Analyze Factorial Data in R via JDBC

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use standard R functions and the development environment of your choice to analyze Factorial data with the CData JDBC Driver for Factorial.

Access Factorial 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 Factorial and the RJDBC package to work with remote Factorial 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 Factorial and visualize Factorial 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 Factorial as a JDBC Data Source

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

  • Driver Class: Set this to cdata.jdbc.api.APIDriver
  • 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 Factorial:

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

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

Authentication

Factorial uses OAuth 2.0 for authentication to connect to your HR data or to allow other users to connect to their data.

Using OAuth Authentication

To connect using OAuth, follow these steps:

  1. Navigate to your Factorial admin panel and create a new OAuth application.
  2. Copy the Client ID and Client Secret from your application configuration.
  3. Configure the following connection properties:

After setting the following connection properties, you are ready to connect:

  • AuthScheme: Set this to OAuth.
  • OAuthClientId: Set this to your OAuth Client ID.
  • OAuthClientSecret: Set this to your OAuth Client Secret.
  • Scope: Set this to specify the data access permissions (default: "read write").

Built-in Connection String Designer

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

java -jar cdata.jdbc.api.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:api:Profile=C:\profiles\Factorial.apip;AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

Schema Discovery

The driver models Factorial 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 Factorial API:

agreements <- dbGetQuery(conn,"SELECT ,  FROM Agreements WHERE ProcessId = '123'")

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

View(agreements)

Plot Factorial Data

You can now analyze Factorial 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(agreements$, main="Factorial Agreements", names.arg = agreements$, horiz=TRUE)

Ready to get started?

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