avaradharaju / igz_sparkk8s

MLOps NYC 2019 training session: Runnign Spark on Kubernetes

Running Spark on Kubernetes

MLOps NYC 2019 training session: Runnign Spark on Kubernetes. This setup will be discussed at the MLOps NY conference on September 24th 2019. http://mlopsnnyc.com

Pre Requisities

• Docker desktop with Kubernetes enabled
  To run the demo configure Docker with 3 cpus and 4GB of ram

Download all the artifacts from this repository

Make note of the location where you downloaded

Install components

From a Windows command line or terminal in Mac

Confirm Kubernetes is running

kubetctl get pods

Setup Kubernetes dashboard

kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v1.10.1/src/deploy/recommended/kubernetes-dashboard.yaml

Start proxy (on second window)

You can stop it after running helm

kubectl proxy

Install helm

For this setup download the Windows or Mac binary.
Extract and expand somewhere local.
Documentation: https://helm.sh/docs/
ALL binaries: https://github.com/helm/helm/releases
Windows Binary: https://get.helm.sh/helm-v3.0.0-beta.3-windows-amd64.zip

Create namespace (File provided)

Go to the location where you downloaded the files from this repository kubectl apply -f spark-operator.json

Deploy Spark Operator Kubernetes packages

Location of heml\helm repo add incubator http://storage.googleapis.com/kubernetes-charts-incubator
Location of heml\helm install incubator/sparkoperator --generate-name --namespace spark-operator --set sparkJobNamespace=default

Optional

kubectl create clusterrolebinding add-on-cluster-admin --clusterrole=cluster-admin --serviceaccount=kube-system:default

Configure the Spark application

Get the Spark service account. Make not of the sparkoprator-xxxxxx-spark name

kubectl get serviceaccounts

Edit spark-pi.yaml

Change the serviceAccount line value to the value you got in the previous command

Run the test application

You must be in the directory where you extracted this repository

kubectl apply -f spark-pi.yaml

Monitor application

Driver and workers show when running. You should see spark-pi-driver and one worker

kubectl get pods

List all Spark applications kubectl get sparkapplications

Detailed list in JSON format Watch state under status

kubectl get sparkapplications -o json

Watch the job execution

kubectl logs spark-pi-driver -f

Delete the application

kubectl delete -f spark-pi.yaml