This document describes how to connect to Azure Databricks from Denodo Virtual DataPort.
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.
- Provide the Name for the JDBC Data source.
- Select the respective Database adapter. In this example, we are using the Spark SQL 2.x Databricks Adapter.
- Next, provide the Database URI.
Format : ‘jdbc:spark://<host_name>:<port>/<database_name>;’, also, some parameters can be added to URI after the database name like httpPath, Spark Server Type, SSL etc. To know more about the parameters refer to Configure JDBC/ODBC connection.
- 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’.
- In the Login provide the username you use for the Azure Databricks instance.
- In the Password, provide the access key token.
- After providing the connection, you can test the connection by clicking on the Test Connection button.
- You should be getting the ‘Spark SQL <Version>’
- 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’.
- Click ‘Save’ to save the base view
- You can also use the ‘Create from query’ option if you wish to custom your base view.
Virtual DataPort Administration Guide - JDBC Sources
Virtual DataPort Administration Guide - Supported JDBC Data Sources
Azure Databricks Documentation - Configure JDBC/ODBC connection