Knowledge Base

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Goal

This document describes how to connect to Azure Databricks from Denodo Virtual DataPort.

Content

Azure Databricks is an Apache Spark-based analytics platform optimized for Microsoft Azure cloud services.

Connecting to Azure Databricks from Denodo

From the Denodo Design Studio, create a new JDBC data source by selecting Virtual Database > New > Data source > JDBC. This will open the wizard to create a connection to JDBC data source.

Select the respective Database adapter. In this example, we are using the Databricks Adapter.
Since Denodo 8.0 update 20220815, the default Driver classpath is databricks-2. The driver is not included in this class path, so we recommend downloading and installing the latest driver.

Next, provide the Database URI.
Format : ‘jdbc:databricks://<host_name>:<port>/<database_name>;’, also, some parameters are added to the URI after the database name like httpPath, SSL etc. To know more about the parameters refer to Configure the Databricks ODBC and JDBC drivers.
If you are using a Databricks driver version < 2.6.25, you may need to change the Driver class to ‘com.simba.spark.jdbc.Driver’ and the Database URI to ‘jdbc:spark://<host_name>:<port>/<database_name>;’
You can select what type of Transaction Isolation you want from the options provided. In this example, we use the ‘Database Default’.
Authentication: There are three options provided. In our example, we are using the ‘Use login and password’ using a personal access token.
In the User, enter ‘token’.
In the Password, provide the access key token.
After providing the connection, you can test the connection by clicking on the Test Connection button.
Save the data source.
Once saved, click on the ‘Create base view’ tab to introspect source metadata available through the Data Source.
To incorporate some of the tables into the Denodo virtual schema, you have to check the box near the tables or views you want to import and then click ‘Create selected’.