danielhstahl / argo-sparkoperator

example of using spark operator in argo

spark on k8s

This runs XGBoost on spark, and saves the trained model

prereqs

Minikube, helm

create storage for spark

mkdir /tmp/spark

cp iris.csv /tmp/spark

start minikube and set mount

minikube start --memory 8192 --cpus 5 --mount-string /tmp/spark:/data --mount --kubernetes-version v1.15.3 # older k8s version for working with spark 2.4.5

Create registry to push images to

minikube addons enable registry

docker run --rm -it --network=host alpine ash -c "apk add socat && socat TCP-LISTEN:5000,reuseaddr,fork TCP:$(minikube ip):5000"

build image include spark jar

docker build . -t xgboost

docker tag xgboost localhost:5000/xgboost

docker push localhost:5000/xgboost

install spark operator for k8s

kubectl create namespace spark-operator

helm install spark-operator incubator/sparkoperator --namespace spark-operator --set sparkJobNamespace=default,enableWebhook=true,operatorVersion=v1beta2-1.1.2-2.4.5

kubectl create serviceaccount spark

kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount=default:spark

kubectl apply -f operator.yml

start k8s dashboard

minikube dashboard # use this to monitor pods

argo

This schedules/orchestrates the xgboost job

install helm chart

kubectl create clusterrolebinding spark-admin --clusterrole=cluster-admin --serviceaccount=default:default --namespace=default

helm repo add argo https://argoproj.github.io/argo-helm

helm update

helm install argo-wf argo/argo -f argo.yml

allow dashboard

kubectl port-forward deployment/argo-wf-server 2746:2746

submit job

argo submit --watch argo_wf.yml