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Copy file name to clipboardExpand all lines: samples/features/sql-big-data-cluster/deployment/kubeadm/ubuntu/README.md
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@@ -24,5 +24,8 @@ In this example, we will deploy Kubernetes over multiple Linux machines (physica
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1. Execute [setup-k8s-master.sh](setup-k8s-master.sh/) script on the machine designated as Kubernetes master (_not_ under sudo su as otherwise you'll setup K8S .kube/config permissions for root)
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1. After successful initialization of the Kubernetes master, follow the kubeadm join commands output by the setup script on each agent machine
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1. Execute [setup-volumes-agent.sh](setup-volumes-agent.sh/) script on each agent machine to create volumes for local storage
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1. Execute ***kubectl apply -f local-storage-provisioner.yaml*** against the Kubernetes cluster to create the local storage provisioner.
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1. Now, you can deploy the SQL Server 2019 big data cluster following instructions [here](https://docs.microsoft.com/en-us/sql/big-data-cluster/deployment-guidance?view=sqlallproducts-allversions)
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1. Execute ***kubectl apply -f local-storage-provisioner.yaml*** against the Kubernetes cluster to create the local storage provisioner. This will create a Storage Class named "local-storage".
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1. Now, you can deploy the SQL Server 2019 big data cluster following instructions [here](https://docs.microsoft.com/en-us/sql/big-data-cluster/deployment-guidance?view=sqlallproducts-allversions).
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Simply type in "local-storage" twice (once for data, once for logs) when facing the following prompt by azdata :
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`Kubernetes Storage Class - Config Path: spec.storage.data.className - Description: This indicates the name of the Kubernetes Storage Class to use. You must pre-provision the storage class and the persistent volumes or you can use a built in storage class if the platform you are deploying provides this capability. - Please provide a value:`
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