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How to connect to Azure Data Lake Storage Data from Spring Boot

Connect to Azure Data Lake Storage in a Spring Boot Application using CData JDBC Azure Data Lake Storage Driver

Spring Boot is a framework that makes engineering Java web applications easier. It offers the ability to create standalone applications with minimal configuration. When paired with the CData JDBC driver for Azure Data Lake Storage, Spring Boot can work with live Azure Data Lake Storage data. This article shows how to configure data sources and retrieve data in your Java Spring Boot Application, using the CData JDBC Driver for Azure Data Lake Storage.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Azure Data Lake Storage data. When you issue complex SQL queries to Azure Data Lake Storage, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Data Lake Storage 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 Azure Data Lake Storage data using native data types.

Creating the Spring Boot Project in Java

In an IDE (in this tutorial, we use IntelliJ), choose a Maven project: In the generated project, go to the pom.xml file, and add the required dependencies for Spring Boot:


<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.7.2</version>
<relativePath/>
</parent>
<groupId>com.example</groupId>
<artifactId>demo</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>demo</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>1.8</java.version>
</properties>
<build>
<plugins>
	<plugin>
		<groupId>org.springframework.boot</groupId>
		<artifactId>spring-boot-maven-plugin</artifactId>
	</plugin>

	<plugin>
		<groupId>org.apache.maven.plugins</groupId>
		<artifactId>maven-install-plugin</artifactId>
		<version>2.5.1</version>
		<executions>
			<execution>
				<id>id.install-file</id>
				<phase>clean</phase>
				<goals>
					<goal>install-file</goal>
				</goals>
				<configuration>
					<file>C:\Program Files\CData[product_name] ####\lib\cdata.jdbc.adls.jar</file>
					<groupId>org.cdata.connectors</groupId>
					<artifactId>cdata-adls-connector</artifactId>
					<version>23</version>
					<packaging>jar</packaging>
				</configuration>
			</execution>
		</executions>
	</plugin>
</plugins>
</build>

<dependencies>
<dependency>
	<groupId>org.springframework.boot</groupId>
	<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
	<groupId>org.springframework.boot</groupId>
	<artifactId>spring-boot-starter-jdbc</artifactId>
	<version>2.7.0</version>
</dependency>
<dependency>
	<groupId>org.cdata.connectors</groupId>
	<artifactId>cdata-adls-connector</artifactId>
	<version>23</version>
</dependency>

<dependency>
	<groupId>org.springframework.boot</groupId>
	<artifactId>spring-boot-starter-test</artifactId>
	<scope>test</scope>
</dependency>
</dependencies>



<distributionManagement>
<repository>
	<uniqueVersion>false</uniqueVersion>
	<id>test</id>
	<name>My Repository</name>
	<url>scp://repo/maven2</url>
	<layout>default</layout>
</repository>
</distributionManagement>

</project>

Note: The year (####) and the version number (as seen in the provided XML script) should be adjusted according to the current version of the CData JDBC driver being utilized.

Project Structure

In the java directory, create a new package. Usually the name of the package is the name of the groupId (com.example) followed by the artifactId (.MDS).

Mark the "java" directory as the "Sources Root" (denoted by a blue color). To do this, right-click the java directory and choose Mark Directory as -> Sources Root (As shown below). Additionally, mark the "resources" directory as the "Resources Root."

Store Database Connection Properties

Create an "application.properties" file to store the database connection properties. To do this, right-click on the "resources" folder, opt for New -> File, input the file name as "application.properties," and press Enter.

In the application.properties file, we set the configuration properties for the Azure Data Lake Storage JDBC Driver, using the Class name and JDBC URL:


	spring.datasource.driver=cdata.jdbc.adls.ADLSDriver
	spring.datasource.url=jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Azure Data Lake Storage JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.


java -jar cdata.jdbc.adls.jar

Authenticating to a Gen 1 DataLakeStore Account

Gen 1 uses OAuth 2.0 in Azure AD for authentication.

For this, an Active Directory web application is required. You can create one as follows:

Sign in to your Azure Account through the .
Select "Azure Active Directory".
Select "App registrations".
Select "New application registration".
Provide a name and URL for the application. Select Web app for the type of application you want to create.
Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

Schema: Set this to ADLSGen1.
Account: Set this to the name of the account.
OAuthClientId: Set this to the application Id of the app you created.
OAuthClientSecret: Set this to the key generated for the app you created.
TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

Authenticating to a Gen 2 DataLakeStore Account

To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

Schema: Set this to ADLSGen2.
Account: Set this to the name of the account.
FileSystem: Set this to the file system which will be used for this account.
AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

After setting the properties in the application.properties file, we now configure them.

Data Source Configuration

First, we mark the Azure Data Lake Storage data source as our primary data source. Then, we create a Data Source Bean.

Create a DriverManagerDataSource.java file and create a Bean within it, as shown below. If @Bean gives an error, Spring Boot may not have loaded properly. To fix this, go to File -> Invalidate Caches and restart. Additionally, make sure that Maven has added the Spring Boot dependencies.

To create a data source bean, we use the DriverManagerDataSource Class. This class allows us to set the properties of the data source. To create this Java class, right-click on "com.example.MDS" package, and choose New -> Java Class.

The following code shows the bean definition of our data source. Each driver should have a bean.


import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.jdbc.DataSourceBuilder;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Primary;
import org.springframework.core.env.Environment;
import javax.sql.DataSource;

public class DriverManagerDataSource{
	@Autowired
	private static Environment env;

	@Bean(name ="ADLS")
	@Primary
	public static DataSource ADLSDataSource()
	{

	DataSourceBuilder<?> dataSourceBuilder = DataSourceBuilder.create();
		dataSourceBuilder.driverClassName("cdata.jdbc.adls.ADLSDriver");
		dataSourceBuilder.url("jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH");
		return dataSourceBuilder.build();
	}
	
	//@Override
	public void setEnvironment( final Environment environment) {
	env=environment;
	}
}

Next, move the Azure Data Lake Storage jar file to the Documents folder (see path in command below) - The idea is to have a path without any spaces for the jar file. Then, click the Maven icon (top right corner of IntelliJ) and click "Execute Maven Goal." Now, run the following command:


mvn install:install-file "-Dfile=C:\Program Files\CData[product_name] ####\lib\cdata.jdbc.adls.jar" -DgroupId=org.cdata.connectors -DartifactId=cdata-adls-connector -Dversion=23 -Dpackaging=jar

Follow either of the given steps to run this command:

The "-Dfile location" can be kept as the default installation path of the CData JDBC Driver. Make sure to keep the path in quotations in this case. Also, change the year and "Dversion" based on the current version of the driver being used.
As mentioned earlier in the article, in case you relocate the jar file to the Documents folder, make sure to modify the path in the provided command. In such instances, avoid enclosing the Dfile location in quotations and edit "Dversion" based on the current version of the driver being used.

After pressing enter, we see the following output:

Testing the Connection

The last step is testing the connection. Create a new Java class following the format (e.g., "MDSApplication"). You have the flexibility to select any name for the application class. We call the data source in the main method of MDSApplication.java:


import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import java.sql.Connection;
import java.sql.SQLException;
import static com.example.demo.DriverManagerDataSources.ADLSDataSource;


@SpringBootApplication(exclude = {DataSourceAutoConfiguration.class})
	public class MDSApplication {
		//remove the comment on the line below
		public static void main (){
		SpringApplication.run(DemoApplication.class, args);
		Connection conn = ADLSDataSource().getConnection();
		System.out.println("Catalog: "+ conn.getCatalog());
	}
}

The output generated should look like this:

Free Trial & More Information

Download a free, 30-day trial of the CData JDBC Driver for Azure Data Lake Storage and start working with your live Azure Data Lake Storage in Spring Boot.

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