Real ChatGPT answer · index seedkJBet1y3DOscompleteB2B software · data and analytics platformsinformational
How do I analyze my team's Snowflake query history to identify the top three users or dashboards responsible for our runaway compute costs?
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The searches the AI actually ran for this prompt.
SEED QUERY
How do I analyze my team's Snowflake query history to identify the top three users or dashboards responsible for our runaway compute costs?
1 real search · 1 real-search pass
Snowflake ACCOUNT_USAGE QUERY_HISTORY documentation execution time bytes scanned query_tag warehouse metering history cost attributionGoogle ↗
OBSERVED
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.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
Snowflake ACCOUNT_USAGE QUERY_HISTORY documentation execution time bytes scanned query_tag warehouse metering history cost attribution Google ↗
- QUERY_ATTRIBUTION_HISTORY view · docs.snowflake.com
- Attributing cost · docs.snowflake.com
- QUERY_METERING_HISTORY view · docs.snowflake.com
- QUERY_HISTORY view · docs.snowflake.com