Access Live Sage X3 Cloud Data in AWS Lambda

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Connect to live Sage X3 Cloud data in AWS Lambda using the CData JDBC Driver.

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 Sage X3 Cloud data when paired with the CData JDBC Driver for Sage X3 Cloud. This article describes how to connect to and query Sage X3 Cloud data from an AWS Lambda function built in Eclipse.

At the time this article was written (June 2022), Eclipse version 2019-12 and Java 8 were the highest versions supported by the AWS Toolkit for Eclipse.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Sage X3 Cloud data. When you issue complex SQL queries to Sage X3 Cloud, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage X3 Cloud 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 Sage X3 Cloud data using native data types.

Gather Connection Properties and Build a Connection String

Sage X3 Cloud uses the OAuth 2.0 Client Credentials flow, and an X-API-Key is also required for API access. Set AuthScheme to OAuth and specify the following connection properties:

  • URL: The base URL of your Sage X3 Cloud instance.
  • OAuthAccessTokenUrl: The OAuth token endpoint (e.g., https://your-auth-domain/oauth/token).
  • OAuthClientId: Your OAuth application client ID.
  • OAuthClientSecret: Your OAuth application client secret.
  • Audience: The API audience value for the token request.
  • XAPIKey: The X-API-Key provided by your Sage X3 Cloud administrator.
  • Folder: The Sage X3 folder name (e.g., SEED). This folder is used as the default schema.
  • Folders (optional): A comma-separated list of Sage X3 folders (e.g., SEED,PERF). Each folder is exposed as a separate schema, so you can query across folders with the Schema.Table syntax.

The driver obtains an access token with the Client Credentials flow and sends it with the X-API-Key on every API request. With InitiateOAuth set to GETANDREFRESH (the default), the driver acquires and refreshes the token automatically.

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 Sage X3 Cloud JDBC Driver. Double-click the JAR file or execute the jar file from the command line.


java -jar cdata.jdbc.sagex3cloud.jar
Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

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

Create an AWS Lambda Function

  1. Download the CData JDBC Driver for Sage X3 Cloud installer, unzip the package, and run the JAR file to install the driver.
  2. Create a new AWS Lambda Java Project in Eclipse using the AWS Toolkit for Eclipse. You can follow the tutorial from AWS (amazon.com).

    For this article, set the Input Type for the project to "Custom" so we can enter a table name as the input.

    Creating a new AWS Lambda Java project
  3. Add the CData JDBC Driver for Sage X3 Cloud JAR file (cdata.jdbc.sagex3cloud.jar) to the build path. The file is found in INSTALL_PATH\lib\. Adding the JDBC Driver JAR file
  4. 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;
    
  5. 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;
    
    try {
    	Class.forName("cdata.jdbc.sagex3cloud.SageX3CloudDriver");
    } catch (ClassNotFoundException ex) {
    	context.getLogger().log("Error: class not found");
    }
    
    Connection connection = null;
     
    try {
    	connection = DriverManager.getConnection("jdbc:cdata:sagex3cloud:RTK=52465...;AuthScheme=OAuth;URL=https://x3server/;OAuthAccessTokenUrl=https://auth-domain/oauth/token;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;Audience=https://api-audience;XAPIKey=your_api_key;Folder=SEED;");
    } 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());
    }
     
    String output = "query: " + query + " complete";
    return output;
    

Deploy and Run the Lambda Function

Once you build the function in Eclipse, you are ready to upload and run the function. In this article, the output is written to the AWS logs, but you can use this is a template to implement you own custom business logic to work with Sage X3 Cloud data in AWS Lambda functions.

  1. Right-click the Package and select Amazon Web Services -> Upload function to AWS Lamba. Uploading the function to AWS Lambda
  2. 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).
  3. Right-click the Package and select Amazon Web Services -> Run function on AWS Lambda and set the input to the name of the Sage X3 Cloud object you wish to query (i.e. "BPCUSTOMER"). Entering the table name as input
  4. After the job runs, you can view the output in the CloudWatch logs. The data in AWS CloudWatch (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData JDBC Driver for Sage X3 Cloud and start working with your live Sage X3 Cloud data in AWS Lambda. Reach out to our Support Team if you have any questions.

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