On Mon, Dec 26, 2022 at 6:59 PM Amit Kapila <amit.kapil...@gmail.com> wrote: >
In the commit message, there is a statement like this "However, if the leader apply worker times out while attempting to send a message to the parallel apply worker, it will switch to "partial serialize" mode - in this mode the leader serializes all remaining changes to a file and notifies the parallel apply workers to read and apply them at the end of the transaction." I think it is a good idea to serialize the change to the file in this case to avoid deadlocks, but why does the parallel worker need to wait till the transaction commits to reading the file? I mean we can switch the serialize state and make a parallel worker pull changes from the file and if the parallel worker has caught up with the changes then it can again change the state to "share memory" and now the apply worker can again start sending through shared memory. I think generally streaming transactions are large and it is possible that the shared memory queue gets full because of a lot of changes for a particular transaction but later when the load switches to the other transactions then it would be quite common for the worker to catch up with the changes then it better to again take advantage of using memory. Otherwise, in this case, we are just wasting resources (worker/shared memory queue) but still writing in the file. -- Regards, Dilip Kumar EnterpriseDB: http://www.enterprisedb.com