Why project structure scales with team size in dbt - Performance Analysis
When many people work on a dbt project, the way the project is organized affects how fast and smoothly work gets done.
We want to understand how adding more team members changes the work involved in managing the project structure.
Analyze the time complexity of the following dbt project structure setup.
# dbt_project.yml
name: my_project
version: '1.0'
models:
my_project:
+materialized: view
staging:
+schema: staging
marts:
+schema: marts
sales:
+tags: ['sales_team']
marketing:
+tags: ['marketing_team']
This code organizes models into folders and schemas to separate work for different teams.
- Primary operation: Managing and updating model folders and configurations as team size grows.
- How many times: Once per team or sub-team added, the project structure expands to include new folders and settings.
As the number of team members (or sub-teams) increases, the project structure grows to keep work organized.
| Team Size (n) | Approx. Structure Units |
|---|---|
| 1 | 1 main folder with few subfolders |
| 5 | 5 folders or schemas to separate work |
| 20 | 20 or more folders and configurations to manage |
Pattern observation: The project structure grows roughly in proportion to the number of teams to keep work clear and avoid conflicts.
Time Complexity: O(n)
This means the effort to manage project structure grows linearly as the team size increases.
[X] Wrong: "Adding more team members doesn't affect project structure complexity much."
[OK] Correct: More people mean more parts to organize, so the structure must grow to keep things clear and avoid confusion.
Understanding how project structure scales with team size shows you can plan for teamwork and keep projects manageable as they grow.
"What if we used one big folder for all teams instead of separate folders? How would the time complexity change?"