About dbt run command

Overview

dbt run executes compiled sql model files against the current target database. dbt connects to the target database and runs the relevant SQL required to materialize all data models using the specified materialization strategies. Models are run in the order defined by the dependency graph generated during compilation. Intelligent multi-threading is used to minimize execution time without violating dependencies.

Deploying new models frequently involves destroying prior versions of these models. In these cases, dbt run minimizes the amount of time in which a model is unavailable by first building each model with a temporary name, then dropping the existing model, then renaming the model to its correct name. The drop and rename happen within a single database transaction for database adapters that support transactions.

Refresh incremental models

If you provide the --full-refresh flag to dbt run, dbt will treat incremental models as table models. This is useful when

1. The schema of an incremental model changes and you need to recreate it.
2. You want to reprocess the entirety of the incremental model because of new logic in the model code.

bash

dbt run --full-refresh

You can also supply the flag by its short name: dbt run -f.

In the dbt compilation context, this flag will be available as flags.FULL_REFRESH. Further, the is_incremental() macro will return false for all models in response when the --full-refresh flag is specified.

models/example.sql

select * from all_events

-- if the table already exists and `--full-refresh` is
-- not set, then only add new records. otherwise, select
-- all records.
{% if is_incremental() %}
   where collector_tstamp > (
     select coalesce(max(max_tstamp), '0001-01-01') from {{ this }}
   )
{% endif %}

Running specific models

dbt will also allow you select which specific models you'd like to materialize. This can be useful during special scenarios where you may prefer running a different set of models at various intervals. This can also be helpful when you may want to limit the tables materialized while you develop and test new models.

For more information, see the Model Selection Syntax Documentation.

For more information on running parents or children of specific models, see the Graph Operators Documentation.

Treat warnings as errors

See global configs

Failing fast

See global configs

Enable or Disable Colorized Logs

See global configs

Status codes

When calling the list_runs api, you will get a status code for each run returned. The available run status codes are as follows:

• Starting = 1
• Running = 3
• Success = 10
• Error = 20
• Canceled = 30
• Skipped = 40