dispatch job #58
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| name: dispatch job | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| repo: | |
| description: 'The https github url for the recipe feedstock' | |
| required: true | |
| ref: | |
| description: 'The tag or branch to target in your recipe repo' | |
| required: true | |
| default: 'main' | |
| feedstock_subdir: | |
| description: 'The subdir of the feedstock directory in the repo' | |
| required: true | |
| default: 'feedstock' | |
| bucket: | |
| description: 'This job runner leverages s3fs.S3FileSystem for your recipe cache and output. Choices currently are: "default"' | |
| required: true | |
| default: 'default' | |
| prune: | |
| description: 'Only run the first two time steps' | |
| required: true | |
| default: '0' | |
| parallelism: | |
| description: 'Number of task managers to spin up' | |
| required: true | |
| default: '1' | |
| jobs: | |
| name-job: | |
| runs-on: ubuntu-latest | |
| outputs: | |
| repo_name: ${{ steps.string_manipulation.outputs.result }} | |
| steps: | |
| - name: manipuluate strings | |
| id: string_manipulation | |
| run: | | |
| repo_name=$(basename -s .git "${{ github.event.inputs.repo }}") | |
| echo "result=$repo_name" >> $GITHUB_OUTPUT | |
| run-job: | |
| name: kickoff job ${{ needs.name-job.outputs.repo_name }}@${{ github.event.inputs.ref }} | |
| needs: name-job | |
| outputs: | |
| job_name: ${{ steps.report_ids.outputs.job_name }} | |
| job_id: ${{ steps.report_ids.outputs.job_id }} | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: checkout repository | |
| uses: actions/checkout@v3 | |
| - name: set up python 3.10 | |
| uses: actions/setup-python@v3 | |
| with: | |
| python-version: '3.10' | |
| - name: echo server | |
| run: | | |
| echo "Manually triggered workflow: \ | |
| ${{ github.event.inputs.repo }} \ | |
| ${{ github.event.inputs.ref }} \ | |
| ${{ github.event.inputs.bucket }} \ | |
| ${{ github.event.inputs.parallelism }} \ | |
| ${{ github.event.inputs.prune }}" | |
| - name: install deps | |
| run: | | |
| # TODO: move to requirements file | |
| python -m pip install --upgrade pip | |
| pip install \ | |
| fsspec \ | |
| s3fs \ | |
| boto3 \ | |
| apache-beam==2.52.0 \ | |
| pangeo-forge-recipes>=0.10.0 \ | |
| pangeo-forge-runner>=0.9.1 \ | |
| python-cmr==0.9.0 | |
| - name: set up aws credentials for job runner user | |
| uses: aws-actions/configure-aws-credentials@v2 | |
| with: | |
| aws-access-key-id: ${{ secrets.GH_ACTIONS_AWS_ACCESS_KEY_ID }} | |
| aws-secret-access-key: ${{ secrets.GH_ACTIONS_AWS_SECRET_ACCESS_KEY }} | |
| aws-region: ${{ secrets.GH_ACTIONS_AWS_REGION }} | |
| - name: install kubectl | |
| run: | | |
| curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl" | |
| chmod +x ./kubectl | |
| sudo mv ./kubectl /usr/local/bin/kubectl | |
| - name: update kubeconfig with cluster | |
| run: | | |
| aws eks update-kubeconfig --name pangeo-forge-v3 --region ${{ secrets.GH_ACTIONS_AWS_REGION }} | |
| - name: execute recipe on k8s cluster | |
| id: executejob | |
| continue-on-error: true | |
| run: | | |
| # NOTE: we can't use `2>&1 | tee execute.log` b/c it hangs forever | |
| # so if the command fails (for example b/c it doesn't have the right requirements) | |
| # then we wont' be able to see the errors until we run it without redirecting output | |
| pangeo-forge-runner \ | |
| bake \ | |
| --repo=${{ github.event.inputs.repo }} \ | |
| --ref=${{ github.event.inputs.ref }} \ | |
| -f .github/workflows/config.py > execute.log | |
| # export all the valuable information from the logs | |
| JOB_NAME=$(cat execute.log | grep -oP 'flinkdeployment\.flink\.apache\.org/\K[^ ]+' | head -n1) | |
| echo "JOB_NAME=$JOB_NAME" >> $GITHUB_ENV | |
| JOB_ID=$(cat execute.log | grep -oP 'Started Flink job as \K[^ ]+') | |
| echo "JOB_ID=$JOB_ID" >> $GITHUB_ENV | |
| FLINK_DASH=$(cat execute.log | grep -oP "You can run '\K[^']+(?=')") | |
| echo "FLINK_DASH=$FLINK_DASH" >> $GITHUB_ENV | |
| env: | |
| REPO: ${{ github.event.inputs.repo }} | |
| REF: ${{ github.event.inputs.ref }} | |
| FEEDSTOCK_SUBDIR: ${{ github.event.inputs.feedstock_subdir }} | |
| PRUNE_OPTION: ${{ github.event.inputs.prune }} | |
| PARALLELISM_OPTION: ${{ github.event.inputs.parallelism }} | |
| S3_BUCKET: ${{ github.event.inputs.bucket }} | |
| S3_DEFAULT_AWS_ACCESS_KEY_ID: ${{ secrets.S3_DEFAULT_AWS_ACCESS_KEY_ID }} | |
| S3_DEFAULT_AWS_SECRET_ACCESS_KEY: ${{ secrets.S3_DEFAULT_AWS_SECRET_ACCESS_KEY }} | |
| - name: cleanup if "pangeo-forge-runner bake" failed | |
| if: steps.executejob.outcome == 'failure' | |
| run: | | |
| echo "The previous 'bake' command failed or timed out. Running cleanup logic..." | |
| # much easier to do in bash than in Python via subprocess | |
| echo "##################### OPERATOR ######################" | |
| kubectl get pod | grep operator | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | tail -n 1000 | |
| echo "##################### JOB MANAGER ######################" | |
| kubectl get pod | grep -v manager | grep $JOB_NAME | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | tail -n 1000 | |
| # delete the flinkdeployment so we don't have old failures hanging around | |
| kubectl get flinkdeployment --no-headers | grep $JOB_NAME | cut -d' ' -f1 | xargs -I{} kubectl delete flinkdeployment/{} | |
| # force GH action to show failed result | |
| exit 128 | |
| - name: report running job id for user | |
| id: report_ids | |
| run: | | |
| # TODO: we also need to report historyserver URL and flink dashboard URL | |
| # but this also requires us to think how we're going to have a thin | |
| # layer of authentication around these services so they aren't totally public | |
| echo '############ JOB NAME ################' | |
| echo $JOB_NAME | |
| echo "job_name=$JOB_NAME" >> $GITHUB_OUTPUT | |
| echo '############ JOB ID ################' | |
| echo $JOB_ID | |
| echo "job_id=$JOB_ID" >> $GITHUB_OUTPUT | |
| echo '############ FLINK DASHBOARD ################' | |
| echo $FLINK_DASH | |
| echo "flink_dash=$FLINK_DASH" >> $GITHUB_OUTPUT | |
| monitor-job: | |
| runs-on: ubuntu-latest | |
| name: monitor job ${{ needs.name-job.outputs.repo_name }}@${{ github.event.inputs.ref }} | |
| needs: [name-job, run-job] | |
| steps: | |
| - name: set up aws credentials for job runner user | |
| uses: aws-actions/configure-aws-credentials@v2 | |
| with: | |
| aws-access-key-id: ${{ secrets.GH_ACTIONS_AWS_ACCESS_KEY_ID }} | |
| aws-secret-access-key: ${{ secrets.GH_ACTIONS_AWS_SECRET_ACCESS_KEY }} | |
| aws-region: ${{ secrets.GH_ACTIONS_AWS_REGION }} | |
| - name: install kubectl | |
| run: | | |
| curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl" | |
| chmod +x ./kubectl | |
| sudo mv ./kubectl /usr/local/bin/kubectl | |
| - name: update kubeconfig with cluster | |
| run: | | |
| aws eks update-kubeconfig --name pangeo-forge-v3 --region ${{ secrets.GH_ACTIONS_AWS_REGION }} | |
| - name: monitor logs of job manager | |
| id: monitorjob | |
| timeout-minutes: 120 | |
| continue-on-error: true | |
| run: | | |
| # TODO: this needs to not check the logs but the historyserver status | |
| # but first we need think about authentication and a reverse proxy | |
| echo "find job status on the job manager logs..." | |
| while [[ -z "$(kubectl get pod --no-headers | grep -v manager | grep ${{ needs.run-job.outputs.job_name }} | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | grep 'ExecutionGraph.*Job BeamApp.*from state RUNNING.*' | head -n 1)" ]]; do | |
| echo "still waiting for a status on the job manager logs..." | |
| sleep 1 | |
| done | |
| input_status=$(kubectl get pod --no-headers | grep -v manager | grep ${{ needs.run-job.outputs.job_name }} | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | grep 'ExecutionGraph.*Job BeamApp.*from state RUNNING.*' | head -n 1) | |
| echo "##### INPUT STATUS #####" | |
| echo $input_status | |
| status=$(echo "$input_status" | grep -oP '\b\w+(?=\.$)') | |
| echo "##### STATUS #####" | |
| echo $status | |
| if [[ "$status" == "FAILING" || "$status" == "FAILED" ]]; then | |
| echo "job failed with '$status', will dump the logs now..." | |
| # force exit so we can move to next step | |
| exit 128 | |
| fi | |
| - name: cleanup if monitor job fails | |
| if: steps.monitorjob.outcome == 'failure' | |
| run: | | |
| # much easier to do in bash than in Python via subprocess | |
| echo "##################### OPERATOR ######################" | |
| kubectl get pod | grep operator | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | tail -n 1000 | |
| echo "##################### JOB MANAGER ######################" | |
| kubectl get pod | grep -v taskmanager | grep ${{ needs.run-job.outputs.job_name }} | cut -d' ' -f1 | xargs -I{} kubectl logs pod/{} | tail -n 1000 | |
| echo "##################### TASK MANAGER ######################" | |
| # depending on the `inputs.parallism` we can more than one taskmanager so grab the first one | |
| # TODO: loop through them all and dump the logs | |
| kubectl get pod | grep taskmanager | grep ${{ needs.run-job.outputs.job_name }} | cut -d' ' -f1 | head -n1 | xargs -I{} kubectl logs pod/{} -c flink-main-container > /tmp/taskmanager.log | |
| cat /tmp/taskmanager.log | |
| # delete the flinkdeployment so we don't have old failures hanging around | |
| kubectl get flinkdeployment --no-headers | grep ${{ needs.run-job.outputs.job_name }} | cut -d' ' -f1 | xargs -I{} kubectl delete flinkdeployment/{} | |
| # grok if this is a JVM OOM error | |
| jvm_error=$(cat /tmp/taskmanager.log | grep "java.lang.OutOfMemoryError") | |
| if [[ "$jvm_error" ]]; then | |
| RED='\033[0;31m' | |
| GREEN='\033[0;32m' | |
| NOCOLOR='\033[0m' # To reset the color | |
| echo "###################################################" | |
| echo -e "${RED}ERROR: ${NOCOLOR}${GREEN}There seems to be a JVM OOM error in the task manager logs...${NOCOLOR}" | |
| jvm_error_log_dump=$(cat /tmp/taskmanager.log | grep -a20 "java.lang.OutOfMemoryError") | |
| echo "$jvm_error_log_dump" | |
| fi | |
| # force GH action to show failed result | |
| exit 128 |