What is the easiest way to identify redundant charts in our Tableau server that consume heavy database CPU every morning during the automated refresh cycle?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the easiest way to identify redundant charts in our Tableau server that consume heavy database CPU every morning during the automated refresh cycle?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
Tableau Server repository administrative views background tasks for extracts performance of views query logs official documentation Google ↗
Tableau Server identify duplicate workbooks views redundant charts database CPU query logs performance recording official Google ↗
- Create Custom Administrative Views · help.tableau.com
- Collect Data with the Tableau Server Repository · help.salesforce.com
- Optimize for Extracts · help.tableau.com
- General Performance Guidelines · help.tableau.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Tableau Server repository administrative views background tasks for extracts performance of views query logs official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
Tableau Server identify duplicate workbooks views redundant charts database CPU query logs performance recording official OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |