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Analyze Sugar CRM Data in R

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

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

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

  • Driver Class: Set this to cdata.jdbc.sugarcrm.SugarCRMDriver
  • 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 Sugar CRM:

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

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

The User and Password properties, under the Authentication section, must be set to valid SugarCRM user credentials. This will use the default OAuth token created to allow client logins. OAuthClientId and OAuthClientSecret are required if you do not wish to use the default OAuth token.

You can generate a new OAuth consumer key and consumer secret in Admin -> OAuth Keys. Set the OAuthClientId to the OAuth consumer key. Set the OAuthClientSecret to the consumer secret.

Additionally, specify the URL to the SugarCRM account.

Note that retrieving SugarCRM metadata can be expensive. It is advised that you store the metadata locally as described in the "Caching Metadata" chapter of the help documentation.

Built-in Connection String Designer

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

java -jar cdata.jdbc.sugarcrm.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:sugarcrm:User=MyUser;Password=MyPassword;URL=MySugarCRMAccountURL;CacheMetadata=True;")

Schema Discovery

The driver models Sugar CRM 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 Sugar CRM API:

accounts <- dbGetQuery(conn,"SELECT Name, AnnualRevenue FROM Accounts")

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

View(accounts)

Plot Sugar CRM Data

You can now analyze Sugar CRM 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(accounts$AnnualRevenue, main="Sugar CRM Accounts", names.arg = accounts$Name, horiz=TRUE)