Model naming conventions in dbt - Time & Space Complexity

Time Complexity: Model naming conventions

O(n)

Understanding Time Complexity

We want to understand how the time it takes to run dbt models changes as the number of models grows.

Specifically, how does naming models affect the process of selecting and running them?

Scenario Under Consideration

Analyze the time complexity of the following dbt model selection snippet.

-- Select models with a specific prefix
models:
  +materialized: table
  +tags: [finance]

select * from {{ ref('finance_revenue') }}
select * from {{ ref('finance_expenses') }}
select * from {{ ref('marketing_campaigns') }}

This snippet shows selecting models by name prefixes and tags to run specific models.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Searching through the list of model names to find matches by prefix or tag.
• How many times: Once for each model in the project during selection.

How Execution Grows With Input

As the number of models increases, the time to check each model's name or tag grows linearly.

Input Size (n)	Approx. Operations
10	10 checks
100	100 checks
1000	1000 checks

Pattern observation: The number of operations grows directly with the number of models.

Final Time Complexity

Time Complexity: O(n)

This means the time to select models grows in direct proportion to how many models there are.

Common Mistake

[X] Wrong: "Naming models with prefixes makes selection instant regardless of project size."

[OK] Correct: Even with prefixes, dbt still checks each model name once, so time grows with the number of models.

Interview Connect

Understanding how naming affects model selection time helps you design scalable dbt projects and shows you think about efficiency in real work.

Self-Check

"What if we indexed model names in a dictionary for selection? How would the time complexity change?"

Practice

1. Which of the following is the best practice for naming a dbt model?

easy

A. Use clear, lowercase names with underscores to separate words

B. Use uppercase letters and spaces between words

C. Use special characters like # or $ in the name

D. Use very long names without any separators

Solution

1. Step 1: Understand dbt naming conventions

   dbt recommends using clear, lowercase names with underscores to separate words for readability and consistency.

2. Step 2: Evaluate each option

   Use clear, lowercase names with underscores to separate words follows the recommended style. Options A, B, and D do not follow best practices.

3. Final Answer:

   Use clear, lowercase names with underscores to separate words -> Option A

4. Quick Check:

   Clear lowercase with underscores = C [OK]

Hint: Choose lowercase with underscores for clarity [OK]

Common Mistakes:

• Using uppercase letters in model names
• Including spaces or special characters
• Using inconsistent naming styles

2. Which of these is a valid dbt model name?

easy

A. customer_orders

B. SalesReport2023

C. Inventory-List

D. Profit$Summary

Solution

1. Step 1: Check naming rules for dbt models

   Model names should be lowercase and use underscores to separate words, avoiding special characters and uppercase letters.

2. Step 2: Analyze each option

   customer_orders uses lowercase letters and underscores only, making it valid. Options B, C, and D contain uppercase letters or special characters.

3. Final Answer:

   customer_orders -> Option A

4. Quick Check:

   Lowercase with underscores = A [OK]

Hint: Pick lowercase with underscores, no special chars [OK]

Common Mistakes:

• Using uppercase letters in model names
• Including hyphens or special characters
• Starting names with numbers

3. Given the following dbt model names, which one best describes a model that summarizes monthly sales data?
monthly_sales_summary
salesMonthlySummary
monthly-sales-summary
MonthlySalesSummary

medium

A. MonthlySalesSummary

B. salesMonthlySummary

C. monthly-sales-summary

D. monthly_sales_summary

Solution

1. Step 1: Identify the best naming style for dbt models

   dbt prefers lowercase names with underscores to separate words for clarity and consistency.

2. Step 2: Compare each model name

   monthly_sales_summary uses lowercase with underscores and clearly describes the model. Options A and B use camel case or uppercase letters, and C uses hyphens, which are not recommended.

3. Final Answer:

   monthly_sales_summary -> Option D

4. Quick Check:

   Lowercase with underscores = D [OK]

Hint: Look for lowercase with underscores describing content [OK]

Common Mistakes:

• Using camelCase or PascalCase
• Using hyphens instead of underscores
• Ignoring clarity in names

4. You have a dbt model named CustomerOrders. What is the issue with this name and how can you fix it?

medium

A. It uses underscores incorrectly; rename to customerorders

B. It uses uppercase letters; rename to customer_orders

C. It is too short; rename to customer_orders_summary

D. It uses special characters; rename to customer-orders

Solution

1. Step 1: Identify naming convention violation

   The model name uses uppercase letters, which is against dbt's lowercase naming convention.

2. Step 2: Apply correct naming style

   Rename the model to lowercase letters with underscores: customer_orders.

3. Final Answer:

   It uses uppercase letters; rename to customer_orders -> Option B

4. Quick Check:

   Uppercase letters not allowed = A [OK]

Hint: Rename uppercase to lowercase with underscores [OK]

Common Mistakes:

• Ignoring uppercase letters in names
• Removing underscores instead of fixing case
• Adding unnecessary special characters

5. You want to create a dbt model that calculates the total revenue per product category for the last year. Which model name follows best practices and clearly describes the model's purpose?

hard

A. totalRevenuePerCategoryLastYear

B. Total_Revenue_Per_Category_Last_Year

C. total_revenue_per_category_last_year

D. revenue-category-last-year

Solution

1. Step 1: Understand naming best practices

   dbt model names should be lowercase, use underscores, and clearly describe the model's content.

2. Step 2: Evaluate each option

   total_revenue_per_category_last_year uses lowercase letters and underscores, and clearly describes the model. Options A and C use uppercase or camel case, and D uses hyphens.

3. Final Answer:

   total_revenue_per_category_last_year -> Option C

4. Quick Check:

   Lowercase with underscores and clear description = B [OK]

Hint: Use lowercase with underscores and descriptive words [OK]

Common Mistakes:

• Using camelCase or PascalCase
• Using hyphens instead of underscores
• Using uppercase letters