Model dependencies and parallelism in dbt - Step-by-Step Execution

Concept Flow - Model dependencies and parallelism

Start: Define models

↓

Identify dependencies

↓

Build dependency graph

↓

Find models with no dependencies

↓

Run independent models in parallel

↓

Wait for dependent models

↓

Run dependent models

↓

Repeat until all models built

↓

End: All models built

This flow shows how dbt finds which models depend on others, then runs independent models at the same time, waiting to run dependent models after their dependencies finish.

Execution Sample

dbt

models:
  - name: customers
    depends_on: []
  - name: orders
    depends_on: [customers]
  - name: order_items
    depends_on: [orders]
  - name: products
    depends_on: []

Defines four models with dependencies: 'orders' depends on 'customers', 'order_items' depends on 'orders', 'products' has no dependencies.

Execution Table

Step	Action	Models Run	Dependencies Met?	Parallelism	Notes
1	Identify models with no dependencies	customers, products	Yes	Run both in parallel	Start with independent models
2	Wait for customers and products to finish	customers, products	Yes	Waiting	Dependent models wait
3	Run orders (depends on customers)	orders	customers done	Single run	Orders can run now
4	Wait for orders to finish	orders	Yes	Waiting	order_items waits
5	Run order_items (depends on orders)	order_items	orders done	Single run	Final dependent model
6	All models built	-	-	-	Process complete

💡 All models have been run respecting dependencies and maximizing parallelism.

Variable Tracker

Variable	Start	After Step 1	After Step 3	After Step 5	Final
customers_status	not run	running	done	done	done
products_status	not run	running	done	done	done
orders_status	not run	not run	running	done	done
order_items_status	not run	not run	not run	running	done

Key Moments - 3 Insights

Why can 'customers' and 'products' run at the same time?

Because they have no dependencies, as shown in execution_table step 1, they can run in parallel safely.

Why must 'orders' wait until 'customers' finishes?

Orders depend on customers, so orders can only run after customers are done, as shown in step 3 where dependencies are met.

What happens if a model has multiple dependencies?

It waits until all dependencies are done before running, ensuring data correctness, similar to how 'order_items' waits for 'orders' in step 5.

Visual Quiz - 3 Questions

Look at the execution table, which models run in parallel at step 1?

A customers and products

B orders and order_items

C orders only

D order_items only

💡 Hint

Check the 'Models Run' and 'Parallelism' columns in step 1 of the execution_table.

At which step does 'orders' start running?

A Step 5

B Step 1

C Step 3

D Step 2

💡 Hint

Look at the 'Action' and 'Models Run' columns in the execution_table to find when 'orders' runs.

If 'products' depended on 'customers', how would step 1 change?

A 'orders' would run at step 1

B Only 'customers' would run at step 1

C 'products' would run before 'customers'

D No models would run at step 1

💡 Hint

Consider dependencies and which models have none at step 1 in the execution_table.

Concept Snapshot

dbt runs models respecting dependencies.
Models with no dependencies run in parallel.
Dependent models wait until their dependencies finish.
This speeds up builds and keeps data correct.
Define dependencies clearly to maximize parallelism.

Full Transcript

In dbt, models can depend on other models. The system builds a graph of these dependencies. Models without dependencies run first and can run at the same time, or in parallel. Models that depend on others wait until those finish. This process repeats until all models are built. For example, 'customers' and 'products' run together because they have no dependencies. 'orders' waits for 'customers' to finish. 'order_items' waits for 'orders'. This approach speeds up the build while ensuring data is ready when needed.