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Birst is a cloud business intelligence (BI) tool and analytics platform that helps organizations quickly understand and optimize complex processes. When paired with the CData JDBC Driver for Databricks, you can connect to live Databricks data through the Birst Cloud Agent and build real-time visualizations. In this article, we walk you through, step-by-step, how to connect to Databricks using the Cloud Agent and create dynamic reports in Birst.
With powerful data processing capabilities, the CData JDBC driver offers unmatched performance for live Databricks data operations in Birst. When you issue complex SQL queries from Birst to Databricks, the driver pushes supported SQL operations, like filters and aggregations, directly to Databricks and utilizes the embedded SQL Engine to process unsupported operations client-side (often SQL functions and JOIN operations). With built-in dynamic metadata querying, the JDBC driver enables you to visualize and analyze Databricks data using native Birst data types.
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Before creating the Birst project, you will need to install the Birst Cloud Agent (in order to work with the installed JDBC Driver). Also, copy the JAR file for the JDBC Driver (and the LIC file, if it exists) to the /drivers/ directory in the installation location for the Cloud Agent.
With the driver and Cloud Agent installed, you are ready to begin.
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, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
For assistance in constructing the JDBC URL, use the connection string designer built into the Databricks JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.databricks.jar
Fill in the connection properties and copy the connection string to the clipboard.
π Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)When you configure the JDBC URL, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
Below is a typical JDBC connection string for Databricks:
jdbc:databricks:Server=127.0.0.1;Port=443;TransportMode=HTTP;HTTPPath=MyHTTPPath;UseSSL=True;User=MyUser;Password=MyPassword;
NOTE: Since authentication to Databricks is managed from the connection string, you can leave Security Credentials blank.
Now that the connection is configured, we are ready to configure the schema for the dataset, choosing the tables, views, and columns we wish to visualize.
With the objects configured, you can perform any data preparation and discover any relationships in your data using the Pronto Prepare and Relate tools.
After you prepare your data and define relationships between the connected objects, you are ready to build your visualization.
Using the CData JDBC Driver for Databricks with the Cloud Agent and Birst, you can easily create robust visualizations and reports on Databricks data. Download a free, 30-day trial and start building Birst visualizations today.
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