Hi Tison, Sorry for the late reply. I am busy with some internal urgent work last week. I tried to read the FLIP-73, from my limited understanding. The scope of this FLIP is to unify the deployment process of each type of cluster management system. As the implementation details is unclear, I have some question about it.
1) How will the change existing deployment solution? Currently, the deployment process for yarn is managed by FlinkYarnSessionClient, the user program is only used for generating the the PackagedProgram and then JobGraph. The job submission and session lifecycle management is handled with it. Are you proposing the executor implementation for yarn talk to FlinkYarnSessionClient? How the module dependency is managed? 2) I feel the FLIP-73 only impacts session cluster mode, as it needs to use cluster clients to talk to the existing Flink cluster. The proposal for FLIP-85 is only for per job mode, does it mean there is no conflicts? Best Regards Peter Huang On Thu, Dec 12, 2019 at 12:48 AM tison <wander4...@gmail.com> wrote: > A quick idea is that we separate the deployment from user program that it > has always been done > outside the program. On user program executed there is always a > ClusterClient that communicates with > an existing cluster, remote or local. It will be another thread so just for > your information. > > Best, > tison. > > > tison <wander4...@gmail.com> 于2019年12月12日周四 下午4:40写道： > > > Hi Peter, > > > > Another concern I realized recently is that with current Executors > > abstraction(FLIP-73) > > I'm afraid that user program is designed to ALWAYS run on the client > side. > > Specifically, > > we deploy the job in executor when env.execute called. This abstraction > > possibly prevents > > Flink runs user program on the cluster side. > > > > For your proposal, in this case we already compiled the program and run > on > > the client side, > > even we deploy a cluster and retrieve job graph from program metadata, it > > doesn't make > > many sense. > > > > cc Aljoscha & Kostas what do you think about this constraint? > > > > Best, > > tison. > > > > > > Peter Huang <huangzhenqiu0...@gmail.com> 于2019年12月10日周二 下午12:45写道： > > > >> Hi Tison, > >> > >> Yes, you are right. I think I made the wrong argument in the doc. > >> Basically, the packaging jar problem is only for platform users. In our > >> internal deploy service, > >> we further optimized the deployment latency by letting users to > packaging > >> flink-runtime together with the uber jar, so that we don't need to > >> consider > >> multiple flink version > >> support for now. In the session client mode, as Flink libs will be > shipped > >> anyway as local resources of yarn. Users actually don't need to package > >> those libs into job jar. > >> > >> > >> > >> Best Regards > >> Peter Huang > >> > >> On Mon, Dec 9, 2019 at 8:35 PM tison <wander4...@gmail.com> wrote: > >> > >> > > 3. What do you mean about the package? Do users need to compile > their > >> > jars > >> > inlcuding flink-clients, flink-optimizer, flink-table codes? > >> > > >> > The answer should be no because they exist in system classpath. > >> > > >> > Best, > >> > tison. > >> > > >> > > >> > Yang Wang <danrtsey...@gmail.com> 于2019年12月10日周二 下午12:18写道： > >> > > >> > > Hi Peter, > >> > > > >> > > Thanks a lot for starting this discussion. I think this is a very > >> useful > >> > > feature. > >> > > > >> > > Not only for Yarn, i am focused on flink on Kubernetes integration > and > >> > come > >> > > across the same > >> > > problem. I do not want the job graph generated on client side. > >> Instead, > >> > the > >> > > user jars are built in > >> > > a user-defined image. When the job manager launched, we just need to > >> > > generate the job graph > >> > > based on local user jars. > >> > > > >> > > I have some small suggestion about this. > >> > > > >> > > 1. `ProgramJobGraphRetriever` is very similar to > >> > > `ClasspathJobGraphRetriever`, the differences > >> > > are the former needs `ProgramMetadata` and the latter needs some > >> > arguments. > >> > > Is it possible to > >> > > have an unified `JobGraphRetriever` to support both? > >> > > 2. Is it possible to not use a local user jar to start a per-job > >> cluster? > >> > > In your case, the user jars has > >> > > existed on hdfs already and we do need to download the jars to > >> deployer > >> > > service. Currently, we > >> > > always need a local user jar to start a flink cluster. It is be > great > >> if > >> > we > >> > > could support remote user jars. > >> > > >> In the implementation, we assume users package flink-clients, > >> > > flink-optimizer, flink-table together within the job jar. Otherwise, > >> the > >> > > job graph generation within JobClusterEntryPoint will fail. > >> > > 3. What do you mean about the package? Do users need to compile > their > >> > jars > >> > > inlcuding flink-clients, flink-optimizer, flink-table codes? > >> > > > >> > > > >> > > > >> > > Best, > >> > > Yang > >> > > > >> > > Peter Huang <huangzhenqiu0...@gmail.com> 于2019年12月10日周二 上午2:37写道： > >> > > > >> > > > Dear All, > >> > > > > >> > > > Recently, the Flink community starts to improve the yarn cluster > >> > > descriptor > >> > > > to make job jar and config files configurable from CLI. It > improves > >> the > >> > > > flexibility of Flink deployment Yarn Per Job Mode. For platform > >> users > >> > > who > >> > > > manage tens of hundreds of streaming pipelines for the whole org > or > >> > > > company, we found the job graph generation in client-side is > another > >> > > > pinpoint. Thus, we want to propose a configurable feature for > >> > > > FlinkYarnSessionCli. The feature can allow users to choose the job > >> > graph > >> > > > generation in Flink ClusterEntryPoint so that the job jar doesn't > >> need > >> > to > >> > > > be locally for the job graph generation. The proposal is organized > >> as a > >> > > > FLIP > >> > > > > >> > > > > >> > > > >> > > >> > https://cwiki.apache.org/confluence/display/FLINK/FLIP-85+Delayed+JobGraph+Generation > >> > > > . > >> > > > > >> > > > Any questions and suggestions are welcomed. Thank you in advance. > >> > > > > >> > > > > >> > > > Best Regards > >> > > > Peter Huang > >> > > > > >> > > > >> > > >> > > >
