Access Azure Data Lake Storage Data in Anypoint Using SQL

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Azure Data Lake Storage MuleSoft Connector



Create a simple Mule Application that uses HTTP and SQL with the CData Mule Connector for Azure Data Lake Storage to create a JSON endpoint for Azure Data Lake Storage data.

The CData Mule Connector for Azure Data Lake Storage connects Azure Data Lake Storage data to Mule applications enabling read functionality with familiar SQL queries. The Connector allows users to easily create Mule Applications to backup, transform, report, and analyze Azure Data Lake Storage data.

This article demonstrates how to use the CData Mule Connector for Azure Data Lake Storage inside of a Mule project to create a Web interface for Azure Data Lake Storage data. The application created allows you to request Azure Data Lake Storage data using an HTTP request and have the results returned as JSON. The exact same procedure outlined below can be used with any CData Mule Connector to create a Web interface for the 200+ available data sources.

  1. Create a new Mule Project in Anypoint Studio.
  2. Add an HTTP Connector to the Message Flow.
  3. Configure the address for the HTTP Connector.
  4. Add a CData Azure Data Lake Storage Connector to the same flow, after the HTTP Connector.
  5. Create a new Connection (or edit an existing one) and configure the properties to connect to Azure Data Lake Storage (see below). Once the connection is configured, click Test Connection to ensure the connectivity to Azure Data Lake Storage.

    Authenticating to a Gen 1 DataLakeStore Account

    Gen 1 uses OAuth 2.0 in Azure AD for authentication.

    For this, an Active Directory web application is required. You can create one as follows:

    1. Sign in to your Azure Account through the .
    2. Select "Azure Active Directory".
    3. Select "App registrations".
    4. Select "New application registration".
    5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
    6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
    7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

    To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen1.
    • Account: Set this to the name of the account.
    • OAuthClientId: Set this to the application Id of the app you created.
    • OAuthClientSecret: Set this to the key generated for the app you created.
    • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

    Authenticating to a Gen 2 DataLakeStore Account

    To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen2.
    • Account: Set this to the name of the account.
    • FileSystem: Set this to the file system which will be used for this account.
    • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
  6. Configure the CData Azure Data Lake Storage Connector.
    1. Set the Operation to 'Select with Streaming'.
    2. Set the Query type to Dynamic.
    3. Set the SQL query to SELECT * FROM #[message.inboundProperties.'http.query.params'.get('table')] to parse the URL parameter table and use it as the target of the SELECT query. You can customize the query further by referencing other potential URL parameters.
  7. Add a Transform Message Component to the flow.
    1. Map the Payload from the input to the Map in the output.
    2. Set the Output script to the following to convert the payload to JSON:
      %dw 1.0
      %output application/json
      ---
      payload
              
  8. To view your Azure Data Lake Storage data, navigate to the address you configured for the HTTP Connector (localhost:8081 by default) and pass a table name as the table URL parameter: http://localhost:8081?table=Resources
    The Resources data is available as JSON in your Web browser and any other tools capable of consuming JSON endpoints.

At this point, you have a simple Web interface for working with Azure Data Lake Storage data (as JSON data) in custom apps and a wide variety of BI, reporting, and ETL tools. Download a free, 30 day trial of the Mule Connector for Azure Data Lake Storage and see the CData difference in your Mule Applications today.