Analyze Smartsheet Data in R via JDBC

Access Smartsheet 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 Smartsheet and the RJDBC package to work with remote Smartsheet 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 Smartsheet and visualize Smartsheet data by calling standard R functions.

Getting Started

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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 Smartsheet as a JDBC Data Source

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

• Driver Class: Set this to cdata.jdbc.smartsheet.SmartsheetDriver
• 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 Smartsheet:

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

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

Smartsheet uses the OAuth authentication standard. To authenticate using OAuth, register an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

However, for testing purposes you can instead use the Personal Access Token you get when you create an application; set this to the OAuthAccessToken connection property.

Built-in Connection String Designer

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

java -jar cdata.jdbc.smartsheet.jar

Fill in the connection properties and copy the connection string to the clipboard.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:smartsheet:OAuthClientId=MyOauthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;")

Schema Discovery

The driver models Smartsheet 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 Smartsheet API:

sheet_event_plan_budget <- dbGetQuery(conn,"SELECT TaskName, Progress FROM Sheet_Event_Plan_Budget")

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

View(sheet_event_plan_budget)

Plot Smartsheet Data

You can now analyze Smartsheet 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(sheet_event_plan_budget$Progress, main="Smartsheet Sheet_Event_Plan_Budget", names.arg = sheet_event_plan_budget$TaskName, horiz=TRUE)

👁 A basic bar plot. (Salesforce is shown.)