SONAR - database quality - sql

I have recently implemented Continuous Integration for SQL Server using SSDT, Jenkins and Perforce.
This has proven to be a revelation to our firm, and our turn around time for database changes is now extremely fast. The DBA Team are on board with this new methodology, as their number of support issues have dramatically dropped.
I have implemented a database build server, that is an empty shell, each time a database change is checked into to perforce the whole database is deployed to this shell. Thus any breaking dependencies are picked up.
We use SONAR to report the quality of code for C# and Java. I would like to extend this not only to T-SQL but also generically to database platforms that have a supported JDBC driver.
To make the database review generic, and also allow the DBA Team to write the rules, I would like to write a plugin that will run SQL scripts (each a rule) against a database, and then report the results.
The idea is that a DBA Team could write a suite of scripts (rules) that will give them confidence in the data model. Examples include
list all tables that do not have a primary key
list all tables that do not have a unique index
list all tables that are not referenced by a foreign key constraint
list all roles that are not used
Ideas would be appreciated.
Dave.

Related

What is the best way to design, generate, and version a database schema script for MS SQL Server?

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!

How to manage/ track changes to SQL Server database without compare tool

I'm working on a project as an outsourcing developer where i don't have access to testing and production servers only the development environment.
To deploy changes i have to create sql scripts containing the changes to make on each server for the feature i wish to deploy.
Examples:
When i make each change on the database, i save the script to a folder, but sometimes this is not enought because i sent a script to alter a view, but forgot to include new tables that i created in another feature.
Another situation would be changing a table via SSMS GUI and forgot to create a script with the changed or new columns and later have to send a script to update the table in testing.
Since some features can be sent for testing and others straight to production (example: queries to feed excel files) its hard to keep track of what i have to send to each environment.
Since the deployment team just executes the scripts i sent them to update the database, how can i manage/ keep track of changes to sql server database without a compare tool ?
[Edit]
The current tools that i use are SSMS, VS 2008 Professional and TFS 2008.
I can tell you how we at xSQL Software do this using our tools:
deployment team has an automated process that takes a schema snapshot of the staging and production databases and dumps the snapshots nightly on a share that the development team has access to.
every morning the developers have up to date schema snapshots of the production and staging databases available. They use our Schema Compare tool to compare the dev database with the staging/production snapshot and generate the change scripts.
Note: to take the schema snapshot you can either use the Schema Compare tool or our Schema Compare SDK.
I'd say you can have a structural copy of test and production servers as additional development databases and keep in mind to always apply change when you send something.
On these databases you can establish triggers that will capture all DDL events and put them into table with getdate() attached. With that you should be able to handle changes pretty easily and some simple compare will also be easier to apply.
Look into Liquibase specially at the SQL format and see if that gives you what you want. I use it for our database and it's great.
You can store all your objects in separate scripts, but when you do a Liquibase "build" it will generate one SQL script with all your changes in it. The really important part is getting your Liquibase configuration to put the objects in the correct dependency order. That is tables get created before foreign key constraints for one example.
http://www.liquibase.org/

SQL Server database change workflow best practices

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.

What strategies are available for migrating Access databases to SQL server-based applications?

I'm considering undertaking a project to migrate a very large MS Access application to a new system based on SQL Server. The existing system is essentially an ERP application with a couple of dozen users, all sharing the Access database over the network. The database has around 300 tables and lots of messy VBA code. This system is beginning to break down (actually, it's amazing it has worked as long as it has).
Due to the size and complexity of the Access application, a 'big bang' approach is not really feasible. It seems sensible to rope off chunks of functionality and migrate them piecemeal to the new system. During the migration process, which I expect to take several months, there may be a need for both databases to be in operation and be able to query and modify data in both systems.
I have considered using something like the ADO.NET Entity Framework to implement a data abstraction layer to handle this, but as far as I can tell, the Entity Framework has no Access provider.
Does my approach seem reasonable? What other strategies have people used to accomplish similar goals?
You may find that the main problem is using the MS Access JET engine as the backend. I'm assuming that you do have an Access FE (frontend) with all objects except tables, and a BE (backend - tables only).
You may find that migrating the data to SQL Server, and linking the Access FE to that, would help alleviate problems immediately.
Then, if you don't want to continue to use MS Access as the FE, you could consider breaking it up into 'modules', and redesign modules one by one using a separate development platform.
We faced a similar situation a few years ago, but we knew from the beginning that we'll have to swich one day to SQL SERVER, so the whole code was written to work from an Access client to both Access AND SQL server databases.
The idea of having a 'one-step' migration to SQL server is certainly the easier way to manage this on the database side, and there are many tools for that. But, depending on the way your client app talks to the database, your code might then not work properly. If, for example, your code includes a lot of SQL instructions (or generates them on the fly by, for example, adding filters to SELECT instructions), your syntax might not be 'SQL server' compatible: access wildcards, dates, functions, will not work on SQL server.
In addition to this, and as said by #mjv, the other drawback of a one time switch to MS SQL is that you will inheritate many of the problems from the original database: wrong or inapropriate field names, inapropriate primary/foreign key policies, hidden one-to-many relations that you'd like to implement in the new database model, etc.
I'll propose here some principles and rules to implement a 'soft transition' solution, which clearly best fits you. Just to say that it's not going to be easy, but it's definitely very interesting, paticularly when dealing with 300 tables! Lucky you!
I assume here that yo have the ability to update the client code, and you'd prefer to keep at all times the same client interface. It is of course possible to have at transition time two different interfaces, one for each database, but this will be very confusing for the users, and a permanent source of frustration for them.
According to me, the best solution strongly depend on:
The original connection technology,
and the way data is managed in your
client's code: Access linked tables,
ODBC, ADODB, recordset, local
tables, forms recordsources, batch
updating, etc.
The possibilities to split your
tables and your app in 'mostly
independant' modules.
And you will not spare the following mandatory activities:
setup up of a transfer
procedure from Access database to SQL server. You
can use already existing tools (The
access upsizing wizard is very poor,
so do not hesitate to buy a real
one, like SSW or EMS SQL Manager,
very powerfull) or build your own
one with Visual Basic. If your plan
is to make some changes in Data
Definition, you'll definitely have
to write some code. Keep in mind
that you will run this code
maaaaaany times, so make sure that
it includes all time-saving
instructions that will allow you to
restart the process from the start
as many times as you want. You will
have to choose between 2 basic data
import strategies when importing data:
a - DELETE existing record, then INSERT imported record
b - UPDATE existing record from imported record
If you plan to switch to new Primary\foreign key types, you'll have to keep track of old identifiers in your new database model during the transition period. Do not hesitate to switch to GUID Primary Keys at this stage, especially if the plan is to replicate data on multiple sites one of these days.
This transfer procedure will be divided in modules corresponding to the 'logical' modules defined previously, and you should be able to run any of these modules independantly (keeping of course in mind that they'll probably have to be implemented in a specific order, where the 'customers' module has to run before the 'invoicing' module).
implement in your client's code the possibility to connect to both original ms-access database and new MS SQL server. Ideally, you should be able to manage from within your code both connections for displaying and validating data.
This possibility will be implemented by modules, where you will have, for each of them, a 'trial period', ie the possibility to choose at testing time between access connection and sql connection when using the module. Once testing is done and complete, the module can then be run in exclusive SQL server mode.
During the transfer period, that can last a few months, you will have to manage programatically the database constraints that exist between 'SQL server' modules and 'Access' modules. Going back to our customers/invoicing example, the customers module will be first switched to MS SQL. Before the Invoicing module can be switched, you'll have to implement programmatically the one to many relations between Customers and Invoices, where each of the tables will be in a different database. Such a constraint can be implemented on the Invoice form by populating the Customers combobox with the Customers recordset from the SQL server.
My proposal is to build your modules following your database model, allways beginning with the 'one' tables or your 'one-to-many' relations: basic lists like 'Units', 'Currencies', 'Countries', shall be switched first. You'll have a first 'hands on' experience in writting data transfer code, and managing a second connection in your client interface. You'll be then able to 'go up' in your database model, switching the 'products' and 'customers' tables (where units, countries and currencies are foreign keys) to the new server.
Good luck!
I would second the suggestion to upsize the back end to SQL Server as step 1.
I would never go to the suggested Step 2, though (i.e., replacing the Access front end with something else). I would instead suggest investing the effort in fixing the flaws of the schema, and adjusting the Access app to work with the new schema.
Obviously, it is never the case that everything just works hunky dory when you upsize -- some things that were previously quite fast will be dogs, and some things that were previously quite slow will be fast. And I've found that it is often the case that the problems are very often not where you anticipate that they will be. You can only figure out what needs to be fixed by testing.
Basically, anything that works poorly gets re-architected, or moved entirely server-side.
Leverage the investment in the existing Access app rather than tossing all that out and starting from scratch. Access is a fine front end for a SQL Server back end as long as you don't assume it's going to work just the same way as it would with a Jet/ACE back end.
...thinking out loud... I think this may work.
I appears that the complexity of the application resides in the various VBA modules rather than the database table/schema themselves. A possible migration path could therefore be to first migrate the data storage to SQL server, exactly as-is, as follow:
prevent any change to the data for a few hours
duplicate all tables to the SQL server; be sure to create the same indexes as well.
create linked tables to ODBC Source pointing to the newly created tables on SQL Server
these tables should have the very same name as the original tables (which therefore may require being renamed, say with a leading underscore, for possible reference).
Now, the application can be restarted and should be using the SQL tables rather than the Access tables. All logic should work as previously (right...), possible slowness to be expected, depending on the distance between the two machines.
All the above could be tested in about a day's work or so; the most tedious being the creation of the tables on SQL server (much of that can be automated, I'm sure). The next most tedious task is to assert that the application effectively works as previously, but with its storage on SQL.
EDIT: As suggested by a comment, I should stress that there is a [fair ?] possibility that the application would not readily work so smoothly under SQL server back-end, and could require weeks of hard work in testing and fixing. However, and unless some of these difficulties can be anticipated because of insight into the application not expressed in the question, I propose that attempting the "As-is" migration to SQL Server should be considered; after all, it may just work with minimal effort, and if it doesn't, we'd know this very quickly. This is therefore a hi-return, low risk proposal...
The main advantage sought with this approach is that there will be a single storage during the [as the OP expects] longer period during which the old Access application will co-exist with the new application.
The drawback of this approach, is that, at least at first, the schema of original database is reproduced verbatim, i.e. including some of its known quirks and legacy-herited idiosyncrasies. These schema issues (and the underlying application logic) can be in time corrected, but this is of course less easy than if the new application starts ab initio, with its own, separate, storage, and distinct schema.
After the storage is moved to SQL server, the most used and/or the most independent modules of the Access application can be re-written in the new application, and as significant portions of the original application is ported, effective usage, by select beta testers or by actual users can start to be switched to the new application.
Possibly, some kind of screen-scraping based logic or some other system could be used to produce an hybrid application which would provide the end users with a comprehensive application, which sometimes work from new logic, and sometimes from the original MS-Access program.

How can I maintain consistent DB schema accross 18 databases (sql server)?

We have 18 databases that should have identical schemas, but don't. In certain scenarios, a table was added to one, but not the rest. Or, certain stored procedures were required in a handful of databases, but not the others. Or, our DBA forgot to run a script to add views on all of the databases.
What is the best way to keep database schemas in sync?
For legacy fixes/cleanup, there are tools, like SQLCompare, that can generate scripts to sync databases.
For .NET shops running SQL Server, there is also the Visual Studio Database Edition, which can create change scripts for schema changes that can be checked into source control, and automatically built using your CI/build process.
SQL Compare by Red Gate is a great tool for this.
SQLCompare is the best tool that I have used for finding differences between databases and getting them synced.
To keep the databases synced up, you need to have several things in place:
1) You need policies about who can make changes to production. Generally this should only be the DBA (DBA team for larger orgs) and 1 or 2 backaps. The backups should only make changes when the DBA is out, or in an emergency. The backups should NOT be deploying on a regular basis. Set Database rights according to this policy.
2) A process and tools to manage deployment requests. Ideally you will have a development environment, a test environment, and a production environment. Developers should do initial development in the dev environment, and have changes pushed to test and production as appropriate. You will need some way of letting the DBA know when to push changes. I would NOT recommend a process where you holler to the next cube. Large orgs may have a change control committee and changes only get made once a month. Smaller companies may just have the developer request testing, and after testing is passed a request for deployment to production. One smaller company I worked for used Problem Tracker for these requests.
Use whatever works in your situation and budget, just have a process, and have tools that work for that process.
3) You said that sometimes objects only need to go to a handful of databases. With only 18 databases, probably on one server, I would recommend making each Databse match objects exactly. Only 5 DBs need usp_DoSomething? So what? Put it in every databse. This will be much easier to manage. We did it this way on a 6 server system with around 250-300 DBs. There were exceptions, but they were grouped. Databases on server C got this extra set of objects. Databases on Server L got this other set.
4) You said that sometimes the DBA forgets to deploy change scripts to all the DBs. This tells me that s/he needs tools for deploying changes. S/He is probably taking a SQL script, opening it in in Query Analyzer or Manegement Studio (or whatever you use) and manually going to each database and executing the SQL. This is not a good long term (or short term) solution. Red Gate (makers of SQLCompare above) have many great tools. MultiScript looks like it may work for deployment purposes. I worked with a DBA that wrote is own tool in SQL Server 2000 using O-SQl. It would take an SQL file and execute it on each database on the server. He had to execute it on each server, but it beat executing on each DB. I also helped write a VB.net tool that would do the same thing, except it would also go through a list of server, so it only had to be executed once.
5) Source Control. My current team doesn't use source control, and I don't have enough time to tell you how many problems this causes. If you don't have some kind of source control system, get one.
I haven't got enough reputation to comment on the above answer but the pro version of SQL Compare has a scriptable API. Given that you have to replicate stuff to all of these databases you could use this to make an automated job to either generate the change scripts or to validate that the databases are all in sync. It's also not much more expensive than the standard version.
Aside from using database comparison tools, with 18 databases you should have a DBA, so enforce a policy that only the DBA can change tables at the database level by restricting access to CREATE and ALTER to the DBA only. On both your test and live databases. The dev database shouldn't have this, of course! Make the developers who have been creating or altering the schemas willy-nilly go via the DBA.
Create a single source-controlled DDL/SQL script for each release and only use it to update the databases. The diff tools can be useful but mainly for checking that you haven't made a mistake and getting out of trouble when the policies fail. Combine the DDL, SQL, and stored procedure scripts into a single script so that it's not easy to "forget" to run one of the scripts.
We have got a tool called DB Schema Difftective that can compare and sync database schemas. With our other tool, DB MultiRun you can easily deploy generated (sync) scripts to multiple db servers (project based).
I realize this post is old, but TurnKey is correct. If you are a developer working in a team environment, the best way to maintain a database schema for a large application, is to make updates to a Master Schema in what ever source safe you use. Simply write your own Scripting class and your Database will be perfect every time.