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Exercise 1: Run your first QKO example

Let's run an example to calculate the value of Pi.

Install the Spark Operator​

helm repo add spark-operator https://kubeflow.github.io/spark-operator
helm repo update
helm install spark-operator spark-operator/spark-operator \
  --namespace spark-operator \
  --create-namespace \
  --set "spark.jobNamespaces={default}"

kubectl get pods -n spark-operator     # spark-operator-controller should be Running

Install the Quanton Operator​

helm upgrade --install quanton-operator oci://registry-1.docker.io/onehouseai/quanton-operator \
    --namespace quanton-operator \
    --create-namespace \
    --set "quantonOperator.jobNamespaces={default}" \
    --set onehouseConfig.enableAIAgent=true \
    -f /path/to/onehouse-values.yaml

kubectl get pods -n quanton-operator   # quanton-controller should reach 3/3 Running

The enableAIAgent=true flag tells the operator to auto-inject the agent plugin into every job — we'll use this in the next exercise. Drop it if you don't want the agent.

Submit the Pi example​

git clone https://github.com/onehouseinc/quanton-operator
cd quanton-operator

kubectl apply -f examples/quanton-application.yaml
kubectl get pods -A | grep driver       # driver pod will reach Running in ~1 min

When the driver pod is Running, tail the output:

kubectl logs -f quanton-spark-pi-java-example-driver | grep -i "pi is"
# Pi is roughly 3.1416568