我有一个像这样的工作:
DataStream<SomeObject> input1 = environment.addSource(mySource()).setParallelism(1).setMaxParallelism(1);
DataStream<SomeObject> input2 = environment.addSource(mySourceTwo());
input1.union(input2)
.map(doSomething())
.output(outputSomething());
因此,一个运算符必须保持并行度为1,而其他运算符可以根据需要提高。
当我使用Rest API(https://ci.apache.org/projects/flink/flink-docs-release-1.6/monitoring/rest_api.html)重新缩放作业时,出现错误,因为它试图重新缩放所有运算符。
Caused by: org.apache.flink.util.FlinkException: Cannot rescale vertex Source: Scheduled BookingSignals because its maximum parallelism 1 is smaller than the new parallelism 3.
是否可以通过REST API重新缩放flink作业,而不必尝试重新缩放超出其最大并行度的运算符?