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Data Modeling & Transformation Flashcards

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Read the first 7 Data Modeling & Transformation flashcards as text
  1. Which macro filters rows in an incremental model so only new data is processed on subsequent runs?

    Answer: {{ is_incremental() }}

    is_incremental() returns true when the model already exists, is configured incremental, and no full refresh is requested.

  2. In an incremental model's SQL, which relation does {{ this }} refer to?

    Answer: The currently building model's existing table in the warehouse

    {{ this }} resolves to the already-built relation of the model, used to find the max timestamp.

  3. What does running `dbt run --full-refresh` do to an incremental model?

    Answer: Drops and rebuilds it from scratch

    Full refresh rebuilds incremental models as if they did not exist, ignoring is_incremental() logic.

  4. Which config tells an incremental model how to match existing rows for updating?

    Answer: unique_key

    unique_key identifies rows to update or replace, depending on the incremental strategy.

  5. Which materialization creates no object in the warehouse and inlines the model as a CTE in downstream models?

    Answer: ephemeral

    Ephemeral models are interpolated as CTEs into dependent models and are not built.

  6. What does the on_schema_change config control for an incremental model?

    Answer: How new or removed columns in the source query are handled

    Options such as ignore, fail, append_new_columns, and sync_all_columns govern schema drift.

  7. Which is a typical drawback of using the view materialization for a heavily queried, complex model?

    Answer: It reruns the underlying query every time it is queried

    Views store only the query, so each downstream query pays the compute cost.

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