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Flink中ExecutionGraph的构建-CSDN博客
一、ExecutionGraph概述 在JobGraph向ExecutionGraph转化的过程中,主要的工作内容根据Operator的并行度来拆分JobVertext,每一个Jobvertex根据自身并行度会拆分成多个ExecutionVertex,使用IntermediateResultPartition对象来接收ExecutionVertex的输出。对于同一个ExecutionVertex的多个输出IntermediaResultPartition对象组成了一个IntermediateResult对象。1.12之后没有了ExecutionEdge 取而代之的是ConsumedPartitionGroup和ConsumedVertexGroup。 在flink的ExecutionGraph中,有一对一和多对多两种模式,当上游节点处于多对多模式时,会遍历所有的ExecutionGraph,时间复杂度为O(n的平方)。这将占用大量内存用于大规模作业。...
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