How it Works

The expect_table_column_count_to_equal_other_table test from the dbt-expectations package validates that two tables have the same number of columns. This is useful for ensuring that a transformed model retains the same schema width as a source or reference table, guarding against silent column additions or removals.

Steps and Conditions

1. Comparison Model: Specify the reference model using compare_model.

2. Execution: The column counts of both tables are retrieved and compared.

3. Outcome: Pass if the counts are equal; fail if they differ.

Example Usage: Staging Layer

A data team wants to ensure their stg_products model always has the same number of columns as the raw raw_products source, detecting any columns inadvertently added or dropped during transformation.

models:
  - name: stg_products
    tests:
      - dbt_expectations.expect_table_column_count_to_equal_other_table:
          compare_model: source('raw', 'products'

models:
  - name: stg_products
    tests:
      - dbt_expectations.expect_table_column_count_to_equal_other_table:
          compare_model: source('raw', 'products'

models:
  - name: stg_products
    tests:
      - dbt_expectations.expect_table_column_count_to_equal_other_table:
          compare_model: source('raw', 'products'

Any schema divergence between staging and source is caught before it propagates to downstream models.