Hi Konstantin, First of all, sorry for the delay. We at Cloudera are currently relying on per-job mode deploying Flink applications over YARN.
Specifically, we allow users to upload connector jars and other artifacts. There are also some default jars that we need to ship. These are all stored on the local file system of our service’s node. The Flink job is submitted on the users’ behalf by our service, which also specifies the jars to ship. The service runs on a single node, not on all nodes with Flink TM/JM. It would thus be difficult to manage the jars on every node. We are not familiar with the reasoning behind why application mode currently doesn’t ship the user jars, besides the deployment being faster this way. Would it be possible for the application mode to (optionally, enabled by some config) distribute these, or are there some technical limitations? For us it would be crucial to achieve the functionality we have at the moment over YARN. We started to track https://issues.apache.org/jira/browse/FLINK-24897 that Biao Geng mentioned as well. Considering the above, for us the more soonish removal does not sound really well. We can live with this feature as deprecated of course, but it would be nice to have some time to figure out how we can utilize Application Mode exactly and make necessary changes if required. Thank you, F On 2022/01/13 08:30:48 Konstantin Knauf wrote: > Hi everyone, > > I would like to discuss and understand if the benefits of having Per-Job > Mode in Apache Flink outweigh its drawbacks. > > > *# Background: Flink's Deployment Modes* > Flink currently has three deployment modes. They differ in the following > dimensions: > * main() method executed on Jobmanager or Client > * dependencies shipped by client or bundled with all nodes > * number of jobs per cluster & relationship between job and cluster > lifecycle* (supported resource providers) > > ## Application Mode > * main() method executed on Jobmanager > * dependencies already need to be available on all nodes > * dedicated cluster for all jobs executed from the same main()-method > (Note: applications with more than one job, currently still significant > limitations like missing high-availability). Technically, a session cluster > dedicated to all jobs submitted from the same main() method. > * supported by standalone, native kubernetes, YARN > > ## Session Mode > * main() method executed in client > * dependencies are distributed from and by the client to all nodes > * cluster is shared by multiple jobs submitted from different clients, > independent lifecycle > * supported by standalone, Native Kubernetes, YARN > > ## Per-Job Mode > * main() method executed in client > * dependencies are distributed from and by the client to all nodes > * dedicated cluster for a single job > * supported by YARN only > > > *# Reasons to Keep** There are use cases where you might need the > combination of a single job per cluster, but main() method execution in the > client. This combination is only supported by per-job mode. > * It currently exists. Existing users will need to migrate to either > session or application mode. > > > *# Reasons to Drop** With Per-Job Mode and Application Mode we have two > modes that for most users probably do the same thing. Specifically, for > those users that don't care where the main() method is executed and want to > submit a single job per cluster. Having two ways to do the same thing is > confusing. > * Per-Job Mode is only supported by YARN anyway. If we keep it, we should > work towards support in Kubernetes and Standalone, too, to reduce special > casing. > * Dropping per-job mode would reduce complexity in the code and allow us to > dedicate more resources to the other two deployment modes. > * I believe with session mode and application mode we have to easily > distinguishable and understandable deployment modes that cover Flink's use > cases: > * session mode: olap-style, interactive jobs/queries, short lived batch > jobs, very small jobs, traditional cluster-centric deployment mode (fits > the "Hadoop world") > * application mode: long-running streaming jobs, large scale & > heterogenous jobs (resource isolation!), application-centric deployment > mode (fits the "Kubernetes world") > > > *# Call to Action* > * Do you use per-job mode? If so, why & would you be able to migrate to one > of the other methods? > * Am I missing any pros/cons? > * Are you in favor of dropping per-job mode midterm? > > Cheers and thank you, > > Konstantin > > -- > > Konstantin Knauf > > https://twitter.com/snntrable > > https://github.com/knaufk >
