Yes, it might be the case. Hard to tell for sure without looking at the job, metrics etc. Just be mindful of what I described, and if you want to fine tune a job and set different parallelism values for different operators, pay attention to where those operators are being distributed. Usually in practice there is little reason to choose (1-2-1-1-1) over (2-2-2-2-2). If you spread a load of some operators more than you need? Usually not an issue. On the other hand with (2-2-2-2-2) you will spread the load more evenly across task managers, which makes it easier to tune/analyse/optimise.
Best, Piotrek pt., 5 mar 2021 o 09:10 Jan Nitschke <nitschke...@web.de> napisał(a): > Hey Piotr, > > thanks for your answer, that makes perfect sense. However, when looking at > the number of messages being processed, we can see that both subtasks on > task 2 will produce the same amount of messages in the (1-2-1-1-1) > scenario, even with the first task hitting backpressure. We assume that > this has to do with the distribution of messages between task. As messages > are being distributed equally among subtasks in our case, would this be an > explanation for that behavior? > > Best, > Jan > > > *Gesendet:* Mittwoch, 03. März 2021 um 19:53 Uhr > *Von:* "Piotr Nowojski" <pnowoj...@apache.org> > *An:* "Jan Nitschke" <nitschke...@web.de> > *Cc:* "user" <user@flink.apache.org> > *Betreff:* Re: Independence of task parallelism > Hi Jan, > > As far as I remember, Flink doesn't handle very well cases like > (1-2-1-1-1) and two Task Managers. There are no guarantees how the > operators/subtasks are going to be scheduled, but most likely it will be as > you mentioned/observed. First task manager will be handling all of the > operators, while the second task manager will only be running a single > instance of the second operator (for load balancing reasons it would be > better to spread the tasks across those two Task Managers more evenly). > > No, Flink doesn't hold any resources (appart of network buffers) per task. > All of the available memory and CPU resources are shared across all of the > running tasks. So in the (1-2-1-1-1) case, if the first task manager will > be overloaded (for example if it has very few CPU cores), the second task > will perform much better on the second task manager (which will be empty), > causing a throughput skew. From this perspective, (2-2-2-2-2) would most > likely be performing better, as the load would be more evenly spread. > > Piotrek > > niedz., 28 lut 2021 o 13:10 Jan Nitschke <nitschke...@web.de> napisał(a): > >> Hello, >> >> We are working on a project where we want to gather information about the >> job performance across different task level parallelism settings. >> Essentially, we want to see how the throughput of a single task varies >> across different parallelism settings, e.g. for a job of 5 tasks: 1-1-1-1-1 >> vs. 1-2-1-1-1 vs. 2-2-2-2-2. >> >> *We are running flink on Kubernetes, a job with 5 tasks, slot sharing is >> enabled, operator chasing is disabled and each task manager has one slot.* >> >> So, the number of task managers is always the number of the highest >> parallelism and wen can fit the entire job into one task manager slot. >> >> We are then running the job against multiple parallelism configs (such as >> those above), collect the relevant metrics and try to get some useful >> information out of them. >> >> We are now wondering how independent our results are from one another. >> More specifically, if we now look at the parallelism of the second task, is >> its performance independent of the parallelism of the other tasks? So, will >> a the second task perform the same in (1-2-1-1-1) as in (2-2-2-2-2)? >> >> Our take on it is the following: With our setup, (1-2-1-1-1) should >> result in one task manager holding the entire job and a second task manager >> that only runs the second task. (2-2-2-2-2) will run two task managers with >> the entire job. So, theoretically, the second task should have much more >> resources available in the first setup as it has the entire resources of >> that task manager to its disposal. Does that assumption hold or will flink >> assign a certain amount of resources to a task in a task manager no matter >> how many other tasks are running on that same task manager slot? >> >> We would highly appreciate any help. >> >> Best, >> Jan >> >
