GPars还定义通过线程池(比如actors)调度的逻辑数据流任务并通过数据流变量进行传输。

GPars also defines logical dataflow tasks that are scheduled over a thread pool (like actors) and communicate via dataflow variables.

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操作、销售和财务人员也因消除了任务关键数据流中的迟滞现象而获得了实时的决策支持。

Operations, Sales and Finance personnel also have real-time decision support by removing the latency in the flow of mission critical data.

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在设计的过程中，关键的任务是指定从数据源到目标的数据流，即如何重建并将源模型合并到目标模型中。

The key task during design time is to specify the data flow from the sources to the target — that is, how to restructure and merge source models into the target model.

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