ETL Sage 300 in Oracle Data Integrator

Leverage existing skills by using the JDBC standard to connect to Sage 300: Through drop-in integration into ETL tools like Oracle Data Integrator (ODI), the CData JDBC Driver for Sage 300 connects real-time Sage 300 data to your data warehouse, business intelligence, and Big Data technologies.

JDBC connectivity enables you to work with Sage 300 just as you would any other database in ODI. As with an RDBMS, you can use the driver to connect directly to the Sage 300 APIs in real time instead of working with flat files.

This article walks through a JDBC-based ETL -- Sage 300 to Oracle. After reverse engineering a data model of Sage 300 entities, you will create a mapping and select a data loading strategy -- since the driver supports SQL-92, this last step can easily be accomplished by selecting the built-in SQL to SQL Loading Knowledge Module.

Install the Driver

To install the driver, copy the driver JAR and .lic file, located in the installation folder, into the ODI appropriate directory:

• UNIX/Linux without Agent: ~/.odi/oracledi/userlib
• UNIX/Linux with Agent: $ODI_HOME/odi/agent/lib
• Windows without Agent: %APPDATA%\Roaming\odi\oracledi\userlib
• Windows with Agent: %APPDATA%\Roaming\odi\agent\lib

Restart ODI to complete the installation.

Reverse Engineer a Model

Reverse engineering the model retrieves metadata about the driver's relational view of Sage 300 data. After reverse engineering, you can query real-time Sage 300 data and create mappings based on Sage 300 tables.

1. In ODI, connect to your repository and click New -> Model and Topology Objects.
2. On the Model screen of the resulting dialog, enter the following information:
   • Name: Enter Sage300.
   • Technology: Select Generic SQL (for ODI Version 12.2+, select Microsoft SQL Server).
   • Logical Schema: Enter Sage300.
   • Context: Select Global.
3. On the Data Server screen of the resulting dialog, enter the following information:
   • Name: Enter Sage300.
   • Driver List: Select Oracle JDBC Driver.
   • Driver: Enter cdata.jdbc.sage300.Sage300Driver
   • URL: Enter the JDBC URL containing the connection string.

     Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.

     • Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the option under Security Groups (per each module required).
     • Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
     • Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.

     Authenticate to Sage 300 using Basic authentication.

     Connect Using Basic Authentication

     You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.

     • Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
     • User: Set this to the username of your account.
     • Password: Set this to the password of your account.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Sage 300 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

     java -jar cdata.jdbc.sage300.jar

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

     Below is a typical connection string:

     jdbc:sage300:User=SAMPLE;Password=password;URL=http://127.0.0.1/Sage300WebApi/v1/-/;Company=SAMINC;
4. On the Physical Schema screen, enter the following information:
   • Name: Select from the Drop Down menu.
   • Database (Catalog): Enter CData.
   • Owner (Schema): If you select a Schema for Sage 300, enter the Schema selected, otherwise enter Sage300.
   • Database (Work Catalog): Enter CData.
   • Owner (Work Schema): If you select a Schema for Sage 300, enter the Schema selected, otherwise enter Sage300.
5. In the opened model click Reverse Engineer to retrieve the metadata for Sage 300 tables.

Edit and Save Sage 300 Data

After reverse engineering you can now work with Sage 300 data in ODI. To view Sage 300 data, expand the Models accordion in the Designer navigator, right-click a table, and click View data.

Create an ETL Project

Follow the steps below to create an ETL from Sage 300. You will load OEInvoices entities into the sample data warehouse included in the ODI Getting Started VM.

1. Open SQL Developer and connect to your Oracle database. Right-click the node for your database in the Connections pane and click new SQL Worksheet.

   Alternatively you can use SQLPlus. From a command prompt enter the following:

   sqlplus / as sysdba
2. Enter the following query to create a new target table in the sample data warehouse, which is in the ODI_DEMO schema. The following query defines a few columns that match the OEInvoices table in Sage 300: CREATE TABLE ODI_DEMO.TRG_OEINVOICES (APPROVEDLIMIT NUMBER(20,0),InvoiceUniquifier VARCHAR2(255));
3. In ODI expand the Models accordion in the Designer navigator and double-click the Sales Administration node in the ODI_DEMO folder. The model is opened in the Model Editor.
4. Click Reverse Engineer. The TRG_OEINVOICES table is added to the model.
5. Right-click the Mappings node in your project and click New Mapping. Enter a name for the mapping and clear the Create Empty Dataset option. The Mapping Editor is displayed.
6. Drag the TRG_OEINVOICES table from the Sales Administration model onto the mapping.
7. Drag the OEInvoices table from the Sage 300 model onto the mapping.
8. Click the source connector point and drag to the target connector point. The Attribute Matching dialog is displayed. For this example, use the default options. The target expressions are then displayed in the properties for the target columns.
9. Open the Physical tab of the Mapping Editor and click OEINVOICES_AP in TARGET_GROUP.
10. In the OEINVOICES_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab.

You can then run the mapping to load Sage 300 data into Oracle.