This template provides an example of how to perform analytics on the historic as well as real time streaming data stored in Azure Blob Storage. The data from the event hub is taken by the Azure Stream Analytics Job to perform transformation and the output is stored in Azure Blob Storage and is visualized in PowerBI. The analytics is applied on the historic data stored in Blob storage by Azure Data Analytics and the movement of extracted, transformed and published data and the orchestration is done by Data Factory. The published data is further visualized in PowerBI
This Azure Resource Manager template was created by a member of the community and not by Microsoft. Each Resource Manager template is licensed to you under a license agreement by its owner, not Microsoft. Microsoft is not responsible for Resource Manager templates provided and licensed by community members and does not screen for security, compatibility, or performance. Community Resource Manager templates are not supported under any Microsoft support program or service, and are made available AS IS without warranty of any kind.
Parameters
| Parameter Name | Description |
|---|---|
| location | The location in which the resources will be created.Check supported locations |
| eventHubNamespaceName | Name of the EventHub namespace |
| captureTime | the time window in seconds for the archival |
| captureSize | the size window in bytes for event hub capture |
| eventhubSku | The messaging tier for service Bus namespace |
| skuCapacity | MessagingUnits for premium namespace |
| isAutoInflateEnabled | Enable or disable AutoInflate |
| messageRetentionInDays | How long to retain the data in Event Hub |
| partitionCount | Number of partitions chosen |
| captureEncodingFormat | The encoding format Eventhub capture serializes the EventData when archiving to your storage |
| adlAnalyticsName | The name of the Data Lake Analytics account to create. |
| adlStoreName | The name of the Data Lake Store account to create. |
| vmSize | Size of vm Eg. Standard_D1_v2 |
| vm_username | Username for the Virtual Machine. |
| vm_password | Password for the Virtual Machine. |
| OptionalWizardInstall | Select whether the VM should be in production or not. |
| dataFactoryName | Name of the data factory. Must be globally unique. |
| appName | Name of the Azure datalake UI app registered. Must be globally unique. |
| servicePrincipalId | The ID of the service principal that has permissions to create HDInsight clusters in your subscription. |
| servicePrincipalKey | The access key of the service principal that has permissions to create HDInsight clusters in your subscription. |
| dataLakeAnalyticsLocation | The location in which the resources will be created.Check supported locations |
| _artifactsLocation | The base URI where artifacts required by this template are located here |
| _artifactsLocationSasToken | The sasToken required to access _artifactsLocation. When the template is deployed using the accompanying scripts, a sasToken will be automatically generated. Use the defaultValue if the staging location is not secured. |
Use the template
PowerShell
New-AzResourceGroup -Name <resource-group-name> -Location <resource-group-location> #use this command when you need to create a new resource group for your deploymentInstall and configure Azure PowerShell
New-AzResourceGroupDeployment -ResourceGroupName <resource-group-name> -TemplateUri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/yash-datalake/azuredeploy.json
Command line
az group create --name <resource-group-name> --location <resource-group-location> #use this command when you need to create a new resource group for your deploymentInstall and Configure the Azure Cross-Platform Command-Line Interface
az group deployment create --resource-group <my-resource-group> --template-uri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/yash-datalake/azuredeploy.json