| :py:mod:`airflow.providers.google.cloud.triggers.dataproc` |
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| .. py:module:: airflow.providers.google.cloud.triggers.dataproc |
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| .. autoapi-nested-parse:: |
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| This module contains Google Dataproc triggers. |
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| Module Contents |
| --------------- |
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| Classes |
| ~~~~~~~ |
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| .. autoapisummary:: |
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| airflow.providers.google.cloud.triggers.dataproc.DataprocBaseTrigger |
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| .. py:class:: DataprocBaseTrigger(job_id, region, project_id = None, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, delegate_to = None, polling_interval_seconds = 30) |
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| Bases: :py:obj:`airflow.triggers.base.BaseTrigger` |
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| Trigger that periodically polls information from Dataproc API to verify job status. |
| Implementation leverages asynchronous transport. |
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| .. py:method:: serialize() |
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| Returns the information needed to reconstruct this Trigger. |
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| :return: Tuple of (class path, keyword arguments needed to re-instantiate). |
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| .. py:method:: run() |
| :async: |
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| Runs the trigger in an asynchronous context. |
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| The trigger should yield an Event whenever it wants to fire off |
| an event, and return None if it is finished. Single-event triggers |
| should thus yield and then immediately return. |
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| If it yields, it is likely that it will be resumed very quickly, |
| but it may not be (e.g. if the workload is being moved to another |
| triggerer process, or a multi-event trigger was being used for a |
| single-event task defer). |
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| In either case, Trigger classes should assume they will be persisted, |
| and then rely on cleanup() being called when they are no longer needed. |
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