• ETL job details and operational metadata.

    ETL作业详细信息和操作元数据。

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  • Identify jobs that will benefit from t-etl.

    识别可从t -ETL中获益的作业。

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  • There is no commonly accepted benchmark for ETL tools.

    有没有一个被普遍接受的基准的ETL工具?

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  • ETL of short-term history snapshot and configuration data.

    短期历史快照和配置数据的etl。

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  • The issue needs to be addressed with a scalable ETL architecture.

    这个问题需要用一个可伸缩的ETL架构来解决。

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  • Extract, Transform, and Load (ETL) technologies can be used here.

    可以在此处使用提取、转换和加载(Extract, Transform, and Load,ETL)技术。

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  • First, the ETL places a significant load on your production databases.

    首先,ETL给生产数据库增加了明显的负担。

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  • Data propagation: ETL process to aggregate and enhance data for data marts.

    数据传播:用于为数据集市聚集和增强数据的ETL过程。

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  • The centralized approach is typically managed by ETL or replication technologies.

    集中化方法通常由etl或是复制技术来管理。

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  • This case involves using the Loader package ETL programs as the previous use case.

    这个案例包含了Loader包里的ETL程序,这在上一个使用案例中也被使用了。

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  • Many ETL tools exist that extract and transform data before loading into the warehouse.

    目前有的很多etl工具,可在将数据加载到数据仓库之前对数据进行提取与转换。

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  • As you might expect, there are several ways to program an ETL job for this scenario.

    正如您所预料的,有多种方式为本场景编写ETL任务。

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  • Figure 25 shows a sample ETL job that illustrates the TDEE data extract and load features.

    图25所示的示例ETL作业演示了TDEE数据提取和加载特性。

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  • They can be re-used not only by other business processes, but also by ETL and applications.

    不仅可以供其他业务流程重用,ETL和应用程序也可以对其进行重用。

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  • Figure 27 shows a sample ETL job that illustrates the TDMLOAD data export and load features.

    图27所示的示例ETL作业演示了TDMLOAD数据导出和加载特性。

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  • Federation, ETL, caching, replication, and event publishing are all aimed to meet QoS goals.

    联盟、ETL、缓存、复制和事件的发布功能的目的都是为了与QoS的目标相匹配。

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  • The tried-and-true technique of extract, transform, and load, or ETL, is one way to manage this.

    行之有效的提取、转换和加载或etl技术是管理这个的一种方式。

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  • Once you understand the ETL process, you can apply the same process to other database environments.

    一旦理解了ETL过程,你可以在其他的数据库环境中应用相同的过程。

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  • Metadata management: business requirements, data models, ETL process designs, user manuals, and so on.

    元数据管理:业务需求、数据模型、ETL过程设计、用户手册,等等。

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  • This is part of the reason Microsoft would support the creation of an industry standard ETL benchmark.

    基于这部分原因,微软将支持建立一个行业标准的ETL的基准。

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  • In this section, a simple ETL job is designed to illustrate the design steps and the extract functions.

    本节将设计一个简单的ETL任务,以演示设计步骤和提取功能。

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  • Generally, ETL processes manually specify when to update MQT rather than allow this to happen automatically.

    通常,ETL过程是手动地指定何时更新MQT,而不是让更新自动发生。

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  • Designing ETL jobs (or data flows) is an important aspect of integrating XML into data warehouse environments.

    设计ETL任务(或数据流)是将XML集成到数据仓库环境的重要方面。

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  • Unlike ETL and data replication, event publishing does not know where the data is going and how it will be used.

    和ETL以及数据复制不同,事件发布并不清楚数据的去向以及如何使用数据。

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  • A third method is to have the summary tables rebuilt after the ETL process using SQL sum and aggregate functions.

    第三种方法是在ETL流程之后使用SQLSUM和汇总函数来重构汇总表。

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  • The data staging module stores the original data and temporary data from all data sources for ETL processing.

    数据分级模块存储所有数据源的初始数据和临时数据,以用于ETL处理。

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  • The T-ETL job shown in Figure 4 executed in just 127 seconds -- an overall elapsed time improvement of 38 percent.

    而图4 中显示的 T-ETL 作业的执行时间只有 127秒 —— 总体执行时间缩短了 38% 之多。

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  • The data repository module stores all integrated business data, it is the final target of data acquisition ETL process.

    数据存储库存储所有的集成业务数据,它是数据获取ETL过程的最终目标。

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  • If your business has nice offline Windows for the ETL, that's great, but if not, managing the scale becomes a challenge.

    如果你的业务有空窗期可以做etl,那是最好的;如果没有,管理可伸缩性就是很大的挑战。

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  • This operational information will be very helpful to debug problems later, such as inconsistent data or ETL job failure.

    这些操作信息对于调试问题非常有帮助,比如数据不一致或ETL作业失败。

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