I was wondering what are the best practices in order to write SQL scripts to set up databases for production and/or development, for instance:
Should I include the CREATE DATABASE statement?
Should I create users for the database in the same script?
Is correct to disable FK check before executing the body of the script?
May I include the hole script in a transaction?
Is better to generate 1 script per database than one script for all of them?
Thanks!
The problem with your question is is hard to answer as it depends on the way the scripts are used in what you are trying to achieve. you also don't say which DB server you are using as there are tools provided which can make some tasks easier.
Taking your points in order, here are some suggestions, which will probably be very different to everyone elses :)
Should I include the CREATE DATABASE
statement?
What alternative are you thinking of using? If your question is should you put the CREATE DATABASE statement in the same script as the table creation it depends. When developing DB I use a separate create DB script as I have a script to drop all objects and so I don't need to create the database again.
Should I create users for the database in the same script?
I wouldn't, simply because the users may well change but your schema has not. Might as well manage those changes in a smaller script.
Is correct to disable FK check before executing the body of the script?
If you are importing the data in an attempt to recover the database then you may well have to if you are using auto increment IDs and want to keep the same values. Also you may end up importing the tables "out of order" an not want checks performed.
May I include the whole script in a transaction?
Yes, you can, but again it depends on the type of script you are running. If you are importing data after rebuilding a db then the whole import should work or fail. However, your transaction file is going to be huge during the import.
Is better to generate 1 script per database than one script for all of them?
Again, for maintenance purposes it's probably better to keep them separate.
This probably depends what kind of database and how it is used and deployed. I am developing a n-tier standard application that is deployed at many different customer sites.
I do not add a CREATE DATABASE statement in the script. Creating the the database is a part of the installation script which allows the user to choose server, database name and collation
I have no knowledge about the users at my customers sites so I don't add create users statements also the only user that needs access to the database is the user executing the middle tire application.
I do not disable FK checks. I need them to protect the consistency of the database, even if it is I who wrote the body scripts. I use FK to capture my errors.
I do not include the entire script in one transaction. I require from the users to take a backup of the db before they run any db upgrade scripts. For creating of a new database there is nothing to protect so running in a transaction is unnecessary. For upgrades there are sometimes extensive changes to the db. A couple of years ago we switched from varchar to nvarchar in about 250 tables. Not something you would like to do in one transaction.
I would recommend you to generate one script per database and version control the scripts separately.
Direct answers, please ask if you need to expand on any point
* Should I include the CREATE DATABASE statement?
Normally I would include it since you are creating and owning the database.
* Should I create users for the database in the same script?
This is also a good idea, especially if your application uses specific users.
* Is correct to disable FK check before executing the body of the script?
If the script includes data population, then it helps to disable it so that the order is not too important, otherwise you can get into complex scripts to insert (without fk link), create fk record, update fk column.
* May I include the hole script in a transaction?
This is normally not a good idea. Especially if data population is included as the transaction can become quite unwieldy large. Since you are creating the database, just drop it and start again if something goes awry.
* Is better to generate 1 script per database than one script for all of them?
One per database is my recommendation so that they are isolated and easier to troubleshoot if the need arises.
For development purposes it's a good idea to create one script per database object (one script for each table, stored procedure, etc). If you check them into your source control system that way then developers can check out individual objects and you can easily keep track of versions and know what changed and when.
When you deploy you may want to combine the changes for each release into one single script. Tools like Red Gate SQL compare or Visual Studio Team System will help you do that.
Should I include the CREATE DATABASE statement?
Should I create users for the database in the same script?
That depends on your DBMS and your customer.
In an Oracle environment you will probably never be allowed to do such a thing (mainly because in the Oracle world a "database" is something completely different than e.g. in the PostgreSQL or MySQL world).
Sometimes the customer will have a DBA that won't let you create databases (or schemas or users - depending on the DBMS in use). So you will need to supply that information to the DBA in order for him/her to prepare the environment for your script.
May I include the hole script in a transaction?
That totally depends on the DBMS that you are using.
Some DBMS don't support transactional DDL and will implicitely commit any transaction when you execute a DDL statement, so you need to consider the order of your installation script.
For populating the tables with data I would definitely try to do that in a single transaction, but again this depends on your DBMS.
Some DBMS are faster if you commit only once or very seldomly (Oracle and PostgreSQL fall into this category) but will slow down if you commit more often.
Other DBMS handle smaller but more transactions better and will slow down if the transactions get too big (SQL Server and MySQL tend to fall into that direction)
The best practices will differ considerably on whether it is the first time set-up or a new version being pushed. For the first time set-up yes you need create database and create table scripts. For a new version, you need to script only the changes from the previous version, so no create database and no create table unless it is a new table. Now you need alter table statements becasue you don't want to lose the existing data. I do usually write stored procs, functions and views with a drop and create statment as dropping those pbjects doesn't generally affect the underlying data.
I find it best to create all database changes with scripts that are stored in source control under the version. So if a client is new, you run the create version 1.0 scripts, then apply all the other versions in order. If a client is just upgrading from version 1.2 to version 1.3, then you run just the scripts in version 1.3 source control repository. This would also include scripts to populate or add records to lookup tables.
For transactions you may want to break them up into several chunks not to leave a prod database locked in one transaction.
We also write reversal scripts to return to the old version if need be. This makes life easier if you have a part of a change that causes unanticipated problems on prod (usually performance issues).
Related
I have never really seen any questions (with answers) as general as this, so I'm hoping to get some useful feedback. The reason I'm asking is because I've done all of this before and I have my own ways, but sometimes I feel it's not the best practice.
Let's take for example that I can't afford better db modeling tools and I only have sql server and ms sql server management studio. What I do is:
I design with mssms, all of the entities in my db (tables, primary keys, foreign keys, indexes, etc)
then I just generate the schema script using 'Generate Scripts...' command in mssms. The script that's generated is rather large (using sql server express 2012) and seems like it's not organized for maintenance very well.
Example: after all the table creation scripts are setup, there's a bunch of ALTER TABLE commands to add all the constraints. This kind of thing seems like it would be better in the table creation script section, maybe not. Also, for upgrade-ability, I normally add for each table creation section, 'IF NOT EXISTS', so that it doesn't throw an error when I need to re-run the sql script when the db is updated with new tables, columns, etc.
Then for versioning, I generally have a separate script that I run to add the schema version in a VERSION table in the db itself (with just one row).
This allows me to do incremental upgrades when I run the script by adding 'if new-version > current-version' sort of thing.
It seems to have worked out for me in the past, but it just seems kind of, I don't know, not very sophisticated. Can a sql expert shed some light on this subject? It's something we all do for every data driven web app we create, over and over again. I'd like to see how other developers do it.
To recap,
how do you go about designing your db model and generate scripts (do you do it with a design tool, write from scratch, etc?),
how to you manage incremental db changes over time?
How do you version control your database?
SQL Server Data Tools is ideal for this. It has all the design features you require and configurable scripting. It will also diff two databases and generate the change script for you. Oh - and it's free!
I have quite old application with current database (on MSSQL but it does not matter). I scripted it completely with all required static data. Now I want to introduce DB change only via update scripts. So each function, each SP will be placed in stand-alone file and all schema update scripts will be stored in files named like 'SomeProduct01_0001' what means that this script belongs to product SomeProduct, sprint 1 and it is first schema update script.
I know that each script must be absolutely re-runnable, but anyway I want to have functionality to combine these scripts into one based on DB version (stored in DB table).
What common best practices there is to handle bunches of update scripts?
What is better - implement version anylyzis in collector
(bat or exe file) or add some SQL header to each file? From other point of view I am already have version - it will consist of sprint identifier and script identifier, not sure that it is ok to duplicate this information in script header.
How to skip file content if user tries to apply it to newer database but keep
availability combine this script with any other to perform updates
of other old database?
How to avoid database conflicts if combined scripts operates columns/table which still does not exists in database but will be created byt this script (for example, in line 10 table created and in line 60 it is used in trigger or constraint, as I know script will not be validated)? Maybe wrap in EXEC('') entire script? What I need to escape besides sigle quote characters?
UPD: As David Tanzer asnwered it is better to use ready solutions for DB migrations, so it may be best solution for cases like mine. It was not and answer exactly for my question, but it is suitable for new solutions.
You don't have to implement this yourself, there are tools that do it. Take a look at dbmaintain, it provides almost exactly the functionality you described:
http://www.dbmaintain.org/overview.html
I know of and have worked with several teams who use it to manage their database schemas in all their environments: Development, Testing, Staging and Production.
http://flywaydb.org/ seems to be another tool to do this, and it has even more features. They even have a comparison of multiple tools on their homepage (including dbmaintain)
I have a structured database and software to handle it and I wanted to setup a demo version based off of a simple template version. I'm reading through some resources on temporary tables but I have questions.
What is the best way to go about cloning a "temporary" database while keeping a clean list of databases?
From what I've seen, there are two ways to do this - temporary local versions that are terminated at the end of the session, and tables that are stored in the database until deleted by the client or me.
I think I would prefer the 2nd option, because I would like to be able to see what they do with it. However, I do not want add a ton of throw-away databases and clutter my system.
How can I a) schedule these for deletion after say 30 days and b) if possible, keep these all under one umbrella, or in other words, is there a way to keep them out of my main list of databases and grouped by themselves.
I've thought about having one database and then serving up the information by using a unique ID for the user and 'faux indexes' so that it appears as 1,2,3 instead of 556,557,558 to solve B. I'm unsure how I could solve A, other than adding a date and protected columns and having a script that runs daily and deletes if over 30 days and not protected.
I apologize for the open-ended question, but the resources I've found are a bit ambiguous.
These aren't true temp tables in the sense that your DBMS knows them. What you're looking for is a way to have a demo copy of your database, probably with a cut-down data set. It's really no different from having any other non-production copy of your database.
Don't do this on your production database server.
Do not do this on your production database server.
Script the creation of your database schema. Depending on the DBMS you're using, this may be pretty easy. If you've got a good development/deployment/maintenance process for your system, this should already exist.
Create your database on the non-production server using the script(s) generated in the previous step. Use an easily-identifiable naming convention, like starting the database name with demo.
Load any data required into the tables.
Point the demo version of your app (that's running on your non-production servers) at this new database.
Create a script/process/job which looks at your database server and drops any databases that match your demo DB naming convention and were created more than 30 days ago.
Without details about your actual environment, people can't give concrete examples/sample code/instructions.
If you cannot run a second, independent database server for these demos, then you will have to make do with your production server. This is still a bad idea because of potential security exposures and performance impact on your production database (constrained resources).
Create a complete copy of your database (or at least the schema, with a reduced data set) for each demo.
Create a unique set of credentials for each of these demo databases. This account should have access to only its demo database.
Configure the demo instance(s) of your application to connect to the demo database
Here's why I'm pushing so hard for separate databases: If you keep copying your "demo" tables within the database, you will have to update your application code to point at those tables each time you do a new demo. Once you start doing this, you're taking a big risk with your demos - the code you keep changing isn't really the application you're running in production anymore. And if you miss one of those changes, you'll get unexpected results at best, and mangling of your production data at worst.
The Background
My group has 4 SQL Server Databases:
Production
UAT
Test
Dev
I work in the Dev environment. When the time comes to promote the objects I've been working on (tables, views, functions, stored procs) I make a request of my manager, who promotes to Test. After testing, she submits a request to an Admin who promotes to UAT. After successful user testing, the same Admin promotes to Production.
The Problem
The entire process is awkward for a few reasons.
Each person must manually track their changes. If I update, add, remove any objects I need to track them so that my promotion request contains everything I've done. In theory, if I miss something testing or UAT should catch it, but this isn't certain and it's a waste of the tester's time, anyway.
Lots of changes I make are iterative and done in a GUI, which means there's no record of what changes I made, only the end result (at least as far as I know).
We're in the fairly early stages of building out a data mart, so the majority of the changes made, at least count-wise, are minor things: changing the data type for a column, altering the names of tables as we crystallize what they'll be used for, tweaking functions and stored procs, etc.
The Question
People have been doing this kind of work for decades, so I imagine there have got to be a much better way to manage the process. What I would love is if I could run a diff between two databases to see how the structure was different, use that diff to generate a change script, use that change script as my promotion request. Is this possible? If not, are there any other ways to organize this process?
For the record, we're a 100% Microsoft shop, just now updating everything to SQL Server 2008, so any tools available in that package would be fair game.
I should clarify I'm not necessarily looking for diff tools. If that's the best way to sync our environments then it's fine, but if there's a better way I'm looking for that.
An example doing what I want really well are migrations in Ruby on Rails. Dead simple syntax, all changes are well documented automatically and by default, determining what migrations need to run is almost trivially easy. I'd love if there was something similar to this for SQL Server.
My ideal solution is 1) easy and 2) hard to mess up. Rails Migrations are both; everything I've done so far on SQL Server is neither.
Within our team, we handle database changes like this:
We (re-)generate a script which creates the complete database and check it into version control together with the other changes. We have 4 files: tables, user defined functions and views, stored procedures, and permissions. This is completely automated - only a double-click is needed to generate the script.
If a developer has to make changes to the database, she does so on her local db.
For every change, we create update scripts. Those are easy to create: The developer regenerates the db script of his local db. All the changes are now easy to identify thanks to version control. Most changes (new tables, new views etc) can simply be copied to the update script, other changes (adding columns for example) need to be created manually.
The update script is tested either on our common dev database, or by rolling back the local db to the last backup - which was created before starting to change the database. If it passes, it's time to commit the changes.
The update scripts follow a naming convention so everybody knows in which order to execute them.
This works fairly well for us, but still needs some coordination if several developers modify heavily the same tables and views. This doesn't happen often though.
The important points are:
database structure is only modified by scripts, except for the local developer's db. This is important.
SQL scripts are versioned by source control - the db can be created as it was at any point in the past
database backups are created regularly - at least before making changes to the db
changes to the db can be done quickly - because the scripts for those changes are created relatively easily.
However, if you have a lot of long lasting development branches for your projects, this may not work well.
It is by far not a perfect solution, and some special precautions are to be taken. For example, if there are updates which may fail depending on the data present in a database, the update should be tested on a copy of the production database.
In contrast to rails migrations, we do not create scripts to reverse the changes of an update. But this isn't always possible anyway, at least in respect to the data (the content of a dropped column is lost even if you recreate the column).
Version Control and your Database
The root of all things evil is making changes in the UI. SSMS is a DBA tool, not a developer one. Developers must use scripts to do any sort of changes to the database model/schema. Versioning your metadata and having upgrade script from every version N to version N+1 is the only way that is proven to work reliably. It is the solution SQL Server itself deploys to keep track of metadata changes (resource db changes).
Comparison tools like SQL Compare or vsdbcmd and .dbschema files from VS Database projects are just last resorts for shops that fail to do a proper versioned approach. They work in simple scenarios, but I see them all fail spectacularly in serious deployments. One just does not trust a tool to do a change to +5TB table if the tools tries to copy the data...
RedGate sells SQL Compare, an excellent tool to generate change scripts.
Visual Studio also has editions which support database compares. This was formerly called Database Edition.
Where I work, we abolished the Dev/Test/UAT/Prod separation long ago in favor of a very quick release cycle. If we put something broken in production, we will fix it quickly. Our customers are certainly happier, but in the risk avert corporate enterprise, it can be a hard sell.
There are several tools available for you. One is from Red-Gate called SQL Compare. Awesome and highly recommended. SQL Compare will let you do a diff in schemas between two databases and even build the sql change scripts for you.
Note they have been working on a SQL Server source control product for awhile now as well.
Another (if you're a visual studio shop) is the schema and data compare features that is part of Visual Studio (not sure which versions).
Agree that SQL Compare is an amazing tool.
However, we do not make any changes to the database structure or objects that are not scripted and saved in source control just like all other code. Then you know exactly what belongs in the version you are promoting because you have the scripts for that particular version.
It is a bad idea anyway to make structural changes through the GUI. If you havea lot of data, it is far slower than using alter table at least in SQL Server. You only want to use tested scripts to make changes to prod as well.
I agree with the comments made by marapet, where each change must be scripted.
The problem that you may be experiencing, however, is creating, testing and tracking these scripts.
Have a look at the patching engine used in DBSourceTools.
http://dbsourcetools.codeplex.com
It's been specifically designed to help developers get SQL server databases under source-code control.
This tool will allow you to baseline your database at a specific point, and create a named version (v1).
Then, create a deployment target - and increment the named version to v2.
Add patch scripts to the Patches directory for any changes to schema or data.
Finally, check the database and all patches into source-code control, to distribute with devs.
What this gives you is a repeatable process to test all patches to be applied from v1 to v2.
DBSourceTools also has functionality to help you create these scripts, i.e. schema compare or script data tools.
Once you are done, simply send all of the files in the patches directory to your DBA to upgrade from v1 to v2.
Have fun.
Another "Diff" tool for databases:
http://www.xsqlsoftware.com/Product/Sql_Data_Compare.aspx
Keep database version in a versioning table
Keep script file name that was successfully applied
Keep md5 sum of each sql script that has been applied. It should ignore spaces when calculate md5 sum. Must be effective.
Keep info about who applied a script Keep info about when a script was applied
Database should be verified on application start-up
New sql script should be applied automatically
If md5 sum of a script that was already applied is changed, error should be thrown (in a production mode)
When script have been released it must not be changed. It must be
immutable in a production environment.
Script should be written in a way, so it could be applied to different types of database (see liquibase)
Since most ddl statements are auto-committing on most databases, it is best to have a single ddl statement per SQL script.
DDL sql statement should be run in a way, so it can be executed several times without errors. Really helps in a dev mode, when you may edit script several times. For instance, create a new table, only if it does not exist, or even drop table before creating a new one. It will help you in a dev mode, with a script that has not been released, change it, clear md5 sum for this script, rerun it again.
Each sql script should be run in its own transaction.
Triggers/procedures should be dropped and created after each db
update.
Sql script is kept in a versioning system like svn
Name of a script contains date when it was committed, existing (jira) issue id, small description
Avoid adding rollback functionality in scripts (liquibase allow to do that). It makes them more complicated to write and support. If you use exactly one ddl statement per script, and dml statements are run within a
transaction, even failing a script will not be a big trouble to
resolve it
This is the workflow we have been using succesfully:
Development instance: SQL objects are created/updated/deleted in DB using MSSQL Studio and all operations are saved to scritps we include in each version of our code.
Moving to production: We compare schema between dev and prod db using SQL Schema Compare in Microsoft Visual Studio. We update prod using the same tool.
here's a more general question on how you handle database schema changes in a development team.
We are a team of developers and the databases used during development are running locally on everyone's box as we want to avoid the requirement to have web access all the time. So running a single central database instance somewhere is not a real option.
Whenever one of us decides that it is time to extend/change the db schema, we mail database files (MYI/MYD) or SQL files to execute around, or give others instructions on the phone what they need to do to get the changed code running on their local DBs. That's not the perfect approach for sure. The same problem arises when we need to adjust the DB schema on staging or production once a new release is ready.
I was wondering ... how do you guys handle this kind of stuff? For source code, we use SVN.
Really appreciate your input!
Thanks,
Michael
One approach we've used in the past is to script the entire DDL for the database, along with any test/setup data needed. Store that in SVN, then when there's a change, any developer can pull down the changes, drop the database, and rebuild it from the script files.
At the very least you should have the scripts of all the objects in the database (tables, stored procedures, etc) under source control.
I don't think mailing schema changes is a real option for a professional development team.
We had a system on one of my previous teams that was the best I've encountered for dealing with this situation.
The nightly build of the application included a build of a database (SQL Server). The database got built to the Test DB server. Each developer then had a DTS package (this was a while ago, and I'm sure they upgraded to SSIS packages) to pull down that nightly DB build to their local DB environment.
This kept the master copy in one location and put the onus on the developers to keep their local dev databases fresh.
At my work, we deal with pretty large databases that are time-consuming to generate, so for us, starting from scratch with a new DB isn't ideal. Like Harper, we have our DDL in SVN. Additionally, we store a version number in a database table. Every check-in that changes the DB must be accompanied by a script that:
Will upgrade the database schema and modify any existing data appropriately, and
Will update the version number in the database.
Further, we number the scripts and database versions such that a script we've written knows how to upgrade further along a branch or from an older branch to a newer one without any input from the developer (apart from the database name and the directory to the upgrade scripts).
Thus, if I've got a copy of a customer's 4GB DB that's from a year old version and I want to test how their data will work with the version we cut yesterday, I can just run our script and let it handle the upgrades rather than having to start from scratch and redo every INSERT, UPDATE and DELETE performed since the database was created.
We have a non-SQL description of the database schema. When the application starts, it compares the desired database schema with the actual database schema, and performs whatever ADD TABLE, ADD COLUMN, ADD INDEX, etc. statements it needs to do to get the database to look right.
This doesn't handle every case; sometimes you have to delete the database and recreate if if you've changed something that the schema resolver can't handle, but most of the time we don't need to worry about it.
I'd certainly keep the database schema in source code control.
At my present job, every time there's a schema change, we write the SQL for the change (alter table xyz add column ...) and put it in SVN. Then developers can update test databases by running this script. It's pretty clumsy but it works.
At a previous job I wrote some code that at application start-up would automatically compare the actual database schema to what it expected, and if it was not up to date perform the updates. Mostly this was done for deployment reasons: When we shipped new copies of the software, it would then automatically update the user's database. But it was also handy for developers.
I think there should be some generic SQL tool to do this. Maybe there is, but I've never seen one.