Quickstart: Create Apache HBase cluster in Azure HDInsight using Bicep
In this quickstart, you use Bicep to create an Apache HBase cluster in Azure HDInsight. HBase is an open-source, NoSQL database that is built on Apache Hadoop and modeled after Google BigTable.
Bicep is a domain-specific language (DSL) that uses declarative syntax to deploy Azure resources. It provides concise syntax, reliable type safety, and support for code reuse. Bicep offers the best authoring experience for your infrastructure-as-code solutions in Azure.
Prerequisites
If you don't have an Azure subscription, create a free account before you begin.
Review the Bicep file
The Bicep file used in this quickstart is from Azure Quickstart Templates.
@description('The name of the HDInsight cluster to create.')
param clusterName string
@description('These credentials can be used to submit jobs to the cluster and to log into cluster dashboards.')
param clusterLoginUserName string
@description('The password must be at least 10 characters in length and must contain at least one digit, one upper case letter, one lower case letter, and one non-alphanumeric character except (single-quote, double-quote, backslash, right-bracket, full-stop). Also, the password must not contain 3 consecutive characters from the cluster username or SSH username.')
@minLength(10)
@secure()
param clusterLoginPassword string
@description('These credentials can be used to remotely access the cluster.')
param sshUserName string
@description('SSH password must be 6-72 characters long and must contain at least one digit, one upper case letter, and one lower case letter. It must not contain any 3 consecutive characters from the cluster login name')
@minLength(6)
@maxLength(72)
@secure()
param sshPassword string
@description('Location for all resources.')
param location string = resourceGroup().location
@description('This is the headnode Azure Virtual Machine size, and will affect the cost. If you don\'t know, just leave the default value.')
@allowed([
'Standard_A4_v2'
'Standard_A8_v2'
'Standard_E2_v3'
'Standard_E4_v3'
'Standard_E8_v3'
'Standard_E16_v3'
'Standard_E20_v3'
'Standard_E32_v3'
'Standard_E48_v3'
])
param HeadNodeVirtualMachineSize string = 'Standard_E4_v3'
@description('This is the worerdnode Azure Virtual Machine size, and will affect the cost. If you don\'t know, just leave the default value.')
@allowed([
'Standard_A4_v2'
'Standard_A8_v2'
'Standard_E2_v3'
'Standard_E4_v3'
'Standard_E8_v3'
'Standard_E16_v3'
'Standard_E20_v3'
'Standard_E32_v3'
'Standard_E48_v3'
])
param WorkerNodeVirtualMachineSize string = 'Standard_E4_v3'
@description('This is the Zookeepernode Azure Virtual Machine size, and will affect the cost. If you don\'t know, just leave the default value.')
@allowed([
'Standard_A4_v2'
'Standard_A8_v2'
'Standard_E2_v3'
'Standard_E4_v3'
'Standard_E8_v3'
'Standard_E16_v3'
'Standard_E20_v3'
'Standard_E32_v3'
'Standard_E48_v3'
])
param ZookeeperNodeVirtualMachineSize string = 'Standard_E4_v3'
var defaultStorageAccount = {
name: uniqueString(resourceGroup().id)
type: 'Standard_LRS'
}
resource storageAccount 'Microsoft.Storage/storageAccounts@2021-08-01' = {
name: defaultStorageAccount.name
location: location
sku: {
name: defaultStorageAccount.type
}
kind: 'Storage'
properties: {}
}
resource cluster 'Microsoft.HDInsight/clusters@2021-06-01' = {
name: clusterName
location: location
properties: {
clusterVersion: '4.0'
osType: 'Linux'
clusterDefinition: {
kind: 'hbase'
configurations: {
gateway: {
'restAuthCredential.isEnabled': true
'restAuthCredential.username': clusterLoginUserName
'restAuthCredential.password': clusterLoginPassword
}
}
}
storageProfile: {
storageaccounts: [
{
name: replace(replace(reference(storageAccount.id, '2021-08-01').primaryEndpoints.blob, 'https://', ''), '/', '')
isDefault: true
container: clusterName
key: listKeys(storageAccount.id, '2021-08-01').keys[0].value
}
]
}
computeProfile: {
roles: [
{
name: 'headnode'
targetInstanceCount: 2
hardwareProfile: {
vmSize: HeadNodeVirtualMachineSize
}
osProfile: {
linuxOperatingSystemProfile: {
username: sshUserName
password: sshPassword
}
}
}
{
name: 'workernode'
targetInstanceCount: 2
hardwareProfile: {
vmSize: WorkerNodeVirtualMachineSize
}
osProfile: {
linuxOperatingSystemProfile: {
username: sshUserName
password: sshPassword
}
}
}
{
name: 'zookeepernode'
targetInstanceCount: 3
hardwareProfile: {
vmSize: ZookeeperNodeVirtualMachineSize
}
osProfile: {
linuxOperatingSystemProfile: {
username: sshUserName
password: sshPassword
}
}
}
]
}
}
}
output cluster object = cluster.properties
Two Azure resources are defined in the Bicep file:
- Microsoft.Storage/storageAccounts: create an Azure Storage Account.
- Microsoft.HDInsight/cluster: create an HDInsight cluster.
Deploy the Bicep file
Save the Bicep file as main.bicep to your local computer.
Deploy the Bicep file using either Azure CLI or Azure PowerShell.
az group create --name exampleRG --location eastus az deployment group create --resource-group exampleRG --template-file main.bicep --parameters clusterName=<cluster-name> clusterLoginUserName=<cluster-username> sshUserName=<ssh-username>You need to provide values for the parameters:
- Replace <cluster-name> with the name of the HDInsight cluster to create.
- Replace <cluster-username> with the credentials used to submit jobs to the cluster and to log in to cluster dashboards.
- Replace <ssh-username> with the credentials used to remotely access the cluster.
You'll be prompted to enter the following:
- clusterLoginPassword, which must be at least 10 characters long and must contain at least one digit, one uppercase letter, one lowercase letter, and one non-alphanumeric character except single-quote, double-quote, backslash, right-bracket, full-stop. It also must not contain three consecutive characters from the cluster username or SSH username.
- sshPassword, which must be 6-72 characters long and must contain at least one digit, one uppercase letter, and one lowercase letter. It must not contain any three consecutive characters from the cluster login name.
Note
When the deployment finishes, you should see a message indicating the deployment succeeded.
Review deployed resources
Use the Azure portal, Azure CLI, or Azure PowerShell to list the deployed resources in the resource group.
az resource list --resource-group exampleRG
Clean up resources
When no longer needed, use the Azure portal, Azure CLI, or Azure PowerShell to delete the resource group and its resources.
az group delete --name exampleRG
Next steps
In this quickstart, you learned how to create an Apache HBase cluster in HDInsight using Bicep. In the next article, you learn how to query HBase in HDInsight with HBase Shell.