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docs/integrations/data-ingestion/etl-tools/dbt/materialization-materialized-view.md

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@@ -316,7 +316,6 @@ WHERE database = 'your_schema'
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AND engine = 'MaterializedView'
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```
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#### Check if dbt recognizes a table as an MV target {#check-dbt-recognition}
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During a dbt run, look for this log message:
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| Next dbt run | **Individual resources cannot be managed, all happen together:**<br /><br />**target table**: <br /> changes managed with the `on_schema_change` setting. By default it has the setting `ignore` so new columns are not processed.<br /><br />**MVs**: all updated with `alter table modify query` operations | **Changes can be applied individually:<br /><br />target table**: <br />automatic detection to know if they are target tables from dbt defined MVs. If they are, the columns evolution is managed by default with the `mv_on_schema_change` setting with `fail` value so it will fail if columns changes. We added this default value as a protection layer<br /><br />**MVs**: Their SQL gets updated with `alter table modify query` operations. |
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| dbt run --full-refresh | **Individual resources cannot be managed, all happen together:<br /><br />target table**: <br />target table recreated empty. `catchup` available to configure a backfill with the SQL of all the MVs together. `catchup` is `True` by default<br /><br />**MVs**: all get recreated. | **Changes will be applied individually:<br /><br />target table:** will be recreated as usual.<br /><br />**MVs**: drop and recreate. `catchup` available for an initial backfill. `catchup` is `True` by default. <br /><br />**Note: During the process, the target table will be empty or partially loaded until the MVs are recreated. To avoid this, check the next section about how to iterate the target table.**|
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### Behavior during active ingestion {#behavior-during-active-ingestion}
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When iterating your models, you need to be aware of how the different operations interact with the data being inserted:

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