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https://issues.apache.org/jira/browse/AIRFLOW-1774?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16433662#comment-16433662
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ASF subversion and git services commented on AIRFLOW-1774:
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Commit 65e7025f3af378dfa825eb04d005ec1f7a422cde in incubator-airflow's branch 
refs/heads/master from [~wileeam]
[ https://git-wip-us.apache.org/repos/asf?p=incubator-airflow.git;h=65e7025 ]

[AIRFLOW-1774] Allow consistent templating of arguments in 
MLEngineBatchPredictionOperator

Fix a minor typo and a wrong non-default
assignment

Fix one more typo

Adapt tests to new error messages and fix another
typo

Fix exception type in utils operator test class

Improve cleansing of non-valid training and
prediciton job names

Closes #2746 from wileeam/ml-engine-prediction-
job-normalization


> Better handling of templated parameters in Google ML batch 
> prediction/training operators
> ----------------------------------------------------------------------------------------
>
>                 Key: AIRFLOW-1774
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-1774
>             Project: Apache Airflow
>          Issue Type: Improvement
>          Components: contrib, operators
>    Affects Versions: Airflow 2.0, 1.9.0
>            Reporter: Guillermo Rodríguez Cano
>            Assignee: Guillermo Rodríguez Cano
>            Priority: Major
>
> The {{MLEngineBatchPredictionOperator}} does not support well the templated 
> parameter {{job_id}} due to a helper function used to detect and cleanup bad 
> job names inhibiting the templating engine to work. I suspect the same may 
> happen with {{MLEngineTrainingOperator}} as well.
> Google ML requieres a unique job id, therefore it is critical to have the 
> possibility to customise the job's name easily, and preferably with some data 
> related to the DAG, for example, appending the day to the job's name via a 
> macro like {{ds}}



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