Invocation modes#

Added in version 1.4.

For ExecutionMode.LOCAL execution mode, Cosmos supports two invocation modes for running dbt:

  1. InvocationMode.SUBPROCESS: In this mode, Cosmos runs dbt cli commands using the Python subprocess module and parses the output to capture logs and to raise exceptions.

  2. InvocationMode.DBT_RUNNER: In this mode, Cosmos uses the dbtRunner available for dbt programmatic invocations to run dbt commands. In order to use this mode, dbt must be installed in the same local environment. This mode does not have the overhead of spawning new subprocesses or parsing the output of dbt commands and is faster than InvocationMode.SUBPROCESS. It is up to the user to resolve Apache Airflow® and dbt dependencies conflicts when using this mode.

Note

When InvocationMode.DBT_RUNNER is used with ExecutionMode.LOCAL, Cosmos automatically appends --no-static-parser to every dbt command it invokes during task execution. Cosmos copies the dbt project into a temporary directory at both DAG parse time and task execution time, and the differing temp paths can interfere with dbt’s static parser and cause task hangs. Disabling the static parser is a workaround for this interaction. If you rely on dbt’s static parser, use InvocationMode.SUBPROCESS instead. See #1751 and #1760 for the investigation that led to this workaround.

The invocation mode can be set in the ExecutionConfig as shown below:

from cosmos.constants import InvocationMode

dag = DbtDag(
    # ...
    execution_config=ExecutionConfig(
        execution_mode=ExecutionMode.LOCAL,
        invocation_mode=InvocationMode.DBT_RUNNER,
    ),
)

If the invocation mode is not set, Cosmos will attempt to use InvocationMode.DBT_RUNNER if dbt is installed in the same environment as the worker, otherwise it will fall back to InvocationMode.SUBPROCESS.