MLEngineManageVersionOperator

Google

Operator for managing a Google Cloud ML Engine version.

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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

model_namestrThe name of the Google Cloud ML Engine model that the version belongs to. (templated)
version_namestrA name to use for the version being operated upon. If not None and the version argument is None or does not have a value for the name key, then this will be populated in the payload for the name key. (templated)
versiondictA dictionary containing the information about the version. If the operation is create, version should contain all the information about this version such as name, and deploymentUrl. If the operation is get or delete, the version parameter should contain the name of the version. If it is None, the only operation possible would be list. (templated)
operationstrThe operation to perform. Available operations are:create: Creates a new version in the model specified by model_name, in which case the version parameter should contain all the information to create that version (e.g. name, deploymentUrl).set_defaults: Sets a version in the model specified by model_name to be the default. The name of the version should be specified in the version parameter.list: Lists all available versions of the model specified by model_name.delete: Deletes the version specified in version parameter from the model specified by model_name). The name of the version should be specified in the version parameter.
project_idstrThe Google Cloud project name to which MLEngine model belongs. 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 managing a Google Cloud ML Engine version.

Warning

This operator is deprecated. Consider using operators for specific operations: MLEngineCreateVersionOperator, MLEngineSetDefaultVersionOperator, MLEngineListVersionsOperator, MLEngineDeleteVersionOperator.

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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