转型和行动的火花工作在哪里完成? [英] where is the spark job of transformation and action done?

问题描述

我一直在使用Spark + Python完成一些工作，这很棒，但是我心中有一个疑问:

变革和行动的火花工作在哪里完成? 转换工作是在Spark Master(或驱动程序)中完成的，而动作是在工作人员(执行人)中完成的，还是两者都在工作人员(执行人)中完成了?

谢谢

解决方案

工人(又名奴隶)正在运行执行者居住的Spark实例 执行任务.

当操作方法被调用时，转换是在工作程序上执行的.将计算出的数据带回到驱动程序中.

Spark中的应用程序分三个步骤执行:

1.创建RDD图形，即RDD的DAG (directed acyclic graph)代表整个计算.

2.创建阶段图，即DAG of stages，它是基于RDD图的逻辑执行计划.通过在随机边界处打破RDD图来创建阶段.

3.根据计划，schedule and execute 工人的任务.

I have been using Spark + Python to finish some works, it's great, but I have a question in my mind:

where is the spark job of transformation and action done? Is transformation job done in Spark Master ( or Driver ) while action job is done in Workers ( Executors ), or both of them are done in Workers ( Executors )

Thanks

解决方案

Workers (aka slaves) are running Spark instances where executors live to execute tasks.

Transformations are performed at the worker, when the action method is called the computed data is brought back to the driver.

An application in Spark is executed in three steps:

1.Create RDD graph, i.e. DAG (directed acyclic graph) of RDDs to represent entire computation.

2.Create stage graph, i.e. a DAG of stages that is a logical execution plan based on the RDD graph. Stages are created by breaking the RDD graph at shuffle boundaries.

3.Based on the plan, schedule and execute tasks on workers.

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