• Programs that need to pre-generate data tables

    需要提前生成数据表的程序

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  • PWH data tables containing SQL activity trace data.

    包含SQL活动跟踪数据的PWH数据表。

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  • First, create bean classes for all your data tables.

    首先,为所有数据表创建bean类。

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  • PWH data tables containing snapshot and configuration data.

    包含快照和配置数据的PWH数据表。

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  • The SQL activity trace data is loaded into the following data tables.

    SQL活动跟踪数据加载到下列数据表中。

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  • Some meaningful characteristic curves and data tables are given.

    文中给出了一些有意义的特征曲线和数表。

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  • What is the easiest way to use the data tables in GIEWS web publications?

    使用GIEWS网上出版物中的数据表的最简单方法是什么?

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  • Data tables from analytical runs of clinical or preclinical samples.

    临床或临床前分析批数据表。

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  • After the aggregation, the data is loaded into the following data tables.

    汇总后,数据被加载到下列数据表中。

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  • Data tables are bound to multipart pieces of data, such as arrays or lists.

    数据表与多个数据相联系,例如数组或者列表。

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  • The end result is that there's no need to define data tables and write code to maintain them.

    最终结果是不需要定义数据表以及编写代码来进行维护。

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  • In such cases, writing a program to build static data tables is usually your best answer.

    在这种情况中,编写一个程序来构建一张静态表通常是最好的解决方案。

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  • Understanding the differences in behavior between the live data tables and the historical data.

    理解数据表格与历史性数据之间在行为上的不同之处。

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  • Using simple data tables, complex data tables, and th elements as demonstrated in the Techniques for WCAG 2.0.

    如《WCAG 2.0技术规范》示范的那样正确使用简单数据表,复杂数据表,以及th元素。

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  • The results of individual trials, and any statistical summary of these, should be included in Data tables.

    数据表中应把单个试验的结果以及所以这些单个试验的统计学概要都包括在内。

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  • LightSwitch simplifies attaching to data with data source wizards or creating data tables with table designers.

    LightSwitch通过数据源向导简化了数据连接,同时通过表设计器简化了数据表的创建。

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  • Saving modified data from related data tables is a little more complex than saving data from a single table.

    保存相关数据表中修改过的数据比保存单个表中的数据稍为复杂。

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  • Provides step by step details for saving modified data in two related data tables to the underlying database.

    提供将两个关联的资料表中已修改的资料,储存至基础资料库的逐步详细资料。

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  • Static files, templates, and code are served from disk, as are the data tables and indexes that make up the database.

    静态文件、模板和代码都来自磁盘,组成数据库的数据表和索引也来自磁盘。

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  • There are many complicated data tables and line drawings to be processed in the computer aided machinery design.

    计算机辅助机械设计中有许多复杂的数表和线图需要处理。

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  • In a relational language, such a query would require a join that might span several data tables and system catalog tables.

    而在关系语言中,这种查询需要进行也许跨越了多个数据表和系统目录表的联接。

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  • Use Import Export Manager to bring metadata about data files, data tables, business terms, reports, and models into Workbench.

    使用ImportExportManager把关于数据文件、数据表、业务术语、报告和模型的元数据导入到Workbench中。

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  • The more complex components, such as grids and data tables, have additional CSS-related attributes for their facets and elements.

    更复杂的组件,比如网格和数据表,则会有针对其facet和元素的额外的css属性。

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  • The generate data set dialog allows you to both generate new data sets and include the resulting set data tables in an existing project data set.

    生成数据集对话框既允许您生成新的数据集,又支持在现有的项目数据集中包含结果集数据表。

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  • Unfortunately these techniques often involve breaking up data at the block level and redistributing it, or deleting it based on meta-data tables.

    不幸的是,这些技术往往都涉及到打破块级别上的数据并重新分配,或根据元数据表格将其删除。

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  • Once it's been migrated to their servers, you can collaborate on the data tables with your colleagues and easily build applications for your business.

    一旦数据库迁移到Zoho的服务器上,你可以使用这些数据表与你的同事协同工作,以及轻松的制作公司的应用。

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  • IRAD simplifies this situation by providing stub Data Tables, which allow you to specify how stubs should behave in reaction to requests from the CUT.

    IRAD通过提供Stub数据表简化了这种情况的处理,你可以设定Stub采取怎样的动作来对CUT的请求做出反应。

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  • We load everything asynchronously, including simple things like data tables and localisation texts, and complex things like entities, scenes and UIs.

    不论简单的数据表、本地化字典,还是复杂的实体、场景、界面,我们都将使用异步加载。

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  • During this process, operational data is retrieved from a product source as an XML resource, mapped to relational data tables, and normalized in the data warehouse.

    在这个过程期间,操作性数据是从一个产品源中获取以作为一个XML资源,映射到关系数据表中,并在数据仓库中得到标准化。

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  • Very simply, YQL treats individual web services as though they were data tables, allowing developers to formulate SQL-like queries to extract information from them.

    很简单,YQL对待各个Web服务就仿佛它们是数据表一样,允许开发人员制定类似SQL的查询以便从其中提取信息。

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