日期:2014-05-16  浏览次数:20441 次

为关系数据库设计对象

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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