Promiscuous Women Cause Problems for Database Administrators

This is a fiction story that never happened:

Juliet Capulet meets Paul Smith; they fell in love and marry on 25th August 2009. When Juliet is back at work she asks the db admin to change her name in a company database. The admin is not happy to have additional work with this stuff but he does it for her.

Juliet’s and Paul’s marriage is not going well and Juliet divorces Paul after a short period. Soon Juliet feels alone, she meets Romeo Montague and, of course, falls in desperate love with him. Logically, another wedding is arranged and Juliet asks db admin to change her name again on 10th January 2010.

The tragedy of all Juliet’s love relationships finishes when she finds her husband Romeo as a roulette player spending all their money. She divorces again and changes her name to Juliet Singleton on 21st July 2010 with the vision not to marry anybody again. Needless to say, the db admin is close to committing suicide because his database does not allow changing the name more than twice.

What would you suggest the database admin to do better in his next life?

Problem description

Let us summarize what the db admin was asked to do with Juliet’s personal data:

• Juliet Capulet gets the job on 2005-03-01
• Name Juliet Capulet changes to Juliet Smith on 2009-08-25
• Name Juliet Smith changes to Juliet Montague on 2010-01-10
• Name Juliet Montague changes to Julie Singleton on 2010-07-21

Solution No.1: Roll off Out-dated data

The simplest solution for keeping historical data in the database is to create a duplicated record before update. After that we can update the requested data. In case of tracing Juliet’s name we get these data in the database table:

In real database schema, id is primary key and has to be unique. So we need extra column containing information about row id from which data were rolled off. Additionally, it would be helpful to have a column representing status of the record. Because situation gets more complex here I show how data evolve in database:

Juliet Capulet gets the job on 2005-03-01.

Name Juliet Capulet changes to Juliet Smith on 2009-08-25.

Name Juliet Smith changes to Juliet Montague on 2010-01-10.

Name Juliet Montague changes to Julie Singleton on 2010-07-21.

You can see that each change to the record with id=124 invokes a) creating duplicated row with status=history and b) updating the column name to a requested value with created_date set to current date. When the active record is going to be “deleted” then only the status flag changes the value from active to history.

Advantages

It is simple to implement audit logging based on rolling out old data. You do not need additional tables. Maintenance is simple, too. If you decide to remove old data then it is the matter of one SQL.

Disadvantages

But what if you need to implement audit logging in more tables? You need to add columns original_id, status, created_date and created_by. And you have to implement previously introduced roll-off logic, either to database directly (usually with table triggers) or in the application.

The problem can be that when data changes then the whole record is copied, i.e. also data which do not change. It causes data duplication and, potentially, database disk space can increase markedly if changes occur frequently. For example, if table persons has a column photo with binary data containing the photography then each and every time Juliet’s name changes the whole record (including the photo) is copied to rolled-off record.

Another disadvantage is that the complexity of each table supporting audit logging increases. You must have in mind all the time that retrieving the records is not simple. You always have to use the SELECT clause with condition

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SELECT * FROM persons WHERE status='active'

When you need to roll back historical data for a particular record you have to copy all columns from the historical record to the active record. It would be easier just to switch status value from “history” to “active” but it would break reference integrity if the record was referenced in other tables.

Solution No.2: Dedicated Data-Tracing Table

Another approach is based on separate audit log table that is dedicated to logging data changes coming from all tables having audit log feature:

Advantages

This solutions separates the concerns much better. There is only one common data store for all historical data. Further, you have to implement audit log feature only once for all tables which should support it.

Compared to the previous solution, when the record changes only the changed data are logged. Thus it is expected to be a little bit faster but I did not do any tests so I cannot prove it exactly. The real advantage is that you need lower disk space to store data changes. You can improve the table structure when you normalize the log table and you put just integer references to “table” and “column”.

You can easily retrieve user activity just by the query

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SELECT * FROM audit_log WHERE changed_by='admin'

Disadvantages

All data changes are logged in a common table so old and new values stored there must be of some generic type. For example, in MS SQL it can be “sql_variant”. Or you can convert the values to “varchar” before storing them in the log table.

Rollback is rather difficult task to be implemented. If you want to roll data back to 3rd March 21010 you have to use query

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SELECT [table], [column], old_value, new_value FROM audit_log WHERE [table]='persons' AND row=124 and changed_date > '2010-03-01' ORDER BY changed_date

and then you iterate through the result set and build the dynamic query because table and column info is in the result. It is more complicated compared to the previous solution. Fortunately, the feature has to be implemented only once and the can be reused across the whole application.

Related posts:

• Database Continuous Integration with DBTracer

TypeText(string) is slow because during run it fires sequences of key events: KeyDown(char), KeyPress(char), KeyUp(char). The sequence is invoked as many times as the length of the input string is. As the result, the input text is typed to the text field one by one char. It is slow and when you have hundreds of tests then you wait tens of minutes for their execution! I created simple extension method to speed up typing of text markedly – for a string 10 chars long the performance of typing is around 30 times higher.

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public static class WatiNExtensions
{
    public static void TypeTextQuickly(this TextField textField, string text)
    {
        textField.SetAttributeValue("value", text);
    }
}

In my solution I do not use simulated key events. I use direct setting of value attribute in text field. The limitation of this solution is that it does not raise focus and blur events. Additionally, no key events are fired.

Usage is simple:

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var browser = new IE("http://google.com");
browser.TextField("q").TypeTextQuickly("WatiN"); // fast - raises neither key events nor focus and blur on text field
// browser.TextField("q").TypeText("WatiN"); // slow - raises key events

No related posts.

C:\Program Files\Git\bin>git svn init -s file:///D:/path/to/svn/repository
Initialized empty Git repository in C:/Program Files/Git/bin/.git/

But Ooops! Error occurred when I tried to fetch all the history to Git repository:

C:\Program Files\Git\bin>git svn fetch
 A       notes.txt
 A       pages.txt
 A       settings.config
r7 = f3dba0984f11e2f358923c23d89440789eb4591b (refs/remotes/references)
Permission denied: Can't open '/tmp/report.tmp': Permission denied at C:\Program Files\Git/libexec/git-core/git-svn line 2723

It was an misguiding error since I had neither a “tmp” directory in the original svn repository nor “report.tmp” directory. For my surprise the problem was caused by different formats used by in original Subversion repository and by Subversion module included in my Git instance that probably uses older Subversion format. I use Git 1.6.5.1.1367.gcd48 that probably has Subversion module supporting format 4 but my Subversion repository was in format 5.

Solution

Luckily the solution for such WTF exists. If I access Subversion repository via SVN server instead of directly via file path problem will not occur. Thus, at first it is necessary to run SVN server:

svnserve.exe -d -r D:/parent/path/to/repository/

And then you can access Subversion repository via its server:

git.exe svn init -s "svn://localhost/relative/path/to/subversion/repository"

No related posts.

The common repository for all source code changes is Subversion (currently we think of migrating to Git, anyway). For tracking changes of database schema changes we use Subversion, too.

In our team each developer has his own database server installed on his PC and he is an administrator of his own database server. The core of everything is the SCM. Developers check out latest code from there, integration server uses it as well to get code base and integration tests. The idea connected with tracking changes of database schema was to include changes under version control. Then both developers and integration server were able to retrieve database schema changes and to handle them.

Database Change Scripts

If a developer wishes to do some changes in database schema, he can freely do that on his local database without fear to influence work of the others. As the result of his work he is expected to create a database change script that includes all schema changes needed to be implemented. Let’s say we need to add a column to the table. The change script will contain these SQL commands:

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ALTER TABLE Order
ADD Status int NOT NULL DEFAULT 0
GO

The script will add a column “Status” to a table “Order”. You can feel it would be very annoying for a developer to change database schema only via change scripts in regular daily work. We established a helpful practice how to make things easier for the developer. The change script should be the result of his work that he wish to be integrated. We work as follows:

1. When developer is going to do schema changes (on his local machine, of course), first he creates a clone of database version that was already fully integrated to source control. Let’s say that database is in version 1.5 so he creates a clone of it with help of DBTracer:

   cmd> dbt create /database=reference_db_v_1_5 /db-version=1.5 /connection=(local)

2. At this point he has a reference database that will serve him as a reference point when he will compare it with his test database. The test database is created in the same way as reference one:

   cmd> dbt create /database=test /connection=(local) /db-version=1.5 /override-if-exists

3. Now the developer is ready to do whatever he wants in the “test” database. For example he can add a column “Status” to a table “Order”. Of course you are not limited to add only one schema change to one change script.
4. When he is ready with schema changes he compares the test database with a reference database “reference_db_v_1_5″. Tools for comparing databases are very much helpful here. In my team we use EMS DB Comparer.
5. The tool generates a change script. It is possible to modify it manually if we are not satisfied with the result. After that, the change script is ready to be checked in to version control.

Change Script Names

We use the following convention for our change scripts:

<major_version>.<minor_version>.<revision>-<some description of change script>.UP.sql

For example:

003.012.0541-add column Status to table Order.UP.sql

In this example the change script lies within database major version=3, minor version=12 and its revision=541. There is also a short description “add column Status to table Order” defining what is inside the change script. Additionally, the keyword “UP” in the change script is reserved for future when we will need to distinguish between upgrade change scripts and downgrade change scripts.

Now the change script is ready to go to version control.

Our Solution – DBTracer

We searched for a simple tool that would maintain a our database migration scripts. Additionally, it should provide following features:

• command line interface
• storing SQL database version in the database itself

Unfortunately, no such tool existed that would have been acceptable. Hence, we inspired by Alexander Kleshchevnikov and wrote our own tool DBTracer. Currently it is in experimental phase for public. We use it internally in our team but still API changes are going on.

Further Reading

• Three Rules for Database Work
• Database Continuous Integration in .NET
• Evolutionary Database Design

Related posts:

• Audit Trail – Tracing Data Changes in Database