Since we can point and click in SSMS to obtain DDL, there must be an assembly or DLL of some sort called by the GUI. Does anyone have any familiarity with how to tap into that?
The drive for this comes from our need to capture DDL as part of jobs. Some of our batches only need the data for one table or even one index, others could use the entire database. Getting the detail as needed is critical. That detail might be used as part of a procedure or placed into a file.
I know there are various solutions to the problem of batch/automated retrieval of SQL Server DDL (versions 2000-2014) on the web. None are directly supported by Microsoft, and for what I need, that is a considerable weakness.
Of the items on the web, some use scripts and the system views/tables to build DDL. I admire the work that went into these, but such things may have problematic support and can break from SQL Server version to SQL Server version. Also, a number of vendors have tools, and there is at least one open source project (OpenDiff) that ventures into this area. But vendor tools won't easily fit into my batch streams. And third party tools also require installation on client systems, which is always a sensitive area, and usually have licensing requirements. Any third party tool, of course, introduces the various types of vendor dependencies.
There is one item I have found, SMOScript, that uses SMOs (with which I am only slightly familiar). Perhaps that is doing something similar to what I want, though the limited notes on the project imply that it does not allow the detail needed such as for a single index. From a management viewpoint, it also introduces a dependency on that project and its single author.
That assembly used by SSMS, whatever it is, must be kept up to date by MS. If calling that is possible (though I am sure it is foolish to hope it is also simple), the weakness of a third party dependency is eliminated. So I don't need web links to scripts and third party tools for those I have (yet thanks for the thought), but if someone can point me toward what SSMS is using, that might be a great help. In the meantime, for what its worth, I'll be researching SMOs.
This may be more opinionated than I like, but please forgive me. I'm searching for a definitive answer.
I am using GIT, JIRA (Issue Management), Bitbucket (online GIT projects) and SourceTree (GIT GUI client) for a project that involves multiple cross-code and cross-platform segments.
My issue is specifically with how to handle database source control in relation to the applications that utilize said database and it's objects?
For example, let's say you have a web based tool that was developed to pull data from said database using stored procedures. Would the database stored procedures be stored in the same repository as the web application?
In another example, let's say the same web application just used basic SQL queries. But, the systems that prepared the data such as a complex ETL system, helped make it happen. Would the ETL system source code be in the repository too?
(Note: I am not referring to database changes to the data types, indexes or schema. I'm referring to SQL scripts, stored procedures, SSIS packages, SSRS source and even possibly OLAP cube frameworks that are stored in the service. But of course, are not members of a DRC or CSM system for control outside of developer control.)
I hope this isn't too broad. There is just very little documentation out there in handling relational database objects in relation to a application or related systems. Databases by themselves do not seem to be that popular for DRC and CSM systems even though they are a critical part of the puzzle.
Unfortunately, there is no definite answer to this question. Where to store part of your system (or where to draw the line between systems) is hight context dependent.
Some considerations that might help you to decide are:
Who is developing the code?
If everything is created and maintained by the same team then it might be best to store everything together
At what rate is the code changing?
If the code to show the data is changing rapidly, while the code to create the data is only changing sometimes it might be best to separate the two code-bases
How is the code deployed/run?
If the deployment and running of various parts of a system is vastly different then it could make sense to store and handle them in a different way.
To link this to your examples, in the first situation I would probably suggest to keep everything together based on considerations 1 and 3. For the second example, all considerations together would suggest moving the ETL system to a separate repository.
Does anyone know how to confirm if a branch was merged via SQL query? In the long run, I want to create an on demand SSRS report so this can be reviewed after a series of releases have been deployed. I know that there are specific Command bit values taken from tbl_Version (I did this to identify a renamed branch) but I haven't been able to identify the bit values that identify a branch if it was merged.
Any ideas?
These tables are not supported for reporting. Any solution you build should use the TFS Object Model to load the data into the warehouse. Or use the client object model directly to retrieve the data.
What you're trying to do is really hard since the data isn't stored in the warehouse. You can query merge data by calling the VersionControlServer.QueryMerges method or by going through each Changeset individually after calling VersionControlServer.QueryHistory.
Building a DatawarehouseAdapter is harder still, since there is little documentation available and since you should have a deep knowledge of both the TFS Object Model, the Warehouse structure and Analysis Server in general. There is a ranger project underway to provide additional guidance on this subject, but until that's done you will find mostly just a scattered few blogposts and a very bad example.
You might be able to find good pointers towards building something outside of the scope of Reporting Server in open source projects, such as the TfsChangeLog project or the Community TFS Build Manager.
We're an ISV that's completed our first app on force.com. It's an xRM-like app with extended workflow to build out complex campaigns (not simple marketing-like campaigns) and integration with on-premise software. The platform brings enormous value, and at the same time some challenges. Interested in other ISV experiences around the following:
Application upgrade process. Customers expect cloud app upgrade to "just happen". Reality is that there's inevitable manual pre- and post-upgrade steps that can fill many pages. We don't want to burden the customer with this, and at the same time while we're happy to do the upgrade work for the customer, we don't want access to customer data and the need for elaborate security assurances that come along with that access. A conundrum.
Development environment. Agile/scrum development relies on achieving full test automation and continuous integration, yet full automation beyond unit test seems difficult or impossible.
Background processing. Constraints on scheduled jobs, callouts, and futures, and issues with transaction management present challenges to traditional software development.
Curious what other ISVs have found.
Thanks!
I am now working at my second Force.com ISV and so have a fair amount of experience in releasing products on the platform (have seen 4 separate products releases, 1 which included 3 version releases and 1 including another version update).
If possible, you should try to remove any pre/post install steps that the user requires to do. It sounds tough, and it is, but its the biggest reason people don't adopt a product. The idea is that it is quick and easy to install, one click, and any extra effort detracts from the user experience. Ensuring your system is data independent is a good way of getting around the data security issues you referred to, and obviously you can offer a consultancy to do the upgrade work. A sensible idea might be to have a list of all the objects and fields that are affected by your products installation and then to do a check of the customer org before installing. I would also say that installing in sandbox and doing a couple of weeks user testing can highlight any problems you may have in future very effectively.
It is not true that full test automation beyond unit tests cannot occur and is actually very simple. The key is having the necessary framework setup. So you would have a central version control system where your code is stored (a key agile part). Then you create a script so that when code is committed, it runs an install on a SFDC org, running all tests and reporting back. You can then get this script to run a set of apex classes or upload a bunch of CSV files to put data in with either further fuller apex tests to run functionality or selenium running to do a set of tests. You can then also use this test data and script for knocking out demo environments for sales guys.
The governor and background processing limits are a bit tight, but they keep on being increased. Maybe you should integrate with Heroku or similar to do some larger external processing? I will say though I think it improves programming abilities in general, making you think about what it is your doing and the best way to do it. This then leads to a more pleasant end user experience. Batch apex jobs area a good way of doing this processing and you can use the asyncapexjob object to report back on the status f a run to users.
Hope that helps and gives you a different perspective!
Paul
There has been some discussion on the SO community wiki about whether database objects should be version controlled. However, I haven't seen much discussion about the best-practices for creating a build-automation process for database objects.
This has been a contentious point of discussion for my team - particularly since developers and DBAs often have different goals, approaches, and concerns when evaluating the benefits and risks of an automation approach to database deployment.
I would like to hear some ideas from the SO community about what practices have been effective in the real world.
I realize that it is somewhat subjective which practices are really best, but I think a good dialog about what work could be helpful to many folks.
Here are some of my teaser questions about areas of concern in this topic. These are not meant to be a definitive list - rather a starting point for people to help understand what I'm looking for.
Should both test and production environments be built from source control?
Should both be built using automation - or should production by built by copying objects from a stable, finalized test environment?
How do you deal with potential differences between test and production environments in deployment scripts?
How do you test that the deployment scripts will work as effectively against production as they do in test?
What types of objects should be version controlled?
Just code (procedures, packages, triggers, java, etc)?
Indexes?
Constraints?
Table Definitions?
Table Change Scripts? (eg. ALTER scripts)
Everything?
Which types of objects shouldn't be version controlled?
Sequences?
Grants?
User Accounts?
How should database objects be organized in your SCM repository?
How do you deal with one-time things like conversion scripts or ALTER scripts?
How do you deal with retiring objects from the database?
Who should be responsible for promoting objects from development to test level?
How do you coordinate changes from multiple developers?
How do you deal with branching for database objects used by multiple systems?
What exceptions, if any, can be reasonable made to this process?
Security issues?
Data with de-identification concerns?
Scripts that can't be fully automated?
How can you make the process resilient and enforceable?
To developer error?
To unexpected environmental issues?
For disaster recovery?
How do you convince decision makers that the benefits of DB-SCM truly justify the cost?
Anecdotal evidence?
Industry research?
Industry best-practice recommendations?
Appeals to recognized authorities?
Cost/Benefit analysis?
Who should "own" database objects in this model?
Developers?
DBAs?
Data Analysts?
More than one?
Here are some some answers to your questions:
Should both test and production environments be built from source control? YES
Should both be built using automation - or should production by built by copying objects from a stable, finalized test environment?
Automation for both. Do NOT copy data between the environments
How do you deal with potential differences between test and production environments in deployment scripts?
Use templates, so that actually you would produce different set of scripts for each environment (ex. references to external systems, linked databases, etc)
How do you test that the deployment scripts will work as effectively against production as they do in test?
You test them on pre-production environment: test deployment on exact copy of production environment (database and potentially other systems)
What types of objects should be version controlled?
Just code (procedures, packages, triggers, java, etc)?
Indexes?
Constraints?
Table Definitions?
Table Change Scripts? (eg. ALTER scripts)
Everything?
Everything, and:
Do not forget static data (lookup lists etc), so you do not need to copy ANY data between environments
Keep only current version of the database scripts (version controlled, of course), and
Store ALTER scripts: 1 BIG script (or directory of scripts named liked 001_AlterXXX.sql, so that running them in natural sort order will upgrade from version A to B)
Which types of objects shouldn't be version controlled?
Sequences?
Grants?
User Accounts?
see 2. If your users/roles (or technical user names) are different between environments, you can still script them using templates (see 1.)
How should database objects be organized in your SCM repository?
How do you deal with one-time things like conversion scripts or ALTER scripts?
see 2.
How do you deal with retiring objects from the database?
deleted from DB, removed from source control trunk/tip
Who should be responsible for promoting objects from development to test level?
dev/test/release schedule
How do you coordinate changes from multiple developers?
try NOT to create a separate database for each developer. you use source-control, right? in this case developers change the database and check-in the scripts. to be completely safe, re-create the database from the scripts during nightly build
How do you deal with branching for database objects used by multiple systems?
tough one: try to avoid at all costs.
What exceptions, if any, can be reasonable made to this process?
Security issues?
do not store passwords for test/prod. you may allow it for dev, especially if you have automated daily/nightly DB rebuilds
Data with de-identification concerns?
Scripts that can't be fully automated?
document and store with the release info/ALTER script
How can you make the process resilient and enforceable?
To developer error?
tested with daily build from scratch, and compare the results to the incremental upgrade (from version A to B using ALTER). compare both resulting schema and static data
To unexpected environmental issues?
use version control and backups
compare the PROD database schema to what you think it is, especially before deployment. SuperDuperCool DBA may have fixed a bug that was never in your ticket system :)
For disaster recovery?
How do you convince decision makers that the benefits of DB-SCM truly justify the cost?
Anecdotal evidence?
Industry research?
Industry best-practice recommendations?
Appeals to recognized authorities?
Cost/Benefit analysis?
if developers and DBAs agree, you do not need to convince anyone, I think (Unless you need money to buy a software like a dbGhost for MSSQL)
Who should "own" database objects in this model?
Developers?
DBAs?
Data Analysts?
More than one?
Usually DBAs approve the model (before check-in or after as part of code review). They definitely own performance related objects. But in general the team own it [and employer, of course :)]
I treat the SQL as source-code when possible
If I can write it in standard's compliant SQL then it generally goes in a file in my source control. The file will define as much as possible such as SPs, Table CREATE statements.
I also include dummy data for testing in source control:
proj/sql/setup_db.sql
proj/sql/dummy_data.sql
proj/sql/mssql_specific.sql
proj/sql/mysql_specific.sql
And then I abstract out all my SQL queries so that I can build the entire project for MySQL, Oracle, MSSQL or anything else.
Build and test automation uses these build-scripts as they are as important as the app source and tests everything from integrity through triggers, procedures and logging.
We use continuous integration via TeamCity. At each checkin to source control, the database and all the test data is re-built from scratch, then the code, then the unit tests are run against the code. If you're using a code-generation tool like CodeSmith, it can also be placed into your build process to generate your data access layer fresh with each build, making sure that all your layers "match up" and do not produce errors due to mismatched SP parameters or missing columns.
Each build has its own collection of SQL scripts that are stored in the $project\SQL\ directory in source control, assigned a numerical prefix and executed in order. That way, we're practicing our deployment procedure at every build.
Depending on the lookup table, most of our lookup values are also stored in scripts and run to make sure the configuration data is what we expect for, say, "reason_codes" or "country_codes". This way we can make a lookup data change in dev, test it out and then "promote" it through QA and production, instead of using a tool to modify lookup values in production, which can be dangerous for uptime.
We also create a set of "rollback" scripts that undo our database changes, in case a build to production goes screwy. You can test the rollback scripts by running them, then re-running the unit tests for the build one version below yours, after its deployment scripts run.
+1 for Liquibase:
LiquiBase is an open source (LGPL), database-independent library for tracking, managing and applying database changes. It is built on a simple premise: All database changes (structure and data) are stored in an XML-based descriptive manner and checked into source control.
The good point, that DML changes are stored semantically, not just diff, so that you could track the purpose of the changes.
It could be combined with GIT version control for better interaction. I'm going to configure our dev-prod enviroment to try it out.
Also you could use Maven, Ant build systems for building production code from scripts.
Tha minus is that LiquiBase doesnt integrate into widespread SQL IDE's and you should do basic operations yourself.
In adddition to this you could use DBUnit for DB testing - this tool allows data generation scripts to be used for testing your production env with cleanup aftewards.
IMHO:
Store DML in files so that you could
version them.
Automate schema build process from
source control.
For testing purposes developer could
use local DB builded from
source control via build system +
load testing Data with scripts, or
DBUnit scripts (from Source
Control).
LiquiBase allows you to provide "run
sequence" of scripts to respect
dependences.
There should be DBA team that checks master
brunch with ALL changes
before production use. I mean they
check trunk/branch from other DBA's
before committing into MASTER trunk.
So that master is always consistent
and production ready.
We faced all mentioned problems with code changes, merging, rewriting in our billing production database. This topic is great for discovering all that stuff.
By asking "teaser questions" you seem to be more interested in a discussion than someone's opinion of final answers. The active (>2500 members) mailing list agileDatabases has addressed many of these questions and is, in my experience, a sophisticated and civil forum for this kind of discussion.
I basically agree with every answer given by van. Fore more insight, my baseline for database management is K. Scott Allen series (a must read, IMHO. And Jeff's opinion too it seems).
Database objects can always be rebuilt from scratch by launching a single SQL file (that can itself call other SQL files) : Create.sql. This can include static data insertion (lists...).
The SQL scripts are parameterized so that no environment-dependent and/or sensitive information is stored in plain files.
I use a custom batch file to launch Create.sql : Create.cmd. Its goal is mainly to check for pre-requisites (tools, environment variables...) and send parameters to the SQL script. It can also bulk-load static data from CSV files for performance issues.
Typically, system user credentials would be passed as a parameter to the Create.cmd file.
IMHO, dynamic data loading should require another step, depending on your environment. Developers will want to load their database with test, junk or no data at all, while at the other end production managers will want to load production data. I would consider storing test data in source control as well (to ease unit testing, for instance).
Once the first version of the database has been put into production, you will need not only build scripts (mainly for developers), but also upgrade scripts (based on the same principles) :
There must be a way to retrieve the version from the database (I use a stored procedure, but a table would do as well).
Before releasing a new version, I create an Upgrade.sql file (that can call other ones) that allows upgrading version N-1 to version N (N being the version being released). I store this script under a folder named N-1.
I have a batch file that does the upgrade : Upgrade.cmd. It can retrieve the current version (CV) of the database via a simple SELECT statement, launch the Upgrade.sql script stored under the CV folder, and loop until no folder is found. This way, you can automatically upgrade from, say, N-3 to N.
Problems with this are :
It is difficult to automatically compare database schemas, depending on database vendors. This can lead to incomplete upgrade scripts.
Every change to the production environment (usually by DBAs for performance tuning) should find its way to the source control as well. To make sure of this, it is usually possible to log every modification to the database via a trigger. This log is reset after every upgrade.
More ideally, though, DBA initiated changes should be part of the release/upgrade process when possible.
As to what kind of database objects do you want to have under source control ? Well, I would say as much as possible, but not more ;-) If you want to create users with passwords, get them a default password (login/login, practical for unit testing purposes), and make the password change a manual operation. This happens a lot with Oracle where schemas are also users...
We have our Silverlight project with MSSQL database in Git version control. The easiest way is to make sure you've got a slimmed down database (content wise), and do a complete dump from f.e. Visual Studio. Then you can do 'sqlcmd' from your build script to recreate the database on each dev machine.
For deployment this is not possible since the databases are too large: that's the main reason for having them in a database in the first place.
I strongly believe that a DB should be part of source control and to a large degree part of the build process. If it is in source control then I have the same coding safe guards when writing a stored procedure in SQL as I do when writing a class in C#. I do this by including a DB scripts directory under my source tree. This script directory doesn't necessarily have one file for one object in the database. That would be a pain in the butt! I develop in my db just a I would in my code project. Then when I am ready to check in I do a diff between the last version of my database and the current one I am working on. I use SQL Compare for this and it generates a script of all the changes. This script is then saved to my db_update directory with a specific naming convention 1234_TasksCompletedInThisIteration where the number is the next number in the set of scripts already there, and the name describes what is being done in this check in. I do this this way because as part of my build process I start with a fresh database that is then built up programatically using the scripts in this directory. I wrote a custom NAnt task that iterates through each script executing its contents on the bare db. Obviously if I need some data to go into the db then I have data insert scripts too. This has many benefits too it. One, all of my stuff is versioned. Two, each build is a fresh build which means that there won't be any sneaky stuff eking its way into my development process (such as dirty data that causes oddities in the system). Three, when a new guy is added to the dev team, they simply need to get latest and their local dev is built for them on the fly. Four, I can run test cases (I didn't call it a "unit test"!) on my database as the state of the database is reset with each build (meaning I can test my repositories without worrying about adding test data to the db).
This is not for everyone.
This is not for every project. I usually work on green field projects which allows me this convenience!
Rather than get into white tower arguments, here's a solution that has worked very well for me on real world problems.
Building a database from scratch can be summarised as managing sql scripts.
DBdeploy is a tool that will check the current state of a database - e.g. what scripts have been previously run against it, what scripts are available to be run and therefore what scripts are needed to be run.
It will then collate all the needed scripts together and run them. It then records which scripts have been run.
It's not the prettiest tool or the most complex - but with careful management it can work very well. It's open source and easily extensible. Once the running of the scripts is handled nicely adding some extra components such as a shell script that checks out the latest scripts and runs dbdeploy against a particular instance is easily achieved.
See a good introduction here:
http://code.google.com/p/dbdeploy/wiki/GettingStarted
You might find that Liquibase handles a lot of what you're looking for.
Every developer should have their own local database, and use source code control to publish to the team. My solution is here : http://dbsourcetools.codeplex.com/
Have fun,
- Nathan