Friday, February 3, 2012

Tables Are No Domain Objects: Field Aggregations

This is the fourth part of the series about "Tables Are No Domain Objects". After an Introduction the other parts covered Relation Transformations and Many To Many Relations.

In this post I want to talk about field aggregations. By nature table columns are arranged side by side on same hierarchy level. Sometimes there are two or more columns that are tightly coupled with each other, where one (or more) is useless with out the others. Whenever we find collaborations of columns in a table we also found something to consider to aggregate into own classes when dematerializing into our object model. This can avoid duplicate code, centralize logic, and effect more natural object interfaces.

Person Tables

Tables containing person information often contain columns that are more or less related to each other. I'm sure many of you have already seen databases with one or more tables like those shown here.

When designing the domain objects we could create two classes where each contains all columns of the based table, but there are two collaborations of columns that could be considered to be aggregated into own classes.

This not only enables us to reuse helper methods like those I denoted in the PersonName class, but also enables us to easily reuse other methods without designing methods that take many parameters (one for each property). Consider a method that creates a letterhead for a payment check (for employees) or a delivery note (for customers).


At least since Martin Fowlers' legendary book Patterns Of Enterprise Application Architecture where he introduced the Money Pattern we know that calculating with money can be really awkward .

Since Mr. Fowler did a great job in his book I'll not try to explain the whole pattern but only give you a short summary. Apart from all the issues with multiplication and division of money values the pattern describes the relation between an amount column and a currency column. The following diagram shows a possible table structure.

By applying the Money pattern we will get the class structure shown in the diagram below, where all calculation logic is moved into a separate Money class. (BTW: You can find a really good .NET implementation at Code Project: A Money type for the CLR.)

If we would need to calculate with money values of different currencies we would even need a further class like a CurrencyCalculator, but this is far out of scope of this post.

System Information

Often database tables not only store business data but also contain different kinds of additional system information that might be less (or not) business relevant but might be needed for support, analysis or other investigations.

Here is a short list of possible system information columns.

NameShort Description
CreationDate The date/time where the row was inserted into the table.
LastUpdate The date/time of the rows last update. If there have not been any updates yet this value is often either NULL or equal to the creation date.
Creator A key that describes the employee who caused the insertion of the row.
LastUpdater A key that describes the employee who caused the last update of the row.
CreationHost The host computer that caused the insertion of the row.
LastUpdateHost The computer that caused the last update of the row.
Version The current version of the row, if the data in the table are version controlled.

And here are two possible database tables.

Moving the system information into an own class will give us entities that are easier to use, because they really focus on the business, not on the system.

In addition, keeping the properties in each of our entities can cause a remarkable amount of duplicated code or reflection based solutions that are hard to maintain, slow at runtime and not compiler checked.


I hope this post showed you another reason why it is not always the best way to design a domain object model with exactly the same structure as a database.

The easiest way to find candidates for field aggregations is to keep reviewing the table columns or class properties and search for columns/properties that are related to each other.

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