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Jira Query example

In this example, we will be outlining some very basic data loading pipelines using the Jira Query component in the Matillion Designer. These examples will result in a table that gives only Jira issues for a specific project.

The Jira Query component is available through the Components tab when editing an orchestration pipeline. This component will connect to your Jira account using a username/password or username/API token, stage the data in a storage area, and then load that data into a Snowflake table.


Authentication

The Jira Query component can take a username/password as authentication or a username/API token. We'll be using username/API token for this example and this means registering our Jira API token as a secret on the AWS Secrets Manager. The general process for this is given below:

  1. Log in to the AWS account that houses your agent.
  2. Browse to the Secrets Manager service.
  3. Ensure you're in the same AWS Region as your agent.
  4. Click Store a new secret.
  5. Click Other type of secret.
  6. Enter a memorable key name and then your Jira API token as the value.
  7. Click Next until the secret creation is completed.

You then need to register a Secret definition in the Designer. Follow these steps:

  1. Navigate to Designer in the Hub.
  2. Select your Project. Secret definitions are project-specific.
  3. Click the Secret definitions tab.
  4. Click Add secret definition.
  5. Configure your secret definition.
    • Secret definition name: An arbitrary name that Designer will refer to this secret with.
    • Description: A description of the secret.
    • Select Secret: Select a secret that exists already in your AWS account.
    • Select Secret Key: Select the key that belongs to your selected secret.
  6. Click Create Secret.

The value of the selected key will be used when this definition is referenced inside the Designer. For example, when this definition is selected as the password for connector authentication.

Secret definitions do not create secrets, they create a reference to an existing secret for use within the Designer.


Loading using the Jira Query component

Our first option to create project-specific Jira datasets is to use the Filter property on the Jira Query component. The component can be called multiple times in a single pipeline with each pointing to a different table.

Jira example canvas

To filter the data, click the Jira Query component and click to configure the Data Selection property. Ensure the ProjectName column is being loaded by moving it to the Selected Data Selection panel. Next, click the Data Source Filter property and configure with the following details:

Input Column Qualifier Comparator Value
ProjectName Is Equal to [YourProjectName]

Only rows that match this criteria will be kept in the data load.


Filtering with the Filter component

Alternatively, the Jira Query component can be used with no filter included to load all Jira issues data with a single load, and then we can let a transformation pipeline do the filtering by using the Filter component and then outputting to different tables using Rewrite Table.

Jira transformation canvas

If the Filter component does not validate as expected, try re-validating the pipeline so the Designer can acknowledge your columns from the Table Input component.