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Posted to dev@flink.apache.org by Shammon FY <zj...@gmail.com> on 2022/09/16 05:32:34 UTC
Re: [Discuss] Let's Session Cluster JobManager take a breather (FLIP-257: Flink JobManager Process Split)
Thanks @XintongSong and sorry for replying late. Also thanks Zhengyu for
bringing this discussion up.
We use flink session cluster to run olap queries in ByteDance, and have
supported several users in production. The maximum single cluster has 2000
cores, and we focus on the job scheduling performance, stability and
serviceability of the olap cluster.
I think @chesnay raised an interesting question: using multiple clusters
VS. expand a single cluster. Flink Session Cluster is a stateless compute
cluster, and we can deploy multiple clusters to solve performance and
stability problems.
In fact, we did deploy multiple clusters due to the lack of flink job
scheduling performance a few months ago. We have even deployed 5 session
clusters to support tens of QPS needs for the single user. But after we
finished optimizing Flink job scheduling performance, we immediately merged
these clusters into one. Even in the future, we hope to be able to test the
large cluster of 50000 cores and unify some users with low isolation
requirements to the large cluster.
We really don't like to deploy multiple clusters for each user. Besides the
resource and use cost mentioned by @jam.gzczy, there are some other
problems:
1. We should add monitors and alarms for each cluster
2. When a user has problems, it will increase the cost of problem tracing
in multiple clusters
3. Increase Cluster upgrade costs due to the number of clusters
4. Multiple clusters will reduce the user's confidence in system
performance, and the system should support horizontal expansion, it's very
important
The advantages of using a single cluster instead of multiple clusters to
provide services are obvious. But there's a single point problem of
JobManager in the cluster. How to solve the single point problem? When we
started to use Flink to provide olap services, it was on our list.
JobManager single point has the following problems in flink olap:
1. Recovery time of the cluster. When JobManager fails, the cluster can't
provide services until the JobManager recovers. We have added a hook in the
JobManager to improve the recovery time from stand-by one in about 400ms,
but recovery time may take tens of seconds in some corner cases, it's
terrible.
2. Workload and stability. There may be fullgc in JobManager or it is
processing a large amount of results for some olap queries, other queries
will be affected, resulting in increased latency or decreased throughput.
Therefore, in terms of olap scenarios, we want to split the JobManager, and
it's an important feature. However, we believe that it should be a careful
decision. We need to divide the functions of JobManager carefully,
including REST, Dispatcher, ResourceManager and etc. roles. It involves job
submission, job management, web ui and other core functions.
Personally, I have reservations about the design in
https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split.
It doesn't solve the single point problem of cluster for olap scenario, and
even worse, it increases the network interaction of olap query and the
complexity of the JobManager module.
Thanks
Xintong Song <to...@gmail.com> 于2022年8月28日周日 14:48写道：
> Sorry for joining the discussion late. And thanks Zhengyu for bringing
> this discussion up.
>
> I think this is an interesting topic. I actually had something similar in
> mind for a long time. I haven't carried it out for the same concerns as
> others already mentioned, that the benefit for this effort may not be that
> significant compared to the complexity it introduces. However, I think
> Matthias has come up with an inspiring idea, to simply offload some of the
> JobMasters to standby JobManager processes, which potentially reduces the
> complexity significantly and sounds promising to me.
>
> # My understanding on the session mode
>
> In the early days, a standalone session cluster was probably the most
> straightforward way to deploy Flink on a bunch of machines / VMs. Nowadays,
> as K8s / Yarn deployments become more and more convenient and application
> mode becomes available for the standalone deployment, why (or whether) do
> users still need the session mode?
>
> From my experiences, I see users still want to use session mode in
> production mainly for 2 reasons:
> - To reduce the job bootstrap time. Leveraging an existing session cluster
> would save the time for requesting resources from K8s / Yarn and launching
> / initializing the processes, which in many cases is the major time
> consumption in launching a job. This is valued typically for interactive
> workloads.
> - To improve resource efficiency. Session cluster allows multiple jobs to
> share the same JobManager & TaskManager processes. This reduces the
> framework resource overhead for small workloads.
>
> # Concrete use cases
>
> I've seen 2 use cases which may benefit from this proposal.
>
> - AFAIK, ByteDance builds a large scale OLAP query service with Flink.
> They have a large Flink session cluster that runs >100 sql queries per
> seconds, where the JobManager process becomes the single-pointed
> performance bottleneck. I asked the same question as Chesnay did, that
> whether this can be fulfilled by having multiple session clusters plus a
> load-balancing service. Seems that's exactly the approach they were using,
> but with many limitations. Cc-ed @Shammon, would you like to provide more
> details?
> - One of our users at Alibaba has hundreds of Flink jobs for event
> processing. The workload of each job is typically low (tens of records per
> hour), meanwhile there's a high requirement on the timeliness (records upon
> received must be processed immediately). Consequently, they have a large
> session cluster that runs hundreds of long-running jobs. The reason they
> don't like multiple session clusters is that, as business develops, they
> may frequently create new jobs and retire old ones. It is inconvenient to
> maintain / migrate the long-running jobs across multiple clusters.
>
> # My opinion on this proposal
>
> I do see a value behind this proposal. Admittedly, I haven't seen any use
> cases that absolutely cannot be solved by having multiple session clusters.
> But it would definitely reduce the complexity on the user side if Flink can
> support larger scale session clusters. Additionally, there's a chance that
> spreading the JobMasters across multiple JobManager processes may also help
> with the high availability, that only part of the jobs are affected upon
> JobManager failures.
>
> On the other hand, I share the concern that the current design complicates
> the coordination & deployment components way more than the benefit it
> brings.
>
> I would suggest looking a bit more along the direction of leveraging
> standby JobManager processes as Matthias pointed out, see if the benefit is
> worth the price.
>
> Best,
>
> Xintong
>
>
>
> On Fri, Aug 26, 2022 at 5:55 PM Zheng Yu Chen <ja...@gmail.com> wrote:
>
>> Hi Chesnay ,
>> I have also considered the method you mentioned. If we deploy some
>> load balancing or intelligent scheduling in front of multiple
>> SessionClusters, this may cause the following problems
>> ● Insufficient resource utilization. When we distribute these
>> resources on each cluster, the job cannot make full use of the overall
>> TM resources. Some clusters may have very high workload and some are
>> idle, resulting in wasted resources.
>> ● The user's usage cost increases, and the user introduces additional
>> components to adapt to the SessionCluster. The problem is caused by
>> the overload of the JobManager. If there is a solution on the Flink
>> side, it will be better.
>> Maybe there is a better way to deal with it, I am sorting it out, and
>> I will reply with new ideas in the emails later.
>>
>> Chesnay Schepler <ch...@apache.org> 于2022年8月17日周三 22:31写道：
>> >
>> > To be honest I'm terrified at the idea of splitting the Dispatcher into
>> > several processes, even more so if this is supposed to be opt-in and
>> > specific to session mode.
>> > It would fragment the coordination layer even more than it already is,
>> > and make ops more complicated (yet another set of processes to monitor,
>> > configure etc.).
>> >
>> > I'm not convinced that this proposal really gets us a lot of benefits;
>> > and would rather propose that you split your single session cluster into
>> > multiple session clusters (with the scheduling component in front of it
>> > to distribute jobs) to even the load.
>> >
>> > > The currently idling JobManagers could be utilized to take over some
>> > of the workload from the leader.
>> >
>> > This would also be the path I would go down if we'd try to tackle this.
>> >
>> > On 17/08/2022 16:22, Matthias Pohl wrote:
>> > > Hi Conrad,
>> > > thanks for reaching out to the community with your proposal. I looked
>> > > through FLIP-257 [1]. Your motivation sounds interesting. Can you
>> > > elaborate a bit more on the concrete use-cases you have in mind? How
>> > > do these match the user-cases of the two favored execution modes, i.e.
>> > > Flink's Session and Application mode?
>> > >
>> > > As mentioned in [2], Application Mode should be preferred for single
>> > > long-running jobs to isolate the resources of each of those jobs from
>> > > each other. In contrast, Session Mode is the natural choice when
>> > > running rather small/short-lived jobs (e.g. FlinkSQL queries) or when
>> > > deploying some kind of dev environment for testing out job
>> > > implementations. It feels like your use-case is somewhere in between a
>> > > bit? It would be interesting to get a better understanding of where
>> > > you're coming from. Maybe, you could provide some workload statistics?
>> > >
>> > > That considered, I guess it's a topic worth looking into. Here are a
>> > > few thoughts after looking into FLIP-257:
>> > > - As far as I can see, the BlobServer is used for sharing
>> > > configuration information (e.g. Classpath information) as part of the
>> > > ExecutionGraph instantiation [3]. The JobGraph is not persisted
>> > > through the BlobServer but rather stored in the JobGraphStore backed
>> > > by the HighAvailabilityServices implementation. The HA side is not
>> > > really covered in FLIP-257, yet.
>> > > - The approach of having the current Dispatcher living next to the new
>> > > JobMasterDispatcher (that encapsulates the logic around distributing
>> > > the workload onto multiple runners) leaves me with some doubt whether
>> > > there wouldn't be a better separation of concerns here. What about
>> > > leaving the Dispatcher as is but adding some abstraction between
>> > > JobManagerRunner/JobMaster and the Dispatcher that hides the logic
>> > > around whether these instances are "deployed" on the same machine or
>> > > somewhere else.
>> > > - About distributing JobManager workload: The JobManager already
>> > > utilizes leader election for faster recovery. Hence, one can set up
>> > > multiple JobManagers in idle mode which wait to gain leadership and
>> > > pick up the work (i.e. recovering the jobs) of the previously failed
>> > > JobManager leader. What about utilizing this setup: The currently
>> > > idling JobManagers could be utilized to take over some of the workload
>> > > from the leader. I haven't thought this through, yet. But I'm
>> > > wondering whether that would be a path we could go down. This would
>> > > enable us to still stick to the JobManager/TaskManager setup which
>> > > users are already used to rather than introducing another type of
>> > > cluster node.
>> > > - The JobManager initialization logic is kind of tricky to get your
>> > > head around. There is some overhead, I hope, we could clean up as part
>> > > of the efforts of removing the per-Job Mode from Flink [4]. It was
>> > > decided to deprecate per-Job Mode in Flink 1.15. But we have to stick
>> > > with it for some time (i.e. it's not going to be removed in 1.16)
>> > > since it's a quite basic feature users might rely on. This shouldn't
>> > > be a blocker. I just wanted to mention it to have it in the back of
>> > > our minds when looking into ways to come up with a solid proposal for
>> > > FLIP-257.
>> > > - My concern is that this FLIP might turn out to be larger than
>> > > expected and that it might be worth cutting it down into smaller
>> > > chunks with each being covered in a separate FLIP down the road if we
>> > > have some agreement and a clearer picture on how this should be
>> tackled.
>> > >
>> > > I'm gonna add Chesnay and David to this discussion.
>> > >
>> > > Best,
>> > > Matthias
>> > >
>> > >
>> > > [1]
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > [2]
>> > >
>> https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/overview/#deployment-modes
>> > > [3]
>> > >
>> https://github.com/apache/flink/blob/9ed70a1e8b5d59abdf9d7673bc5b44d421140ef0/flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/DefaultExecutionGraph.java#L333
>> > > [4] https://lists.apache.org/thread/b8g76cqgtr2c515rd1bs41vy285f317n
>> > >
>> > >
>> > > On Tue, Aug 16, 2022 at 11:43 AM Zheng Yu Chen <ja...@gmail.com>
>> > > wrote:
>> > >
>> > > Hi community ~
>> > >
>> > > I think this title should be quite interesting. The idea is to
>> > > reduce the
>> > > workload of the JobManager and make the SessionCluster [2] more
>> > > stable in
>> > > the process of running jobs. I designed a plan for splitting the
>> > > JobManager
>> > > on FLIP-257 [1]:
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > <
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+JobMaster+Thread+Split+to+Process
>> >
>> > >
>> > > This proposal proposes a splitting scheme for the current process
>> > > and a new
>> > > process implementation idea that is compatible with the original
>> > > process
>> > > model: splitting the internal JobMaster component of the
>> > > JobManager, and
>> > > controlling whether to enable this new process through a parameter
>> > > In the
>> > > split scheme, when the user configures, the JobMaster will make it
>> > > run as
>> > > an independent service, reducing the workload of the JobManager.
>> By
>> > > implementing a new Dispatcher to communicate and interact with a
>> > > single
>> > > split JobMaster or multiple JobMasters, to achieve job management
>> > >
>> > > The main features that it provides is:
>> > >
>> > > - After the user submits the job, the JobMaster thread was
>> > > split into
>> > > other processes to run in the past. They no longer run in the
>> > > JobManager,
>> > > but in other processes.
>> > > - Users can deploy multiple components mentioned above, which
>> run
>> > > multiple JobMaster threads, thereby reducing the workload of
>> > > the JobManager
>> > >
>> > > Some of the challenging use cases that these features solve are:
>> > >
>> > > - Compatible with the original job running mode (run JobMaster
>> > > Thread on
>> > > JobManager)
>> > > - Implement a new Dispatcher that forwards client operations
>> > > related to
>> > > jobs
>> > >
>> > >
>> > > I would love to hear and address your thoughts and feedback ,
>> and if
>> > > possible drive a FLIP-257 ！
>> > >
>> > >
>> > > [1]
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > <
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+JobMaster+Thread+Split+to+Process
>> >
>> > >
>> > > [2]
>> > >
>> https://nightlies.apache.org/flink/flink-docs-release-1.15/docs/deployment/overview/#session-mode
>> > >
>> > >
>> > > --
>> > >
>> > > Have a nice day ~
>> > >
>> > > ConradJam
>> > >
>>
>> --
>> Best
>>
>> ConradJam
>>
>
Fwd: [Discuss] Let's Session Cluster JobManager take a breather (FLIP-257: Flink JobManager Process Split)
Posted by Shammon FY <zj...@gmail.com>.
Thanks @XintongSong and sorry for replying late. Also thanks Zhengyu for
bringing this discussion up.
We use flink session cluster to run olap queries in ByteDance, and have
supported several users in production. The maximum single cluster has 2000
cores, and we focus on the job scheduling performance, stability and
serviceability of the olap cluster.
I think @chesnay raised an interesting question: using multiple clusters
VS. expand a single cluster. Flink Session Cluster is a stateless compute
cluster, and we can deploy multiple clusters to solve performance and
stability problems.
In fact, we did deploy multiple clusters due to the lack of flink job
scheduling performance a few months ago. We have even deployed 5 session
clusters to support tens of QPS needs for the single user. But after we
finished optimizing Flink job scheduling performance, we immediately merged
these clusters into one. Even in the future, we hope to be able to test the
large cluster of 50000 cores and unify some users with low isolation
requirements to the large cluster.
We really don't like to deploy multiple clusters for each user. Besides the
resource and use cost mentioned by @jam.gzczy, there are some other
problems:
1. We should add monitors and alarms for each cluster
2. When a user has problems, it will increase the cost of problem tracing
in multiple clusters
3. Increase Cluster upgrade costs due to the number of clusters
4. Multiple clusters will reduce the user's confidence in system
performance, and the system should support horizontal expansion, it's very
important
The advantages of using a single cluster instead of multiple clusters to
provide services are obvious. But there's a single point problem of
JobManager in the cluster. How to solve the single point problem? When we
started to use Flink to provide olap services, it was on our list.
JobManager single point has the following problems in flink olap:
1. Recovery time of the cluster. When JobManager fails, the cluster can't
provide services until the JobManager recovers. We have added a hook in the
JobManager to improve the recovery time from stand-by one in about 400ms,
but recovery time may take tens of seconds in some corner cases, it's
terrible.
2. Workload and stability. There may be fullgc in JobManager or it is
processing a large amount of results for some olap queries, other queries
will be affected, resulting in increased latency or decreased throughput.
Therefore, in terms of olap scenarios, we want to split the JobManager, and
it's an important feature. However, we believe that it should be a careful
decision. We need to divide the functions of JobManager carefully,
including REST, Dispatcher, ResourceManager and etc. roles. It involves job
submission, job management, web ui and other core functions.
Personally, I have reservations about the design in
https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split.
It doesn't solve the single point problem of cluster for olap scenario, and
even worse, it increases the network interaction of olap query and the
complexity of the JobManager module.
Thanks
Xintong Song <to...@gmail.com> 于2022年8月28日周日 14:48写道：
> Sorry for joining the discussion late. And thanks Zhengyu for bringing
> this discussion up.
>
> I think this is an interesting topic. I actually had something similar in
> mind for a long time. I haven't carried it out for the same concerns as
> others already mentioned, that the benefit for this effort may not be that
> significant compared to the complexity it introduces. However, I think
> Matthias has come up with an inspiring idea, to simply offload some of the
> JobMasters to standby JobManager processes, which potentially reduces the
> complexity significantly and sounds promising to me.
>
> # My understanding on the session mode
>
> In the early days, a standalone session cluster was probably the most
> straightforward way to deploy Flink on a bunch of machines / VMs. Nowadays,
> as K8s / Yarn deployments become more and more convenient and application
> mode becomes available for the standalone deployment, why (or whether) do
> users still need the session mode?
>
> From my experiences, I see users still want to use session mode in
> production mainly for 2 reasons:
> - To reduce the job bootstrap time. Leveraging an existing session cluster
> would save the time for requesting resources from K8s / Yarn and launching
> / initializing the processes, which in many cases is the major time
> consumption in launching a job. This is valued typically for interactive
> workloads.
> - To improve resource efficiency. Session cluster allows multiple jobs to
> share the same JobManager & TaskManager processes. This reduces the
> framework resource overhead for small workloads.
>
> # Concrete use cases
>
> I've seen 2 use cases which may benefit from this proposal.
>
> - AFAIK, ByteDance builds a large scale OLAP query service with Flink.
> They have a large Flink session cluster that runs >100 sql queries per
> seconds, where the JobManager process becomes the single-pointed
> performance bottleneck. I asked the same question as Chesnay did, that
> whether this can be fulfilled by having multiple session clusters plus a
> load-balancing service. Seems that's exactly the approach they were using,
> but with many limitations. Cc-ed @Shammon, would you like to provide more
> details?
> - One of our users at Alibaba has hundreds of Flink jobs for event
> processing. The workload of each job is typically low (tens of records per
> hour), meanwhile there's a high requirement on the timeliness (records upon
> received must be processed immediately). Consequently, they have a large
> session cluster that runs hundreds of long-running jobs. The reason they
> don't like multiple session clusters is that, as business develops, they
> may frequently create new jobs and retire old ones. It is inconvenient to
> maintain / migrate the long-running jobs across multiple clusters.
>
> # My opinion on this proposal
>
> I do see a value behind this proposal. Admittedly, I haven't seen any use
> cases that absolutely cannot be solved by having multiple session clusters.
> But it would definitely reduce the complexity on the user side if Flink can
> support larger scale session clusters. Additionally, there's a chance that
> spreading the JobMasters across multiple JobManager processes may also help
> with the high availability, that only part of the jobs are affected upon
> JobManager failures.
>
> On the other hand, I share the concern that the current design complicates
> the coordination & deployment components way more than the benefit it
> brings.
>
> I would suggest looking a bit more along the direction of leveraging
> standby JobManager processes as Matthias pointed out, see if the benefit is
> worth the price.
>
> Best,
>
> Xintong
>
>
>
> On Fri, Aug 26, 2022 at 5:55 PM Zheng Yu Chen <ja...@gmail.com> wrote:
>
>> Hi Chesnay ,
>> I have also considered the method you mentioned. If we deploy some
>> load balancing or intelligent scheduling in front of multiple
>> SessionClusters, this may cause the following problems
>> ● Insufficient resource utilization. When we distribute these
>> resources on each cluster, the job cannot make full use of the overall
>> TM resources. Some clusters may have very high workload and some are
>> idle, resulting in wasted resources.
>> ● The user's usage cost increases, and the user introduces additional
>> components to adapt to the SessionCluster. The problem is caused by
>> the overload of the JobManager. If there is a solution on the Flink
>> side, it will be better.
>> Maybe there is a better way to deal with it, I am sorting it out, and
>> I will reply with new ideas in the emails later.
>>
>> Chesnay Schepler <ch...@apache.org> 于2022年8月17日周三 22:31写道：
>> >
>> > To be honest I'm terrified at the idea of splitting the Dispatcher into
>> > several processes, even more so if this is supposed to be opt-in and
>> > specific to session mode.
>> > It would fragment the coordination layer even more than it already is,
>> > and make ops more complicated (yet another set of processes to monitor,
>> > configure etc.).
>> >
>> > I'm not convinced that this proposal really gets us a lot of benefits;
>> > and would rather propose that you split your single session cluster into
>> > multiple session clusters (with the scheduling component in front of it
>> > to distribute jobs) to even the load.
>> >
>> > > The currently idling JobManagers could be utilized to take over some
>> > of the workload from the leader.
>> >
>> > This would also be the path I would go down if we'd try to tackle this.
>> >
>> > On 17/08/2022 16:22, Matthias Pohl wrote:
>> > > Hi Conrad,
>> > > thanks for reaching out to the community with your proposal. I looked
>> > > through FLIP-257 [1]. Your motivation sounds interesting. Can you
>> > > elaborate a bit more on the concrete use-cases you have in mind? How
>> > > do these match the user-cases of the two favored execution modes, i.e.
>> > > Flink's Session and Application mode?
>> > >
>> > > As mentioned in [2], Application Mode should be preferred for single
>> > > long-running jobs to isolate the resources of each of those jobs from
>> > > each other. In contrast, Session Mode is the natural choice when
>> > > running rather small/short-lived jobs (e.g. FlinkSQL queries) or when
>> > > deploying some kind of dev environment for testing out job
>> > > implementations. It feels like your use-case is somewhere in between a
>> > > bit? It would be interesting to get a better understanding of where
>> > > you're coming from. Maybe, you could provide some workload statistics?
>> > >
>> > > That considered, I guess it's a topic worth looking into. Here are a
>> > > few thoughts after looking into FLIP-257:
>> > > - As far as I can see, the BlobServer is used for sharing
>> > > configuration information (e.g. Classpath information) as part of the
>> > > ExecutionGraph instantiation [3]. The JobGraph is not persisted
>> > > through the BlobServer but rather stored in the JobGraphStore backed
>> > > by the HighAvailabilityServices implementation. The HA side is not
>> > > really covered in FLIP-257, yet.
>> > > - The approach of having the current Dispatcher living next to the new
>> > > JobMasterDispatcher (that encapsulates the logic around distributing
>> > > the workload onto multiple runners) leaves me with some doubt whether
>> > > there wouldn't be a better separation of concerns here. What about
>> > > leaving the Dispatcher as is but adding some abstraction between
>> > > JobManagerRunner/JobMaster and the Dispatcher that hides the logic
>> > > around whether these instances are "deployed" on the same machine or
>> > > somewhere else.
>> > > - About distributing JobManager workload: The JobManager already
>> > > utilizes leader election for faster recovery. Hence, one can set up
>> > > multiple JobManagers in idle mode which wait to gain leadership and
>> > > pick up the work (i.e. recovering the jobs) of the previously failed
>> > > JobManager leader. What about utilizing this setup: The currently
>> > > idling JobManagers could be utilized to take over some of the workload
>> > > from the leader. I haven't thought this through, yet. But I'm
>> > > wondering whether that would be a path we could go down. This would
>> > > enable us to still stick to the JobManager/TaskManager setup which
>> > > users are already used to rather than introducing another type of
>> > > cluster node.
>> > > - The JobManager initialization logic is kind of tricky to get your
>> > > head around. There is some overhead, I hope, we could clean up as part
>> > > of the efforts of removing the per-Job Mode from Flink [4]. It was
>> > > decided to deprecate per-Job Mode in Flink 1.15. But we have to stick
>> > > with it for some time (i.e. it's not going to be removed in 1.16)
>> > > since it's a quite basic feature users might rely on. This shouldn't
>> > > be a blocker. I just wanted to mention it to have it in the back of
>> > > our minds when looking into ways to come up with a solid proposal for
>> > > FLIP-257.
>> > > - My concern is that this FLIP might turn out to be larger than
>> > > expected and that it might be worth cutting it down into smaller
>> > > chunks with each being covered in a separate FLIP down the road if we
>> > > have some agreement and a clearer picture on how this should be
>> tackled.
>> > >
>> > > I'm gonna add Chesnay and David to this discussion.
>> > >
>> > > Best,
>> > > Matthias
>> > >
>> > >
>> > > [1]
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > [2]
>> > >
>> https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/overview/#deployment-modes
>> > > [3]
>> > >
>> https://github.com/apache/flink/blob/9ed70a1e8b5d59abdf9d7673bc5b44d421140ef0/flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/DefaultExecutionGraph.java#L333
>> > > [4] https://lists.apache.org/thread/b8g76cqgtr2c515rd1bs41vy285f317n
>> > >
>> > >
>> > > On Tue, Aug 16, 2022 at 11:43 AM Zheng Yu Chen <ja...@gmail.com>
>> > > wrote:
>> > >
>> > > Hi community ~
>> > >
>> > > I think this title should be quite interesting. The idea is to
>> > > reduce the
>> > > workload of the JobManager and make the SessionCluster [2] more
>> > > stable in
>> > > the process of running jobs. I designed a plan for splitting the
>> > > JobManager
>> > > on FLIP-257 [1]:
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > <
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+JobMaster+Thread+Split+to+Process
>> >
>> > >
>> > > This proposal proposes a splitting scheme for the current process
>> > > and a new
>> > > process implementation idea that is compatible with the original
>> > > process
>> > > model: splitting the internal JobMaster component of the
>> > > JobManager, and
>> > > controlling whether to enable this new process through a parameter
>> > > In the
>> > > split scheme, when the user configures, the JobMaster will make it
>> > > run as
>> > > an independent service, reducing the workload of the JobManager.
>> By
>> > > implementing a new Dispatcher to communicate and interact with a
>> > > single
>> > > split JobMaster or multiple JobMasters, to achieve job management
>> > >
>> > > The main features that it provides is:
>> > >
>> > > - After the user submits the job, the JobMaster thread was
>> > > split into
>> > > other processes to run in the past. They no longer run in the
>> > > JobManager,
>> > > but in other processes.
>> > > - Users can deploy multiple components mentioned above, which
>> run
>> > > multiple JobMaster threads, thereby reducing the workload of
>> > > the JobManager
>> > >
>> > > Some of the challenging use cases that these features solve are:
>> > >
>> > > - Compatible with the original job running mode (run JobMaster
>> > > Thread on
>> > > JobManager)
>> > > - Implement a new Dispatcher that forwards client operations
>> > > related to
>> > > jobs
>> > >
>> > >
>> > > I would love to hear and address your thoughts and feedback ,
>> and if
>> > > possible drive a FLIP-257 ！
>> > >
>> > >
>> > > [1]
>> > >
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+Process+Split
>> > > <
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-257+Flink+JobManager+JobMaster+Thread+Split+to+Process
>> >
>> > >
>> > > [2]
>> > >
>> https://nightlies.apache.org/flink/flink-docs-release-1.15/docs/deployment/overview/#session-mode
>> > >
>> > >
>> > > --
>> > >
>> > > Have a nice day ~
>> > >
>> > > ConradJam
>> > >
>>
>> --
>> Best
>>
>> ConradJam
>>
>