数据联合模式的大部分实现都比较强调一个（或数量很有限的）目标模型，以最有效地处理请求。
Most implementations of the data federation pattern have a relatively strong focus on one -- or a very limited number of -- target models in order to process requests most efficiently.
建模者可以将常用计算添加到模型中，使得设计人员更有效率，同时减少发送到数据库的查询数量。
Modellers can add commonly used calculations to the model to help authors be more productive while at the same time reducing the amount queries sent to the database.
但是，在一个长方法(long method)中分组数量众多的逻辑块可能会让人很快忘记该方法的总体意图，因为很少有人可以有效处理这样一个大的数据集。
Grouping numerous blocks of logic in one long method can very quickly cloud the overall intention of the method, however, because few people can effectively handle such a large dataset.
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