Import REST Data Using Azure Data Factory

Microsoft Azure Data Factory (ADF)) is a completely managed, serverless data integration service. When combined with CData Connect Cloud, ADF enables immediate cloud-to-cloud access to REST data within data flows. This article outlines the process of connecting to REST through Connect Cloud and accessing REST data within ADF.

CData Connect Cloud offers a cloud-to-cloud interface tailored for REST, granting you the ability to access live data from REST data within Azure Data Factory without the need for data replication to a natively supported database. Equipped with optimized data processing capabilities by default, CData Connect Cloud seamlessly channels all supported SQL operations, including filters and JOINs, directly to REST. This harnesses server-side processing to expedite the retrieval of the desired REST data.

Configure REST Connectivity for ADF

Connectivity to REST from Azure Data Factory is made possible through CData Connect Cloud. To work with REST data from Azure Data Factory, we start by creating and configuring a REST connection.

CData Connect Cloud uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect Cloud, click Connections and click Add Connection

2. Select "REST" from the Add Connection panel

3. Enter the necessary authentication properties to connect to REST.

   See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models REST APIs as bidirectional database tables and XML/JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

   After setting the URI and providing any authentication values, set Format to "XML" or "JSON" and set DataModel to more closely match the data representation to the structure of your data.

   The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your REST data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling REST Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   
4. Click Create & Test
5. Navigate to the Permissions tab in the Add REST Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

1. Click on your username at the top right of the Connect Cloud app and click User Profile.
2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
3. Give your PAT a name and click Create.

4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured, you are ready to connect to REST data from Azure Data Factory.

Access Live REST Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect Cloud Virtual SQL Server API, follow these steps.

1. Login to Azure Data Factory.

2. If you have not yet created a Data Factory, Click New -> Dataset.

3. In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.

4. Enter the connection settings.
   • Name - enter a name of your choice.
   • Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
   • Database name - enter the Connection Name of the CData Connect Cloud data source you want to connect to (for example, REST1).
   • User Name - enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, [email protected].
   • Password - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
   • Click Create.

5. In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.

6. After creating the linked service, the following screen should appear:

7. Click preview data to see the imported REST table.
You can now use this dataset when creating data flows in Azure Data Factory.

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