Thanks Wang for your detailed answers.
>From what I understand the native_kubernetes also leans towards creating a
>session and submitting a job to it.
Regarding other recommendations, please my inline comments and advice.
On Sunday, February 23, 2020, 10:01:10 PM EST, Yang Wang
<[email protected]> wrote:
Hi Singh,
Glad to hear that you are looking to run Flink on the Kubernetes. I amtrying to
answer your question based on my limited knowledge andothers could correct me
and add some more supplements.
I think the biggest difference between session cluster and per-job clusteron
Kubernetesis the isolation. Since for per-job, a dedicated Flink clusterwill be
started for the only one job and no any other jobs could be submitted.Once the
job is finished, then the Flink cluster will be destroyed immediately.The
second point is one-step submission. You do not need to start a Flinkcluster
first and then submit a job to the existing session.
> Are there any benefits with regards to1. Configuring the jobsNo matter you
>are using the per-job cluster or submitting to the existingsession cluster,
>they share the configuration mechanism. You do not haveto change any codes and
>configurations.
2. Scaling the taskmanagerSince you are using the Standalone cluster on
Kubernetes, it do not providean active resourcemanager. You need to use
external tools to monitor andscale up the taskmanagers. The active integration
is still evolving and youcould have a taste[1].
Mans - If we use the session based deployment option for K8 - I thought K8 will
automatically restarts any failed TM or JM. In the case of failed TM - the job
will probably recover, but in the case of failed JM - perhaps we need to
resubmit all jobs.Let me know if I have misunderstood anything.
3. Restarting jobsFor the session cluster, you could directly cancel the job
and re-submit. Andfor per-job cluster, when the job is canceled, you need to
start a new per-jobcluster from the latest savepoint.
4. Managing the flink jobsThe rest api and flink command line could be used to
managing the jobs(e.g.flink cancel, etc.). I think there is no difference for
session and per-job here.
5. Passing credentials (in case of AWS, etc)
I am not sure how do you provide your credentials. If you put them in the
config map and then mount into the jobmanager/taskmanager pod, then bothsession
and per-job could support this way.
Mans - Is there any safe way of a passing creds ?
6. Fault tolerence and recovery of jobs from failure
For session cluster, if one taskmanager crashed, then all the jobs which have
taskson this taskmanager will failed. Both session and per-job could be
configured with high availability and recoverfrom the latest checkpoint.
Mans - Does a task manager failure cause the job to fail ? My understanding is
the JM failure are catastrophic while TM failures are recoverable.
> Is there any need for specifying volume for the pods?No, you do not need to
>specify a volume for pod. All the data in the pod local directory is
>temporary. When a pod crashed and relaunched, thetaskmanager will retrieve the
>checkpoint from zookeeper + S3 and resumefrom the latest checkpoint.
Mans - So if we are saving checkpoint in S3 then there is no need for disks -
should we use emptyDir ?
[1].
https://ci.apache.org/projects/flink/flink-docs-master/ops/deployment/native_kubernetes.html
M Singh <[email protected]> 于2020年2月23日周日 上午2:28写道：
Hey Folks:
I am trying to figure out the options for running Flink on Kubernetes and am
trying to find out the pros and cons of running in Flink Session vs Flink
Cluster mode
(https://ci.apache.org/projects/flink/flink-docs-stable/ops/deployment/kubernetes.html#flink-session-cluster-on-kubernetes).
I understand that in job mode there is no need to submit the job since it is
part of the job image. But what are other the pros and cons of this approach
vs session mode where a job manager is deployed and flink jobs can be submitted
it ? Are there any benefits with regards to:
1. Configuring the jobs 2. Scaling the taskmanager3. Restarting jobs4. Managing
the flink jobs5. Passing credentials (in case of AWS, etc)6. Fault tolerence
and recovery of jobs from failure
Also, we will be keeping the checkpoints for the jobs on S3. Is there any need
for specifying volume for the pods ? If volume is required do we need
provisioned volume and what are the recommended alternatives/considerations
especially with AWS.
If there are any other considerations, please let me know.
Thanks for your advice.
