> The new introduced decorator
After some offline discussion with Canbin and tison, i totally understand
the evolved decorator design. Each decorator will be self-contained and
is responsible for just one thing. Currently, if we want to mount a new
config
file to jobmanager/taskmanager, then both `ConfigMapDecorator`,
`JobManagerDecorator`, `TaskManagerDecorator` needs to be updated.
It is not convenient for the new contributors to do this. In the new design,
by leveraging the accompanying kubernetes resources in decorator, we
could finish the creating and mounting config map in one decorator.
Since now we just have a basic implementation for native Kubernetes
integration and lots of features need to be developed. And many users
want to participate in and contribute to the integration. So i agree to
refactor
the current decorator implementation and make it easier for the new
contributor.
For the detailed divergences(naming, etc.), i think we could discuss in the
PR.
> Parameters Parser
Currently, the decorator directly use Flink configuration to get the
parameters
to build the Kubernetes resource. It is straightforward, however we could
not
have a unified parameters check. So i am not sure whether you will introduce
a tool to check the parameters or just simply have our own basic check.
BTW, the fabric8 kubernetes-client and Kubernetes api server already has
the parameters check before starting to create the resources. I think the
exceptions
are usually meaning and enough for the users to get the root cause.
Best,
Yang
felixzheng zheng <felixzhen...@gmail.com> 于2020年2月22日周六 上午10:54写道：
> Great thanks for the quick feedback Till. You are right; it is not a
> fundamentally different approach compared to
> what we have right now, all the Kubernetes resources created are the same,
> we aim to evolve the existing decorator approach so that,
> 1. the decorators are monadic and smaller in size and functionality.
> 2. the new decorator design allows reusing the decorators between the
> client and the cluster as much as possible.
> 3. all the decorators are independent with each other, and they could have
> arbitrary order in the chain, they share the same APIs and follow a unified
> orchestrator architecture so that new developers could quickly understand
> what should be done to introduce a new feature.
>
> Besides that, the new approach allows us adding tests for every decorator
> alone instead of doing a final test of all the decorators in the
> Fabric8ClientTest.java.
>
> Cheers,
> Canbin Zheng
>
> Till Rohrmann <trohrm...@apache.org> 于2020年2月22日周六 上午12:28写道：
>
> > 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
> > > > >
> > > >
> > >
> >
>
