How to connect and process HCL Domino data from Azure Databricks

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live HCL Domino data. This article explains how to host the CData JDBC Driver in Azure, as well as connect to and process live HCL Domino data in Databricks.

With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live HCL Domino data. When you issue complex SQL queries to HCL Domino, the driver pushes supported SQL operations, like filters and aggregations, directly to HCL Domino and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze HCL Domino data using native data types.

Install the CData JDBC Driver in Azure

To work with live HCL Domino data in Databricks, install the driver through Azure Data Lake Storage (ADLS). (Please note that the method of connecting through DBFS, which previous versions of this article described, has been deprecated, but has not published an end-of-life.)

1. Upload the JDBC JAR file to a blob container of your choice (i.e. "jdbcjars" container of the "databrickslibraries" storage account).
2. Fetch the Account Key from the storage account by expanding "Security + networking" and clicking on "Access Keys". Show and copy whichever of the two keys you wish to use. 👁 Get Access Key
   
3. Get the JDBC JAR file's URL by navigating to Containers, opening the specific container storing the JAR, and selecting the entry for the JDBC JAR file. This should open the file's details, where there should be a convenient button to copy the URL button to clipboard. This value will look similar to the below, though the "blob" component may vary depending on storage account type:

   https://databrickslibraries.blob.core.windows.net/jdbcjars/cdata.jdbc.salesforce.jar

   👁 Get JAR URL
   
4. In the Configuration tab of your Databricks cluster, click on the Edit button and expand "Advanced options". From there, add the following Spark option (derived from the JAR URL's domain name) with your copied Account key as its value and click Confirm: spark.hadoop.fs.azure.account.key.databrickslibraries.blob.core.windows.net 👁 Apply Account Key
   
5. In the Libraries tab of your Databricks cluster, click on "Install new", and select the ADLS option. Specify the ABFSS URL for the driver JAR (also derived from the JAR URL's domain name), and click Install. The ABFSS URL should resemble the below:

   abfss://[email protected]/cdata.jdbc.salesforce.jar

   👁 Install ADLS Library
   

Connect to HCL Domino from Databricks

With the JAR file installed, we are ready to work with live HCL Domino data in Databricks. Start by creating a new notebook in your workspace. Name the workbook, make sure Python is selected as the language (which should be by default), click on Connect and under General Compute select the cluster where you installed the JDBC driver (should be selected by default).

👁 Attaching to an existing compute resource

Configure the Connection to HCL Domino

Connect to HCL Domino by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.domino.DominoDriver"
url = "jdbc:domino:RTK=5246...;Server=https://domino.corp.com;AuthScheme=OAuthPassword;User=my_domino_user;Password=my_domino_password;"

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.

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.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load HCL Domino Data

Once the connection is configured, you can load HCL Domino data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "ByName") \
	.load ()

Display HCL Domino Data

Check the loaded HCL Domino data by calling the display function.

display (remote_table.select ("Name"))

👁 Displaying HCL Domino Data

Analyze HCL Domino Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the HCL Domino data for analysis.

result = spark.sql("SELECT Name, Address FROM SAMPLE_VIEW WHERE City = 'Miami'")

The data from HCL Domino is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

👁 Displaying HCL Domino Data

Download a free, 30-day trial of the CData JDBC Driver for HCL Domino and start working with your live HCL Domino data in Azure Databricks. Reach out to our Support Team if you have any questions.