How it Works

The expect_table_row_count_to_be_between test from the dbt-expectations package validates that the total number of rows in a model, seed, or source falls within a defined minimum and maximum. This is a fundamental volume check to catch unexpected data loss or explosive data growth that could indicate pipeline issues.

Optional group_by and row_condition arguments allow more targeted checks within data subsets.

Steps and Conditions

1. Define Range: Set min_value and/or max_value for acceptable row counts.

2. Optional Config: Apply group_by and row_condition as needed.

3. Execution: The row count is computed and compared to the range.

4. Outcome: Pass if the count is within range; fail if it falls outside.

Example Usage: E-commerce

An e-commerce platform loads daily orders and expects between 5,000 and 50,000 rows per day under normal operating conditions.

models:
  - name: daily_orders
    tests:
      - dbt_expectations.expect_table_row_count_to_be_between:
          min_value: 5000
          max_value: 50000

models:
  - name: daily_orders
    tests:
      - dbt_expectations.expect_table_row_count_to_be_between:
          min_value: 5000
          max_value: 50000

models:
  - name: daily_orders
    tests:
      - dbt_expectations.expect_table_row_count_to_be_between:
          min_value: 5000
          max_value: 50000

A row count outside this range flags either a data load failure or an abnormal spike in orders requiring investigation.