MLEngineTrainingCancelJobOperator

Google

Operator for cleaning up failed MLEngine training job.

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Last Updated: Mar. 22, 2021

Access Instructions

Install the Google provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.

Parameters

job_idstrA unique templated id for the submitted Google MLEngine training job. (templated)
project_idstrThe Google Cloud project name within which MLEngine training job should run. If set to None or missing, the default project_id from the Google Cloud connection is used. (templated)
gcp_conn_idstrThe connection ID to use when fetching connection info.
delegate_tostrThe account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled.
impersonation_chainUnion[str, Sequence[str]]Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated).

Documentation

Operator for cleaning up failed MLEngine training job.

Example DAGs

Improve this module by creating an example DAG.

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  1. Add an `example_dags` directory to the top-level source of the provider package with an empty `__init__.py` file.
  2. Add your DAG to this directory. Be sure to include a well-written and descriptive docstring
  3. Create a pull request against the source code. Once the package gets released, your DAG will show up on the Registry.

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