详细叙述了数据层次的设计和实现。
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.
难于实现裸数据层次上的整合，因此，我们致力于系统层次上“服务” 的整合。
We try our best to realize the service integrated in the level of system because the integration in the level of data is very difficult.
通过合理分配数据层次，建立冗余度小、推导方便的数据存储结构，同时给出了实例。
Then a data storage structure, having low redundancy rate, being well assigned in data depth and easy in searching, was created. Also an example was given for illustration.
“网络文献”所具有的三个层次的信息分别是：物理载体层次、元数据层次和信息单元层次。
Web documents have information in three levels, i. e. the levels of physical media, metadata and information unit.
我们会通过处理分析的方式，使用数据层次图的概念，以描述数据库分区结构和数据库处理的关系。
We will use the concept of a data hierarchy graph, constructed by means of transaction analysis, to characterize the relationship between a database partition scheme and database transactions.
尽管XML在内部存储为层次化格式，但逻辑上，在数据库表中，它似乎存储在CLOB或BLOB中。
Although internally the XML is stored in a hierarchical format, logically in the database table it appears to be stored in a CLOB or BLOB.
订单可能是数据模型中的其他层次的根。
The Order could be the root of another hierarchy in the data model.
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.
大型、复杂的数据集将传统的数据挖掘技术推向新层次的处理要求。
Large, complex data sets escalate traditional data mining techniques to new levels of processing demand.
现在需要的是更深层次的验证——在数据库层次。
What you need is a deeper level of validation — at the database level.
XMLMarker是一个 XML编辑器，它使用一个同步的表树和文本显示，来向您展示 XML数据的层次视图和表视图。
XML Marker is an XML editor that uses a synchronized table-tree and text display to show you a hierarchal and a tabular view of your XML data.
但是如果您是一名高级用户的话，它向您提供了机会去在Connectionpool层次上配置超过10个不同的属性，并在数据源层次上配置超过10个不同的属性。
But if you are an advanced user, it gives you the option to configure more than 10 different properties at the Connection pool level and more than 10 different properties at the data source level.
本文介绍了一种自顶向下的Web服务开发方法。IBMWebSphereJAX - RPC兼容的工具和运行时为数据模型层次提供了很好的支持。
This article has shown that in a top-down approach to Web services development, data model hierarchies are well-supported by the IBM WebSphere JAX-RPC compliant tools and runtime.
由于客户端拥有完全的数据模型层次，客户端就有可能在Web服务请求中发送层次中的子类。
Since the client has the complete data model hierarchy, it is possible for the client to send subclasses in the hierarchy in a request to the Web service.
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.
如果您无法直接访问数据源，您将需要从客户获得什么层次的IT支持以获得数据？
If you cannot access a data source directly, what level of IT support will you need from your customer to get the data?
原子数据可以用传统的关系型方法进行查询，而对于非层次数据，这要比XML导航更为有效。
The atom data can be queried with traditional relational methods, which for non-hierarchical data is more efficient than XML navigation.
实际上，原子坐标和表是一些非层次数据，而对于这类数据，xml并非最佳选择。
In fact, the atom coordinates and labels are non-hierarchical data for which XML is not the best choice.
模型通过在数据库层次上设置优先级解决了这个问题。
This is addressed by the model by setting priorities at the chunk level.
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.
XML数据可以按照原有的层次化格式与关系数据一起存储。
Instead, XML data can be stored intact in its native hierarchical format alongside relational data.
正如前面提到的，DB 2允许根据xml列中存储的层次化数据创建关系视图。
As mentioned previously, DB2 enables firms to create relational views over hierarchical data stored in XML columns.
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.
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.
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.
尤其要注意子数据集的层次结构定义。
Note especially the hierarchy definitions for the depending cubes.
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.
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.
数据源之间所有深层次的交流都是使用数据源系统表的本地查询来实现的。
All further communication with the data source is performed using native queries to the system tables of the data source.
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