Partial runs can help speed up workspace authoring by which of the following?

Partial runs can help speed up workspace authoring by which of the following?

• A. Allowing you to only run part of your workspace.
• B. Allowing you to update a single cache.
• C. Allowing you to quickly inspect data you just added to the canvas.
• D. All of the above.

Answer: (D)

Partial runs let you execute just a portion of a workspace, which speeds up authoring by giving you quick feedback on changes without reprocessing the entire dataset. You can run from a breakpoint to a chosen endpoint or from a specific transformer, so you see the effects of edits right where you’re focusing. This is especially useful for updating a single cache, because you can re-run only the segment that populates or refreshes that cache instead of rebuilding everything. It also lets you quickly inspect data you just added to the canvas by running the path that leads to that new data, so you can visualize and verify it without waiting for the whole workflow to run. Because partial runs provide these targeted, faster feedback benefits, all of the above describes how they speed up workspace authoring.

Partial runs let you execute just a portion of a workspace, which speeds up authoring by giving you quick feedback on changes without reprocessing the entire dataset. You can run from a breakpoint to a chosen endpoint or from a specific transformer, so you see the effects of edits right where you’re focusing.

This is especially useful for updating a single cache, because you can re-run only the segment that populates or refreshes that cache instead of rebuilding everything. It also lets you quickly inspect data you just added to the canvas by running the path that leads to that new data, so you can visualize and verify it without waiting for the whole workflow to run.

Because partial runs provide these targeted, faster feedback benefits, all of the above describes how they speed up workspace authoring.