Hi devs, I'd like to bring the discussion over FLIP-141[1], which proposes how managed memory should be shared by various use cases within a slot. This is an extension to FLIP-53[2], where we assumed that RocksDB state backend and batch operators are the only use cases of managed memory for streaming and batch jobs respectively, which is no longer true with the introduction of Python UDFs.
Please notice that we have not reached consensus between two different designs. The major part of this FLIP describes one of the candidates, while the alternative is discussed in the section "Rejected Alternatives". We are hoping to borrow intelligence from the community to help us resolve the disagreement. Any feedback would be appreciated. Thank you~ Xintong Song [1] https://cwiki.apache.org/confluence/display/FLINK/FLIP-141%3A+Intra-Slot+Managed+Memory+Sharing#FLIP141:IntraSlotManagedMemorySharing-compatibility [2] https://cwiki.apache.org/confluence/display/FLINK/FLIP-53%3A+Fine+Grained+Operator+Resource+Management
