Hi Lorenzo, Could you provide some code example to reproduce your question? As I understand, IterativeStream#keyBy is supported since it is a subclass of DataStream.
Moreover, we have implemented an unified iteration module for Flink [1] in Flink ML [2], which relies on Flink 1.15.2. Probably you can also have a try. [1] https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=184615300 [2] https://github.com/apache/flink-ml/blob/master/flink-ml-iteration/src/main/java/org/apache/flink/iteration/Iterations.java Lorenzo Nicora <lorenzo.nic...@gmail.com> 于2023年2月18日周六 17:00写道： > > Hi all, > > I am trying to implement an iterative streaming job that processes the loop > with a KeyedProcessFunction. > > I need a KeyedProcessFunction to use keyed state and to emit a side-output > (that after further transformations becomes the feedback) > > Problem is IterativeStream.process() only accepts ProcessFunction, no > KeyedProcessFunction. > > The main and feedback streams have the same payload type, and I am keying > both before starting and closing the iteration. > I understand I cannot re-key after starting the iteration, as IterativeStream > does not support keyBy() and throws an UnsupportedOperationException "Cannot > change the input partitioning of an iteration head directly. Apply the > partitioning on the input and feedback streams instead." > > Is there any way of using keyed state within an iteration? > BTW, > I am using Flink 1.15.2 and I am bound to that version > > Regards > Lorenzo -- best, Zhipeng
