Real ChatGPT answer · index seed86NrxVA3ZeQcompleteB2B software · data and analytics platformscommercial
What are the main performance bottlenecks people experience when running heavy Looker queries against large BigQuery datasets, and how do you fix them?
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The searches the AI actually ran for this prompt.
SEED QUERY
What are the main performance bottlenecks people experience when running heavy Looker queries against large BigQuery datasets, and how do you fix them?
2 real searches · 1 real-search pass
Google BigQuery query performance best practices partitioning clustering materialized views query plan slots Looker persistent derived tablesGoogle ↗
OBSERVED
Looker BigQuery performance optimization symmetric aggregates fanout joins aggregate awareness persistent derived tables cachingGoogle ↗
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 2 queries…
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ChatGPT2 real searches · gpt-6
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Google BigQuery query performance best practices partitioning clustering materialized views query plan slots Looker persistent derived tables OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Looker BigQuery performance optimization symmetric aggregates fanout joins aggregate awareness persistent derived tables caching OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |