One model per source table rule in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the 'One model per source table' rule mean in dbt?

It means creating one dbt model for each source table to keep transformations simple and organized.

beginner

Why is it helpful to have one model per source table?

It makes debugging easier, improves clarity, and helps track data lineage clearly.

intermediate

How does the 'One model per source table' rule affect complex transformations?

Complex transformations are built by layering simple models, each based on one source table, making the process easier to manage.

beginner

What is a common mistake when not following the 'One model per source table' rule?

Combining multiple source tables in one model can make the code hard to read and maintain.

intermediate

How does this rule help with testing in dbt?

Testing is simpler because each model corresponds to one source table, so tests can focus on one data set at a time.

What is the main benefit of having one model per source table in dbt?

A Reduces the number of models needed

B Simplifies debugging and improves clarity

C Combines all data into one place

D Avoids writing SQL code

Having one model per source table keeps transformations simple and makes debugging easier.

What happens if you combine multiple source tables in one dbt model?

A The code can become complex and hard to read

B It automatically improves performance

C The model becomes easier to maintain

D It reduces the need for testing

Combining multiple source tables in one model can make the code complex and harder to maintain.

How does the 'One model per source table' rule help with data lineage?

A It hides the source tables

B It makes data lineage unclear

C It clearly shows how data flows from source to model

D It removes the need for documentation

Each model corresponds to one source table, making it easy to track data lineage.

Which of these is a good practice when following the 'One model per source table' rule?

A Create one model that joins all source tables

B Write all transformations in one SQL file

C Avoid creating models for source tables

D Create separate models for each source table

Creating separate models for each source table keeps the project organized and easier to manage.

How does this rule affect testing in dbt?

A Testing can focus on one source table at a time

B Testing becomes more complicated

C Testing is not needed

D Testing must cover all tables together

Testing is simpler because each model corresponds to one source table, allowing focused tests.

Explain the 'One model per source table' rule and why it is important in dbt projects.

Think about how this rule helps keep your project clean and easy to understand.

Describe how following the 'One model per source table' rule impacts testing and maintenance.

Consider how simple models help you find and fix problems faster.

Practice

1. What is the main reason for following the one model per source table rule in dbt?

easy

A. To avoid using source tables in models

B. To combine multiple source tables into one model

C. To write fewer SQL queries

D. To keep models simple and easy to understand

Solution

1. Step 1: Understand the rule and its benefits

   The rule encourages creating one dbt model for each source table to keep things simple and clear. This approach helps with clarity, debugging, and teamwork by avoiding complex combined models.

2. Final Answer:

   To keep models simple and easy to understand -> Option D

3. Quick Check:

   One model per source table = simplicity [OK]

Hint: One model per source table means simpler, clearer models [OK]

Common Mistakes:

• Thinking it means combining tables into one model
• Believing it reduces the number of models
• Assuming it avoids using source tables

2. Which of the following is the correct way to define a dbt model for a source table named customers?

easy

A. Create a model file named all_data.sql combining all source tables

B. Create a model file named customers.sql with a SELECT from the source table

C. Create a model file named customers.sql but do not select from the source table

D. Create a model file named source_customers.sql without referencing the source

Solution

1. Step 1: Match model name to source table and reference it

   Following the rule, the model file should be named after the source table, here customers.sql. The model should select data from the source table to represent it clearly.

2. Final Answer:

   Create a model file named customers.sql with a SELECT from the source table -> Option B

3. Quick Check:

   Model name = source table name + SELECT from source [OK]

Hint: Model file name matches source table name and selects from it [OK]

Common Mistakes:

• Naming model file unrelated to source table
• Not selecting from the source table
• Combining multiple tables in one model

3. Given this dbt model SQL for source table orders:

select * from {{ source('sales_db', 'orders') }}

What will be the output if the source table has 100 rows?

medium

A. The model will return 100 rows identical to the source table

B. The model will return zero rows

C. The model will return 1 row with aggregated data

D. The model will cause a syntax error

Solution

1. Step 1: Understand the SQL query and predict output

   The query selects all columns and rows from the source table orders. Since it selects all rows without filtering, the output will have the same 100 rows as the source.

2. Final Answer:

   The model will return 100 rows identical to the source table -> Option A

3. Quick Check:

   Select * from source = same rows [OK]

Hint: Select * from source returns all rows unchanged [OK]

Common Mistakes:

• Thinking it returns zero rows
• Assuming aggregation happens automatically
• Expecting syntax errors from correct source() usage

4. You wrote this dbt model for source table products:

select * from source('inventory', 'products')

But dbt throws an error. What is the problem?

medium

A. Model file name does not match source table

B. Wrong source table name

C. Missing double curly braces around the source function

D. Using select * is not allowed

Solution

1. Step 1: Check dbt source function syntax and identify issue

   The source function must be wrapped in double curly braces: {{ source(...) }}. The model uses source(...) without {{ }}, causing a syntax error.

2. Final Answer:

   Missing double curly braces around the source function -> Option C

3. Quick Check:

   dbt functions need {{ }} [OK]

Hint: Always wrap dbt functions in {{ }} [OK]

Common Mistakes:

• Forgetting {{ }} around source()
• Assuming select * is disallowed
• Ignoring model file naming conventions

5. You have two source tables: customers and orders. According to the one model per source table rule, how should you organize your dbt models if you want to create a report showing total orders per customer?

hard

A. Create separate base models for customers and orders, then create a third model joining them for the report

B. Create one model combining both source tables directly without base models

C. Create a single model selecting from both source tables with UNION

D. Create only one model for orders and ignore customers

Solution

1. Step 1: Follow one model per source table for base models and build report model

   Create one model for customers and one for orders separately to keep base models simple. Create a third model that joins these base models to calculate total orders per customer, keeping transformations clear and modular.

2. Final Answer:

   Create separate base models for customers and orders, then create a third model joining them for the report -> Option A

3. Quick Check:

   Base models per source + separate report model [OK]

Hint: Base models per source, then join in separate model [OK]

Common Mistakes:

• Combining sources in one base model
• Skipping base models and joining sources directly
• Ignoring one source table