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Analyze Sage 300 Data in R

Use standard R functions and the development environment of your choice to analyze Sage 300 data with the CData JDBC Driver for Sage 300.

Access Sage 300 data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Sage 300 and the RJDBC package to work with remote Sage 300 data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Sage 300 and visualize Sage 300 data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to Sage 300 as a JDBC Data Source

You will need the following information to connect to Sage 300 as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.sage300.Sage300Driver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Sage 300:

driver <- JDBC(driverClass = "cdata.jdbc.sage300.Sage300Driver", classPath = "MyInstallationDir\lib\cdata.jdbc.sage300.jar", identifier.quote = "'")

You can now use DBI functions to connect to Sage 300 and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

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 sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:sage300:User=SAMPLE;Password=password;URL=http://127.0.0.1/Sage300WebApi/v1/-/;Company=SAMINC;")

Schema Discovery

The driver models Sage 300 APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Sage 300 API:

oeinvoices <- dbGetQuery(conn,"SELECT InvoiceUniquifier, ApprovedLimit FROM OEInvoices WHERE AllowPartialShipments = 'Yes'")

You can view the results in a data viewer window with the following command:

View(oeinvoices)

Plot Sage 300 Data

You can now analyze Sage 300 data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2)) barplot(oeinvoices$ApprovedLimit, main="Sage 300 OEInvoices", names.arg = oeinvoices$InvoiceUniquifier, horiz=TRUE)