Hi Konstantin, I'm not very familiar with the implementation of per-job mode and application mode. But is there any instruction for users abou how to migrate platforms/jobs to application mode? IIUC, the biggest difference between the two modes is where the main() method is executed. However, SQL jobs are not jar applications and don't have the main() method. For example, SQL CLI submits SQL jobs by invoking `StreamExecutionEnvironment#executeAsync(StreamGraph)`. How SQL Client and SQL platforms (e.g. Zeppelin) support application mode?
Best, Jark On Fri, 28 Jan 2022 at 23:33, Konstantin Knauf <kna...@apache.org> wrote: > Hi everyone, > > Thank you for sharing your perspectives. I was not aware of > these limitations of per-job mode on YARN. It seems that there is a general > agreement to deprecate per-job mode and to drop it once the limitations > around YARN are resolved. I've started a corresponding vote in [1]. > > Thanks again, > > Konstantin > > > [1] https://lists.apache.org/thread/v6oz92dfp95qcox45l0f8393089oyjv4 > > On Fri, Jan 28, 2022 at 1:53 PM Ferenc Csaky <ferenc.cs...@pm.me.invalid> > wrote: > > > Hi Yang, > > > > Thank you for the clarification. In general I think we will have time to > > experiment with this until it will be removed totally and migrate our > > solution to use application mode. > > > > Regards, > > F > > > > On 2022/01/26 02:42:24 Yang Wang wrote: > > > Hi all, > > > > > > I remember the application mode was initially named "cluster mode". As > a > > > contrast, the per-job mode is the "client mode". > > > So I believe application mode should cover all the functionalities of > > > per-job except where we are running the user main code. > > > In the containerized or the Kubernetes world, the application mode is > > more > > > native and easy to use since all the Flink and user > > > jars are bundled in the image. I am also in favor of deprecating and > > > removing the per-job in the long run. > > > > > > > > > > > > @Ferenc > > > IIRC, the YARN application mode could ship user jars and dependencies > via > > > "yarn.ship-files" config option. The only > > > limitation is that we could not ship and load the user dependencies > with > > > user classloader, not the parent classloader. > > > FLINK-24897 is trying to fix this via supporting "usrlib" directory > > > automatically. > > > > > > > > > Best, > > > Yang > > > > > > > > > > > > Ferenc Csaky <fe...@pm.me.invalid> 于2022年1月25日周二 22:05写道： > > > > > > > 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 > > > > > > > > > > > > > -- > > Konstantin Knauf > > https://twitter.com/snntrable > > https://github.com/knaufk >
