Build HCL Domino-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for HCL Domino enables users to access live HCL Domino data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping HCL Domino data to any data source natively supported in Google Data Fusion, this article explains how to pipe data from HCL Domino to Google BigQuery,

Upload the CData JDBC Driver for HCL Domino to Google Data Fusion

Upload the CData JDBC Driver for HCL Domino to your Google Data Fusion instance to work with live HCL Domino data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatadomino-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver 👁 Image
   
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.domino) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.domino.DominoDriver)
   👁 Configuring the driver (Salesforce is shown.)
   
5. Click "Finish"

Connect to HCL Domino Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live HCL Domino data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver 👁 Adding a database source
   
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-domino)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for HCL Domino. For example:
     
     jdbc:domino:RTK=5246...;Server=https://domino.corp.com;AuthScheme=OAuthPassword;User=my_domino_user;Password=my_domino_password;

     Connecting to Domino

     To connect to Domino data, set the following properties:

     • URL: The host name or IP of the server hosting the Domino database. Include the port of the server hosting the Domino database. For example: http://sampleserver:1234/
     • DatabaseScope: The name of a scope in the Domino Web UI. The driver exposes forms and views for the schema governed by the specified scope. In the Domino Admin UI, select the Scopes menu in the sidebar. Set this property to the name of an existing scope.

     Authenticating with Domino

     Domino supports authenticating via login credentials or an Entra ID (formerly Azure AD) OAuth application:

     Login Credentials

     To authenticate with login credentials, set the following properties:

     • AuthScheme: Set this to "OAuthPassword"
     • User: The username of the authenticating Domino user
     • Password: The password associated with the authenticating Domino user

     The driver uses the login credentials to automatically perform an OAuth token exchange.

     EntraID (formerly AzureAD)

     This authentication method uses Entra ID (formerly Azure AD) as an IdP to obtain a JWT token. You need to create a custom OAuth application in Entra ID (formerly Azure AD) and configure it as an IdP. To do so, follow the instructions in the Help documentation. Then set the following properties:

     • AuthScheme: Set this to "EntraID (formerly AzureAD)"
     • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
     • OAuthClientId: The Client ID obtained when setting up the custom OAuth application.
     • OAuthClientSecret: The Client secret obtained when setting up the custom OAuth application.
     • CallbackURL: The redirect URI defined when you registered your app. For example: https://localhost:33333
     • AzureTenant: The Microsoft Online tenant being used to access data. Supply either a value in the form companyname.microsoft.com or the tenant ID.

       The tenant ID is the same as the directory ID shown in the Azure Portal's Entra ID (formerly Azure AD) > Properties page.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the HCL Domino JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.domino.jar
      

     Fill in the connection properties and copy the connection string to the clipboard.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
   • Set Import Query to a SQL query that will extract the data you want from HCL Domino, i.e.:
     SELECT * FROM ByName
   👁 Configuring the database source
   
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like domino-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert HCL Domino data into
   👁 Configuring the BigQuery sink
   

With the Source and Sink configured, you are ready to pipe HCL Domino data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from HCL Domino and import it into Google BigQuery. 👁 Image

While this is a simple pipeline, you can create more complex HCL Domino pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for HCL Domino and start working with your live HCL Domino data in Google Data Fusion today.