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How do I use query profiling to find inefficient joins that are inflating our monthly data warehouse bill during peak business hours

ChatGPTgpt-63 queries10/31/2026
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Fan-out diagram

The searches the AI actually ran for this prompt.

SEED QUERY
How do I use query profiling to find inefficient joins that are inflating our monthly data warehouse bill during peak business hours
3 real searches · 1 real-search pass
Snowflake query profile joins exploding rows partitions scanned bytes spilled official documentationGoogle ↗
OBSERVED
Google BigQuery query execution graph joins shuffle output rows official documentationGoogle ↗
OBSERVED
Databricks query profile join metrics shuffle spill official documentationGoogle ↗
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 3 queries…

Searches and sources

ChatGPT3 real searches · gpt-6
Snowflake query profile joins exploding rows partitions scanned bytes spilled official documentation Google ↗
Google BigQuery query execution graph joins shuffle output rows official documentation Google ↗
Databricks query profile join metrics shuffle spill official documentation Google ↗

Queries

3 queries · click a column to sort
Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
Snowflake query profile joins exploding rows partitions scanned bytes spilled official documentation
OBSERVED
Google ↗
AI Mode ↗
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of 1
Google BigQuery query execution graph joins shuffle output rows official documentation
OBSERVED
Google ↗
AI Mode ↗
————1x
of 1
Databricks query profile join metrics shuffle spill official documentation
OBSERVED
Google ↗
AI Mode ↗
————1x
of 1