Databricks Lakehouse Federation enables organizations to query and integrate data from multiple sources without requiring data movement. It allows federated queries across databases, data warehouses, and lakehouses, providing a unified interface for data analysis and management within Databricks. When combined with CData Connect AI, it enables seamless access to Jira data for data virtualization, while also supporting data lineage and fine-grained access control.
This article explains how to use CData Connect AI to establish a live connection to Jira and how to access live Jira data from the Databricks platform.
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
CData Connect AI offers a seamless SQL Server, cloud-to-cloud interface for Jira, enabling you to effortlessly create dashboards and visualizations using live Jira data in Databricks. While building visualizations, Databricks requires SQL queries to retrieve the necessary data. With built-in optimized data processing, CData Connect AI pushes all supported SQL operations (such as filters and JOINs) directly to Jira, utilizing server-side processing for fast and efficient data retrieval of Jira data.
Configure Jira connectivity for Databricks in CData Connect AI
To work with Jira data in Databricks - Lakehouse Federation, you need to connect to Jira from Connect AI and provide user access to the connection.
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Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection
- Select "Jira" from the Add Connection panel
👁 Selecting a data source
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Enter the necessary authentication properties to connect to Jira.
To connect to JIRA, provide the User and Password. Additionally, provide the Url; for example, https://yoursitename.atlassian.net.
👁 Configuring a connection (Salesforce is shown)
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Click Save & Test
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Navigate to the Permissions tab in the Add Jira Connection page and update the User-based permissions.
👁 Updating permissions
Add a Personal Access Token
When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.
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Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
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On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
👁 Creating a new PAT
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The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the connection configured and a PAT generated, you are ready to connect to Jira data from Databricks.
Connecting live Jira data in Databricks
Follow these steps to establish a connection from Databricks to the CData Connect AI Virtual SQL Server API.
- Log into Databricks.
- Navigate to SQL Warehouses and start any warehouse of your choice.
👁 Start SQL Warehouse
- In the navigation pane, select Catalog. Click and select Create a connection.
👁 Create a connection
- In the Connection basics section (or Step 1 of Set up connection page), enter the following connection details and click Next:
- Connection name: a user-defined connection name.
- Connection type: select SQL Server from the drop-down list.
- Auth type: select Username and password.
👁 Add connection basics details
- In the Authentication section (or Step 2), enter the required authentication details, and click Next:
- Host: tds.cdata.com
- Port: 14333
- User: enter your CData Connect AI username, displayed in the top-right corner of the CData Connect AI interface. For example, [email protected]
- Password: enter the PAT generated and copied in the previous section.
👁 Add authentication details
- In the Connection details section (or Step 3), enable the Trust server certificate checkbox and select the appropriate Application intent. Click Create Connection.
👁 Add connection details
- In the Catalog basics section (or Step 4), enter the required details and click Create catalog:
- Catalog name: enter a name of your choice
- Connection: this will be the Databricks connection you defined earlier
- Database: enter your Jira connection name (for example, Jira1)
👁 Add catalog basics details
- In the Access section (or Step 5), assign the Workspace, User access rights, and Grant read or edit privileges to the catalog.
👁 Add the access rights
👁 Grant the access rights
- Click Next > Save to save all the details for the catalog.
👁 Save the catalog details and set up the connection
Access the catalog and visualize live Jira data in Databricks
To access the newly created catalog and create a dashboard to visualize live Jira data in Databricks, follow these steps:
- Select the catalog and expand it. A list of tables from Jira will appear on the screen.
👁 Select and expand the catalog
- Choose the desired table and click the Overview tab to view the table metadata.
👁 Select Overview
👁 View the table metadata
- Click the Sample Data tab to view real-time data in the table.
👁 Select Sample Data to view the table data
- Now, click Create at the top right corner and select Dashboard.
👁 Create a new dashboard
- Manually create a visualization by selecting at least one field in the visualization editor from the widget, or choose one of the visualization options suggested by Databricks AI.
👁 Create the dashboard manually or using the Databricks AI
- Once the visualization is created, edit the details in the widget settings of the dashboard.
👁 Visualization is created
- Click Publish to publish the dashboard report.
👁 Publish the dashboard
Live access to Jira data from cloud applications
At this stage, you have established a direct, cloud-to-cloud connection to live Jira data in Databricks. This enables you to create dashboards to monitor and visualize your data seamlessly.
For more details on accessing live data from over 100 SaaS, Big Data, and NoSQL sources through cloud applications like Databricks, visit our Connect AI page. As always, let us know if you have any questions during your evaluation. Our world-class CData Support Team is always available to help!
