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.