Hi Eugene, Glad that helped you out and thanks for the PR tweaking it for GCP.
To fetch the containers from GCR, I had to log into Docker inside the Flink nodes, specifically inside the taskmanager container, using something like “kubectl exec pod/flink-taskmanager-blahblah -c taskmanager — docker login -u oauth2accesstoken —password $(gcloud auth print-access-token)” Ouch that seems painful. I find this “precaching” step pretty silly and have considered making the DockerEnvironmentFactory a little more intelligent about how it deals with timeouts (e.g. no activity). It doesn’t seem like it would be too difficult to also add first-class support for pulling images from protected repositories. Extending the DockerPayload protobuf to pass along the additional information and tweaking the DockerEnvironmentFactory? I’m not a java expert but that might be worth exploring if this continues to be problematic. I found the time it takes to pull can be dramatically improved if you store everything in memory <https://github.com/sambvfx/beam-flink-k8s/blob/master/k8s/flink.yaml#L186>. In the end, I got my pipeline to start, create the uber jar (about 240MB in size), take a few minutes to transmit it to Flink You could explore spinning up the beam-flink-job-server <https://github.com/sambvfx/beam-flink-k8s/blob/master/k8s/beam-flink-jobserver.yaml> and using the PortableRunner. In theory that should reduce the amount of data you’re syncing to the cluster. It does require exposing at least two ingress points (8099 and 8098) so you can hit the job and artifact services respectively. Cheers, Sam On Fri, Aug 28, 2020 at 5:50 PM Eugene Kirpichov <[email protected]> wrote: > Woohoo thanks Kyle, adding --save_main_session made it work!!! > > On Fri, Aug 28, 2020 at 5:02 PM Kyle Weaver <[email protected]> wrote: > >> > rpc error: code = Unimplemented desc = Method not found: >> org.apache.beam.model.job_management.v1.LegacyArtifactRetrievalService/GetManifest >> >> This is a known issue: https://issues.apache.org/jira/browse/BEAM-10762 >> >> On Fri, Aug 28, 2020 at 4:57 PM Eugene Kirpichov <[email protected]> >> wrote: >> >>> P.S. Ironic how back in 2018 I was TL-ing the portable runners effort >>> for a few months on Google side, and now I need community help to get it to >>> work at all. >>> Still pretty miraculous how far Beam's portability has come since >>> then, even if it has a steep learning curve. >>> >>> On Fri, Aug 28, 2020 at 4:54 PM Eugene Kirpichov <[email protected]> >>> wrote: >>> >>>> Hi Sam, >>>> >>>> You're a wizard - this got me *way* farther than my previous attempts. >>>> Here's a PR https://github.com/sambvfx/beam-flink-k8s/pull/1 with a >>>> couple of changes I had to make. >>>> >>>> I had to make some additional changes that do not make sense to share, >>>> but here they are for the record: >>>> - Because I'm running on k8s engine and not minikube, I had to put the >>>> docker-flink image on GCR, changing flink.yaml "image: docker-flink:1.10" >>>> -> "image: us.gcr.io/$PROJECT_ID/docker-flink:1.10". I of course also >>>> had to build and push the container. >>>> - Because I'm running with a custom container based on an unreleased >>>> version of Beam, I had to push my custom container to GCR too, and change >>>> your instructions to use that image name instead of the default one >>>> - To fetch the containers from GCR, I had to log into Docker inside the >>>> Flink nodes, specifically inside the taskmanager container, using something >>>> like "kubectl exec pod/flink-taskmanager-blahblah -c taskmanager -- docker >>>> login -u oauth2accesstoken --password $(gcloud auth print-access-token)" >>>> - Again because I'm using an unreleased Beam SDK (due to a bug whose >>>> fix will be released in 2.24), I had to also build a custom Flink job >>>> server jar and point to it via --flink_job_server_jar. >>>> >>>> In the end, I got my pipeline to start, create the uber jar (about >>>> 240MB in size), take a few minutes to transmit it to Flink (which is a long >>>> time, but it'll do for a prototype); the Flink UI was displaying the >>>> pipeline, and was able to *start* the worker container - however it >>>> quickly failed with the following error: >>>> >>>> 2020/08/28 15:49:09 Initializing python harness: /opt/apache/beam/boot >>>> --id=1-1 --provision_endpoint=localhost:45111 >>>> 2020/08/28 15:49:09 Failed to retrieve staged files: failed to get >>>> manifest >>>> caused by: >>>> rpc error: code = Unimplemented desc = Method not found: >>>> org.apache.beam.model.job_management.v1.LegacyArtifactRetrievalService/GetManifest >>>> (followed by a bunch of other garbage) >>>> >>>> I'm assuming this might be because I got tangled in my custom images >>>> related to the unreleased Beam SDK, and should be fixed if running on clean >>>> Beam 2.24. >>>> >>>> Thank you again! >>>> >>>> On Fri, Aug 28, 2020 at 10:21 AM Eugene Kirpichov <[email protected]> >>>> wrote: >>>> >>>>> Holy shit, thanks Sam, this is more help than I could have asked for!! >>>>> I'll give this a shot later today and report back. >>>>> >>>>> On Thu, Aug 27, 2020 at 10:27 PM Sam Bourne <[email protected]> wrote: >>>>> >>>>>> Hi Eugene! >>>>>> >>>>>> I’m struggling to find complete documentation on how to do this. >>>>>> There seems to be lots of conflicting or incomplete information: several >>>>>> ways to deploy Flink, several ways to get Beam working with it, bizarre >>>>>> StackOverflow questions, and no documentation explaining a complete >>>>>> working >>>>>> example. >>>>>> >>>>>> This *is* possible and I went through all the same frustrations of >>>>>> sparse and confusing documentation. I’m glossing over a lot of details, >>>>>> but >>>>>> the key thing was setting up the flink taskworker(s) to run docker. This >>>>>> requires running docker-in-docker as the taskworker itself is a docker >>>>>> container in k8s. >>>>>> >>>>>> First create a custom flink container with docker: >>>>>> >>>>>> # docker-flink Dockerfile >>>>>> >>>>>> FROM flink:1.10 >>>>>> # install docker >>>>>> RUN apt-get ... >>>>>> >>>>>> Then setup the taskmanager deployment to use a sidecar >>>>>> docker-in-docker service. This dind service is where the python sdk >>>>>> harness >>>>>> container actually runs. >>>>>> >>>>>> kind: Deployment >>>>>> ... >>>>>> containers: >>>>>> - name: docker >>>>>> image: docker:19.03.5-dind >>>>>> ... >>>>>> - name: taskmanger >>>>>> image: myregistry:5000/docker-flink:1.10 >>>>>> env: >>>>>> - name: DOCKER_HOST >>>>>> value: tcp://localhost:2375 >>>>>> ... >>>>>> >>>>>> I quickly threw all these pieces together in a repo here: >>>>>> https://github.com/sambvfx/beam-flink-k8s >>>>>> >>>>>> I added a working (via minikube) step-by-step in the README to prove >>>>>> to myself that I didn’t miss anything, but feel free to submit any PRs if >>>>>> you want to add anything useful. >>>>>> >>>>>> The documents you linked are very informative. It would be great to >>>>>> aggregate all this into digestible documentation. Let me know if you have >>>>>> any further questions! >>>>>> >>>>>> Cheers, >>>>>> Sam >>>>>> >>>>>> On Thu, Aug 27, 2020 at 10:25 AM Eugene Kirpichov < >>>>>> [email protected]> wrote: >>>>>> >>>>>>> Hi Kyle, >>>>>>> >>>>>>> Thanks for the response! >>>>>>> >>>>>>> On Wed, Aug 26, 2020 at 5:28 PM Kyle Weaver <[email protected]> >>>>>>> wrote: >>>>>>> >>>>>>>> > - With the Flink operator, I was able to submit a Beam job, but >>>>>>>> hit the issue that I need Docker installed on my Flink nodes. I >>>>>>>> haven't yet >>>>>>>> tried changing the operator's yaml files to add Docker inside them. >>>>>>>> >>>>>>>> Running Beam workers via Docker on the Flink nodes is not >>>>>>>> recommended (and probably not even possible), since the Flink nodes are >>>>>>>> themselves already running inside Docker containers. Running workers as >>>>>>>> sidecars avoids that problem. For example: >>>>>>>> https://github.com/GoogleCloudPlatform/flink-on-k8s-operator/blob/master/examples/beam/with_job_server/beam_flink_cluster.yaml#L17-L20 >>>>>>>> >>>>>>>> The main problem with the sidecar approach is that I can't use the >>>>>>> Flink cluster as a "service" for anybody to submit their jobs with >>>>>>> custom >>>>>>> containers - the container version is fixed. >>>>>>> Do I understand it correctly? >>>>>>> Seems like the Docker-in-Docker approach is viable, and is mentioned >>>>>>> in the Beam Flink K8s design doc >>>>>>> <https://docs.google.com/document/d/1z3LNrRtr8kkiFHonZ5JJM_L4NWNBBNcqRc_yAf6G0VI/edit#heading=h.dtj1gnks47dq> >>>>>>> . >>>>>>> >>>>>>> >>>>>>>> > I also haven't tried this >>>>>>>> <https://github.com/GoogleCloudPlatform/flink-on-k8s-operator/blob/master/docs/beam_guide.md> >>>>>>>> yet >>>>>>>> because it implies submitting jobs using "kubectl apply" which is >>>>>>>> weird - >>>>>>>> why not just submit it through the Flink job server? >>>>>>>> >>>>>>>> I'm guessing it goes through k8s for monitoring purposes. I see no >>>>>>>> reason it shouldn't be possible to submit to the job server directly >>>>>>>> through Python, network permitting, though I haven't tried this. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> On Wed, Aug 26, 2020 at 4:10 PM Eugene Kirpichov < >>>>>>>> [email protected]> wrote: >>>>>>>> >>>>>>>>> Hi folks, >>>>>>>>> >>>>>>>>> I'm still working with Pachama <https://pachama.com/> right now; >>>>>>>>> we have a Kubernetes Engine cluster on GCP and want to run Beam Python >>>>>>>>> batch pipelines with custom containers against it. >>>>>>>>> Flink and Cloud Dataflow are the two options; Cloud Dataflow >>>>>>>>> doesn't support custom containers for batch pipelines yes so we're >>>>>>>>> going >>>>>>>>> with Flink. >>>>>>>>> >>>>>>>>> I'm struggling to find complete documentation on how to do this. >>>>>>>>> There seems to be lots of conflicting or incomplete information: >>>>>>>>> several >>>>>>>>> ways to deploy Flink, several ways to get Beam working with it, >>>>>>>>> bizarre >>>>>>>>> StackOverflow questions, and no documentation explaining a complete >>>>>>>>> working >>>>>>>>> example. >>>>>>>>> >>>>>>>>> == My requests == >>>>>>>>> * Could people briefly share their working setup? Would be good to >>>>>>>>> know which directions are promising. >>>>>>>>> * It would be particularly helpful if someone could volunteer an >>>>>>>>> hour of their time to talk to me about their working Beam/Flink/k8s >>>>>>>>> setup. >>>>>>>>> It's for a good cause (fixing the planet :) ) and on my side I >>>>>>>>> volunteer to >>>>>>>>> write up the findings to share with the community so others suffer >>>>>>>>> less. >>>>>>>>> >>>>>>>>> == Appendix: My findings so far == >>>>>>>>> There are multiple ways to deploy Flink on k8s: >>>>>>>>> - The GCP marketplace Flink operator >>>>>>>>> <https://cloud.google.com/blog/products/data-analytics/open-source-processing-engines-for-kubernetes> >>>>>>>>> (couldn't >>>>>>>>> get it to work) and the respective CLI version >>>>>>>>> <https://github.com/GoogleCloudPlatform/flink-on-k8s-operator> (buggy, >>>>>>>>> but I got it working) >>>>>>>>> - https://github.com/lyft/flinkk8soperator (haven't tried) >>>>>>>>> - Flink's native k8s support >>>>>>>>> <https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/native_kubernetes.html> >>>>>>>>> (super >>>>>>>>> easy to get working) >>>>>>>>> <https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/native_kubernetes.html> >>>>>>>>> >>>>>>>>> I confirmed that my Flink cluster was operational by running a >>>>>>>>> simple Wordcount job, initiated from my machine. However I wasn't yet >>>>>>>>> able >>>>>>>>> to get Beam working: >>>>>>>>> >>>>>>>>> - With the Flink operator, I was able to submit a Beam job, but >>>>>>>>> hit the issue that I need Docker installed on my Flink nodes. I >>>>>>>>> haven't yet >>>>>>>>> tried changing the operator's yaml files to add Docker inside them. I >>>>>>>>> also >>>>>>>>> haven't tried this >>>>>>>>> <https://github.com/GoogleCloudPlatform/flink-on-k8s-operator/blob/master/docs/beam_guide.md> >>>>>>>>> yet because it implies submitting jobs using "kubectl apply" which is >>>>>>>>> weird - why not just submit it through the Flink job server? >>>>>>>>> >>>>>>>>> - With Flink's native k8s support, I tried two things: >>>>>>>>> - Creating a fat portable jar using --output_executable_path. >>>>>>>>> The jar is huge (200+MB) and takes forever to upload to my Flink >>>>>>>>> cluster - >>>>>>>>> this is a non-starter. But if I actually upload it, then I hit the >>>>>>>>> same >>>>>>>>> issue with lacking Docker. Haven't tried fixing it yet. >>>>>>>>> - Simply running my pipeline --runner=FlinkRunner >>>>>>>>> --environment_type=DOCKER --flink_master=$PUBLIC_IP:8081. The Java >>>>>>>>> process >>>>>>>>> appears to send 1+GB of data to somewhere, but the job never even >>>>>>>>> starts. >>>>>>>>> >>>>>>>>> I looked at a few conference talks: >>>>>>>>> - >>>>>>>>> https://www.cncf.io/wp-content/uploads/2020/02/CNCF-Webinar_-Apache-Flink-on-Kubernetes-Operator-1.pdf >>>>>>>>> - seems to imply that I need to add a Beam worker "sidecar" to the >>>>>>>>> Flink >>>>>>>>> workers; and that I need to submit my job using "kubectl apply". >>>>>>>>> - https://www.youtube.com/watch?v=8k1iezoc5Sc which also mentions >>>>>>>>> the sidecar, but also mentions the fat jar option >>>>>>>>> >>>>>>>>> -- >>>>>>>>> Eugene Kirpichov >>>>>>>>> http://www.linkedin.com/in/eugenekirpichov >>>>>>>>> >>>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Eugene Kirpichov >>>>>>> http://www.linkedin.com/in/eugenekirpichov >>>>>>> >>>>>> >>>>> >>>>> -- >>>>> Eugene Kirpichov >>>>> http://www.linkedin.com/in/eugenekirpichov >>>>> >>>> >>>> >>>> -- >>>> Eugene Kirpichov >>>> http://www.linkedin.com/in/eugenekirpichov >>>> >>> >>> >>> -- >>> Eugene Kirpichov >>> http://www.linkedin.com/in/eugenekirpichov >>> >> > > -- > Eugene Kirpichov > http://www.linkedin.com/in/eugenekirpichov >
