Jira Data Generator asks the user how many projects, issues ... etc to create and how many fields are to be populated for each issue. The thing is DG selects which fields to populate for each issue individually. This produces an output where each issue in the project has different fields populated.
This is far from representing an actual use case. Even if the system has a few hundred projects and a few hundred custom fields, usually issues in any given project use the same set of custom fields.
I am trying to create a large Jira instance to performance test my plugin. The "large instance" definition given by Atlassian (as of today) has 1500+ projects 1400+ custom fields 1M+ issues, etc.. By default all custom fields created by Data Generator has global contexts but a production instance this large will definitely have its custom field contexts customized and narrowed down to projects that actually use those custom fields.
After I created the required number of projects, custom fields, issues; I tried to use the recently introduced custom field optimizer but since custom fields are randomly selected per issue while generating data, all custom fields are already used in all projects and optimizer can't optimize anything.
This should be a problem for evenybody, including Atlassian. How can I create a large test instance with this data generator?
I tried to create an issue in JDG project of ecosystem.atlassian.net about this but I get an error saying "the default assignee does not have assignable user permission".
Long story short, I strongly believe that Data Generator must be updated to pick the given number of custom fields per project and populate the same set of custom fields for each issue in that project. Does anybody know of a workaround I can use. How do you guys create large instances?
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