Run multiple models

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Run

1. Under the data loader block you just added, click the button dbt model, then click the option All models.
2. In the dbt project name input field, enter the name of the dbt project that contains the models you want to build and run (e.g. demo).
3. In the dbt profile target input field, enter the name of the dbt connection profile (e.g. dev) that you want to use when running the selected dbt models.
4. In the text area of the code block, write the models you want to select or exclude using dbt’s --select and --exclude flags and syntax. For more information on the --select and --exclude syntax, read dbt’s documentation. For example:
   --select

   --exclude

   Copy

   $ dbt run --select my_dbt_project_name   # runs all models in your project
   $ dbt run --select my_dbt_model          # runs a specific model
   $ dbt run --select path.to.my.models     # runs all models in a specific directory
   $ dbt run --select my_package.some_model # run a specific model in a specific package
   $ dbt run --select tag:nightly           # run models with the "nightly" tag
   $ dbt run --select path/to/models        # run models contained in path/to/models
   $ dbt run --select path/to/my_model.sql  # run a specific model by its path
   

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Variables

# other optional dbt command line arguments

--vars '{"key": "value"}'

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Interpolate values

1. Upstream block output
2. Variables
   1. Global variables
   2. Pipeline variables
   3. Runtime variables
3. Environment variables

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Upstream block output

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block_uuid

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parse

• data If the block_uuid argument isn’t present, then the 1st argument in the lambda function is a list of objects. The list of objects contain the data from an upstream block’s output. The positional order of the data in the list corresponds to the current block’s upstream blocks order. For example, if the current block has the following upstream blocks with the following output:
  1. load_api_data: [1, 2, 3]
  2. load_users_data: { 'mage': 'powerful' }
  Then the 1st argument in the lambda function will be the following list:
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  [
      [1, 2, 3],
      { 'mage': 'powerful' },
  ]
  

  Optional	❌
  Type	If block_uuid argument is present, then the type depends on the output from that block. If block_uuid isn’t present, then the type is list.
  Example	{ 'mage': 'powerful' }

• variables A dictionary containing pipeline variables and runtime variables.

  Optional	❌
  Type	dict
  Example	{ 'fire': 40 }

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Example

--select models/{{ block_output('data_loader_block') }}.sql

--select models/{{ block_output('data_loader_block', parse=lambda data, variables: data['runtime'] * variables['tries']) }}.sql

--vars '{"user_id": "{{ block_output('load_recent_user', parse=lambda user, _variables: user['id']) }}"}'

--select models/{{ block_output() }}.sql

--select models/{{ block_output(parse=lambda outputs, variables: outputs[1]['runtime'] * variables['tries']) }}.sql

--vars '{"user_id": "{{ block_output(parse=lambda outputs, _variables: outputs[0]['id']) }}"}'

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Variables

1. Global variables
2. Pipeline variables
3. Runtime variables

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Example

--select models/{{ variables('some_var_name') }}.sql

--vars '{"mage": "{{ variables('power') }}"}'

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Environment variables

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Example

--select models/{{ env_var('some_environment_variable_name') }}.sql

--vars '{"environment": "{{ env_var('ENV') }}"}'