Analyze SAP SuccessFactors LMS Data in R via JDBC

Access SAP SuccessFactors LMS 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 SAP SuccessFactors LMS and the RJDBC package to work with remote SAP SuccessFactors LMS 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 SAP SuccessFactors LMS and visualize SAP SuccessFactors LMS 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 SAP SuccessFactors LMS as a JDBC Data Source

You will need the following information to connect to SAP SuccessFactors LMS as a JDBC data source:

• Driver Class: Set this to cdata.jdbc.sapsuccessfactorslms.SAPSuccessFactorsLMSDriver
• 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 SAP SuccessFactors LMS:

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

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

SAP SuccessFactors LMS uses OAuth authentication. Before connecting, you must configure an OAuth application tied to your SAP SuccessFactors LMS account.

To establish a connection, set the following properties:

• User: Your SAP SuccessFactors LMS username.
• CompanyId: Your SAP SuccessFactors company identifier.
• Url: The SAP SuccessFactors API URL (e.g., https://api4.successfactors.com).
• OAuthClientId: The client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.

See the Getting Started chapter of the help documentation for a guide to creating a custom OAuth app and using OAuth.

Built-in Connection String Designer

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

java -jar cdata.jdbc.sapsuccessfactorslms.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:sapsuccessfactorslms:User=username;CompanyId=CompanyId;Url=https://api4.successfactors.com;InitiateOAuth=GETANDREFRESH;")

Schema Discovery

The driver models SAP SuccessFactors LMS 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 SAP SuccessFactors LMS API:

items <- dbGetQuery(conn,"SELECT ItemID, ItemTitle FROM [Admin].[Search_Service].[Items] WHERE Active = true")

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

View(items)

Plot SAP SuccessFactors LMS Data

You can now analyze SAP SuccessFactors LMS 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(items$ItemTitle, main="SAP SuccessFactors LMS Items", names.arg = items$ItemID, horiz=TRUE)