Integrate with Azure Data Lake Storage Data in SnapLogic

SnapLogic's iPaaS platform helps organizations automate application, data and cloud integrations. When paired with CData Connect Cloud, SnapLogic gets access to live Azure Data Lake Storage data. This article demonstrates how to connect to Azure Data Lake Storage using Connect Cloud and integrate with Azure Data Lake Storage data in SnapLogic.

CData Connect Cloud provides a pure SQL Server interface for Azure Data Lake Storage, allowing you to query data from Azure Data Lake Storage without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to Azure Data Lake Storage, leveraging server-side processing to return the requested Azure Data Lake Storage data quickly.

Configure Azure Data Lake Storage Connectivity for SnapLogic

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

1. Log into Connect Cloud, click Connections and click Add Connection
2. Select "Azure Data Lake Storage" from the Add Connection panel
3. Enter the necessary authentication properties to connect 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.
4. Click Create & Test
5. Navigate to the Permissions tab in the Add Azure Data Lake Storage 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.

Connect to Azure Data Lake Storage from SnapLogic using Connect Cloud

To establish a connection from SnapLogic to CData Connect Cloud, you will need to download the JDBC Driver.

1. Open the Client Tools page of CData Connect Cloud.
2. In the Dev Tools section, click JDBC.
3. Download and run the setup file.
4. When the installation is complete, locate the JDBC Connect JAR file in the JDBC driver's installation directory, for example, C:\Program Files\CData\JDBC Driver for CData Connect\lib.
5. Copy the JDBC Connect JAR file (cdata.jdbc.connect.jar).

After copying the JDBC CData Connect JAR file, you will need to paste it into the SnapLogic installation location and configure the connection to Connect Cloud.

1. Log into SnapLogic.
2. Click the Managers tab.
3. Select a folder from the Project Spaces to add the JDBC JAR file to.
4. Click the Files tab.
5. Click the button in the top right to upload the CData Connect Cloud JDBC JAR file. It appears as a file once uploaded.
6. Click the Designer tab.
7. Click JDBC to expand the options for "snaps."
8. Click and drag a Generic JDBC - Select "snap" onto the designer.
9. Click Add Account > Continue.
10. Enter the JDBC connection properties.
    • JDBC driver: add the CData Connect Cloud JAR file
    • JDBC driver Class: enter cdata.jdbc.connect.ConnectDriver
    • JDBC Url: enter a JDBC connection string for the JDBC driver. For example: jdbc:connect:AuthScheme=Basic;User={username};Password={PAT};
    • Username: 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: enter the PAT you generated on the Settings page.
11. Click Validate. If the connection succeeds, the "snap" is ready to use.
12. Click Apply.

You can now create reports with the connected data.

Get CData Connect Cloud

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