Migrating data from HCL Domino to Databricks using CData SSIS Components.

Databricks is a unified data analytics platform that allows organizations to easily process, analyze, and visualize large amounts of data. It combines data engineering, data science, and machine learning capabilities in a single platform, making it easier for teams to collaborate and derive insights from their data.

The CData SSIS Components enhance SQL Server Integration Services by enabling users to easily import and export data from various sources and destinations.

In this article, we explore the data type mapping considerations when exporting to Databricks and walk through how to migrate HCL Domino data to Databricks using the CData SSIS Components for HCL Domino and Databricks.

Data Type Mapping

Special Considerations

• String/VARCHAR: String columns from Databricks can map to different data types depending on the length of the column. If the column length exceeds 4000, then the column is mapped to nvarchar (max). Otherwise, the column is mapped to nvarchar (length).
• DECIMAL Databricks supports DECIMAL types up to 38 digits of precision, but any source column beyond that can cause load errors.

Prerequisites

• Visual Studio 2022
• SQL Server Integration Services Projects extension for Visual Studio 2022
• CData SSIS Components for Databricks
• CData SSIS Components for HCL Domino

Create the project and add components

1. Open Visual Studio and create a new Integration Services Project.
2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
3. Add a CData HCL Domino Source control and a CData Databricks Destination control to the data flow task.

Configure the HCL Domino source

Follow the steps below to specify properties required to connect to HCL Domino.

1. Double-click the CData HCL Domino Source to open the source component editor and add a new connection.
2. In the CData HCL Domino Connection Manager, configure the connection properties, then test and save the connection.

   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.

   
3. After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData HCL Domino Source Editor.

Configure the Databricks destination

With the HCL Domino Source configured, we can configure the Databricks connection and map the columns.

1. Double-click the CData Databricks Destination to open the destination component editor and add a new connection.
2. In the CData Databricks Connection Manager, configure the connection properties, then test and save the connection. To connect to a Databricks cluster, set the properties as described below.

   Note: The needed values can be found in your Databricks instance by navigating to Clusters, selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

   • Server: Set to the Server Hostname of your Databricks cluster.
   • HTTPPath: Set to the HTTP Path of your Databricks cluster.
   • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).

   Other helpful connection properties

   • QueryPassthrough: When this is set to True, queries are passed through directly to Databricks.
   • ConvertDateTimetoGMT: When this is set to True, the components will convert date-time values to GMT, instead of the local time of the machine.
   • UseUploadApi: Setting this property to true will improve performance if there is a large amount of data in a Bulk INSERT operation.
   • UseCloudFetch: This option specifies whether to use CloudFetch to improve query efficiency when the table contains over one million entries.
   
3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the project

You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.