Build JD Edwards-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for JD Edwards enables users to access live JD Edwards data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping JD Edwards data to any data source natively supported in Google Data Fusion, this article explains how to pipe data from JD Edwards to Google BigQuery,

Upload the CData JDBC Driver for JD Edwards to Google Data Fusion

Upload the CData JDBC Driver for JD Edwards to your Google Data Fusion instance to work with live JD Edwards data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatajdedwards-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.jdedwards) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.jdedwards.JDEdwardsDriver)
   
5. Click "Finish"

Connect to JD Edwards Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live JD Edwards data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, 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.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-jdedwards)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for JD Edwards. For example:
     
     jdbc:jdedwards:RTK=5246...;URL=https://your-jde-environment-app.example.com;User=admin;Password=myPassword;

     The driver connects to JD Edwards through your Application Interface Services (AIS) Server. Set the following connection properties:

     • URL: The base HTTPS URL of your AIS Server (e.g., https://jde-ais.example.com:8300).
     • User: Your JD Edwards username.
     • Password: Your JD Edwards password.
     • Environment (optional): The JD Edwards environment to use (e.g., PD920 for production or DV920 for development). If not specified, the AIS Server's default environment is used.
     • Role (optional): The JD Edwards role for the session. If not specified, the AIS Server's default role is used.
     • DeviceName (optional): An identifier for the connecting device or application, used for auditing and logging on the AIS Server.
     • Jasserver (optional): The specific Java Application Server (JAS) instance to route requests through, useful in clustered environments.

     Choosing Which Data Is Exposed

     JD Edwards organizes tables and business views by System Code, and the driver exposes each System Code as its own schema. Use these properties to control which schemas are available:

     • DataModel: One or more ERP modules (comma-separated) whose System Codes are exposed as schemas, or All to expose every System Code in the connected instance. Defaults to FinancialManagement.
     • SystemCodes: A comma-separated list of additional System Codes to expose alongside those from DataModel (e.g., 42,43).

     When you connect, the driver sends your credentials to the AIS Server to obtain a session token and caches it. The driver requests a new token automatically before the session expires.

     Built-in Connection String Designer

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

     
           java -jar cdata.jdbc.jdedwards.jar
           

     Fill in the connection properties and copy the connection string to the clipboard.

     
   • Set Import Query to a SQL query that will extract the data you want from JD Edwards, i.e.:
     SELECT * FROM AccountsPayable.AccountLedger
   
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like jdedwards-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert JD Edwards data into
   

With the Source and Sink configured, you are ready to pipe JD Edwards data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from JD Edwards and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex JD Edwards pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for JD Edwards and start working with your live JD Edwards data in Google Data Fusion today.