Integrate with Databricks Data using Apache Camel2

Apache Camel is an open source integration framework that allows you to integrate various systems consuming or producing data. When paired with the CData JDBC Driver for Databricks, you can write Java apps that use Camel routes that integrate with live Databricks data. This article walks through creating an app in NetBeans that connects, queries, and routes Databricks data to a JSON file.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Databricks data. When you issue complex SQL queries 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). Its built-in dynamic metadata querying allows you to work with and analyze Databricks data using native data types.

Creating A New Maven/Java Project

Follow the steps below to create a new Java project and add the appropriate dependencies:

1. Open NetBeans and create a new project.
2. Select Maven from the categories list and Java Application from the projects list, then click Next.
3. Name the project (and adjust any other properties) and click Finish.
4. In the source package, create a new Java class (we used App.java for this article) and add the main method to the class.

Adding Project Dependencies

With the project created, we can start adding the dependencies needed to work with live Databricks data from our App. If you have not already done so, install Maven in your environment, as it is required to add the JAR file for the CData JDBC Driver to your project.

Installing the CData JDBC Driver for Databricks with Maven

1. Download the CData JDBC Driver for Databricks installer, unzip the package, and run the JAR file to install the driver.
2. Use Maven to install the JDBC Driver as a connector.

   mvn install:install-file 
   	-Dfile="C:\Program Files\CData[product_name] 2019\lib\cdata.jdbc.databricks.jar" 
   	-DgroupId="org.cdata.connectors" 
   	-DartifactId="cdata-databricks-connector" 
   	-Dversion="19" 
   	-Dpackaging=jar
   

Once the JDBC Driver is installed, we can add dependencies to our project. To add a dependency, you can either edit the pom.xml file or right-click the dependencies folder and click Add Dependency. The properties for each dependency follow, but you can search through the available libraries by typing the name of the dependency in the Query box in the Add Dependency wizard.

Required Dependencies

Accessing Databricks Data in Java Apps with Camel

After adding the required dependencies, we can use the Java DSL (Domain Specific Language) to create routes with access to live Databricks data. Code snippets follow. Download the sample project (zip file) to follow along (make note of the TODO comments).

Start by importing the necessary classes into our main class.

import org.apache.camel.CamelContext;
import org.apache.camel.builder.RouteBuilder;
import org.apache.camel.impl.DefaultCamelContext;
import org.apache.camel.support.SimpleRegistry;
import org.apache.commons.dbcp2.BasicDataSource;
import org.apache.log4j.BasicConfigurator;

Then in the main method, we configure logging, create a new BasicDataSource and add it to the registry, create a new CamelContext, and finally add a route to the context. In this sample, we route Databricks data to a JSON file.

Configure Logging

BasicConfigurator.configure();

Create a BasicDataSource

Create a BasicDataSource and set the driver class name (cdata.jdbc.salesforce.SalesforceDriver) and URL (using the required connection properties).

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.

• 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).

BasicDataSource basic = new BasicDataSource();
basic.setDriverClassName("cdata.jdbc.databricks.DatabricksDriver");
basic.setUrl("jdbc:databricks:Server=127.0.0.1;Port=443;TransportMode=HTTP;HTTPPath=MyHTTPPath;UseSSL=True;User=MyUser;Password=MyPassword;");

The CData JDBC Driver includes a built-in connection string designer to help you configure the connection URL.

Built-in Connection String Designer

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.

Add the BasicDataSource to the Registry and Create a CamelContext

SimpleRegistry reg = new SimpleRegistry();
reg.bind("myDataSource", basic);

CamelContext context = new DefaultCamelContext(reg);

Add Routing to the CamelContext

The routing below uses a timer component to run one time and passes a SQL query to the JDBC Driver. The results are marshaled as JSON (and formatted for pretty print) and passed to a file component to write to disk as a JSON file.

context.addRoutes(new RouteBuilder() {
	@Override
	public void configure() {
		from("timer://foo?repeatCount=1")
			.setBody(constant("SELECT * FROM Account LIMIT 10"))
			.to("jdbc:myDataSource")
			.marshal().json(true)
			.to("file:C:\\Users\\USER\\Documents?fileName=account.json");
	}
});

Managing the CamelContext Lifecycle

With the route defined, start the CamelContext to begin the lifecycle. In this example, we wait 10 seconds and then shut down the context.

context.start();
Thread.sleep(10000);
context.stop();

Free Trial, Sample Project & Technical Support

Now, you have a working Java application that uses Camel to route data from Databricks to a JSON file. Download a free, 30-day trial of the CData JDBC Driver for Databricks and the sample project (make note of the TODO comments) and start working with your live Databricks data in Apache Camel. Reach out to our Support Team if you have any questions.