Prepare local environment with minikube

Install minikube

Install minikube according to the official documentation.
Install the minikube addons dashboard, ingress, metrics-server.

Install docker postgres outside minikube on host machine

Run the following command which will initialize and start the docker container:
docker run -itd -e POSTGRES_USER=admin -e POSTGRES_PASSWORD=admin -p 5432:5432 -v ~/postgresql/data:/var/lib/postgresql/data --name postgres postgres
Check that container is running:
docker ps -a
Stop container:
docker stop postgres
Start container:
docker start postgres
Test connection to postgres with example command (provide password on prompt):
psql -h localhost -p 5432 -d postgres -U admin
Create sql database:
create database "dataflow";
Connect to new database and create schema:
create schema "batch-framework"; Data for the SCDF server spring batch/task orchestration will be auto generated when the SCDF server is deployed.
Data for the spring batch/task actual record results will be auto generated on the first connection to the database during registration of the applications and tasks.

Update SCDF server files:

Modify the following:

• Update the batch-common/server/server-config.yaml file with the postgres credentials and the minikube domain host.minikube.internal if it not there.
• Update the batch-common/server/ingress.yaml file host and replace the ip in the scdf-server-<minikube-ip>.nip.io with the ip from minikube retrieved from:
  minikube ip

Deploying Spring Cloud Data Flow in k8s

Create the server objects:
kubectl create -f batch-common/kubernetes/server

Once it is started we should be able to see the auto generated spring batch/task tables in the database under the public schema.

Delete the server objects:
kubectl delete -f batch-common/kubernetes/server

Build the project

Maven build the project to generate the .jar files.

Build docker images in the minikube registry

When building the docker images from a terminal first run:
eval $(minikube docker-env)
Then run the bash script to build and deploy all images:
cd batch-common/script
./docker-build.sh

Prepare the SCDF jobs

Copy the file batch-client/src/test/resources/application.properties.sample to batch-client/src/test/resources/application.properties.
Update the batch-client/src/test/resources/application.properties with the correct credentials.
Register the SCDF 'applications' by running the test method data.RegistrationTestIT.registerApplications.
Create the SCDF 'tasks' by running the test method data.RegistrationTestIT.createTasks. Access the SCDF server UI. From the address in the batch-common/server/ingress.yaml we should see a list of links as a response from the server.
From those links we click on the link that has the prefix /dashboard to access the UI where we should now be able to see all applications and tasks registered.
If needed we can destroy(will also delete k8s historical pods) the tasks using data.RegistrationTestIT.destroyTasks. If needed we can unregister the applications using data.RegistrationTestIT.unregisterApplications

Start a job in SCDF

In the test file data.ApplicationTestIT there are test methods for each plugin. To run a plugin we have to update the ARGUMENT_EXECUTION_ID to the execution id for the source data, the identifier of the execution from a previous plugin(this does not apply for the oai plugin).
If you get the error 0/1 nodes are available: 1 Insufficient cpu. preemption: 0/1 nodes are available: 1 No preemption victims found for incoming pod., it means that there are not enough resources available on your machine. To fix that you can make sure there is availability of resources by removing/stopping other pods, or try reducing the resources of the job/pod when sending the launch command.

Run Jobs/Tasks using Spring Cloud Data Flow Shell(old way of accessing the server, possibly outdated)

Download the script .jar from:
https://repo1.maven.org/maven2/org/springframework/cloud/spring-cloud-dataflow-shell/2.11.2/spring-cloud-dataflow-shell-2.11.2.jar

Get into the shell(Update the uri to the data from server location):

java -jar spring-cloud-dataflow-shell-2.11.2.jar --dataflow.uri=http://scdf-server-192.168.49.2.nip.io  

Some example commands:

app list    
app register --name batch-oai-harvest --type task --bootVersion 3 --uri docker:europeana/batch-oai-harvest:latest --metadata-uri file:///data/spring-batch-metis-poc/batch-application.properties  
app info --name batch-oai-harvest --type task
app unregister --name batch-oai-harvest --type task
task create --name batch-oai-harvest --definition batch-oai-harvest
task destroy --name batch-oai-harvest --cleanup true
task execution stop --ids 8
 
task launch --name batch-oai-harvest --properties "\
    app.batch-oai-harvest.spring.datasource.url=jdbc:postgresql://192.168.49.2:30432/dataflow?useSSL=false,\
    app.batch-oai-harvest.spring.datasource.driver-class-name=org.postgresql.Driver,\
    app.batch-oai-harvest.spring.datasource.username=username,\
    app.batch-oai-harvest.spring.datasource.password=password,\
    app.batch-oai-harvest.spring.datasource.hikari.maximumPoolSize=500,\
    app.batch-oai-harvest.spring.jpa.generate-ddl=true,\
    app.batch-oai-harvest.oaiharvest.chunk.size=10,\
    app.batch-oai-harvest.oaiharvest.parallelization.size=10,\
    app.batch-oai-harvest.spring.batch.jdbc.initialize-schema=always" --arguments "datasetId=1 executionId=1 oaiEndpoint=https://metis-repository-rest.test.eanadev.org/repository/oai oaiSet=spring_poc_dataset_with_validation_error oaiMetadataPrefix=edm"
    
task execution list --name batch-oai-harvest
task execution status --id 2 --schemaTarget boot3
task execution cleanup --id 2 --schemaTarget boot3