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https://issues.apache.org/jira/browse/AIRFLOW-245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15339888#comment-15339888
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Jeremiah Lowin commented on AIRFLOW-245:
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I also posted this on PR 1596 but perhaps it's more relevant here:
Something important to keep in mind -- the current version of execute_async()
just requires the task key (a bunch of strings) and the command that runs the
task (another string, something like airflow run task). That's because we make
no assumptions about how the execution is implemented, or on what
machine/environment, or even when it will be run. Passing a task object to the
execute_async() method is contrary to that assumption. In particular, there is
no guarantee that task objects are serializable.
The key should give enough information to load the task inside the executor by
querying the database for the matching taskinstance -- I think that would be
the far preferable way to implement the desired behavior in a custom executor.
> Access to task instance from custom Executor
> --------------------------------------------
>
> Key: AIRFLOW-245
> URL: https://issues.apache.org/jira/browse/AIRFLOW-245
> Project: Apache Airflow
> Issue Type: Improvement
> Components: executor
> Reporter: Alexandr Nikitin
>
> I'm writing a custom executor that executes tasks on mesos and I want to have
> access to task instances from it. So that I can reuse all existing operators
> e.g. DockerOperator and access its fields like image, command, volumes and
> transform them to mesos.
> This can be done by changing `def execute_async(self, key, command,
> queue=None):` in `BaseExecutor`.
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