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Quickstart: Create Apache Hadoop cluster in Azure HDInsight using Bicep

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In this quickstart, you use Bicep to create an Apache Hadoop cluster in Azure HDInsight. Hadoop was the original open-source framework for distributed processing and analysis of big data sets on clusters. The Hadoop ecosystem includes related software and utilities, including Apache Hive, Apache HBase, Spark, Kafka, and many others.

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.

Currently HDInsight comes with seven different cluster types. Each cluster type supports a different set of components. All cluster types support Hive. For a list of supported components in HDInsight, see What's new in the Hadoop cluster versions provided by HDInsight?

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('The type of the HDInsight cluster to create.')
@allowed([
  'hadoop'
  'intractivehive'
  'hbase'
  'storm'
  'spark'
])
param clusterType 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. The username cannot be admin.')
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 workdernode 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'

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: 'StorageV2'
  properties: {}
}

resource cluster 'Microsoft.HDInsight/clusters@2021-06-01' = {
  name: clusterName
  location: location
  properties: {
    clusterVersion: '4.0'
    osType: 'Linux'
    clusterDefinition: {
      kind: clusterType
      configurations: {
        gateway: {
          'restAuthCredential.isEnabled': true
          'restAuthCredential.username': clusterLoginUserName
          'restAuthCredential.password': clusterLoginPassword
        }
      }
    }
    storageProfile: {
      storageaccounts: [
        {
          name: replace(replace(concat(storageAccount.properties.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
            }
          }
        }
      ]
    }
  }
}

output storage object = storageAccount.properties
output cluster object = cluster.properties

Two Azure resources are defined in the Bicep file:

Deploy the Bicep file

  1. Save the Bicep file as main.bicep to your local computer.

  2. 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> clusterType=<cluster-type> 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-type> with the type of the HDInsight cluster to create. Allowed strings include: hadoop, interactivehive, hbase, and spark.
    • 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. The username cannot be admin.

    You'll also be prompted to enter the following parameter:

    • clusterLoginPassword, which must be at least 10 characters long and contain 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 Hadoop cluster in HDInsight using Bicep. In the next article, you learn how to perform an extract, transform, and load (ETL) operation using Hadoop on HDInsight.

Extract, transform, and load data using Interactive Query on HDInsight