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  • How the user sees that persistent data?

    用户如何看到持久性数据?

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  • These diagrams drive the persistent data.

    这些关系图驱动持久性数据。

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  • How long that persistent data remains around?

    持久性数据大约保留多久。

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  • The speed and size of the persistent data store.

    持久性数据存储的速度和大小。

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  • What libraries provide persistent data structures?

    图书馆提供持久化数据结构是什么?

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  • Exactly how persistent data is queried by a client can vary.

    确切地说,客户查询持久性数据的方式可以所有不同。

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  • The data persistence layer comprises all the persistent data stores.

    数据存储层由所有的存储数据仓库组成。

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  • Walrus lets you store persistent data, organized as buckets and objects.

    Walrus可以存储永久数据,以存储桶(buckets)和对象(objects)的结构进行组织。

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  • In the sample application, the file system is used as the persistent data store.

    在样例应用程序中,文件系统用作持久性数据存储。

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  • Entity beans represent persistent data that is typically loaded from a database.

    实体bean代表持久化数据,数据通常是从数据库中装载的。

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  • Finally, the data access layer is a persistent data store, such as a database or file storage.

    最后,数据访问层是持久化的数据存储,比如数据库或文件存储。

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  • Runtime API's provide the functionality to manipulate the platform's persistent data objects.

    运行时api提供了操纵平台固定数据对象的功能。

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  • The Model contains all the business logic necessary to retrieve data from a persistent data store.

    模型包含所有必须的业务逻辑,从存储数据仓库中检索数据。

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  • The provision to access persistent data as resources by a remote client raises data privacy and security concerns.

    向一个远程客户端提供持久化数据访问可能会引起数据保密和安全问题。

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  • Many real-world Java 2 Platform, Enterprise Edition (J2EE) applications need to use persistent data at some point.

    许多投入使用的,J2EE WEB应用程序在一些时候需要进行数据的持久化.

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  • Visual Dashboard is a type of visual project that presents interactive or persistent data to a wide range of users.

    VisualDashboard是一种可视化项目,可以为广泛的用户显示交互式或持久性数据。

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  • Execution of an operation will typically cause one or more persistent data records to be read, written, or modified.

    执行操作通常会导致读、写或修改一个或多个持久性数据。

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  • Finally, more and more scientists are recognizing that persistent data management is crucial to their research.

    最后,越来越多的科学家认为稳定的资料管理对他们的研究是很重要的。

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  • The reason is that this mapping exposes and couples the application too closely to the persistent data store's schema.

    原因在于该映射使得应用程序与持久性数据存储方案之间的耦合变得太过紧密了。

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  • All J2EE persistence technologies provide some mechanism to map business data objects back to a persistent data source.

    所有的J2EE持久化技术都提供了一些机制来将业务数据对象映射回持久性数据源。

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  • Put away (or "detach") the data that your application does not need by storing the data into some persistent data store.

    通过将数据存储到一些永久性数据存储中而收起(或“分离”)应用程序不需要的数据。

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  • When finally there is a need, retrieve the data from the persistent data store before continuing on with processing.

    最后有需要时,在继续处理之前从永久性数据存储中检索数据。

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  • Note that this development scenario involves using Hibernate to present an object-based view of existing persistent data.

    注意,这一开发场景需要使用Hibernate将已有持久性数据表示成基于对象的视图。

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  • Many web applications are data centric-they present persistent data and allow the user to create or update this data.

    很多web应用程序是以数据为中心—它们显示数据并允许用户新建或更新数据。

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  • The fire method uses the persistent data stored in the rule bean and the parameters passed as arguments for the execution of the rule.

    fire方法使用了存储在规则bean及为了执行规则而作为变量传递的参数中的数据。

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  • But, when a Web service wants to maintain persistent data (for example, become a stateful Web service) things become a little more complex.

    但是,当一个Web服务需要维护持久性数据(比如,成为一个有状态的Web服务)时,事情就变得有点复杂了。

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  • The data cleansing pattern specifies a recommended practice for how to improve the data quality of persistent data either at entry or later.

    数据清理模式指定有关如何在输入时或稍后提高持久性数据的数据质量的建议性实践。

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  • The data cleansing pattern specifies a recommended practice for how to improve the data quality of persistent data either at entry or later.

    数据清理模式指定有关如何在输入时或稍后提高持久性数据的数据质量的建议性实践。

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