Tableau Server uses caching to speed up workbook loading by storing query results. After a scheduled extract refresh updates the data, the cache may need recomputing—let’s dive into the mechanics:

Caching Basics:

VizQL Cache: Stores rendered views and query results for faster access.

Refresh Trigger: A scheduled refresh updates the underlying extract (.hyper), but the cache isn’t automatically invalidated—it’s demand-driven.

Recompute Conditions: Tableau recomputes the cache when the workbook is accessed (viewed) and its data has changed (e.g., via refresh).

Evaluation:

Option B (The workbook has upcoming scheduled refresh tasks): Correct.

Why: An upcoming refresh task indicates the workbook relies on an extract with a schedule. After the refresh runs, the data changes, priming the cache for recomputation on next view. Without a schedule, no refresh occurs, so this is a prerequisite.

Detail: Schedules are set inSchedules > Tasks—e.g., "Daily at 2 AM."

Option D (The workbook has been viewed recently): Correct.

Why: Viewing triggers cache recomputation if the data has changed (e.g., post-refresh). Tableau uses a "lazy caching" model—cache updates only when a user loads the workbook, ensuring fresh results.

Detail: "Recently" isn’t strictly defined but implies post-refresh access.

Option A (Published in the last month): Incorrect.

Why: Publish date is irrelevant—cache recomputation ties to data changes and access, not publication timing.

Option C (All Users group has permission rule allowing access): Incorrect.

Why: Permissions enable viewing, but recomputation requires actual access (viewing) and a refresh event, not just potential access.

Why This Matters: Caching balances performance and freshness—understanding triggers prevents stale data surprises.