Bumping this thread. Thanks! Best regards, Yuepeng Pan
Pan Yuepeng <[email protected]> 于2025年12月15日周一 12:40写道： > Hi devs, > > I re-sorted out and supplemented the 'FLIP-339[1] Support Adaptive > Partition Selection for StreamPartitioner' based on Flink JIRA[2]. > > Flink offers multiple partition strategies, some of which bind data to > downstream subtasks, while others do not (e.g., shuffle, rescale, > rebalance). > For [Data not bound to subtasks] scenarios, overloaded sub-task-nodes may > slow down the processing of Flink jobs, leading to backpressure and data > lag. Dynamically adjusting the partition of data to subtasks based on the > processing load of downstream operators helps achieve a peak-shaving and > valley-filling effect, thereby striving to maintain the throughput of Flink > jobs. > > The raw discussions could be found in the Flink JIRA[2]. > I really appreciate developers involved in the discussion for the valuable > help and suggestions in advance. > > Please refer to the FLIP[1] wiki for more details about the proposed > design and implementation. > > Welcome any feedback and opinions on this proposal. > > [1] https://cwiki.apache.org/confluence/x/nYyzDw > [2] https://issues.apache.org/jira/browse/FLINK-31655 > > Best regards, > Yuepeng Pan >
