Guide me through writing a custom incremental model in dbt that processes only changed rows in Databricks to save on compute credits.
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Guide me through writing a custom incremental model in dbt that processes only changed rows in Databricks to save on compute credits.
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.
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ChatGPT2 real searches · gpt-6
dbt Databricks incremental models unique_key incremental_strategy merge is_incremental documentation Google ↗
Databricks dbt incremental model liquid clustering optimize incremental strategy merge documentation Google ↗
- How to get the most out of running dbt on Databricks · databricks.com
- Databricks configurations · docs.getdbt.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
dbt Databricks incremental models unique_key incremental_strategy merge is_incremental documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Databricks dbt incremental model liquid clustering optimize incremental strategy merge documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |