Access Live Azure Data Catalog Data in AWS Lambda (with IntelliJ IDEA)

AWS Lambda is a compute service that lets you build applications that respond quickly to new information and events. AWS Lambda functions can work with live Azure Data Catalog data when paired with the CData JDBC Driver for Azure Data Catalog. This article describes how to connect to and query Azure Data Catalog data from an AWS Lambda function built with Maven in IntelliJ.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Azure Data Catalog data. When you issue complex SQL queries to Azure Data Catalog, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Data Catalog and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). In addition, its built-in dynamic metadata querying allows you to work with and analyze Azure Data Catalog data using native data types.

Gather Connection Properties and Build a Connection String

Download the CData JDBC Driver for Azure Data Catalog installer, unzip the package, and run the JAR file to install the driver. Then gather the required connection properties.

You can optionally set the following to read the different catalog data returned from Azure Data Catalog.

CatalogName: Set this to the CatalogName associated with your Azure Data Catalog. To get your Catalog name, navigate to your Azure Portal home page > Data Catalog > Catalog Name

Connect Using OAuth Authentication

You must use OAuth to authenticate with Azure Data Catalog. OAuth requires the authenticating user to interact with Azure Data Catalog using the browser. For more information, refer to the OAuth section in the help documentation.

NOTE: To use the JDBC driver in an AWS Lambda function, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

Built-in Connection String Designer

For assistance constructing the JDBC URL, use the connection string designer built into the Azure Data Catalog JDBC Driver. Double-click the JAR file or execute the jar file from the command line.

Fill in the connection properties (including the RTK) and copy the connection string to the clipboard.

Create a Project in IntelliJ

1. In IntelliJ IDEA, click New Project.
2. Select "Maven Archetype" from the Generators
3. Name the project and select "maven.archetypes:maven-archetype-quickstart" Archetype.
4. Click "Create"

Install the CData JDBC Driver for Azure Data Catalog JAR File

Use the following Maven command from the project's root folder to install JAR file in the project.

Add Dependencies

Within the Maven project's pom.xml file, add AWS and the CData JDBC Driver for Azure Data Catalog as dependencies (within the <dependencies> element) using the following XML.

• AWS <dependency> <groupId>com.amazonaws</groupId> <artifactId>aws-lambda-java-core</artifaceId> <version>1.2.2</version> <!--Replace with the actual version--> </dependency>
• CData JDBC Driver for Azure Data Catalog <dependency> <groupId>org.cdata.connectors</groupId> <artifactId>cdata-azuredatacatalog-connector</artifaceId> <version>23</version> <!--Replace with the actual version--> </dependency>

Create an AWS Lambda Function

For this sample project, we create two source files: CDataLambda.java and CDataLambdaTest.java.

Lambda Function Definition

1. Update CDataLambda to implement the RequestHandler interface from the AWS Lambda SDK. You will need to add the handleRequest method, which performs the following tasks when the Lambda function is triggered:
   1. Constructs a SQL query using the input.
   2. Sets up AWS credentials and S3 configuration to store OAuth credentials.
   3. Registers the CData JDBC driver for Azure Data Catalog.
   4. Establishes a connection to Azure Data Catalog using JDBC.
   5. Executes the SQL query on Azure Data Catalog.
   6. Prints the results to the console.
   7. Returns an output message.
2. Add the following import statements to the Java class: import java.sql.Connection; import java.sql.DriverManager; import java.sql.ResultSet; import java.sql.ResultSetMetaData; import java.sql.SQLException; import java.sql.Statement;

3. Replace the body of the handleRequest method with the code below. Be sure to fill in the connection string in the DriverManager.getConnection method call.

   String query = "SELECT * FROM " + input; // Set your AWS credentials String awsAccessKey = "YOUR_AWS_ACCESS_KEY"; String awsSecretKey = "YOUR_AWS_SECRET_KEY"; String awsRegion = "YOUR_AWS_REGION"; // AWS S3 Configuration AmazonS3 s3Client = AmazonS3ClientBuilder.standard() .withRegion(awsRegion) .withCredentials(new AWSStaticCredentialProvider(new BasicAWSCredentials(awsAccessKey, awsSecretKey))) .build(); String bucketName = "MY_AWS_BUCKET"; String oauthSettings = "S:3//"+ bucketName + "/OAuthSettings.txt"; String oauthConnection = "InitiateOAuth=REFRESH;" + "OAuthSettingsLocation=" + oauthSettings = ";" try { Class.forName("cdata.jdbc.azuredatacatalog.AzureDataCatalogDriver"); cdata.jdbc.azuredatacatalog.AzureDataCatalogDriver driver = new cdata.jdbc.azuredatacatalog.AzureDataCatalogDriver(); DriverManager.registerDriver(driver); } catch (SQLException ex) { } catch (ClassNotFoundException e) { throw new RuntimeException(e); } Connection connection = null; try { connection = DriverManager.getConnection("jdbc:cdata:azuredatacatalog:RTK=52465...;" + oauthConnection + ""); } catch (SQLException ex) { context.getLogger().log("Error getting connection: " + ex.getMessage()); } catch (Exception ex) { context.getLogger().log("Error: " + ex.getMessage()); } if(connection != null) { context.getLogger().log("Connected Successfully!\n"); } ResultSet resultSet = null; try { //executing query Statement stmt = connection.createStatement(); resultSet = stmt.executeQuery(query); ResultSetMetaData metaData = resultSet.getMetaData(); int numCols = metaData.getColumnCount(); //printing the results while(resultSet.next()) { for(int i = 1; i <= numCols; i++) { System.out.printf("%-25s", (resultSet.getObject(i) != null) ? resultSet.getObject(i).toString().replaceAll("\n", "") : null ); } System.out.print("\n"); } } catch (SQLException ex) { System.out.println("SQL Exception: " + ex.getMessage()); } catch (Exception ex) { System.out.println("General exception: " + ex.getMessage()); } return "query: " + query + " complete";

Deploy and Run the Lambda Function

Once you build the function in Intellij, you are ready to deploy the entire Maven project as a single JAR file.

1. In IntelliJ, use the mvn install command to build the SNAPSHOT JAR file.
2. Create a new function in AWS Lambda (or open an existing one).
3. Name the function, select an IAM role, and set the timeout value to a high enough value to ensure the function completes (depending on the result size of your query).
4. Click "Upload from" -> ".zip file" and select your SNAPSHOT JAR file.
5. In the "Runtime settings" section, click "Edit" and set Handler to your "handleRequest" method (e.g. package.class::handleRequest)
6. You can now test the function. Set the "Event JSON" field to a table name and click, click "Test"

Free Trial & More Information

Download a free, 30-day trial of the CData JDBC Driver for Azure Data Catalog and start working with your live Azure Data Catalog data in AWS Lambda. Reach out to our Support Team if you have any questions.