cd docker-hadoop
docker build -t hadoop-base:3.2.2 -f .
cd ../docker-hive-metastore
docker build -t localhost:5000/hive-metastore:3.2.2 .
cd ../docker-hive-server2
docker build -t localhost:5000/hive-server2:3.2.2 .
cd ..
docker push localhost:5000/hive-metastore:3.2.2
docker push localhost:5000/hive-server2:3.2.2
First, install a MySQL Database to persist the data, next deploy HiveMetastore to actually use and prepare this data, and finally Hive Server2 to interface with other components. The architecture of Hive deployment is illustrated below.
helm repo add bitnami https://charts.bitnami.com/bitnami
helm install mysql bitnami/mysql
Export Secret
kubectl create secret generic mysql-secret --from-literal=ROOT_PASSWORD=$(kubectl get secret --namespace default mysql -o jsonpath="{.data.mysql-root-password}" | base64 --decode)
helm install hive-metastore ./2.hive-metastore
helm install hive-server2 ./3.hive-server2
helm install trino ./4.trino
https://zero-to-jupyterhub.readthedocs.io/en/0.11.1/jupyterhub/installation.html
helm repo add jupyterhub https://jupyterhub.github.io/helm-chart/
helm repo update
RELEASE=jhub
NAMESPACE=default
helm upgrade --cleanup-on-fail \
--install $RELEASE jupyterhub/jupyterhub \
--namespace $NAMESPACE \
--create-namespace \
--version=0.11.1 \
--values 5.jupyterhub/config.yaml
To reach Trino UI and JupyterHub, first we need to modify /etc/hosts
echo "$(minikube ip) trino.myplatform.ai myplatform.ai" | sudo tee -a /etc/hosts
Trino UI will be available at trino.myplatform.ai
and JupyterHub will be available at myplatform.ai/jupyterhub
.
The inconsistency in the endpoints is forced by the way how ingress-controller works in minikube.