airflow.executors.kubernetes_executor
¶
KubernetesExecutor
See also
For more information on how the KubernetesExecutor works, take a look at the guide: Kubernetes Executor
Module Contents¶
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class
airflow.executors.kubernetes_executor.
ResourceVersion
[source]¶ Singleton for tracking resourceVersion from Kubernetes
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class
airflow.executors.kubernetes_executor.
KubernetesJobWatcher
(namespace: Optional[str], multi_namespace_mode: bool, watcher_queue: ‘Queue[KubernetesWatchType]’, resource_version: Optional[str], scheduler_job_id: Optional[str], kube_config: Configuration)[source]¶ Bases:
multiprocessing.Process
,airflow.utils.log.logging_mixin.LoggingMixin
Watches for Kubernetes jobs
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class
airflow.executors.kubernetes_executor.
AirflowKubernetesScheduler
(kube_config: Any, task_queue: ‘Queue[KubernetesJobType]’, result_queue: ‘Queue[KubernetesResultsType]’, kube_client: client.CoreV1Api, scheduler_job_id: str)[source]¶ Bases:
airflow.utils.log.logging_mixin.LoggingMixin
Airflow Scheduler for Kubernetes
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run_next
(self, next_job: KubernetesJobType)[source]¶ The run_next command will check the task_queue for any un-run jobs. It will then create a unique job-id, launch that job in the cluster, and store relevant info in the current_jobs map so we can track the job’s status
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sync
(self)[source]¶ The sync function checks the status of all currently running kubernetes jobs. If a job is completed, its status is placed in the result queue to be sent back to the scheduler.
- Returns
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process_watcher_task
(self, task: KubernetesWatchType)[source]¶ Process the task by watcher.
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airflow.executors.kubernetes_executor.
get_base_pod_from_template
(pod_template_file: Optional[str], kube_config: Any) → k8s.V1Pod[source]¶ -
Reads either the pod_template_file set in the executor_config or the base pod_template_file
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set in the airflow.cfg to craft a "base pod" that will be used by the KubernetesExecutor
- Parameters
pod_template_file – absolute path to a pod_template_file.yaml or None
kube_config – The KubeConfig class generated by airflow that contains all kube metadata
- Returns
a V1Pod that can be used as the base pod for k8s tasks
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class
airflow.executors.kubernetes_executor.
KubernetesExecutor
[source]¶ Bases:
airflow.executors.base_executor.BaseExecutor
,airflow.utils.log.logging_mixin.LoggingMixin
Executor for Kubernetes
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clear_not_launched_queued_tasks
(self, session=None)[source]¶ If the airflow scheduler restarts with pending “Queued” tasks, the tasks may or may not have been launched. Thus on starting up the scheduler let’s check every “Queued” task to see if it has been launched (ie: if there is a corresponding pod on kubernetes)
If it has been launched then do nothing, otherwise reset the state to “None” so the task will be rescheduled
This will not be necessary in a future version of airflow in which there is proper support for State.LAUNCHED
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execute_async
(self, key: TaskInstanceKey, command: CommandType, queue: Optional[str] = None, executor_config: Optional[Any] = None)[source]¶ Executes task asynchronously
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_change_state
(self, key: TaskInstanceKey, state: Optional[str], pod_id: str, namespace: str)[source]¶
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adopt_launched_task
(self, kube_client, pod, pod_ids: dict)[source]¶ Patch existing pod so that the current KubernetesJobWatcher can monitor it via label selectors
- Parameters
kube_client – kubernetes client for speaking to kube API
pod – V1Pod spec that we will patch with new label
pod_ids – pod_ids we expect to patch.
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