snow dbt execute commands¶

The snow dbt execute command executes one of the following dbt commands (https://docs.getdbt.com/reference/dbt-commands) on Snowflake:

• build (https://docs.getdbt.com/reference/commands/build)
• clean (https://docs.getdbt.com/reference/commands/clean)
• compile (https://docs.getdbt.com/reference/commands/compile)
• deps (https://docs.getdbt.com/reference/commands/deps)
• list (https://docs.getdbt.com/reference/commands/list)
• parse (https://docs.getdbt.com/reference/commands/parse)
• retry (https://docs.getdbt.com/reference/commands/retry)
• run (https://docs.getdbt.com/reference/commands/run)
• run-operation (https://docs.getdbt.com/reference/commands/run-operation)
• seed (https://docs.getdbt.com/reference/commands/seed)
• show (https://docs.getdbt.com/reference/commands/show)
• snapshot (https://docs.getdbt.com/reference/commands/snapshot)
• source freshness (https://docs.getdbt.com/reference/commands/source)
• test (https://docs.getdbt.com/reference/commands/test)

For more information about using dbt commands, see the dbt Command reference (https://docs.getdbt.com/reference/dbt-commands).

Examples¶

The following examples show how to invoke snow dbt execute. The NAME argument identifies the dbt project object you want to run.

• Execute the build dbt command using a fully qualified object name:

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  snow dbt execute uche_db.public.my_dbt_project build
  

• Execute the test dbt command, select a specific model subset, and override the dbt version for this run:

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  snow dbt execute --dbt-version '1.11.11' my_dbt_project test --select my_model+
  

• Execute the run dbt command with inline environment variable overrides for this run:

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  snow dbt execute --env-vars '{"DBT_DATABASE": "tasty_bytes_db", "DBT_SCHEMA": "analytics"}' \
    my_dbt_project run
  

• Execute the run dbt command, pulling DBT_-prefixed variables (excluding DBT_ENV_SECRET_* variables) from your shell environment:

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  snow dbt execute --use-shell-env-vars my_dbt_project run
  

  --env-vars applies inline DBT_-prefixed overrides for a single execution, and --use-shell-env-vars pulls DBT_-prefixed shell variables into the run (excluding DBT_ENV_SECRET_* variables). To select an environment defined in the project’s env.yml file, add the --env flag. These flags require Snowflake CLI 3.21 or later. For more information, see Using SQL environment variables and private Git packages for dbt Projects on Snowflake.

• Run without writing generated target and log files back to the live version:

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  snow dbt execute --no-writeback my_dbt_project run --target dev
  

  Place --writeback or --no-writeback before the dbt command. If you omit the option, the execution uses the object’s DEFAULT_WRITEBACK setting. For concurrent executions of the same dbt project object, Snowflake recommends --no-writeback when target and log artifacts don’t need to persist to the live version. Using --no-writeback avoids conflicts during concurrent executions by preventing writes to overlapping target and log directories. If writeback is required, use distinct, non-overlapping target and log directories for each execution. Snowflake continues to store per-query result artifacts regardless of the setting. For examples, see Run a dbt project object concurrently.

• Run only models that changed since the last successful production execution, along with their downstream dependencies:

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  snow dbt execute \
    --import "SYSTEM\$DBT_GET_LAST_SUCCESSFUL_RUN_TARGET('prod_db.analytics.production_dbt_project') as state" \
    my_dbt_project \
    run --state ./imports/state --defer --select state:modified+
  

  SYSTEM$DBT_GET_LAST_SUCCESSFUL_RUN_TARGET returns the manifest.json and run_results.json from most recent successful execution in the results folder of the production dbt project object. The state alias mounts it under ./imports/state, which is the path passed to dbt with --state. For prerequisites and a complete Slim CI workflow, see Use dbt artifacts for Slim CI and defer to production.

  Repeat --import to mount files from multiple locations. Each alias determines the directory name under ./imports. Imports make files available only to that execution. They don’t permanently copy the files into the dbt project object’s live version. To copy files into or out of the live version, use snow dbt copy.

For more examples and workflow guidance, see Managing dbt Projects on Snowflake using Snowflake CLI.