Hi folks, I just finished reading the previous emails. It was a good discussion. Here are my two cents:
*Is OperatorCoordinator a public API?* Regarding the OperatorCoordinator, although it is marked as internal interface at this point, I intended to make it a public interface when add that in FLIP-27. This is a powerful cross-subtask communication mechanism that enables many use cases, Source / Sink / TF on Flink / CEP here again. To my understanding, OC was marked as internal because we think it is not stable enough yet. We may need to fortify the OperatorEvent delivery semantic a little bit so it works well with checkpoint in general. I think it is a valid concern that user code running in JM may cause instability. However, not providing this communication mechanism only makes a lot of use case even harder to implement. So it seems that having the OC exposed to end users brings more benefits than harm to Flink. At the end of the day, users have many ways to crash a Flink job if they do not write proper code. So making those who know what they do happy seems more important here. *OperatorCoordinator V.S. side-input / broadcast stream* I think both of them can achieve the goal of dynamic patterns. The main difference is the extensibility. OC is a 2-way communication mechanism, i.e. a subtask can also send OperatorEvent to the coordinator to report its owns status, so that the coordinator can act accordingly. This is sometimes useful. For example, a single invalid pattern can be disabled elegantly without crashing the entire Flink job. In the future, if we allow users to send external command to OC via JM, a default self-contained implementation can just update the pattern via the REST API without external dependencies. Another reason I personally prefer OC is because it is an explicit control plain mechanism, where as the side-input / broadcast stream has are more vague semantic. Thanks, Jiangjie (Becket) Qin On Tue, Dec 21, 2021 at 4:25 PM David Morávek <d...@apache.org> wrote: > Hi Yunfeng, > > thanks for drafting this FLIP, this will be a great addition into the CEP > toolbox! > > Apart from running user code in JM, which want to avoid in general, I'd > have one more another concern about using the OperatorCoordinator and that > is re-processing of the historical data. Any thoughts about how this will > work with the OC? > > I have a slight feeling that a side-input (custom source / operator + > broadcast) would a better fit for this case. This would simplify the > consistency concerns (watermarks + pushback) and the re-processing of > historical data. > > Best, > D. > > > On Tue, Dec 21, 2021 at 6:47 AM Nicholas Jiang <nicholasji...@apache.org> > wrote: > > > Hi Konstantin, Martijn > > > > Thanks for the detailed feedback in the discussion. What I still have > left > > to answer/reply to: > > > > -- Martijn: Just to be sure, this indeed would mean that if for whatever > > reason the heartbeat timeout, it would crash the job, right? > > > > IMO, if for whatever reason the heartbeat timeout, it couldn't check the > > PatternProcessor consistency between the OperatorCoordinator and the > > subtasks so that the job would be crashed. > > > > -- Konstantin: What I was concerned about is that we basically let users > > run a UserFunction in the OperatorCoordinator, which it does not seem to > > have been designed for. > > > > In general, we have reached an agreement on the design of this FLIP, but > > there are some concerns on the OperatorCoordinator, about whether > basically > > let users run a UserFunction in the OperatorCoordinator is designed for > > OperatorCoordinator. We would like to invite Becket Qin who is the author > > of OperatorCoordinator to help us to answer this concern. > > > > Best, > > Nicholas Jiang > > > > > > On 2021/12/20 10:07:14 Martijn Visser wrote: > > > Hi all, > > > > > > Really like the discussion on this topic moving forward. I really think > > > this feature will be much appreciated by the Flink users. What I still > > have > > > left to answer/reply to: > > > > > > -- Good point. If for whatever reason the different taskmanagers can't > > get > > > the latest rule, the Operator Coordinator could send a heartbeat to all > > > taskmanagers with the latest rules and check the heartbeat response > from > > > all the taskmanagers whether the latest rules of the taskmanager is > equal > > > to these of the Operator Coordinator. > > > > > > Just to be sure, this indeed would mean that if for whatever reason the > > > heartbeat timeout, it would crash the job, right? > > > > > > -- We have consided about the solution mentioned above. In this > > solution, I > > > have some questions about how to guarantee the consistency of the rule > > > between each TaskManager. By having a coodinator in the JobManager to > > > centrally manage the latest rules, the latest rules of all TaskManagers > > are > > > consistent with those of the JobManager, so as to avoid the > > inconsistencies > > > that may be encountered in the above solution. Can you introduce how > this > > > solution guarantees the consistency of the rules? > > > > > > The consistency that we could guarantee was based on how often each > > > TaskManager would do a refresh and how often we would accept a refresh > to > > > fail. We set the refresh time to a relatively short one (30 seconds) > and > > > maximum failures to 3. That meant that we could guarantee that rules > > would > > > be updated in < 2 minutes or else the job would crash. That was > > sufficient > > > for our use cases. This also really depends on how big your cluster > is. I > > > can imagine that if you have a large scale cluster that you want to > run, > > > you don't want to DDOS the backend system where you have your rules > > stored. > > > > > > -- In summary, the current design is that JobManager tells all > > TaskManagers > > > the latest rules through OperatorCoodinator, and will initiate a > > heartbeat > > > to check whether the latest rules on each TaskManager are consistent. > We > > > will describe how to deal with the Failover scenario in more detail on > > FLIP. > > > > > > Thanks for that. I think having the JobManager tell the TaskManagers > the > > > applicable rules would indeed end up being the best design. > > > > > > -- about the concerns around consistency raised by Martijn: I think a > lot > > > of those can be mitigated by using an event time timestamp from which > the > > > rules take effect. The reprocessing scenario, for example, is covered > by > > > this. If a pattern processor should become active as soon as possible, > > > there will still be inconsistencies between Taskmanagers, but "as soon > as > > > possible" is vague anyway, which is why I think that's ok. > > > > > > I think an event timestamp is indeed a really important one. We also > used > > > that in my previous role, with the ruleActivationTimestamp compared to > > > eventtime (well, actually we used Kafka logAppend time because > > > eventtime wasn't always properly set so we used that time to overwrite > > the > > > eventtime from the event itself). > > > > > > Best regards, > > > > > > Martijn > > > > > > On Mon, 20 Dec 2021 at 09:08, Konstantin Knauf <kna...@apache.org> > > wrote: > > > > > > > Hi Nicholas, Hi Junfeng, > > > > > > > > about the concerns around consistency raised by Martijn: I think a > lot > > of > > > > those can be mitigated by using an event time timestamp from which > the > > > > rules take effect. The reprocessing scenario, for example, is covered > > by > > > > this. If a pattern processor should become active as soon as > possible, > > > > there will still be inconsistencies between Taskmanagers, but "as > soon > > as > > > > possible" is vague anyway, which is why I think that's ok. > > > > > > > > about naming: The naming with "PatternProcessor" sounds good to me. > > Final > > > > nit: I would go for CEP#patternProccessors, which would be consistent > > with > > > > CEP#pattern. > > > > > > > > I am not sure about one of the rejected alternatives: > > > > > > > > > Have each subtask of an operator make the update on their own > > > > > > > > - > > > > > > > > It is hard to achieve consistency. > > > > - > > > > > > > > Though the time interval that each subtask makes the update can > > be > > > > the same, the absolute time they make the update might be > > different. > > > > For > > > > example, one makes updates at 10:00, 10:05, etc, while another > > does > > > > it at > > > > 10:01, 10:06. In this case the subtasks might never processing > > data > > > > with > > > > the same set of pattern processors. > > > > > > > > > > > > I would have thought that it is quite easy to poll for the rules from > > each > > > > Subtask at *about *the same time. So, this alone does not seem to be > > > > enough to rule out this option. I've looped in David Moravek to get > his > > > > opinion of the additional load imposed on the JM. > > > > > > > > Thanks, > > > > > > > > Konstantin > > > > > > > > On Mon, Dec 20, 2021 at 4:06 AM Nicholas Jiang < > > nicholasji...@apache.org> > > > > wrote: > > > > > > > > > Hi Yue, > > > > > > > > > > Thanks for your feedback of the FLIP. I have addressed your > > questions and > > > > > made a corresponding explanation as follows: > > > > > > > > > > -- About Pattern Updating. If we use PatternProcessoerDiscoverer to > > > > update > > > > > the rules, will it increase the load of JM? For example, if the > user > > > > wants > > > > > the updated rule to take effect immediately,, which means that we > > need to > > > > > set a shorter check interval or there is another scenario when > users > > > > rarely > > > > > update the pattern, will the PatternProcessoerDiscoverer be in most > > of > > > > the > > > > > time Do useless checks ? Will a lazy update mode could be used, > > which the > > > > > pattern only be updated when triggered by the user, and do nothing > at > > > > other > > > > > times? > > > > > > > > > > PatternProcessoerDiscoverer is a user-defined interface to discover > > the > > > > > PatternProcessor updates. Periodically checking the > PatternProcessor > > in > > > > the > > > > > database is a implementation of the PatternProcessoerDiscoverer > > > > interface, > > > > > which is that periodically querys all the PatternProcessor table in > > > > certain > > > > > interval. This implementation indeeds has the useless checks, and > > could > > > > > directly integrates the changelog of the table. In addition, in > > addition > > > > to > > > > > the implementation of periodically checking the database, there are > > other > > > > > implementations such as the PatternProcessor that provides Restful > > > > services > > > > > to receive updates. > > > > > > > > > > -- I still have some confusion about how Key Generating Opertator > > and > > > > > CepOperator (Pattern Matching & Processing Operator) work together. > > If > > > > > there are N PatternProcessors, will the Key Generating Opertator > > > > generate N > > > > > keyedStreams, and then N CepOperator would process each Key > > separately ? > > > > Or > > > > > every CepOperator Task would process all patterns, if so, does the > > key > > > > type > > > > > in each PatternProcessor need to be the same? > > > > > > > > > > Firstly the Pattern Matching & Processing Operator is not the > > CepOperator > > > > > at present, because CepOperator mechanism is based on the NFAState. > > > > > Secondly if there are N PatternProcessors, the Key Generating > > Opertator > > > > > combines all the keyedStreams with keyBy() operation, thus the > > Pattern > > > > > Matching & Processing Operator would process all the patterns. In > > other > > > > > words, the KeySelector of the PatternProcessor is used for the Key > > > > > Generating Opertator, and the Pattern and PatternProceessFunction > of > > the > > > > > PatternProcessor are used for the Pattern Matching & Processing > > Operator. > > > > > Lastly the key type in each PatternProcessor is the same, regarded > as > > > > > Object type. > > > > > > > > > > -- Maybe need to pay attention to it when implementing it .If some > > > > Pattern > > > > > has been removed or updated, will the partially matched results in > > > > > StateBackend would be clean up or We rely on state ttl to clean up > > these > > > > > expired states. > > > > > > > > > > If certain Pattern has been removed or updated, the partially > matched > > > > > results in StateBackend would be clean up until the next > checkpoint. > > The > > > > > partially matched result doesn't depend on the state ttl of the > > > > > StateBackend. > > > > > > > > > > 4. Will the PatternProcessorManager keep all the active > > PatternProcessor > > > > > in memory? We have also Support Multiple Rule and Dynamic Rule > > Changing. > > > > > But we are facing such a problem, some users’ usage scenarios are > > that > > > > they > > > > > want to have their own pattern for each user_id, which means that > > there > > > > > could be thousands of patterns, which would make the performance of > > > > Pattern > > > > > Matching very poor. We are also trying to solve this problem. > > > > > > > > > > The PatternProcessorManager keeps all the active PatternProcessor > in > > > > > memory. For scenarios that they want to have their own pattern for > > each > > > > > user_id, IMO, is it possible to reduce the fine-grained pattern of > > > > > PatternProcessor to solve the performance problem of the Pattern > > > > Matching, > > > > > for example, a pattern corresponds to a group of users? The > scenarios > > > > > mentioned above need to be solved by case by case. > > > > > > > > > > Best, > > > > > Nicholas Jiang > > > > > > > > > > On 2021/12/17 11:43:10 yue ma wrote: > > > > > > Glad to see the Community's progress in Flink CEP. After reading > > this > > > > > Flip, > > > > > > I have few questions, would you please take a look ? > > > > > > > > > > > > 1. About Pattern Updating. If we use PatternProcessoerDiscoverer > to > > > > > update > > > > > > the rules, will it increase the load of JM? For example, if the > > user > > > > > wants > > > > > > the updated rule to take effect immediately,, which means that we > > need > > > > to > > > > > > set a shorter check interval or there is another scenario when > > users > > > > > > rarely update the pattern, will the PatternProcessoerDiscoverer > be > > in > > > > > most > > > > > > of the time Do useless checks ? Will a lazy update mode could be > > used, > > > > > > which the pattern only be updated when triggered by the user, and > > do > > > > > > nothing at other times ? > > > > > > > > > > > > 2. I still have some confusion about how Key Generating > > Opertator and > > > > > > CepOperator (Pattern Matching & Processing Operator) work > > together. If > > > > > > there are N PatternProcessors, will the Key Generating Opertator > > > > > generate N > > > > > > keyedStreams, and then N CepOperator would process each Key > > separately > > > > ? > > > > > Or > > > > > > every CepOperator Task would process all patterns, if so, does > the > > key > > > > > type > > > > > > in each PatternProcessor need to be the same ? > > > > > > > > > > > > 3. Maybe need to pay attention to it when implementing it .If > some > > > > > Pattern > > > > > > has been removed or updateed ,will the partially matched results > > in > > > > > > StateBackend would be clean up or We rely on state ttl to clean > up > > > > these > > > > > > expired states. > > > > > > > > > > > > 4. Will the PatternProcessorManager keep all the active > > > > PatternProcessor > > > > > in > > > > > > memory ? We have also Support Multiple Rule and Dynamic Rule > > Changing . > > > > > > But we are facing such a problem, some users’ usage scenarios are > > that > > > > > they > > > > > > want to have their own pattern for each user_id, which means that > > there > > > > > > could be thousands of patterns, which would make the performance > of > > > > > Pattern > > > > > > Matching very poor. We are also trying to solve this problem. > > > > > > > > > > > > Yunfeng Zhou <flink.zhouyunf...@gmail.com> 于2021年12月10日周五 > 19:16写道： > > > > > > > > > > > > > Hi all， > > > > > > > > > > > > > > I'm opening this thread to propose the design to support > multiple > > > > rule > > > > > & > > > > > > > dynamic rule changing in the Flink-CEP project, as described in > > > > > FLIP-200 > > > > > > > [1] > > > > > > > . > > > > > > > > > > > > > > Currently Flink CEP only supports having a single pattern > inside > > a > > > > > > > CepOperator and does not support changing the pattern > > dynamically. In > > > > > order > > > > > > > to reduce resource consumption and to experience shorter > downtime > > > > > during > > > > > > > pattern updates, there is a growing need in the production > > > > environment > > > > > that > > > > > > > expects CEP to support having multiple patterns in one operator > > and > > > > to > > > > > > > support dynamically changing them. Therefore I propose to add > > certain > > > > > > > infrastructure as described in FLIP-200 to support these > > > > > functionalities. > > > > > > > > > > > > > > Please feel free to reply to this email thread. Looking forward > > to > > > > your > > > > > > > feedback! > > > > > > > > > > > > > > [1] > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=195730308 > > > > > > > > > > > > > > Best regards, > > > > > > > > > > > > > > Yunfeng > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > Konstantin Knauf > > > > > > > > https://twitter.com/snntrable > > > > > > > > https://github.com/knaufk > > > > > > > > > >
