Hi Chesney and Piotr, I have seen some jobs with tens of independent vertices that process data for the same business. The sub jobs should be started or stopped together. Splitting them into separate jobs means the user has to manage them separately. But in fact the jobs were running in per-job mode, and maybe there's now a better choice. Let's see if others have some more valuable cases.
By the way, I'd like to point out that if we can checkpoint pipeline regions individually, even a job with only one job graph, if it has no all-to-all edges connecting all vertices into one pipeline region, may benefit from this effort, since any failure, long-time pause or backpressure in a pipeline region will not block the checkpointing of other regions. And @Piotr, this is why I think that this discussion may relate to the task-local checkpoints. Both of them require to checkpoint parts of a job individually, and can restore only a part of the job, without breaking the consistency. The main difference is that to maintain the consistency, task-local checkpoints have to handle the channel data. This is omitted in the approximate task-local recovery since the consistency is not guaranteed, and this is why the approximate task-local recovery may use a part of the global snapshot, rather than individually checkpointing each subtask. However, in the pipeline region checkpoints, consistency is guaranteed naturally. We can focus on how to checkpoint individually, the effort of which is probably necessary if we want to implement the task-local checkpointing with consistency guarantee. On Tue, Feb 8, 2022 at 7:41 PM 丛鹏 <congpeng0...@gmail.com> wrote: > hi guys，If I understand it correctly, will only some checkpoints be > recovered when there is an error in the Flink batch？ > > Piotr Nowojski <pnowoj...@apache.org> 于2022年2月8日周二 19:05写道： > >> Hi, >> >> I second Chesnay's comment and would like to better understand the >> motivation behind this. At the surface it sounds to me like this might >> require quite a bit of work for a very narrow use case. >> >> At the same time I have a feeling that Yuan, you are mixing this feature >> request (checkpointing subgraphs/pipeline regions independently) and a >> very >> very different issue of "task local checkpoints"? Those problems are kind >> of similar, but not quite. >> >> Best, >> Piotrek >> >> wt., 8 lut 2022 o 11:44 Chesnay Schepler <ches...@apache.org> napisał(a): >> >> > Could someone expand on these operational issues you're facing when >> > achieving this via separate jobs? >> > >> > I feel like we're skipping a step, arguing about solutions without even >> > having discussed the underlying problem. >> > >> > On 08/02/2022 11:25, Gen Luo wrote: >> > > Hi, >> > > >> > > @Yuan >> > > Do you mean that there should be no shared state between source >> subtasks? >> > > Sharing state between checkpoints of a specific subtask should be >> fine. >> > > >> > > Sharing state between subtasks of a task can be an issue, no matter >> > whether >> > > it's a source. That's also what I was afraid of in the previous >> replies. >> > In >> > > one word, if the behavior of a pipeline region can somehow influence >> the >> > > state of other pipeline regions, their checkpoints have to be aligned >> > > before rescaling. >> > > >> > > On Tue, Feb 8, 2022 at 5:27 PM Yuan Mei <yuanmei.w...@gmail.com> >> wrote: >> > > >> > >> Hey Folks, >> > >> >> > >> Thanks for the discussion! >> > >> >> > >> *Motiviation and use cases* >> > >> I think motiviation and use cases are very clear and I do not have >> > doubts >> > >> on this part. >> > >> A typical use case is ETL with two-phase-commit, hundreds of >> partitions >> > can >> > >> be blocked by a single straggler (a single task's checkpoint abortion >> > can >> > >> affect all, not necessary failure). >> > >> >> > >> *Source offset redistribution* >> > >> As for the known sources & implementation for Flink, I can not find a >> > case >> > >> that does not work, *for now*. >> > >> I need to dig a bit more: how splits are tracked assigned, not >> > successfully >> > >> processed, succesffully processed e.t.c. >> > >> I guess it is a single shared source OPCoordinator. And how this >> > *shared* >> > >> state (between tasks) is preserved? >> > >> >> > >> *Input partition/splits treated completely independent from each >> other* >> > >> This part I am still not sure, as mentioned if we have shared state >> of >> > >> source in the above section. >> > >> >> > >> To Thomas: >> > >>> In Yuan's example, is there a reason why CP8 could not be promoted >> to >> > >>> CP10 by the coordinator for PR2 once it receives the notification >> that >> > >>> CP10 did not complete? It appears that should be possible since in >> its >> > >>> effect it should be no different than no data processed between CP8 >> > >>> and CP10? >> > >> Not sure what "promoted" means here, but >> > >> 1. I guess it does not matter whether it is CP8 or CP10 any more, >> > >> if no shared state in source, as exactly what you meantinoed, >> > >> "it should be no different than no data processed between CP8 and >> CP10" >> > >> >> > >> 2. I've noticed that from this question there is a gap between >> > >> "*allow aborted/failed checkpoint in independent sub-graph*" and >> > >> my intention: "*independent sub-graph checkpointing indepently*" >> > >> >> > >> Best >> > >> Yuan >> > >> >> > >> >> > >> On Tue, Feb 8, 2022 at 11:34 AM Gen Luo <luogen...@gmail.com> wrote: >> > >> >> > >>> Hi, >> > >>> >> > >>> I'm thinking about Yuan's case. Let's assume that the case is >> running >> > in >> > >>> current Flink: >> > >>> 1. CP8 finishes >> > >>> 2. For some reason, PR2 stops consuming records from the source >> (but is >> > >> not >> > >>> stuck), and PR1 continues consuming new records. >> > >>> 3. CP9 and CP10 finish >> > >>> 4. PR2 starts to consume quickly to catch up with PR1, and reaches >> the >> > >> same >> > >>> final status with that in Yuan's case before CP11 starts. >> > >>> >> > >>> I support that in this case, the status of the job can be the same >> as >> > in >> > >>> Yuan's case, and the snapshot (including source states) taken at >> CP10 >> > >>> should be the same as the composed global snapshot in Yuan's case, >> > which >> > >> is >> > >>> combining CP10 of PR1 and CP8 of PR2. This should be true if neither >> > >> failed >> > >>> checkpointing nor uncommitted consuming have side effects, both of >> > which >> > >>> can break the exactly-once semantics when replaying. So I think >> there >> > >>> should be no difference between rescaling the combined global >> snapshot >> > or >> > >>> the globally taken one, i.e. if the input partitions are not >> > independent, >> > >>> we are probably not able to rescale the source state in the current >> > Flink >> > >>> eiter. >> > >>> >> > >>> And @Thomas, I do agree that the operational burden is >> > >>> significantly reduced, while I'm a little afraid that checkpointing >> the >> > >>> subgraphs individually may increase most of the runtime overhead >> back >> > >>> again. Maybe we can find a better way to implement this. >> > >>> >> > >>> On Tue, Feb 8, 2022 at 5:11 AM Thomas Weise <t...@apache.org> wrote: >> > >>> >> > >>>> Hi, >> > >>>> >> > >>>> Thanks for opening this discussion! The proposed enhancement would >> be >> > >>>> interesting for use cases in our infrastructure as well. >> > >>>> >> > >>>> There are scenarios where it makes sense to have multiple >> disconnected >> > >>>> subgraphs in a single job because it can significantly reduce the >> > >>>> operational burden as well as the runtime overhead. Since we allow >> > >>>> subgraphs to recover independently, then why not allow them to make >> > >>>> progress independently also, which would imply that checkpointing >> must >> > >>>> succeed for non affected subgraphs as certain behavior is tied to >> > >>>> checkpoint completion, like Kafka offset commit, file output etc. >> > >>>> >> > >>>> As for source offset redistribution, offset/position needs to be >> tied >> > >>>> to splits (in FLIP-27) and legacy sources. (It applies to both >> Kafka >> > >>>> and Kinesis legacy sources and FLIP-27 Kafka source.). With the new >> > >>>> source framework, it would be hard to implement a source with >> correct >> > >>>> behavior that does not track the position along with the split. >> > >>>> >> > >>>> In Yuan's example, is there a reason why CP8 could not be promoted >> to >> > >>>> CP10 by the coordinator for PR2 once it receives the notification >> that >> > >>>> CP10 did not complete? It appears that should be possible since in >> its >> > >>>> effect it should be no different than no data processed between CP8 >> > >>>> and CP10? >> > >>>> >> > >>>> Thanks, >> > >>>> Thomas >> > >>>> >> > >>>> On Mon, Feb 7, 2022 at 2:36 AM Till Rohrmann <trohrm...@apache.org >> > >> > >>> wrote: >> > >>>>> Thanks for the clarification Yuan and Gen, >> > >>>>> >> > >>>>> I agree that the checkpointing of the sources needs to support the >> > >>>>> rescaling case, otherwise it does not work. Is there currently a >> > >> source >> > >>>>> implementation where this wouldn't work? For Kafka it should work >> > >>> because >> > >>>>> we store the offset per assigned partition. For Kinesis it is >> > >> probably >> > >>>> the >> > >>>>> same. For the Filesource we store the set of unread input splits >> in >> > >> the >> > >>>>> source coordinator and the state of the assigned splits in the >> > >> sources. >> > >>>>> This should probably also work since new splits are only handed >> out >> > >> to >> > >>>>> running tasks. >> > >>>>> >> > >>>>> Cheers, >> > >>>>> Till >> > >>>>> >> > >>>>> On Mon, Feb 7, 2022 at 10:29 AM Yuan Mei <yuanmei.w...@gmail.com> >> > >>> wrote: >> > >>>>>> Hey Till, >> > >>>>>> >> > >>>>>>> Why rescaling is a problem for pipelined regions/independent >> > >>>> execution >> > >>>>>> subgraphs: >> > >>>>>> >> > >>>>>> Take a simplified example : >> > >>>>>> job graph : source (2 instances) -> sink (2 instances) >> > >>>>>> execution graph: >> > >>>>>> source (1/2) -> sink (1/2) [pieplined region 1] >> > >>>>>> source (2/2) -> sink (2/2) [pieplined region 2] >> > >>>>>> >> > >>>>>> Let's assume checkpoints are still triggered globally, meaning >> > >>>> different >> > >>>>>> pipelined regions share the global checkpoint id (PR1 CP1 matches >> > >>> with >> > >>>> PR2 >> > >>>>>> CP1). >> > >>>>>> >> > >>>>>> Now let's assume PR1 completes CP10 and PR2 completes CP8. >> > >>>>>> >> > >>>>>> Let's say we want to rescale to parallelism 3 due to increased >> > >> input. >> > >>>>>> - Notice that we can not simply rescale based on the latest >> > >> completed >> > >>>>>> checkpoint (CP8), because PR1 has already had data (CP8 -> CP10) >> > >>> output >> > >>>>>> externally. >> > >>>>>> - Can we take CP10 from PR1 and CP8 from PR2? I think it depends >> on >> > >>>> how the >> > >>>>>> source's offset redistribution is implemented. >> > >>>>>> The answer is yes if we treat each input partition as >> > >> independent >> > >>>> from >> > >>>>>> each other, *but I am not sure whether we can make that >> > >> assumption*. >> > >>>>>> If not, the rescaling cannot happen until PR1 and PR2 are aligned >> > >>> with >> > >>>> CPs. >> > >>>>>> Best >> > >>>>>> -Yuan >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> On Mon, Feb 7, 2022 at 4:17 PM Till Rohrmann < >> trohrm...@apache.org >> > >>>> wrote: >> > >>>>>>> Hi everyone, >> > >>>>>>> >> > >>>>>>> Yuan and Gen could you elaborate why rescaling is a problem if >> we >> > >>> say >> > >>>>>> that >> > >>>>>>> separate pipelined regions can take checkpoints independently? >> > >>>>>>> Conceptually, I somehow think that a pipelined region that is >> > >>> failed >> > >>>> and >> > >>>>>>> cannot create a new checkpoint is more or less the same as a >> > >>>> pipelined >> > >>>>>>> region that didn't get new input or a very very slow pipelined >> > >>> region >> > >>>>>> which >> > >>>>>>> couldn't read new records since the last checkpoint (assuming >> > >> that >> > >>>> the >> > >>>>>>> checkpoint coordinator can create a global checkpoint by >> > >> combining >> > >>>>>>> individual checkpoints (e.g. taking the last completed >> checkpoint >> > >>>> from >> > >>>>>> each >> > >>>>>>> pipelined region)). If this comparison is correct, then this >> > >> would >> > >>>> mean >> > >>>>>>> that we have rescaling problems under the latter two cases. >> > >>>>>>> >> > >>>>>>> Cheers, >> > >>>>>>> Till >> > >>>>>>> >> > >>>>>>> On Mon, Feb 7, 2022 at 8:55 AM Gen Luo <luogen...@gmail.com> >> > >>> wrote: >> > >>>>>>>> Hi Gyula, >> > >>>>>>>> >> > >>>>>>>> Thanks for sharing the idea. As Yuan mentioned, I think we can >> > >>>> discuss >> > >>>>>>> this >> > >>>>>>>> within two scopes. One is the job subgraph, the other is the >> > >>>> execution >> > >>>>>>>> subgraph, which I suppose is the same as PipelineRegion. >> > >>>>>>>> >> > >>>>>>>> An idea is to individually checkpoint the PipelineRegions, for >> > >>> the >> > >>>>>>>> recovering in a single run. >> > >>>>>>>> >> > >>>>>>>> Flink has now supported PipelineRegion based failover, with a >> > >>>> subset >> > >>>>>> of a >> > >>>>>>>> global checkpoint snapshot. The checkpoint barriers are spread >> > >>>> within a >> > >>>>>>>> PipelineRegion, so the checkpointing of individual >> > >>> PipelineRegions >> > >>>> is >> > >>>>>>>> actually independent. Since in a single run of a job, the >> > >>>>>> PipelineRegions >> > >>>>>>>> are fixed, we can individually checkpoint separated >> > >>>> PipelineRegions, >> > >>>>>>>> despite what status the other PipelineRegions are, and use a >> > >>>> snapshot >> > >>>>>> of >> > >>>>>>> a >> > >>>>>>>> failing region to recover, instead of the subset of a global >> > >>>> snapshot. >> > >>>>>>> This >> > >>>>>>>> can support separated job subgraphs as well, since they will >> > >> also >> > >>>> be >> > >>>>>>>> separated into different PipelineRegions. I think this can >> > >>> fulfill >> > >>>> your >> > >>>>>>>> needs. >> > >>>>>>>> >> > >>>>>>>> In fact the individual snapshots of all PipelineRegions can >> > >> form >> > >>> a >> > >>>>>> global >> > >>>>>>>> snapshot, and the alignment of snapshots of individual regions >> > >> is >> > >>>> not >> > >>>>>>>> necessary. But rescaling this global snapshot can be >> > >> potentially >> > >>>>>>> complex. I >> > >>>>>>>> think it's better to use the individual snapshots in a single >> > >>> run, >> > >>>> and >> > >>>>>>> take >> > >>>>>>>> a global checkpoint/savepoint before restarting the job, >> > >>> rescaling >> > >>>> it >> > >>>>>> or >> > >>>>>>>> not. >> > >>>>>>>> >> > >>>>>>>> A major issue of this plan is that it breaks the checkpoint >> > >>>> mechanism >> > >>>>>> of >> > >>>>>>>> Flink. As far as I know, even in the approximate recovery, the >> > >>>> snapshot >> > >>>>>>>> used to recover a single task is still a part of a global >> > >>>> snapshot. To >> > >>>>>>>> implement the individual checkpointing of PipelineRegions, >> > >> there >> > >>>> may >> > >>>>>> need >> > >>>>>>>> to be a checkpoint coordinator for each PipelineRegion, and a >> > >> new >> > >>>>>> global >> > >>>>>>>> checkpoint coordinator. When the scale goes up, there can be >> > >> many >> > >>>>>>>> individual regions, which can be a big burden to the job >> > >> manager. >> > >>>> The >> > >>>>>>>> meaning of the checkpoint id will also be changed, which can >> > >>> affect >> > >>>>>> many >> > >>>>>>>> aspects. There can be lots of work and risks, and the risks >> > >> still >> > >>>> exist >> > >>>>>>> if >> > >>>>>>>> we only individually checkpoint separated job subgraphs, since >> > >>> the >> > >>>>>>>> mechanism is still broken. If that is what you need, maybe >> > >>>> separating >> > >>>>>>> them >> > >>>>>>>> into different jobs is an easier and better choice, as Caizhi >> > >> and >> > >>>> Yuan >> > >>>>>>>> mentioned. >> > >>>>>>>> >> > >>>>>>>> On Mon, Feb 7, 2022 at 11:39 AM Yuan Mei < >> > >> yuanmei.w...@gmail.com >> > >>>>>> wrote: >> > >>>>>>>>> Hey Gyula, >> > >>>>>>>>> >> > >>>>>>>>> That's a very interesting idea. The discussion about the >> > >>>> `Individual` >> > >>>>>>> vs >> > >>>>>>>>> `Global` checkpoint was raised before, but the main concern >> > >> was >> > >>>> from >> > >>>>>>> two >> > >>>>>>>>> aspects: >> > >>>>>>>>> >> > >>>>>>>>> - Non-deterministic replaying may lead to an inconsistent >> > >> view >> > >>> of >> > >>>>>>>>> checkpoint >> > >>>>>>>>> - It is not easy to form a clear cut of past and future and >> > >>>> hence no >> > >>>>>>>> clear >> > >>>>>>>>> cut of where the start point of the source should begin to >> > >>> replay >> > >>>>>> from. >> > >>>>>>>>> Starting from independent subgraphs as you proposed may be a >> > >>> good >> > >>>>>>>> starting >> > >>>>>>>>> point. However, when we talk about subgraph, do we mention it >> > >>> as >> > >>>> a >> > >>>>>> job >> > >>>>>>>>> subgraph (each vertex is one or more operators) or execution >> > >>>> subgraph >> > >>>>>>>> (each >> > >>>>>>>>> vertex is a task instance)? >> > >>>>>>>>> >> > >>>>>>>>> If it is a job subgraph, then indeed, why not separate it >> > >> into >> > >>>>>> multiple >> > >>>>>>>>> jobs as Caizhi mentioned. >> > >>>>>>>>> If it is an execution subgraph, then it is difficult to >> > >> handle >> > >>>>>>> rescaling >> > >>>>>>>>> due to inconsistent views of checkpoints between tasks of the >> > >>>> same >> > >>>>>>>>> operator. >> > >>>>>>>>> >> > >>>>>>>>> `Individual/Subgraph Checkpointing` is definitely an >> > >>> interesting >> > >>>>>>>> direction >> > >>>>>>>>> to think of, and I'd love to hear more from you! >> > >>>>>>>>> >> > >>>>>>>>> Best, >> > >>>>>>>>> >> > >>>>>>>>> Yuan >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> >> > >>>>>>>>> On Mon, Feb 7, 2022 at 10:16 AM Caizhi Weng < >> > >>>> tsreape...@gmail.com> >> > >>>>>>>> wrote: >> > >>>>>>>>>> Hi Gyula! >> > >>>>>>>>>> >> > >>>>>>>>>> Thanks for raising this discussion. I agree that this will >> > >> be >> > >>>> an >> > >>>>>>>>>> interesting feature but I actually have some doubts about >> > >> the >> > >>>>>>>> motivation >> > >>>>>>>>>> and use case. If there are multiple individual subgraphs in >> > >>> the >> > >>>>>> same >> > >>>>>>>> job, >> > >>>>>>>>>> why not just distribute them to multiple jobs so that each >> > >>> job >> > >>>>>>> contains >> > >>>>>>>>>> only one individual graph and can now fail without >> > >> disturbing >> > >>>> the >> > >>>>>>>> others? >> > >>>>>>>>>> >> > >>>>>>>>>> Gyula Fóra <gyf...@apache.org> 于2022年2月7日周一 05:22写道： >> > >>>>>>>>>> >> > >>>>>>>>>>> Hi all! >> > >>>>>>>>>>> >> > >>>>>>>>>>> At the moment checkpointing only works for healthy jobs >> > >>> with >> > >>>> all >> > >>>>>>>>> running >> > >>>>>>>>>>> (or some finished) tasks. This sounds reasonable in most >> > >>>> cases >> > >>>>>> but >> > >>>>>>>>> there >> > >>>>>>>>>>> are a few applications where it would make sense to >> > >>>> checkpoint >> > >>>>>>>> failing >> > >>>>>>>>>> jobs >> > >>>>>>>>>>> as well. >> > >>>>>>>>>>> >> > >>>>>>>>>>> Due to how the checkpointing mechanism works, subgraphs >> > >>> that >> > >>>>>> have a >> > >>>>>>>>>> failing >> > >>>>>>>>>>> task cannot be checkpointed without violating the >> > >>>> exactly-once >> > >>>>>>>>> semantics. >> > >>>>>>>>>>> However if the job has multiple independent subgraphs >> > >> (that >> > >>>> are >> > >>>>>> not >> > >>>>>>>>>>> connected to each other), even if one subgraph is >> > >> failing, >> > >>>> the >> > >>>>>>> other >> > >>>>>>>>>>> completely running one could be checkpointed. In these >> > >>> cases >> > >>>> the >> > >>>>>>>> tasks >> > >>>>>>>>> of >> > >>>>>>>>>>> the failing subgraph could simply inherit the last >> > >>> successful >> > >>>>>>>>> checkpoint >> > >>>>>>>>>>> metadata (before they started failing). This logic would >> > >>>> produce >> > >>>>>> a >> > >>>>>>>>>>> consistent checkpoint. >> > >>>>>>>>>>> >> > >>>>>>>>>>> The job as a whole could now make stateful progress even >> > >> if >> > >>>> some >> > >>>>>>>>>> subgraphs >> > >>>>>>>>>>> are constantly failing. This can be very valuable if for >> > >>> some >> > >>>>>>> reason >> > >>>>>>>>> the >> > >>>>>>>>>>> job has a larger number of independent subgraphs that are >> > >>>>>> expected >> > >>>>>>> to >> > >>>>>>>>>> fail >> > >>>>>>>>>>> every once in a while, or if some subgraphs can have >> > >> longer >> > >>>>>>> downtimes >> > >>>>>>>>>> that >> > >>>>>>>>>>> would now cause the whole job to stall. >> > >>>>>>>>>>> >> > >>>>>>>>>>> What do you think? >> > >>>>>>>>>>> >> > >>>>>>>>>>> Cheers, >> > >>>>>>>>>>> Gyula >> > >>>>>>>>>>> >> > >> > >> >
