Loading CSV seeds in dbt - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of seed loading with incremental model

Given a dbt seed file products.csv with 3 rows, and an incremental model that selects all rows from this seed, what will be the number of rows in the model after two runs if the seed file is unchanged?

dbt

models/incremental_products.sql

{{ config(materialized='incremental', unique_key='product_id') }}

select * from {{ ref('products') }}

A 3 rows

B 6 rows

C 0 rows

D Error due to duplicate keys

💡 Hint

Think about how incremental models handle existing rows with the same unique key.

Incremental models add new rows or update existing rows based on the unique key. Since the seed file is unchanged, no new rows are added, so the model remains with 3 rows.

❓ data_output

intermediate

Data output after loading a CSV seed with transformations

You have a seed CSV file sales.csv with columns date, amount. You create a dbt model that loads this seed and adds a new column amount_taxed which is amount * 1.1. What is the output table if the seed has rows:

date,amount
2024-01-01,100
2024-01-02,200

dbt

select date, amount, amount * 1.1 as amount_taxed from {{ ref('sales') }}

A [{'date': '2024-01-01', 'amount': 100, 'amount_taxed': 110.0}, {'date': '2024-01-02', 'amount': 200, 'amount_taxed': 220.0}]

B [{'date': '2024-01-01', 'amount': 100, 'amount_taxed': 100.0}, {'date': '2024-01-02', 'amount': 200, 'amount_taxed': 200.0}]

C [{'date': '2024-01-01', 'amount': 110, 'amount_taxed': 110.0}, {'date': '2024-01-02', 'amount': 220, 'amount_taxed': 220.0}]

D [{'date': '2024-01-01', 'amount': 100, 'amount_taxed': null}, {'date': '2024-01-02', 'amount': 200, 'amount_taxed': null}]

💡 Hint

Remember to multiply the amount by 1.1 to get amount_taxed.

The amount_taxed column is calculated by multiplying amount by 1.1, so 100 becomes 110.0 and 200 becomes 220.0.

🔧 Debug

advanced

Identify the error when loading a CSV seed with invalid config

Consider this dbt seed configuration in dbt_project.yml:

seeds:
  my_project:
    sales:
      file: sales_data.csv
      delimiter: ';'
      header: false

What error will occur when running dbt seed?

A Error: The seed file 'sales_data.csv' is missing header row but 'header' is set to false, causing parsing failure.

B Error: Delimiter ';' is not supported by dbt seed.

C No error, seed loads successfully with semicolon delimiter and no header.

D Error: Invalid config key 'file' in seed configuration.

💡 Hint

Check the valid configuration keys for seeds in dbt.

The 'file' key is not a valid configuration option for seeds in dbt. The seed filename is determined by the CSV file name in the seeds folder, not by config.

🧠 Conceptual

advanced

Understanding seed freshness and reload behavior

When you run dbt seed multiple times without changing the CSV file, what happens to the data in the database table created by the seed?

A The seed command does nothing if the CSV file is unchanged.

B The table is dropped and recreated each time, so data is replaced with the CSV content.

C New rows are appended to the existing table, causing duplicates.

D The table is updated only if the CSV file has a newer timestamp.

💡 Hint

Think about how dbt seed manages the target table on each run.

dbt seed drops and recreates the table on each run, so the data always matches the CSV file exactly, replacing any existing data.

🚀 Application

expert

Predict the output of a seed with mixed data types and nulls

You have a seed CSV users.csv with columns id, name, age:

id,name,age
1,Alice,30
2,Bob,
3,Charlie,25

You load this seed in dbt and run a model that selects all rows where age > 25. What rows will the model return?

dbt

select * from {{ ref('users') }} where age > 25

A [{'id': 1, 'name': 'Alice', 'age': 30}, {'id': 2, 'name': 'Bob', 'age': null}]

B [{'id': 1, 'name': 'Alice', 'age': 30}, {'id': 3, 'name': 'Charlie', 'age': 25}]

C [{'id': 1, 'name': 'Alice', 'age': 30}]

D []

💡 Hint

Remember that null values do not satisfy comparison operators like >.

Only Alice has age 30 which is greater than 25. Bob's age is null and does not satisfy the condition. Charlie's age is 25, which is not greater than 25.