Cross-team model sharing in dbt - Time & Space Complexity

Time Complexity: Cross-team model sharing

O(n)

Understanding Time Complexity

When teams share dbt models, it's important to know how the work grows as more models and teams join.

We want to see how the time to build or update models changes with more shared models.

Scenario Under Consideration

Analyze the time complexity of the following dbt model sharing setup.

-- models/team_a/model_a.sql
select * from source_table

-- models/team_b/model_b.sql
select * from {{ ref('model_a') }}

-- models/team_c/model_c.sql
select * from {{ ref('model_b') }}

This shows three teams sharing models where each model depends on the previous team's model.

Identify Repeating Operations

Look for repeated steps in building models across teams.

• Primary operation: Running each model's SQL query once per build.
• How many times: Once for each model in the dependency chain.

How Execution Grows With Input

As the number of shared models grows, the total work grows too.

Input Size (n models)	Approx. Operations (model runs)
3	3
10	10
100	100

Pattern observation: The total work grows directly with the number of models shared.

Final Time Complexity

Time Complexity: O(n)

This means the time to build all shared models grows in a straight line as more models are added.

Common Mistake

[X] Wrong: "Sharing models means the build time stays the same no matter how many models there are."

[OK] Correct: Each model still needs to run once, so more models mean more total work.

Interview Connect

Understanding how shared models affect build time helps you explain teamwork impact on data pipelines clearly and confidently.

Self-Check

What if models were built in parallel instead of one after another? How would the time complexity change?

Practice

1. What is the main benefit of using ref() in dbt for cross-team model sharing?

easy

A. It allows teams to write raw SQL without any dependencies.

B. It automatically creates new tables in the database without configuration.

C. It connects models from different teams to avoid duplication and ensure consistency.

D. It disables model version control to speed up development.

Solution

1. Step 1: Understand the purpose of ref() in dbt

   ref() is used to reference other models, enabling dependency tracking and collaboration.

2. Step 2: Identify the benefit in cross-team sharing

   By using ref(), teams avoid duplicating models and keep data consistent across projects.

3. Final Answer:

   It connects models from different teams to avoid duplication and ensure consistency. -> Option C

4. Quick Check:

   Cross-team sharing = ref() connects models [OK]

Hint: Remember: ref() links models to share work [OK]

Common Mistakes:

• Thinking ref() creates tables automatically
• Believing ref() removes dependencies
• Confusing ref() with raw SQL execution

2. Which of the following is the correct syntax to reference a model named sales_summary in dbt?

easy

A. select * from ref('sales_summary')

B. select * from {{ ref('sales_summary') }}

C. select * from sales_summary

D. select * from {{ sales_summary }}

Solution

1. Step 1: Recall dbt syntax for referencing models

   dbt uses Jinja templating with double curly braces and ref() to reference models.

2. Step 2: Identify correct syntax

   The correct syntax is select * from {{ ref('model_name') }} to properly resolve the model.

3. Final Answer:

   select * from {{ ref('sales_summary') }} -> Option B

4. Quick Check:

   Use {{ ref('model') }} for model references [OK]

Hint: Use double curly braces with ref() for model references [OK]

Common Mistakes:

• Omitting curly braces around ref()
• Using ref() without quotes
• Trying to reference model without ref()

3. Given two teams with models team_a.orders and team_b.customers, what will be the result of this dbt model SQL?

select o.order_id, c.customer_name
from {{ ref('orders') }} o
join {{ ref('customers') }} c on o.customer_id = c.customer_id

medium

A. A joined table of orders and customers combining data from both teams.

B. An error because ref() cannot reference models from other teams.

C. A table with only orders data, ignoring customers.

D. A table with only customers data, ignoring orders.

Solution

1. Step 1: Understand ref() cross-team referencing

   ref() allows referencing models across teams if they are in the same dbt project or properly configured.

2. Step 2: Analyze the SQL query

   The query joins orders and customers on customer_id, combining data from both models.

3. Final Answer:

   A joined table of orders and customers combining data from both teams. -> Option A

4. Quick Check:

   ref() joins models across teams = combined data [OK]

Hint: ref() joins models across teams if configured [OK]

Common Mistakes:

• Assuming ref() cannot cross teams
• Expecting only one model's data returned
• Ignoring join condition effect

4. You wrote this dbt model to share data across teams:

select * from {{ ref('team_a.orders') }}

But it fails with an error. What is the likely cause?

medium

A. You cannot use dot notation inside ref(); only model names are allowed.

B. The model team_a.orders does not exist in the project.

C. You forgot to wrap ref() in double curly braces.

D. You need to use source() instead of ref() for cross-team models.

Solution

1. Step 1: Check ref() usage rules

   ref() accepts only model names without schema or dot notation.

2. Step 2: Identify error cause

   Using team_a.orders inside ref() causes syntax error; correct usage is just orders.

3. Final Answer:

   You cannot use dot notation inside ref(); only model names are allowed. -> Option A

4. Quick Check:

   ref() = model name only, no dots [OK]

Hint: Use only model names inside ref(), no dots [OK]

Common Mistakes:

• Using schema or team prefix inside ref()
• Confusing ref() with source()
• Missing curly braces around ref()

5. Your company has two teams: marketing and sales. Marketing built a model campaign_performance. Sales wants to use it in their model sales_analysis. How should sales correctly reference marketing's model in dbt to ensure cross-team sharing?

hard

A. Duplicate the campaign_performance SQL in sales_analysis to avoid dependencies.

B. Use select * from marketing.campaign_performance without ref().

C. Use select * from {{ source('marketing', 'campaign_performance') }}.

D. Use select * from {{ ref('campaign_performance') }} assuming both models are in the same dbt project.

Solution

1. Step 1: Understand dbt project structure for cross-team models

   If both teams' models are in the same dbt project, ref() can reference models across folders or teams by model name.

2. Step 2: Choose correct referencing method

   Using ref('campaign_performance') is the correct way to share models and track dependencies.

3. Final Answer:

   Use select * from {{ ref('campaign_performance') }} assuming both models are in the same dbt project. -> Option D

4. Quick Check:

   Cross-team sharing = ref() within same project [OK]

Hint: Use ref() with model name for cross-team sharing in same project [OK]

Common Mistakes:

• Using raw schema.table without ref()
• Duplicating SQL instead of referencing
• Using source() incorrectly for models