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

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 EnterpriseDB Source control and a CData Databricks Destination control to the data flow task.

Configure the EnterpriseDB source

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

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

   The following connection properties are required in order to connect to data.

   • Server: The host name or IP of the server hosting the EnterpriseDB database.
   • Port: The port of the server hosting the EnterpriseDB database.

   You can also optionally set the following:

   • Database: The default database to connect to when connecting to the EnterpriseDB Server. If this is not set, the user's default database will be used.

   Connect Using Standard Authentication

   To authenticate using standard authentication, set the following:

   • User: The user which will be used to authenticate with the EnterpriseDB server.
   • Password: The password which will be used to authenticate with the EnterpriseDB server.

   Connect Using SSL Authentication

   You can leverage SSL authentication to connect to EnterpriseDB data via a secure session. Configure the following connection properties to connect to data:

   • SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
   • SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSLClientCertType: The certificate type of the client store.
   • SSLServerCert: The certificate to be accepted from the server.
   
3. After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData EnterpriseDB Source Editor.

Configure the Databricks destination

With the EnterpriseDB 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.