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URL: https://www.cdata.com/kb/tech/jira-jdbc-aws-databricks.rst

⇱ Process & Analyze Jira Data in Databricks (AWS)

Process & Analyze Jira Data in Databricks (AWS)

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use CData, AWS, and Databricks to perform data engineering and data science on live Jira Data.

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Jira data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Jira data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Jira data. When you issue complex SQL queries to Jira, the driver pushes supported SQL operations, like filters and aggregations, directly to Jira and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Jira data using native data types.

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 the CData JDBC Driver in Databricks

To work with live Jira data in Databricks, install the driver on your Databricks cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "Upload" as the Library Source and "Jar" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.jira.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).
👁 Loading the JDBC JAR File into AWS

Access Jira Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Jira data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Jira, and create a basic report.

Configure the Connection to Jira

Connect to Jira by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

Step 1: Connection Information

driver = "cdata.jdbc.jira.JIRADriver"
url = "jdbc:jira:RTK=5246...;User=admin;Password=123abc;Url=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.

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

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

Load Jira Data

Once you configure the connection, you can load Jira data as a dataframe using the CData JDBC Driver and the connection information.

Step 2: Reading the data

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Issues") \
	.load ()

Display Jira Data

Check the loaded Jira data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Summary"))
👁 Displaying Jira Data

Analyze Jira Data in Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the Jira data for reporting, visualization, and analysis.

% sql

SELECT Summary, TimeSpent FROM SAMPLE_VIEW ORDER BY TimeSpent DESC LIMIT 5
👁 Displaying Jira Data

The data from Jira is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for Jira and start working with your live Jira data in Databricks. Reach out to our Support Team if you have any questions.