这种方法向业务逻辑公开了关系和数据层次结构。
This methodology exposes the relationships and data hierarchy to the business logic.
但数据是孤独的，没有层次结构，没有关系也没有对象。
But the data was alone, with neither hierarchy nor relation nor object.
业务用户经常通过对比在不同层次结构总结的事实，来分析数据。
Business users often analyze data by comparing facts summarized at different levels of a hierarchy.
通过使用XML数据模型，就可以取消整个数据对象包装器层次结构，让开发人员将注意力集中在业务逻辑上，而不会为业务数据管理分心。
Using the XML data model, the whole hierarchy of data object wrappers can be eliminated, leaving the programmer to focus on the business logic rather than on the business data management.
XML使用四个基本组件表示信息—标记、属性、数据元素和层次结构。
XML expresses information using four basic components — tags, attributes, data elements, and hierarchy.
层次结构是组织创建用于表述其数据关系的逻辑结构。
Hierarchies are the logical structures that an organization creates to describe relationships among its data.
整个类层次结构使用一个数据实体。
Spring定义了一致的数据访问异常类层次结构（请参见图12），您可以将其用作服务和DAO 层异常的基础。
Spring defines a coherent data access exception class hierarchy (Figure 12) that you can use as a basis for your service- and DAO-layer exceptions.
通常，大多数APM系统将跟踪程序提交的数据组织到某种分类的层次结构中。
Most APM systems typically organize data submitted by tracers into some sort of categorized and hierarchical structure. Figure 2 illustrates the general flow of this data capture.
使用这种方法，您可以将一个完整类层次结构映射成一个数据实体，而层次结构中所有类的所有属性都存储在这个实体中。
With this approach, you map an entire class hierarchy into one data entity, where all the attributes of all the classes in the hierarchy are stored.
这些对象引用多维数据集模型中使用的事实、维、层次结构和级对象，它们与多维数据集模型中的这些对象是相似的。
These objects reference the facts, dimension, hierarchy, and level objects that are used in the cube model, and they are similar to these objects in the cube model.
定义了产品类型层次结构后，可以继续定义希望为层次结构中的每个类型捕捉的数据。
After you have defined the product type hierarchy, you can then define the data you wish to capture for each type in the hierarchy.
相关信息是用层次结构中位于不同级别的兄弟元素来表示；其结果是，层次结构告诉我们数据元素是如何相互关联的。
Related information is represented in the hierarchy as siblings at various levels; as a result, hierarchy tells us how data elements are related to each other.
这种产品类型层次结构使用元数据结构进行定义，并具有一组相关数据库表和业务服务。
This product type hierarchy is defined in a metadata structure and has an associated set of database tables and business services.
一个切片包含来自多维数据集模型的每个维的层次结构的一个级。
A slice includes a level from a hierarchy of each dimension of the cube model.
el从jsp容器检索数据，遍历对象层次结构，然后对结果执行简单的操作。
The EL retrieves data from the JSP container, traverses object hierarchies, and performs simple operations on the results.
服务可以存在于体系结构的所有层次：基础结构层、ui层和数据层。
Services can be formed at all layers of the architecture: the infrastructure layer, UI layer, and data layer.
在参与分布式查询的所有数据库中，各种数据类型必须定义有相同的层次结构和类型转换。
The distinct data types must have exactly the same hierarchy and casts defined in all databases participating in the distributed queries.
大部分传统OO系统和程序都包括对领域数据对象的层次结构进行操作的业务对象。
Most of the traditional OO systems and programs consist of business objects manipulating hierarchies of domain data objects.
我们可以通过标准的关系方法或使用新的数据类型，在数据库中表示该层次结构关系。
We can represent this hierarchical relationship in the database through standard relational methods or using new data types.
本文假设多维数据集模型的维具有平衡的层次结构和标准部署。
This paper assumes the dimensions of the cube model have hierarchies of balanced type and standard deployment.
就其性质而言，关系数据库比层次数据存储结构(如xml)更灵活。
Relational databases are, by their nature, more flexible than hierarchical data storage structures such as XML.
对于每个多维数据集维，一个多维数据集只能定义一个多维数据集层次结构；但是在多维数据集模型中，一个维可以有多个层次结构。
A cube can have only one cube hierarchy defined for each cube dimension, but a dimension can have many hierarchies that are defined for the cube model.
这使DB2 可以将输入的XML数据存储为原生的层次结构格式。
This causes DB2 to store input XML data in its native hierarchical format.
XML数据可以按照原来的层次结构格式完整地保存。
Instead, XML data can be stored intact in its native hierarchical format.
LDAP数据库以具有层次结构的条目为基础，存储和检索信息，其中每个条目都具有区别于其他条目的名称、类型和属性。
The LDAP database stores and retrieves information based on a hierarchical structure of entries, each with its own distinguishing name, type, and attributes.
必须每月对这些层次结构进行更新，并作为IBM的组织层次结构数据受信任来源提供。
These hierarchical structures must be updated monthly and be made available as IBM's trusted source for organizational hierarchical data.
LOM定义了一个基本模式，这个模式为学习对象元数据定义了数据元素的层次结构。
LOM defines a Base schema that defines a hierarchy of data elements for learning objects metadata.
数据库已经变得更强大了，所以这个类型层次结构也变得更复杂。
As databases have become more powerful, this type hierarchy has grown more complex.
数据库已经变得更强大了，所以这个类型层次结构也变得更复杂。
As databases have become more powerful, this type hierarchy has grown more complex.
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