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from __future__ import annotations

from functools import cached_property
from typing import TYPE_CHECKING, Any, Sequence

from azure.batch import models as batch_models
from deprecated.classic import deprecated

from airflow.exceptions import AirflowException, AirflowProviderDeprecationWarning
from airflow.models import BaseOperator
from import AzureBatchHook

    from airflow.utils.context import Context

[docs]class AzureBatchOperator(BaseOperator): """ Executes a job on Azure Batch Service. :param batch_pool_id: A string that uniquely identifies the Pool within the Account. :param batch_pool_vm_size: The size of virtual machines in the Pool :param batch_job_id: A string that uniquely identifies the Job within the Account. :param batch_task_command_line: The command line of the Task :param batch_task_id: A string that uniquely identifies the task within the Job. :param batch_pool_display_name: The display name for the Pool. The display name need not be unique :param batch_job_display_name: The display name for the Job. The display name need not be unique :param batch_job_manager_task: Details of a Job Manager Task to be launched when the Job is started. :param batch_job_preparation_task: The Job Preparation Task. If set, the Batch service will run the Job Preparation Task on a Node before starting any Tasks of that Job on that Compute Node. Required if batch_job_release_task is set. :param batch_job_release_task: The Job Release Task. Use to undo changes to Compute Nodes made by the Job Preparation Task :param batch_task_display_name: The display name for the task. The display name need not be unique :param batch_task_container_settings: The settings for the container under which the Task runs :param batch_start_task: A Task specified to run on each Compute Node as it joins the Pool. The Task runs when the Compute Node is added to the Pool or when the Compute Node is restarted. :param batch_max_retries: The number of times to retry this batch operation before it's considered a failed operation. Default is 3 :param batch_task_resource_files: A list of files that the Batch service will download to the Compute Node before running the command line. :param batch_task_output_files: A list of files that the Batch service will upload from the Compute Node after running the command line. :param batch_task_user_identity: The user identity under which the Task runs. If omitted, the Task runs as a non-administrative user unique to the Task. :param target_low_priority_nodes: The desired number of low-priority Compute Nodes in the Pool. This property must not be specified if enable_auto_scale is set to true. :param target_dedicated_nodes: The desired number of dedicated Compute Nodes in the Pool. This property must not be specified if enable_auto_scale is set to true. :param enable_auto_scale: Whether the Pool size should automatically adjust over time. Default is false :param auto_scale_formula: A formula for the desired number of Compute Nodes in the Pool. This property must not be specified if enableAutoScale is set to false. It is required if enableAutoScale is set to true. :param azure_batch_conn_id: The :ref:`Azure Batch connection id<howto/connection:azure_batch>` :param use_latest_verified_vm_image_and_sku: Whether to use the latest verified virtual machine image and sku in the batch account. Default is false. :param vm_publisher: The publisher of the Azure Virtual Machines Marketplace Image. For example, Canonical or MicrosoftWindowsServer. Required if use_latest_image_and_sku is set to True :param vm_offer: The offer type of the Azure Virtual Machines Marketplace Image. For example, UbuntuServer or WindowsServer. Required if use_latest_image_and_sku is set to True :param sku_starts_with: The starting string of the Virtual Machine SKU. Required if use_latest_image_and_sku is set to True :param vm_sku: The name of the virtual machine sku to use :param vm_version: The version of the virtual machine :param vm_version: str | None :param vm_node_agent_sku_id: The node agent sku id of the virtual machine :param os_family: The Azure Guest OS family to be installed on the virtual machines in the Pool. :param os_version: The OS family version :param timeout: The amount of time to wait for the job to complete in minutes. Default is 25 :param should_delete_job: Whether to delete job after execution. Default is False :param should_delete_pool: Whether to delete pool after execution of jobs. Default is False """
[docs] template_fields: Sequence[str] = ( "batch_pool_id", "batch_pool_vm_size", "batch_job_id", "batch_task_id", "batch_task_command_line", )
[docs] ui_color = "#f0f0e4"
def __init__( self, *, batch_pool_id: str, batch_pool_vm_size: str, batch_job_id: str, batch_task_command_line: str, batch_task_id: str, vm_node_agent_sku_id: str, vm_publisher: str | None = None, vm_offer: str | None = None, sku_starts_with: str | None = None, vm_sku: str | None = None, vm_version: str | None = None, os_family: str | None = None, os_version: str | None = None, batch_pool_display_name: str | None = None, batch_job_display_name: str | None = None, batch_job_manager_task: batch_models.JobManagerTask | None = None, batch_job_preparation_task: batch_models.JobPreparationTask | None = None, batch_job_release_task: batch_models.JobReleaseTask | None = None, batch_task_display_name: str | None = None, batch_task_container_settings: batch_models.TaskContainerSettings | None = None, batch_start_task: batch_models.StartTask | None = None, batch_max_retries: int = 3, batch_task_resource_files: list[batch_models.ResourceFile] | None = None, batch_task_output_files: list[batch_models.OutputFile] | None = None, batch_task_user_identity: batch_models.UserIdentity | None = None, target_low_priority_nodes: int | None = None, target_dedicated_nodes: int | None = None, enable_auto_scale: bool = False, auto_scale_formula: str | None = None, azure_batch_conn_id="azure_batch_default", use_latest_verified_vm_image_and_sku: bool = False, timeout: int = 25, should_delete_job: bool = False, should_delete_pool: bool = False, **kwargs, ) -> None: super().__init__(**kwargs) self.batch_pool_id = batch_pool_id self.batch_pool_vm_size = batch_pool_vm_size self.batch_job_id = batch_job_id self.batch_task_id = batch_task_id self.batch_task_command_line = batch_task_command_line self.batch_pool_display_name = batch_pool_display_name self.batch_job_display_name = batch_job_display_name self.batch_job_manager_task = batch_job_manager_task self.batch_job_preparation_task = batch_job_preparation_task self.batch_job_release_task = batch_job_release_task self.batch_task_display_name = batch_task_display_name self.batch_task_container_settings = batch_task_container_settings self.batch_start_task = batch_start_task self.batch_max_retries = batch_max_retries self.batch_task_resource_files = batch_task_resource_files self.batch_task_output_files = batch_task_output_files self.batch_task_user_identity = batch_task_user_identity self.target_low_priority_nodes = target_low_priority_nodes self.target_dedicated_nodes = target_dedicated_nodes self.enable_auto_scale = enable_auto_scale self.auto_scale_formula = auto_scale_formula self.azure_batch_conn_id = azure_batch_conn_id self.use_latest_image = use_latest_verified_vm_image_and_sku self.vm_publisher = vm_publisher self.vm_offer = vm_offer self.sku_starts_with = sku_starts_with self.vm_sku = vm_sku self.vm_version = vm_version self.vm_node_agent_sku_id = vm_node_agent_sku_id self.os_family = os_family self.os_version = os_version self.timeout = timeout self.should_delete_job = should_delete_job self.should_delete_pool = should_delete_pool @cached_property
[docs] def hook(self) -> AzureBatchHook: """Create and return an AzureBatchHook (cached).""" return AzureBatchHook(self.azure_batch_conn_id)
@deprecated(reason="use `hook` property instead.", category=AirflowProviderDeprecationWarning)
[docs] def get_hook(self) -> AzureBatchHook: """Create and return an AzureBatchHook.""" return self.hook
def _check_inputs(self) -> Any: if not self.os_family and not self.vm_publisher: raise AirflowException("You must specify either vm_publisher or os_family") if self.os_family and self.vm_publisher: raise AirflowException( "Cloud service configuration and virtual machine configuration " "are mutually exclusive. You must specify either of os_family and" " vm_publisher" ) if self.use_latest_image: if not self.vm_publisher or not self.vm_offer: raise AirflowException( f"If use_latest_image_and_sku is set to True then the parameters vm_publisher, " f"vm_offer, must all be set. " f"Found vm_publisher={self.vm_publisher}, vm_offer={self.vm_offer}" ) if self.vm_publisher: if not all([self.vm_sku, self.vm_offer, self.vm_node_agent_sku_id]): raise AirflowException( "If vm_publisher is set, then the parameters vm_sku, vm_offer," "vm_node_agent_sku_id must be set. Found " f"vm_publisher={self.vm_publisher}, vm_offer={self.vm_offer} " f"vm_node_agent_sku_id={self.vm_node_agent_sku_id}, " f"vm_version={self.vm_version}" ) if not self.target_dedicated_nodes and not self.enable_auto_scale: raise AirflowException( "Either target_dedicated_nodes or enable_auto_scale must be set. None was set" ) if self.enable_auto_scale: if self.target_dedicated_nodes or self.target_low_priority_nodes: raise AirflowException( f"If enable_auto_scale is set, then the parameters target_dedicated_nodes and " f"target_low_priority_nodes must not be set. Found " f"target_dedicated_nodes={self.target_dedicated_nodes}, " f"target_low_priority_nodes={self.target_low_priority_nodes}" ) if not self.auto_scale_formula: raise AirflowException("The auto_scale_formula is required when enable_auto_scale is set") if self.batch_job_release_task and not self.batch_job_preparation_task: raise AirflowException( "A batch_job_release_task cannot be specified without also " " specifying a batch_job_preparation_task for the Job." ) if not all( [ self.batch_pool_id, self.batch_job_id, self.batch_pool_vm_size, self.batch_task_id, self.batch_task_command_line, ] ): raise AirflowException( "Some required parameters are missing.Please you must set all the required parameters. " )
[docs] def execute(self, context: Context) -> None: self._check_inputs() self.hook.connection.config.retry_policy = self.batch_max_retries pool = self.hook.configure_pool( pool_id=self.batch_pool_id, vm_size=self.batch_pool_vm_size, display_name=self.batch_pool_display_name, target_dedicated_nodes=self.target_dedicated_nodes, use_latest_image_and_sku=self.use_latest_image, vm_publisher=self.vm_publisher, vm_offer=self.vm_offer, sku_starts_with=self.sku_starts_with, vm_sku=self.vm_sku, vm_version=self.vm_version, vm_node_agent_sku_id=self.vm_node_agent_sku_id, os_family=self.os_family, os_version=self.os_version, target_low_priority_nodes=self.target_low_priority_nodes, enable_auto_scale=self.enable_auto_scale, auto_scale_formula=self.auto_scale_formula, start_task=self.batch_start_task, ) self.hook.create_pool(pool) # Wait for nodes to reach complete state self.hook.wait_for_all_node_state( self.batch_pool_id, { batch_models.ComputeNodeState.start_task_failed, batch_models.ComputeNodeState.unusable, batch_models.ComputeNodeState.idle, }, ) # Create job if not already exist job = self.hook.configure_job( job_id=self.batch_job_id, pool_id=self.batch_pool_id, display_name=self.batch_job_display_name, job_manager_task=self.batch_job_manager_task, job_preparation_task=self.batch_job_preparation_task, job_release_task=self.batch_job_release_task, ) self.hook.create_job(job) # Create task task = self.hook.configure_task( task_id=self.batch_task_id, command_line=self.batch_task_command_line, display_name=self.batch_task_display_name, container_settings=self.batch_task_container_settings, resource_files=self.batch_task_resource_files, output_files=self.batch_task_output_files, user_identity=self.batch_task_user_identity, ) # Add task to job self.hook.add_single_task_to_job(job_id=self.batch_job_id, task=task) # Wait for tasks to complete fail_tasks = self.hook.wait_for_job_tasks_to_complete(job_id=self.batch_job_id, timeout=self.timeout) # Clean up if self.should_delete_job: # delete job first self.clean_up(job_id=self.batch_job_id) if self.should_delete_pool: self.clean_up(self.batch_pool_id) # raise exception if any task fail if fail_tasks: raise AirflowException(f"Job fail. The failed task are: {fail_tasks}")
[docs] def on_kill(self) -> None: response = self.hook.connection.job.terminate( job_id=self.batch_job_id, terminate_reason="Job killed by user" )"Azure Batch job (%s) terminated: %s", self.batch_job_id, response)
[docs] def clean_up(self, pool_id: str | None = None, job_id: str | None = None) -> None: """ Delete the given pool and job in the batch account. :param pool_id: The id of the pool to delete :param job_id: The id of the job to delete """ if job_id:"Deleting job: %s", job_id) self.hook.connection.job.delete(job_id) if pool_id:"Deleting pool: %s", pool_id) self.hook.connection.pool.delete(pool_id)

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