Flink流:如何控制执行时间 [英] Flink streaming: how to control the execution time

问题描述

火花流提供了用于终止awaitTermination()的API.在t秒钟后，是否有任何类似的API可以正常关闭flink流?

Spark streaming provides API for termination awaitTermination(). Is there any similar API available to gracefully shut down flink streaming after some t seconds?

推荐答案

在执行流作业时，Flink中的驱动程序(即main方法)不会保持运行.您的程序应定义一个数据流，调用execute，然后终止.在Spark中，驱动程序保持运行(AFAIK)，并且awaitTermination与之相关.

Your driver program (i.e. the main method) in Flink doesn't stay running while the streaming job executes. Your program should define a dataflow, call execute, and then terminate. In Spark, the driver program stays running (AFAIK), and awaitTermination relates to that.

请注意，除非您使用带有有限数量元素的绑定"数据源，否则Flink流数据流将继续无限期执行.您还可以取消或停止工作，甚至在停止时设置检查点，以便以后恢复.

Note that a Flink streaming dataflow continues to execute indefinitely, unless you're using a 'bounded' data source with a finite number of elements. You may also cancel or stop a job, and even take a checkpoint upon stopping to be resumed from later.

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