为关系数据库设计对象

 

这是DDD的原文，我认为最好的结论就是最后加粗部分，让模型和数据分开，而不是折中处理，这也是CQRS的本质。

Designing Objects for Relational Databases

The most common nonobject component of primarily object-oriented software systems is the relational database. This reality presents the usual problems of a mixture of paradigms (see Chapter 5). But the database is more intimately related to the object model than are most other components. The database is not just interacting with the objects; it is storing the persistent form of the data that makes up the objects themselves. A good deal has been written about the technical challenges of mapping objects to relational tables and effectively storing and retrieving them. A recent discussion can be found in Fowler 2002. There are reasonably refined tools for creating and managing mappings between the two. Apart from the technical concerns, this mismatch can have a significant impact on the object model.

There are three common cases:

1. The database is primarily a repository for the objects.

2. The database was designed for another system.

3. The database is designed for this system but serves in roles other than object store.

When the database schema is being created specifically as a store for the objects, it is worth accepting some model limitations in order to keep the mapping very simple. Without other demands on schema design, the database can be structured to make aggregate integrity safer and more efficient as updates are made. Technically, the relational table design does not have to reflect the domain model. Mapping tools are sophisticated enough to bridge significant differences. The trouble is, multiple overlapping models are just too complicated. Many of the same arguments presented for MODEL-DRIVEN DESIGN—avoiding separate analysis and design models—apply to this mismatch. This does entail some sacrifice in the richness of the object model, and sometimes compromises have to be made in the database design (such as selective denormalization), but to do otherwise is to risk losing the tight coupling of model and implementation. This approach doesn't require a simplistic one-object/one-table mapping. Depending on the power of the mapping tool, some aggregation or composition of objects may be possible. But it is crucial that the mappings be transparent, easily understandable by inspecting the code or reading entries in the mapping tool.

• When the database is being viewed as an object store, don't let the data model and the object model diverge far, regardless of the powers of the mapping tools. Sacrifice some richness of object relationships to keep close to the relational model. Compromise some formal relational standards, such as normalization, if it helps simplify the object mapping.

• Processes outside the object system should not access such an object store. They could violate the invariants enforced by the objects. Also, their access will lock in the data model so that it is hard to change when the objects are refactored.

On the other hand, there are many cases in which the data comes from a legacy or external system that was never intended as a store of objects. In this situation, there are, in reality, two domain models coexisting in the same system. Chapter 14, "Maintaining Model Integrity," deals with this issue in depth. It may make sense to conform to the model implicit in the other system, or it may be better to make the model completely distinct.

Another reason for exceptions is performance. Quirky design changes may have to be introduced to solve execution speed problems.

 

But for the important common case of a relational database acting as the persistent form of an object-oriented domain, simple directness is best. A table row should contain an object, perhaps along with subsidiaries in an AGGREGATE. A foreign key in the table should translate to a reference to another ENTITY object. The necessity of sometimes deviating from this simple directness should not lead to total abandonment of the principle of simple mappings.

 

The UBIQUITOUS LANGUAGE can help tie the object and relational components together to a single model. The names and associations of elements in the objects should correspond meticulously to those of the relational tables. Although the power of some mapping tools may make this seem unnecessary, subtle differences in relationships will cause a lot of confusion.

 

The tradition of refactoring that has increasingly taken hold in the object world has not really affected relational database design much. What's more, serious data migration issues discourage frequent change. This may create a drag on the refactoring of the object model, but if the object model and the database model start to diverge, transparency can be lost quickly.

 

Finally, there are some reasons to go with a schema that is quite distinct from the object model, even when the database is being created specifically for your system. The database may also be used by other software that will not instantiate objects. The database may require little change, even while the behavior of the objects changes or evolves rapidly. Cutting the two loose from each other is a seductive path. It is often taken unintentionally, when the team fails to keep the database current with the model. If the separation is chosen consciously, it can result in a clean database schema—not an awkward one full of compromises conforming to last year's object model.