Thanks for starting this discussion Canbin. If I understand your proposal
correctly, then you would like to evolve the existing decorator approach so
that decorators are monadic and smaller in size and functionality. The
latter aspect will allow to reuse them between the client and the cluster.
Just to make sure, it is not a fundamentally different approach compared to
what we have right now, is it?
If this is the case, then I think it makes sense to reuse code as much as
possible and to create small code units which are easier to test.
Cheers,
Till
On Fri, Feb 21, 2020 at 4:41 PM felixzheng zheng <felixzhen...@gmail.com>
wrote:
> Thanks for the feedback @Yang Wang. I would like to discuss some of the
> details in depth about why I am confused about the existing design.
>
> Question 1: How do we mount a configuration file?
>
> For the existing design,
>
> 1.
>
> We need several classes to finish it:
> 1.
>
> InitializerDecorator
> 2.
>
> OwnerReferenceDecorator
> 3.
>
> ConfigMapDecorator
> 4.
>
> KubernetesUtils: providing the getConfigMapVolume method to share for
> the FlinkMasterDeploymentDecorator and the TaskManagerPodDecorator.
> 5.
>
> FlinkMasterDeploymentDecorator: mounts the ConfigMap volume.
> 6.
>
> TaskManagerPodDecorator: mounts the ConfigMap volume.
> 7.
>
> If in the future, someone would like to introduce an init Container,
> the InitContainerDecorator has to mount the ConfigMap volume too.
>
>
> I am confused about the current solution to mounting a configuration file:
>
> 1.
>
> Actually, we do not need so many Decorators for mounting a file.
> 2.
>
> If we would like to mount a new file, we have no choice but to repeat
> the same tedious and scattered routine.
> 3.
>
> There’s no easy way to test the file mounting functionality alone; we
> have to construct the ConfigMap, the Deployment or the TaskManagerPod
> first
> and then do a final test.
>
>
> The reason why it is so complex to mount a configuration file is that we
> don’t fully consider the internal connections among those resources in the
> existing design.
>
> The new abstraction we proposed could solve such a kind of problem, the new
> Decorator object is as follows:
>
> public interface KubernetesStepDecorator {
>
> /**
>
> * Apply transformations to the given FlinkPod in accordance with this
> feature. This can include adding
>
> * labels/annotations, mounting volumes, and setting startup command or
> parameters, etc.
>
> */
>
> FlinkPod decorateFlinkPod(FlinkPod flinkPod);
>
> /**
>
> * Build the accompanying Kubernetes resources that should be introduced
> to support this feature. This could
>
> * only applicable to the client-side submission process.
>
> */
>
> List<HasMetadata> buildAccompanyingKubernetesResources() throws
> IOException;
>
> }
>
> The FlinkPod is a composition of the Pod, the main Container, the init
> Container, and the sidecar Container.
>
> Next, we introduce a KubernetesStepDecorator implementation, the method of
> buildAccompanyingKubernetesResources creates the corresponding ConfigMap,
> and the method of decorateFlinkPod configures the Volume for the Pod and
> all the Containers.
>
> So, for the scenario of mounting a configuration file, the advantages of
> this new architecture are as follows:
>
> 1.
>
> One dedicated KubernetesStepDecorator implementation is enough to finish
> all the mounting work, meanwhile, this class would be shared between the
> client-side and the master-side. Besides that, the number of lines of
> code
> in that class will not exceed 300 lines which facilitate code
> readability
> and maintenance.
> 2.
>
> Testing becomes an easy thing now, as we can add a dedicated test class
> for only this class, the test would never rely on the construction of
> other
> components such as the Deployment.
> 3.
>
> It’s quite convenient to mount a new configuration file via the newly
> dedicated KubernetesStepDecorator implementation.
>
>
> Question 2: How do we construct the Pod?
>
> For the existing design,
>
> 1.
>
> The FlinkMasterDeploymentDecorator is responsible for building the
> Deployment and configuring the Pod and the Containers, while the
> TaskManagerPodDecorator is responsible for building the TaskManager Pod.
> Take FlinkMasterDeploymentDecorator as an example, let’s see what it has
> done.
> 1.
>
> Configure the main Container, including the name, command, args,
> image, image pull policy, resource requirements, ports, all kinds of
> environment variables, all kinds of volume mounts, etc.
> 2.
>
> Configure the Pod, including service account, all kinds of volumes,
> and attach all kinds of Container, including the main Container, the
> init
> Container, and the sidecar Container.
> 3.
>
> Configure the Deployment.
>
>
>
> 1.
>
> The InitializerDecorator and the OwnerReferenceDecorator have basic
> logic so that the most complex work is completed in the
> FlinkMasterDeploymentDecorator and the TaskManagerPodDecorator. With the
> introduction of new features for the Pod, such as customized volume
> mounts,
> Hadoop configuration support, Kerberized HDFS support, secret mounts,
> Python support, etc. the construction process could become far more
> complicated, and the functionality of a single class could explode,
> which
> hurts code readability, writability, and testability. Besides that, both
> the client-side and the master-side shares much of the Pod construction
> logic.
>
>
> So the problems are as follows:
>
> 1.
>
> We don’t have a consistent abstraction that is applicable to both the
> client-side and the master-side for Pod construction (including the
> Containers) so that we have to share some of the code via tool classes
> which is a trick solution, however, we can’t share most of the code as
> much
> as possible.
> 2.
>
> We don’t have a step-by-step orchestrator architecture to help the Pod
> construction.
>
>
> For the proposed design,
>
> 1.
>
> The problems above are all solved: we have a consistent abstraction that
> leads to a monadic-step orchestrator architecture to construct the Pod
> step
> by step. One step is responsible for exactly one thing, following that
> is
> the fact that every step is well testable, because each unit can be
> considerably small, and the number of branches to test in any given
> step is
> limited. Moreover, much of the step could be shared between the
> client-side
> and the master-side, such as configuration files mount, etc.
>
>
> Question 3: Could all the resources share the same orchestrator
> architecture?
>
> For the existing design,
>
> 1.
>
> We don’t have a unified orchestrator architecture for the construction
> of all the Kubernetes resources, therefore, we need a Decorator chain
> for
> every Kubernetes resource.
>
>
> For the proposed design,
>
> 1.
>
> Following Question 1 ~ 2 and the design doc[1], we have introduced a
> monadic-step orchestrator architecture to construct the Pod and all the
> Containers. Besides that, this architecture also works for the other
> resources, such as the Services and the ConfigMaps. For example, if we
> need
> a new Service or a ConfigMap, just introduce a new step.
>
>
>
> Question 4: How do we introduce the InitContainer or the side-car
> Container?
>
> For the existing design,
>
> 1.
>
> Both the client-side and the master-side introduce some new Decorators,
>
> the client-side chain could be:
>
> InitializerDecorator -> OwnerReferenceDecorator ->
> FlinkMasterDeploymentDecorator -> InitContainerDecorator ->
> SidecarDecorator -> etc
>
> -
>
> and the master-side could be:
>
> InitializerDecorator -> OwnerReferenceDecorator -> TaskManagerPodDecorator
> -> InitContainerDecorator -> SidecarDecorator -> etc
>
> As we can see, the FlinkMasterDeploymentDecorator or the
> TaskManagerPodDecorator is designed for the Pod construction, including the
> Containers, so we don’t need to treat the init Container and the sidecar
> Container as special cases different from the main Container by introducing
> a dedicated Decorator for every one of them. Such kind of trick solution
> confuses me, maybe to the other developers.
>
> For the proposed design,
>
> 1.
>
> Following Question 1 ~ 4 and the design doc [1], the central premise of
> the proposed orchestrator architecture is that the Pod, the main
> Container,
> the init Container, the sidecar Container, the Services, and the
> ConfigMaps
> all sit on an equal footing. For every one of the Pod, the main
> Container,
> the init Container and the sidecar Container, people could introduce any
> number of steps to finish its construction; we attach all the
> Containers to
> the Pod in the Builder tool classes after the orchestrator architecture
> constructs them.
>
>
> Question 5: What is the relation between the Decorators?
>
> For the existing design,
>
> 1.
>
> The Decorators are not independent; most of them have a strict order in
> the chain.
> 2.
>
> The Decorators do not share common APIs in essence, as their input type
> could be different so that we can’t finish the construction of a
> Kubernetes
> resource such as the Deployment and the TaskManager Pod through a
> one-time
> traversal, there are boxing and unboxing overheads among some of the
> neighboring Decorators.
>
>
> For the proposed design,
>
> 1.
>
> The steps are completely independent so that they could have arbitrary
> order in the chain; The only rule is that the Hadoop configuration
> Decorator should be the last node in the chain.
> 2.
>
> All the steps share common APIs, with the same input type of all the
> methods, so we can construct a Kubernetes resource via a one-time
> traversal.
>
>
> Question 6: What is the number of Decorators chains?
>
> For the existing design,
>
> 1.
>
> People have to introduce a new chain once they introduce a new
> Kubernetes resource. For example, a new ConfigMap Decorator chain for
> mounting a new configuration file. At this moment, we already have five
> Decorator chains.
>
>
> For the proposed design,
>
> 1.
>
> There are always two chains, one is for constructing all the Kubernetes
> resources on the client-side, including the JobManager Pod, the
> Containers,
> the ConfigMap(s), and the Services(s); the other one is for constructing
> the TaskManager Pod and the Containers.
>
>
>
>
>
>
>
> Yang Wang <danrtsey...@gmail.com> 于2020年2月21日周五 下午2:05写道：
>
> > Hi Canbing,
> >
> >
> > Thanks a lot for sharing your thoughts to improve the Flink on K8s native
> > integration.
> > Frankly speaking, your discussion title confuses me and i am wondering
> > whether you
> > want to refactor the whole design. However, after i dive into the details
> > and the provided
> > document, i realize that mostly you want to improve the implementation.
> >
> >
> > Regarding your two main points.
> >
> > >> Introduce a unified monadic-step based orchestrator architecture that
> > has a better,
> > cleaner and consistent abstraction for the Kubernetes resources
> > construction process,
> > both applicable to the client side and the master side.
> >
> > When i introduce the decorator for the K8s in Flink, there is always a
> > guideline in my mind
> > that it should be easy for extension and adding new features. Just as you
> > say, we have lots
> > of functions to support and the K8s is also evolving very fast. The
> current
> > `ConfigMapDecorator`,
> > `FlinkMasterDeploymentDecorator`, `TaskManagerPodDecorator` is a basic
> > implementation with
> > some prerequisite parameters. Of course we could chain more decorators to
> > construct the K8s
> > resources. For example, InitializerDecorator -> OwnerReferenceDecorator
> ->
> > FlinkMasterDeploymentDecorator -> InitContainerDecorator ->
> > SidecarDecorator -> etc.
> >
> > I am little sceptical about splitting every parameter into a single
> > decorator. Since it does
> > not take too much benefits. But i agree with moving some common
> parameters
> > into separate
> > decorators(e.g. volume mount). Also introducing the `~Builder` class and
> > spinning off the chaining
> > decorator calls from `Fabric8FlinkKubeClient` make sense to me.
> >
> >
> >
> > >> Add some dedicated tools for centrally parsing, verifying, and
> managing
> > the Kubernetes parameters.
> >
> > Currently, we always get the parameters directly from Flink
> configuration(
> > e.g. `flinkConfig.getString(KubernetesConfigOptions.CONTAINER_IMAGE)`). I
> > think it could be improved
> > by introducing some dedicated conf parser classes. It is a good idea.
> >
> >
> > Best,
> > Yang
> >
> >
> >
> >
> > felixzheng zheng <felixzhen...@gmail.com> 于2020年2月21日周五 上午9:31写道：
> >
> > > Hi everyone,
> > >
> > > I would like to kick off a discussion on refactoring the existing
> > > Kubernetes resources construction architecture design.
> > >
> > > I created a design document [1] that clarifies our motivation to do
> this
> > > and some improvement proposals for the new design.
> > >
> > > Briefly, we would like to
> > > 1. Introduce a unified monadic-step based orchestrator architecture
> that
> > > has a better, cleaner and consistent abstraction for the Kubernetes
> > > resources construction process, both applicable to the client side and
> > the
> > > master side.
> > > 2. Add some dedicated tools for centrally parsing, verifying, and
> > managing
> > > the Kubernetes parameters.
> > >
> > > It would be great to start the efforts before adding big features for
> the
> > > native Kubernetes submodule, and Tison and I plan to work together for
> > this
> > > issue.
> > >
> > > Please let me know your thoughts.
> > >
> > > Regards,
> > > Canbin Zheng
> > >
> > > [1]
> > >
> > >
> >
> https://docs.google.com/document/d/1dFBjqho8IRyNWxKVhFnTf0qGCsgp72aKON4wUdHY5Pg/edit?usp=sharing
> > > [2] https://issues.apache.org/jira/browse/FLINK-16194
> > >
> >
>
