Hi David,
Thanks for sharing your thoughts. Some quick reply to your comments:
We're still talking about the "web server based"
> pattern_processor_discoverer, but what about other use cases? One of my big
> concerns is that user's can not really reuse any part of the Flink
> ecosystem to implement the discovery logic. For example if they want to
> read patterns from Kafka topic, they need to roll their own discoverer
> based on the vanilla Kafka client. If we're talking about extensibility,
> should we also make sure that the existing primitives can be reused?
KafkaSource is actually more complicated than vanilla KafkaConsumer from
the perspective of consuming Kafka messages. The KafkaSource just helps
make it easier for Flink jobs to process these messages. In fact,
KafkaConsumer is more powerful than KafkaSource in terms of talking to
Kafka. So we are comparing [KafkaConsumer + OperatorCoordinator] and
[KafkaSource + side-input], not [KafkaConsumer + side-input].
This can be done for the side-input as well by filtering invalid patterns
> before the broadcast. You can also send the invalid patterns to any side
> output you want. I have a feeling that we're way too attached to the REST
> server use case in this discussion. I agree that for that case, this
> solution is the most straightforward one.
Depending on whether the invalidity is discovered in pattern definition
time or data processing time. e.g. A valid pattern with invalid data which
fails to process can only be detected in data processing time. So the
pattern won't be filtered out before the broadcast.
I agree that 2-way communication in the "data-flow like" API is tricky,
> because it requires cycles / iterations, which are still not really solved
> (for a good reason, it's really tough nut to crack). This makes me think
> that the OC may be bit of a "incomplete" workaround for not having fully
> working support for iterations.
For example I'm not really confident that the checkpointing of the OC works
> correctly right now, because it doesn't seem to require checkpoint barrier
> alignment as the regular stream inputs. We also don't have a proper support
> for watermarking (this is again tricky, because of the cycle).
If we decide to go down this road, should we first address some of these
> limitations?
I agree. OC is proven to be useful and we should think about how to enhance
it instead of not using it.
If I understand that correctly, this means only the LATEST state of the
> patterns (in other words - patterns that are currently in use). Is this
> really sufficient for historical re-processing? Can someone for example
> want re-process the data in more of a "temporal join" fashion? Also AFAIK
> historical processing in combination with "coordinator checkpoints" is not
> really something that we currently support of the box, are there any plans
> on tackling this (my other concern is that this should not go against the
> "unified batch & stream processing" efforts)?
I think in this case, the state would contain the entire pattern update
history. Not the final state, but the change log. In fact, it is not
possible to guarantee the correct result unless you have the entire change
log. Even with side-input, there still could be late arrivals in the
pattern update stream, and the only way to correct it is to either have all
the data reprocessed (with all the pattern change log loaded upfront) or
having retraction support.
I can imagine that if this should be a concern, we could move the execution
> of the OC to the task managers. This also makes me thing, that we shouldn't
> make any strong assumptions that the OC will always run in the JobManager
> (this is especially relevant for the embedded web-server use case).
This is a very good point. I think we should do this. The reason OC is in
JM is based on the assumption that control plane usually have little
traffic. But if that is not the case, we should move the OC out of JM,
maybe to TM.
I think the key topic we are discussing is what the Flink control plane
should look like, and CEP is just an example use case. There are basically
two options:
1. Using the side-input / broadcast stream
2. Using the OperatorCoordinator.
Although we are having this discussion under the context of supporting CEP
dynamic pattern update, it would be really helpful to reach agreement on
the design principle in general of how Flink should handle similar external
control demands, a.k.a how to provide a decent control plane in Flink to
the users.
Here is my take on these two options, based on the requirements of a
control plane.
*Communication Requirements*
Flink has two kinds of control planes - in-band and out-of-band.
In-band control plane is like watermark and checkpoint marker. It requires
the entire DAG to be in a consistent state, so the control messages flow
with the data in one direction. This is a one-way control flow.
Examples of out-of-band control plane is OC and JM/TM communication. They
do not require a global consistency or awareness across the entire DAG.
Before OC, neither of these two kinds of control plain was exposed to the
users. OC allows the users to leverage the out-of-band control plane so
they can coordinate across subtasks. This is a more widely used control
flow from user defined operator perspective which requires 2-way
communication.
- side-input stream is one-way communication. Moreover, I don't think
iteration is the right way to address this. Unlike the abstraction of data
processing which is a DAG, the control plane may require communication
between arbitrary two operators in different orders. Using iterations may
end up with an explosion of feedback edges that are not only complicated to
express, but also hard to debug and maintain.
- OC provides a decent 2-way communication mechanism.
*Cost for low traffic use case*
An important difference between data channel and control channel is traffic
pattern. Unlike data plane, the control plane is usually idle for the vast
majority of the time with occasional control messages.
- One argument to use the side-input / broadcast stream was that users
can reuse the existing connectors. However, most Flink sources are designed
to handle large throughput of traffic that maintains all the threads,
network connections, etc. Not to say the external resources such as Kafka
topics to store the commands.
- OC can have a much lower constant cost.
*Easy to use*
Personally speaking, I think the most simple and user-friendly interface is
a REST API that accepts control commands.
- One proposal at this point is to have a separate web server
independent of the Flink job. In that case, should users implement that web
server? In order to pass the command to the Flink job, does that mean users
should implement a Flink source that can read the commands from the web
server? Or the web server would send the command to something like Kafka
and let the Flink side-input read from there. There seems to be a lot for
the users to do. And it seems an unnecessarily complicated system to build
to send occasional control messages to a Flink job.
- OC can simply be reached via the JM REST API.
- e.g. http://JM_IP/OperatorEvents?OP_NAME=xxx&Content=xxx
<http://jm_ip/OperatorEvents?OP_NAME=xxx&Content=xxx> would simply
send the Content to the OC of OP_NAME.
*Work well with checkpoints*
- side-input streams works well with checkpoint, thanks to its
compatibility to the DAG abstraction.
- The OperatorCoordinator requires more careful design to work well with
checkpoints. The complexity mostly comes from the 2-way communication. At
this point the OperatorCoordinator message delivery semantic may not be as
robust as side-input streams. However, I think this is mainly due to
potential bugs in implementation instead of fundamental design problems.
Basically the checkpoint semantic should be:
- The JM will first checkpoint all the OperatorCoordinator, more
specifically for each OperatorCoordinator,
- 1) JM blocks the input queue to stop receiving new events from
the subtasks.
- 2) let all the operator coordinator finish processing all the
pending events in the OC input queue.
- 3) flush the OC output queue until all the events sent are
acknowledged.
- 3) unblock the input queue, but block the output queue until all
the subtasks of the OC finish checkpoints.
- The JM starts a normal checkpoint starting from the Source.
- If an operator has a coordinator, and it has sent some events to
the OC but has not been acknowledged. These events need to be
put into the
subtasks' checkpoint.
- After all the subtasks of an operator finishes checkpoint, the
output queue of the corresponding OC can be unblocked.
It looks that the above protocol would let OC have a clear checkpoint
semantic. And this complexity seems must for 2-way communication. I think
we are able to hide the above protocol from users by having an abstract OC
implementation.
*Reprocess command history and repeatable processing results*
This seems not something generally required for a control plane. But if the
control plane changes the data processing behavior, there might be some use
case. Just like the CEP pattern update. In order to do this, users will
need to provide a full command history to the operators. That consists of
two steps:
1. get the full command history. (Flink Source V.S. Custom way to
retrieve command history.)
2. send them to the operators. (Side-input V.S. OC/Operator
communication)l
I actually don't feel much difference between these two options. I am not
sure if a Flink source is necessarily simpler than the user implemented
logic. For example, if all the changes are just written in a database
table. From the user's perspective, I feel fine with querying the DB by
myself using something like JDBC (or use KafkaConsumer to read the pattern
history from a Kafka topic) and send all the pattern change history to the
operators before they start to process the actual events.
*Stability impact to the Flink Job*
I agree this is a valid concern. There is only one JM and currently OC runs
there, which may potentially cause JM crash and result in job failure.
Running in TM may have a less impact. So I think it makes sense to run OC
in TM. However, this is more of how we can implement OC to make it more
robust. It does not forfeit the other semantic and user experience benefits
mentioned above.
To sum up:
1. Regardless of whether CEP chooses OC or side-input stream, a decent
2-way communication control plane seems really helpful and has been proven
by quite a few existing use cases. To me the question is how to make it
more robust, not whether we should use it or not.
2. As for CEP, if we assume OC will be robust enough, personally I feel OC
is a better fit than side-input mainly because of the simplicity and
extensibility.
Thanks,
Jiangjie (Becket) Qin
On Thu, Dec 30, 2021 at 8:43 PM David Morávek <d...@apache.org> wrote:
> Hi all,
>
> sorry for the late reply, vacation season ;) I'm still not 100% sold on
> choosing the OC for this use-case, but on the other hand I don't have
> strong arguments against it. Few more questions / thoughts:
>
> We're still talking about the "web server based"
> pattern_processor_discoverer, but what about other use cases? One of my big
> concerns is that user's can not really reuse any part of the Flink
> ecosystem to implement the discovery logic. For example if they want to
> read patterns from Kafka topic, they need to roll their own discoverer
> based on the vanilla Kafka client. If we're talking about extensibility,
> should we also make sure that the existing primitives can be reused?
>
> For instance, the example I gave in my previous email seems not easily
> > achievable with side-input / broadcast streams: a single invalid pattern
> > detected on a TM can be disabled elegantly globally without crashing the
> > entire Flink job.
>
>
> This can be done for the side-input as well by filtering invalid patterns
> before the broadcast. You can also send the invalid patterns to any side
> output you want. I have a feeling that we're way too attached to the REST
> server use case in this discussion. I agree that for that case, this
> solution is the most straightforward one.
>
> 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.
> >
>
> I agree that 2-way communication in the "data-flow like" API is tricky,
> because it requires cycles / iterations, which are still not really solved
> (for a good reason, it's really tough nut to crack). This makes me think
> that the OC may be bit of a "incomplete" workaround for not having fully
> working support for iterations.
>
> For example I'm not really confident that the checkpointing of the OC works
> correctly right now, because it doesn't seem to require checkpoint barrier
> alignment as the regular stream inputs. We also don't have a proper support
> for watermarking (this is again tricky, because of the cycle).
>
> If we decide to go down this road, should we first address some of these
> limitations?
>
> OperatorCoordinator will checkpoint the full amount of PatternProcessor
> > data. For the reprocessing of historical data, you can read the
> > PatternProcessor snapshots saved by this checkpoint from a certain
> > historical checkpoint, and then recreate the historical data through
> these
> > PatternProcessor snapshots.
> >
>
> If I understand that correctly, this means only the LATEST state of the
> patterns (in other words - patterns that are currently in use). Is this
> really sufficient for historical re-processing? Can someone for example
> want re-process the data in more of a "temporal join" fashion? Also AFAIK
> historical processing in combination with "coordinator checkpoints" is not
> really something that we currently support of the box, are there any plans
> on tackling this (my other concern is that this should not go against the
> "unified batch & stream processing" efforts)?
>
> I do agree that having the user defined control logic defined in the JM
> > increases the chance of instability.
> >
>
> I can imagine that if this should be a concern, we could move the execution
> of the OC to the task managers. This also makes me thing, that we shouldn't
> make any strong assumptions that the OC will always run in the JobManager
> (this is especially relevant for the embedded web-server use case).
>
> If an agreement is reached on OperatorCoodinator, I will start the voting
> > thread.
> >
>
> As for the vote, I'd would be great if we can wait until the next week as
> many people took vacation until end of the year.
>
> Overall, I really like the feature, this will be a great addition to Flink.
>
> Best,
> D.
>
>
>
> On Thu, Dec 30, 2021 at 11:27 AM Martijn Visser <mart...@ververica.com>
> wrote:
>
> > Hi all,
> >
> > I can understand the need for a control plane mechanism. I'm not the
> > technical go-to person for questions on the OperatorCoordinator, but I
> > would expect that we could offer those interfaces from Flink but
> shouldn't
> > recommend running user-code in the JobManager itself. I think the user
> code
> > (like a webserver) should run outside of Flink (like via a sidecar) and
> use
> > only the provided interfaces to communicate.
> >
> > I would like to get @David Morávek <d...@apache.org> opinion on the
> > technical part.
> >
> > Best regards,
> >
> > Martijn
> >
> > On Thu, 30 Dec 2021 at 10:07, Nicholas Jiang <nicholasji...@apache.org>
> > wrote:
> >
> >> Hi Konstantin, Becket, Martijn,
> >>
> >> Thanks for sharing your feedback. What other concerns do you have about
> >> OperatorCoodinator? If an agreement is reached on OperatorCoodinator, I
> >> will start the voting thread.
> >>
> >> Best,
> >> Nicholas Jiang
> >>
> >> On 2021/12/22 03:19:58 Becket Qin wrote:
> >> > Hi Konstantin,
> >> >
> >> > Thanks for sharing your thoughts. Please see the reply inline below.
> >> >
> >> > Thanks,
> >> >
> >> > Jiangjie (Becket) Qin
> >> >
> >> > On Tue, Dec 21, 2021 at 7:14 PM Konstantin Knauf <kna...@apache.org>
> >> wrote:
> >> >
> >> > > Hi Becket, Hi Nicholas,
> >> > >
> >> > > Thanks for joining the discussion.
> >> > >
> >> > > 1 ) Personally, I would argue that we should only run user code in
> the
> >> > > Jobmanager/Jobmaster if we can not avoid it. It seems wrong to me to
> >> > > encourage users to e.g. run a webserver on the Jobmanager, or
> >> continuously
> >> > > read patterns from a Kafka Topic on the Jobmanager, but both of
> these
> >> I see
> >> > > happening with the current design. We've had lots of issues with
> >> > > classloading leaks and other stability issues on the Jobmanager and
> >> making
> >> > > this more complicated, if there is another way, seems unnecessary.
> >> >
> >> >
> >> > I think the key question here is what primitive does Flink provide to
> >> > facilitate the user implementation of their own control logic /
> control
> >> > plane? It looks that previously, Flink assumes that all the user logic
> >> is
> >> > just data processing logic without any control / coordination
> >> requirements.
> >> > However, it turns out that a decent control plane abstraction is
> >> required
> >> > in association with the data processing logic in many cases, including
> >> > Source / Sink and other user defined operators in general. The fact
> >> that we
> >> > ended up with adding the SplitEnumerator and GlobalCommitter are just
> >> two
> >> > examples of the demand of such coordination among user defined logics.
> >> > There are other cases that we see in ecosystem projects, such as
> >> > deep-learning-on-flink[1]. Now we see this again in CEP.
> >> >
> >> > Such control plane primitives are critical to the extensibility of a
> >> > project. If we look at other projects, exposing such control plane
> >> logic is
> >> > quite common. For example, Hadoop ended up with exposing YARN as a
> >> public
> >> > API to the users, which is extremely popular. Kafka consumers exposed
> >> the
> >> > consumer group rebalance logic to the users via
> >> ConsumerPartitionAssigner,
> >> > which is also a control plane primitive.
> >> >
> >> > To me it is more important to think about how we can improve the
> >> stability
> >> > of such a control plane mechanism, instead of simply saying no to the
> >> users.
> >> >
> >> >
> >> >
> >> >
> >> > > 2) In addition, I suspect that, over time we will have to implement
> >> all the
> >> > > functionality that regular sources already provide around
> consistency
> >> > > (watermarks, checkpointing) for the PatternProcessorCoordinator,
> too.
> >> >
> >> >
> >> > I think OperatorCoordinator should have a generic communication
> >> mechanism
> >> > for all the operators, not specific to Source. We should probably have
> >> an
> >> > AbstractOperatorCoordinator help dealing with the communication layer,
> >> and
> >> > leave the state maintenance and event handling logic to the user code.
> >> >
> >> >
> >> > > 3) I understand that running on the Jobmanager is easier if you want
> >> to
> >> > > launch a REST server directly. Here my question would be: does this
> >> really
> >> > > need to be solved inside of Flink or couldn't you start a webserver
> >> next to
> >> > > Flink? If we start using the Jobmanager as a REST server users will
> >> expect
> >> > > that e.g. it is highly available and can be load balanced and we
> >> quickly
> >> > > need to think about aspects that we never wanted to think about in
> the
> >> > > context of a Flink Jobmanager.
> >> > >
> >> >
> >> > I think the REST API is just for receiving commands targeting a
> running
> >> > Flink job. If the job fails, the REST API would be useless.
> >> >
> >> >
> >> > > So, can you elaborate a bit more, why a side-input/broadcast stream
> is
> >> > >
> >> > > a) more difficult
> >> > > b) has vague semantics (To me semantics of a stream-stream seem
> >> clearer
> >> > > when it comes to out-of-orderness, late data, reprocessing or batch
> >> > > execution mode.)
> >> >
> >> >
> >> > I do agree that having the user defined control logic defined in the
> JM
> >> > increases the chance of instability. In that case, we may think of
> other
> >> > solutions and I am fully open to that. But the side-input / broadcast
> >> > stream seems more like a bandaid instead of a carefully designed
> control
> >> > plane mechanism.
> >> >
> >> > A decent control plane requires two-way communication, so information
> >> can
> >> > be reported / collected from the entity being controlled, and the
> >> > coordinator / controller can send decisions or commands to the
> entities
> >> > accordingly, just like our TM / JM communication. IIUC, this is not
> >> > achievable with the existing side-input / broadcast stream as both of
> >> them
> >> > are one-way communication mechanisms. For instance, the example I gave
> >> in
> >> > my previous email seems not easily achievable with side-input /
> >> broadcast
> >> > streams: a single invalid pattern detected on a TM can be disabled
> >> > elegantly globally without crashing the entire Flink job.
> >> >
> >> >
> >> > > Cheers,
> >> > >
> >> > > Konstantin
> >> > >
> >> > >
> >> > > On Tue, Dec 21, 2021 at 11:38 AM Becket Qin <becket....@gmail.com>
> >> wrote:
> >> > >
> >> > > > 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
> >> > > > > > > >
> >> > > > > > >
> >> > > > > >
> >> > > > >
> >> > > >
> >> > >
> >> > >
> >> > > --
> >> > >
> >> > > Konstantin Knauf
> >> > >
> >> > > https://twitter.com/snntrable
> >> > >
> >> > > https://github.com/knaufk
> >> > >
> >> >
> >>
> >
>
