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Analyze Jira Data in R


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

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

About Jira Data Integration

CData simplifies access and integration of live Jira data. Our customers leverage CData connectivity to:

  • Gain bi-directional access to their Jira objects like issues, projects, and workflows.
  • Use SQL stored procedures to perform functional actions like changing issues status, creating custom fields, download or uploading an attachment, modifying or retrieving time tracking settings, and more.
  • Authenticate securely using a variety of methods, including username and password, OAuth, personal access token, API token, Crowd or OKTA SSO, LDAP, and more.

Most users leverage CData solutions to integrate Jira data with their database or data warehouse, whether that's using CData Sync directly or relying on CData's compatibility with platforms like SSIS or Azure Data Factory. Others are looking to get analytics and reporting on live Jira data from preferred analytics tools like Tableau and Power BI.

Learn more about how customers are seamlessly connecting to their Jira data to solve business problems from our blog: Drivers in Focus: Collaboration Tools.


Getting Started


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 Jira as a JDBC Data Source

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

  • Driver Class: Set this to cdata.jdbc.jira.JIRADriver
  • 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 Jira:

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

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

To connect to JIRA, provide the User and Password. Additionally, provide the Url; for example, https://yoursitename.atlassian.net.

Built-in Connection String Designer

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

java -jar cdata.jdbc.jira.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:jira:User=admin;Password=123abc;Url=https://yoursitename.atlassian.net;")

Schema Discovery

The driver models Jira 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 Jira API:

issues <- dbGetQuery(conn,"SELECT Projects.LeadName, Issues.Summary FROM Projects, Issues WHERE Projects.Id=Issues.ProjectId")

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

View(issues)

Plot Jira Data

You can now analyze Jira 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(issues$TimeSpent, main="Jira Issues", names.arg = issues$Summary, horiz=TRUE)

Ready to get started?

Download a free trial of the Jira Driver to get started:

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