to it. You can then capture this extended property in the SSDT project itself, and SSDT will add it as a script (you can then check the publish option that includes extended properties). I then use SQLCMD variables to identify the source and target versions being applied in the current pass. Once you identify the delta of versions between the source (project snapshot) and target (target db about to be updated), you can find all the snapshots that need to be applied. Sadly, this is tricky to do from inside the SSDT deployment, and you'll probably have to move it to the build or deployment pipeline (we use TFS automated deployments and have custom actions to do this).
The next hurdle is to keep snapshots of the schema with their associated data motion scripts. In this case, it helps to make the scripts as idempotent as possible (meaning, you can rerun the scripts without any ill side-effects). It helps to split scripts that can safely be rerun from scripts that must be executed one time only. We're doing the same thing with static reference data (dictionary or lookup tables) - in other words, we have a library of MERGE scripts (one per table) that keep the reference data in sync, and these scripts are included in the post-deployment scripts (via the SQLCMD :r command). The important thing to note here is that you must execute them in the correct order in case any of these reference tables have FK references to each other. We include them in the main post-deploy script in order, and it helps that we created a tool that generates these scripts for us - it also resolves dependency order. We run this generation tool at the close of a "version" to capture the current state of the static reference data. All your other data motion scripts are basically going to be special-case and most likely will be single-use only. In that case, you can do one of two things: you can use an IF statement against the db build/app version, or you can wipe out the 1 time scripts after creating each snapshot package.
It helps to remember that SSDT will disable FK check constraints and only re-enable them after the post-deployment scripts run. This gives you a chance to populate new non-null fields, for example (by the way, you have to enable the option to generate temporary "smart" defaults for non-null columns to make this work). However, FK check constraints are only disabled for tables that SSDT is recreating because of a schema change. For other cases, you are responsible for ensuring that data motion scripts run in the proper order to avoid check constraints complaints (or you manually have disable/re-enable them in your scripts).
DACPAC can help you because DACPAC is essentially a snapshot. It will contain several XML files describing the schema (similar to the build output of the project), but frozen in time at the moment you create it. You can then use SQLPACKAGE.EXE or the deploy provider to publish that package snapshot. I haven't quite figured out how to use the DACPAC versioning, because it's more tied to "registered" data apps, so we're stuck with our own versioning scheme, but we do put our own version info into the DACPAC filename.
I wish I had a more conclusive and exhasutive example to provide, but we're still working out the issues here too.
One thing that really sucks about SSDT is that unlike DBProj, it's currently not extensible. Although it does a much better job than DBProj at a lot of different things, you can't override its default behavior unless you can find some method inside of pre/post scripts of getting around a problem. One of the issues we're trying to resolve right now is that the default method of recreating a table for updates (CCDR) really stinks when you have tens of millions of records.
-UPDATE: I haven't seen this post in some time, but apparently it's been active lately, so I thought I'd add a couple of important notes: if you are using VS2012, the June 2013 release of SSDT now has a Data Comparison tool built-in, and also provides extensibility points - that is to say, you can now include Build Contributors and Deployment Plan Modifiers for the project.
I haven't really found any more useful information on the subject but I've spent some time getting to know the tools, tinkering and playing, and I think I've come up with some acceptable answers to my question. These aren't necessarily the best answers. I still don't know if there are other mechanisms or best practices to better support these scenarios, but here's what I've come up with:
The Pre- and Post-Deploy scripts for a given version of the database are only used migrate data from the previous version. At the start of every development cycle, the scripts are cleaned out and as development proceeds they get fleshed out with whatever sql is needed to safely migrate data from the previous version to the new one. The one exception here is static data in the database. This data is known at design time and maintains a permanent presence in the Post-Deploy scripts in the form of T-SQL MERGE statements. This helps make it possible to deploy any version of the database to a new environment with just the latest publish script. At the end of every development cycle, a publish script is generated from the previous version to the new one. This script will include generated sql to migrate the schema and the hand crafted deploy scripts. Yes, I know the Publish tool can be used directly against a database but that's not a good option for our clients. I am also aware of dacpac files but I'm not really sure how to use them. The generated publish script seems to be the best option I know for production upgrades.
So to answer my scenarios:
1) To upgrade a database from v3 to v8, I would have to execute the generated publish script for v4, then for v5, then for v6, etc. This is very similar to how we do it now. It's well understood and Database Projects seem to make creating/maintaining these scripts much easier.
2) When the schema changes from underneath data, the Pre- and Post-Deploy scripts are used to migrate the data to where it needs to go for the new version. Affected data is essentially backed-up in the Pre-Deploy script and put back into place in the Post-Deploy script.
3) I'm still looking for advice on how best to work with these tools in these scenarios and others. If I got anything wrong here, or if there are any other gotchas I should be aware of, please let me know! Thanks!
In my experience of using SSDT the notion of version numbers (i.e. v1, v2...vX etc...) for databases kinda goes away. This is because SSDT offers a development paradigm known as declarative database development which loosely means that you tell SSDT what state you want your schema to be in and then let SSDT take responsibility for getting it into that state by comparing against what you already have. In this paradigm the notion of deploying v4 then v5 etc.... goes away.
Your pre and post deployment scripts, as you correctly state, exist for the purposes of managing data.
Hope that helps.
JT
I just wanted to say that this thread so far has been excellent.
I have been wrestling with the exact same concerns and am attempting to tackle this problem in our organization, on a fairly large legacy application. We've begun the process of moving toward SSDT (on a TFS branch) but are at the point where we really need to understand the deployment process, and managing custom migrations, and reference/lookup data, along the way.
To complicate things further, our application is one code-base but can be customized per 'customer', so we have about 190 databases we are dealing with, for this one project, not just 3 or so as is probably normal. We do deployments all the time and even setup new customers fairly often. We rely heavily on PowerShell now with old-school incremental release scripts (and associated scripts to create a new customer at that version). I plan to contribute once we figure this all out but please share whatever else you've learned. I do believe we will end up maintaining custom release scripts per version, but we'll see. The idea about maintaining each script within the project, and including a From and To SqlCmd variable is very interesting. If we did that, we would probably prune along the way, physically deleting the really old upgrade scripts once everybody was past that version.
BTW - Side note - On the topic of minimizing waste, we also just spent a bunch of time figuring out how to automate the enforcement of proper naming/data type conventions for columns, as well as automatic generation for all primary and foreign keys, based on naming conventions, as well as index and check constraints etc. The hardest part was dealing with the 'deviants' that didn't follow the rules. Maybe I'll share that too one day if anyone is interested, but for now, I need to pursue this deployment, migration, and reference data story heavily. Thanks again. It's like you guys were speaking exactly what was in my head and looking for this morning.
Is there any way to have data migrations on production database not to be with SQL?
We are using MigratorDotNet and when we build a new funcionality for the application that changes the scheme of the database and we need to do some data updates we have to do this complex and troublesome SQL statements so the data is consistent on production.
Was wondering if there was another way to do this, what are the bests practices to do this? Any ideas on other possible solutions?
We cannot use something like NHibernate because then we have to keep fixing old migrations when the scheme changes, and that can be error prone.
The trick is to use your migration tool and fold said data manipulation statements into the migrations. We use an extended version of the same thing typically for a few projects and it can definitely handle that trick.
If you're already using a migration tool like Migrator.NET then I'd say you're most of the way there. Complex schema/data changes are just a fact of life in the RDBMS world.
Try mite. It let's you do anything that you can do with sql and use sql to do it but have the ability to ensure your database is on the desired version and not risk executing a script that has already run (or miss a script), leaving your database in a consistent state.
If your developers adopt this. Deployments are a simple mite update and then you know problems are product related or data related (but not schema related).
https://github.com/soitgoes/mite
Let me know what you think. I developed this and have been using this with my team for years with great success.
I currently have a website with three builds: development, staging and production. Each of those has it's own MySQL database instance. Each of the instances has different data in it which should not change (orders).
My question is, if I made changes to the structure of the development database, is there an easy way to propogate those changes to staging and production without affecting the data?
Thanks.
Just do all of your schema changes with scripts which you keep in source control. When you release code to staging, then you will ship with the build the scripts to update the schema, and use the same ones when you ship to production.
It's that easy.
Don't EVER manually hack the database schema. Test your migration and rollback scripts (making rollback scripts is a VERY good idea).
I'm sure there is a better solution than the one I'll tell you over here... But until someone posts one... Here you go...
If you can script your database strcture (or you have them already scripted on your source control), you can compare the scripts side by side and then extract the differences to run them on the required database...
I'm sure there are tools out there that would do all that for you... But I can't recall any names and if they're free or not... I hope someone helps you more then :)
For simplicity's sake. I'm using Fluent NHibernate's Automapping combined with NHibernate's SchemaUpdate during runtime. On each run Automapper creates mappings for all entity classes and SchemaUpdate applies the schema to the existing database. I was pleasantly surprised that it works correctly against an empty database as well. It's worked fine so far in a development environment and has allowed me to respond to bugs rather quickly.
My question is whether it is reliable enough to leave in production code. Obviously it doesn't need to run every time the program starts in a production environment but it would be useful for incremental product updates (though I don't plan on making any major changes to the domain after the product ships).
(Perhaps my real question should be how safe is it to use these two tools in conjunction?)
Update
The application has two versions: a standalone desktop and a multiuser client/server. Also due to the nature of the business domain (tax software) I have the luxury of starting with a clean database each year.
For this to be able to run in production code, the account that the production application uses to connect to your database would have to have permission to change the database schema.
That alone should deter you from this approach, irrespective of the quality/reliability of the NHibernate code.
I wouldn't risk it. What works well is to run it on a staging server that has been restored from production, then use a database comparison tool (such as Red Gate) to examine the changes and generate a script.
You may want to consider that SchemaUpdate will always make additive and non-destructive changes, resulting in stale columns and nullable columns where they should be non-nullable.
In other words, absolutely not for production use.
It depends on how critical the data is! I doubt that's such a good idea for a banking system. I have not had any problems with the update apart from one thing. Sometimes it does not rename properly. Further more it's a security risk connecting with an account that can modify the schema like that :)
There is a development_structure.sql inside my /db folder of my rails application (rails 2.3.4, ruby 1.8.7) and I am not sure exactly what it does.
Is it needed for some specific environment? (I think I read somewhere that it's used for tests)
Do I need to add it to my git repository?
This post has been used as a reference by a coworker of mine, but the two answers are not exact or informative enough.
development_structure.sql is a low-level dump of the schema, which is necessary when you start to use proprietary database features - either you want to or not, you're going to use them at some point.
Regarding the question of storing it or not, there's some debate. Here is an informative post: http://www.saturnflyer.com/blog/jim/2010/09/14/always-check-in-schema-rb/.
And my take on this follows.
The objective of the development_structure.sql is to sync, for any given commit, the database structure with the code, without having previous knowledge of the schema structure, that is, without having to rely on a pre-existing state of the schema to get the new one.
In a nutshell, by having a schema structure available, whenever you change branch/commit, you load it directly and forget it.
This is mostly valid for dynamic and "crowded" projects, where different branches have differences in the underlying schema structure.
Without having the schema structure stored, you would need to always use an existing reference schema in your database, and migrate it back or forward every time you change branch/commit; several real-world cases can make this process inefficient (e.g. when another branch doesn't have some migrations you currently have, or some migrations can't be rolled back).
Another problem is automated builds, which suffer from the same problems, and even worse, they can't apply manual changes.
The only downside is that it requires a certain habit, which is, to store it every time you run a migration. Easy to say, but also easy to forget.
I don't say you can't live without development_structure.sql - of course you can.
But if you have it, when changing branch/commit you just load-and-forget; if you don't, you [may] have to go through a series of manual steps.
You should not add it to your git repository.
It is a file created automatically by rails when you run migrations with your database.yml configured to connect against a mysql database.
You can view it as an alternative to schema.rb
I believe you can force rails to create it by adding in your environment.rb:
config.active_record.schema_format = :sql
When present this file is used for example by:
rake db:test:clone_structure
Edit
Relevant section in Ruby On Rails Guides.
http://guides.rubyonrails.org/migrations.html#schema-dumping-and-you
They recommend to check it into source control on the wiki.
I personally like to keep it out of it. I like to be able to run all migrations very quickly. It is for me a good sign. If migrations become slow I feel like I am not in total control of my environment anymore. Slowness in migrations generally means I have a lot of data in my development database which I feel wrong.
However, It seems to be a matter of personal taste nowadays.
Follow your instincts on this one.
It's created when you run a rake task to clone your development database to your test database. The development database is outputted to SQL which is then read in to your test DB. You can safely delete it.
In rails 3, you don't even have to write this line,
config.active_record.schema_format = :sql
You can generate this structure.sql file by simply running the above rake command mentioned above