Migrating data from Anaplan 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 Anaplan data to Databricks using the CData SSIS Components for Anaplan 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 Anaplan

Create the project and add components

1. Open Visual Studio and create a new Integration Services Project. 👁 Create the SSIS project
   
2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
3. Add a CData Anaplan Source control and a CData Databricks Destination control to the data flow task. 👁 Add the source and destination controls (Salesforce is shown)
   

Configure the Anaplan source

Follow the steps below to specify properties required to connect to Anaplan.

1. Double-click the CData Anaplan Source to open the source component editor and add a new connection. 👁 Open the source component editor (Salesforce is shown)
   
2. In the CData Anaplan Connection Manager, configure the connection properties, then test and save the connection.

   Authenticating to Anaplan

   The driver supports authenticating with Basic, Certificate, or OAuth. In every case, set Region to the region where your Anaplan account data is hosted (e.g., , which is the default).

   Using Basic Authentication

   Set AuthScheme to , then supply your Anaplan User and Password. If your workspace uses single sign-on (SSO), you must be assigned as an Exception User to use Basic authentication.

   Using Certificate Authentication

   Set AuthScheme to , then supply the Certificate, CertificateType, and PrivateKey properties (and the matching CertificatePassword / PrivateKeyPassword if either is encrypted). The certificate must be a CA-issued X.509 certificate registered with your Anaplan tenant administrator.

   Using OAuth Authentication

   Register a custom OAuth application in Anaplan, then set the following properties:

   • OAuthClientId: The client Id assigned when you registered your custom OAuth application.
   • OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.
   • CallbackURL: The redirect URI defined when you registered your application.
   • InitiateOAuth: Set to to have the driver manage the OAuth token exchange and refresh automatically.

   See the Getting Started chapter of the help documentation for a guide to creating a custom OAuth app and using OAuth.

   👁 Configure the source connection (Salesforce is shown)
   
3. After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData Anaplan Source Editor. 👁 Select the table to export (Salesforce is shown)
   

Configure the Databricks destination

With the Anaplan 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. 👁 Open the destination component editor
   
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.
   👁 Configure the destination connection
   
3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert. 👁 Choose the destination table
   
4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns. 👁 Map the columns (Salesforce is shown)
   

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.