Build Jira Service Desk-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Jira Service Desk enables users to access live Jira Service Desk data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Jira Service Desk data to any data source natively supported in Google Data Fusion, this article walks through piping data from Jira Service Desk to Google BigQuery,

Upload the CData JDBC Driver for Jira Service Desk to Google Data Fusion

Upload the CData JDBC Driver for Jira Service Desk to your Google Data Fusion instance to work with live Jira Service Desk data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatajiraservicedesk-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.jiraservicedesk) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.jiraservicedesk.JiraServiceDeskDriver)
5. Click "Finish"

Connect to Jira Service Desk Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Jira Service Desk data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-jiraservicedesk)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Jira Service Desk. For example:
     
     jdbc:jiraservicedesk:RTK=5246...;ApiKey=myApiKey;User=MyUser;InitiateOAuth=GETANDREFRESH;

     You can establish a connection to any Jira Service Desk Cloud account or Server instance.

     Connecting with a Cloud Account

     To connect to a Cloud account, you'll first need to retrieve an APIToken. To generate one, log in to your Atlassian account and navigate to API tokens > Create API token. The generated token will be displayed.

     Supply the following to connect to data:

     • User: Set this to the username of the authenticating user.
     • APIToken: Set this to the API token found previously.

     Connecting with a Service Account

     To authenticate with a service account, you will need to supply the following connection properties:

     • User: Set this to the username of the authenticating user.
     • Password: Set this to the password of the authenticating user.
     • URL: Set this to the URL associated with your JIRA Service Desk endpoint. For example, https://yoursitename.atlassian.net.

     Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.

     Accessing Custom Fields

     By default, the connector only surfaces system fields. To access the custom fields for Issues, set IncludeCustomFields.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.jiraservicedesk.jar

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

   • Set Import Query to a SQL query that will extract the data you want from Jira Service Desk, i.e.:
     SELECT * FROM Requests
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like jiraservicedesk-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert Jira Service Desk data into

With the Source and Sink configured, you are ready to pipe Jira Service Desk data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Jira Service Desk and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Jira Service Desk pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Jira Service Desk and start working with your live Jira Service Desk data in Google Data Fusion today.