Source code for airflow.providers.amazon.aws.operators.batch

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"""
An Airflow operator for AWS Batch services

.. seealso::

    - http://boto3.readthedocs.io/en/latest/guide/configuration.html
    - http://boto3.readthedocs.io/en/latest/reference/services/batch.html
    - https://docs.aws.amazon.com/batch/latest/APIReference/Welcome.html
"""
import warnings
from typing import TYPE_CHECKING, Any, Optional, Sequence

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.batch_client import BatchClientHook

if TYPE_CHECKING:
    from airflow.utils.context import Context



[docs]class BatchOperator(BaseOperator):
    """
    Execute a job on AWS Batch

    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:BatchOperator`

    :param job_name: the name for the job that will run on AWS Batch (templated)

    :param job_definition: the job definition name on AWS Batch

    :param job_queue: the queue name on AWS Batch

    :param overrides: the `containerOverrides` parameter for boto3 (templated)

    :param array_properties: the `arrayProperties` parameter for boto3

    :param parameters: the `parameters` for boto3 (templated)

    :param job_id: the job ID, usually unknown (None) until the
        submit_job operation gets the jobId defined by AWS Batch

    :param waiters: an :py:class:`.BatchWaiters` object (see note below);
        if None, polling is used with max_retries and status_retries.

    :param max_retries: exponential back-off retries, 4200 = 48 hours;
        polling is only used when waiters is None

    :param status_retries: number of HTTP retries to get job status, 10;
        polling is only used when waiters is None

    :param aws_conn_id: connection id of AWS credentials / region name. If None,
        credential boto3 strategy will be used.

    :param region_name: region name to use in AWS Hook.
        Override the region_name in connection (if provided)

    :param tags: collection of tags to apply to the AWS Batch job submission
        if None, no tags are submitted

    .. note::
        Any custom waiters must return a waiter for these calls:
        .. code-block:: python

            waiter = waiters.get_waiter("JobExists")
            waiter = waiters.get_waiter("JobRunning")
            waiter = waiters.get_waiter("JobComplete")
    """


[docs]    ui_color = "#c3dae0"


[docs]    arn = None  # type: Optional[str]


[docs]    template_fields: Sequence[str] = (
        "job_name",
        "overrides",
        "parameters",

    )

[docs]    template_fields_renderers = {"overrides": "json", "parameters": "json"}


    def __init__(
        self,
        *,
        job_name: str,
        job_definition: str,
        job_queue: str,
        overrides: dict,
        array_properties: Optional[dict] = None,
        parameters: Optional[dict] = None,
        job_id: Optional[str] = None,
        waiters: Optional[Any] = None,
        max_retries: Optional[int] = None,
        status_retries: Optional[int] = None,
        aws_conn_id: Optional[str] = None,
        region_name: Optional[str] = None,
        tags: Optional[dict] = None,
        **kwargs,
    ):

        BaseOperator.__init__(self, **kwargs)
        self.job_id = job_id
        self.job_name = job_name
        self.job_definition = job_definition
        self.job_queue = job_queue
        self.overrides = overrides or {}
        self.array_properties = array_properties or {}
        self.parameters = parameters or {}
        self.waiters = waiters
        self.tags = tags or {}
        self.hook = BatchClientHook(
            max_retries=max_retries,
            status_retries=status_retries,
            aws_conn_id=aws_conn_id,
            region_name=region_name,
        )


[docs]    def execute(self, context: 'Context'):
        """
        Submit and monitor an AWS Batch job

        :raises: AirflowException
        """
        self.submit_job(context)
        self.monitor_job(context)



[docs]    def on_kill(self):
        response = self.hook.client.terminate_job(jobId=self.job_id, reason="Task killed by the user")
        self.log.info("AWS Batch job (%s) terminated: %s", self.job_id, response)



[docs]    def submit_job(self, context: 'Context'):
        """
        Submit an AWS Batch job

        :raises: AirflowException
        """
        self.log.info(
            "Running AWS Batch job - job definition: %s - on queue %s",
            self.job_definition,
            self.job_queue,
        )
        self.log.info("AWS Batch job - container overrides: %s", self.overrides)

        try:
            response = self.hook.client.submit_job(
                jobName=self.job_name,
                jobQueue=self.job_queue,
                jobDefinition=self.job_definition,
                arrayProperties=self.array_properties,
                parameters=self.parameters,
                containerOverrides=self.overrides,
                tags=self.tags,
            )
            self.job_id = response["jobId"]

            self.log.info("AWS Batch job (%s) started: %s", self.job_id, response)
        except Exception as e:
            self.log.error("AWS Batch job (%s) failed submission", self.job_id)
            raise AirflowException(e)



[docs]    def monitor_job(self, context: 'Context'):
        """
        Monitor an AWS Batch job
        monitor_job can raise an exception or an AirflowTaskTimeout can be raised if execution_timeout
        is given while creating the task. These exceptions should be handled in taskinstance.py
        instead of here like it was previously done

        :raises: AirflowException
        """
        if not self.job_id:
            raise AirflowException('AWS Batch job - job_id was not found')

        if self.waiters:
            self.waiters.wait_for_job(self.job_id)
        else:
            self.hook.wait_for_job(self.job_id)

        self.hook.check_job_success(self.job_id)
        self.log.info("AWS Batch job (%s) succeeded", self.job_id)




[docs]class AwsBatchOperator(BatchOperator):
    """
    This operator is deprecated.
    Please use :class:`airflow.providers.amazon.aws.operators.batch.BatchOperator`.
    """

    def __init__(self, *args, **kwargs):
        warnings.warn(
            "This operator is deprecated. "
            "Please use :class:`airflow.providers.amazon.aws.operators.batch.BatchOperator`.",
            DeprecationWarning,
            stacklevel=2,
        )
        super().__init__(*args, **kwargs)

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