Analyze Copper 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 Copper data with the CData JDBC Driver for Copper.

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

You will need the following information to connect to Copper 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 Copper:

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 Copper and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

Start by setting the Profile connection property to the location of the Copper Profile on disk (e.g. C:\profiles\Copper.apip). Next, set the ProfileSettings connection property to the connection string for Copper (see below).

Copper API Profile Settings

In Copper CRM, go to Settings > Integrations > API Keys and click Generate API Key. Provide both the API key and the email address associated with your account.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Copper 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\Copper.apip;ProfileSettings='APIKey=your_api_key;UserEmail=your_email';")

Schema Discovery

The driver models Copper 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 Copper API:

account <- dbGetQuery(conn,"SELECT Id, Name FROM Account WHERE SettingEnableLeads = 'true'")

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

View(account)

Plot Copper Data

You can now analyze Copper 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(account$Name, main="Copper Account", names.arg = account$Id, horiz=TRUE)

Ready to get started?

Connect to live data from Copper with the API Driver

Connect to Copper