Analyze PivotalTracker Data in R via JDBC

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

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

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

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

PivotalTracker API Profile Settings

Navigate to your Pivotal Tracker Profile settings and locate the API token section to copy your unique API token.

Built-in Connection String Designer

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

Schema Discovery

The driver models PivotalTracker 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 PivotalTracker API:

accountmemberships <- dbGetQuery(conn,"SELECT AccountId, Id FROM AccountMemberships WHERE Admin = 'true'")

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

View(accountmemberships)

Plot PivotalTracker Data

You can now analyze PivotalTracker 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(accountmemberships$Id, main="PivotalTracker AccountMemberships", names.arg = accountmemberships$AccountId, horiz=TRUE)