Source code for airflow.providers.amazon.aws.hooks.batch_client

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"""
A client 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
"""

from random import uniform
from time import sleep
from typing import Dict, List, Optional, Union

import botocore.client
import botocore.exceptions
import botocore.waiter

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.typing_compat import Protocol, runtime_checkable


[docs]@runtime_checkable class AwsBatchProtocol(Protocol): """ A structured Protocol for ``boto3.client('batch') -> botocore.client.Batch``. This is used for type hints on :py:meth:`.AwsBatchClient.client`; it covers only the subset of client methods required. .. seealso:: - https://mypy.readthedocs.io/en/latest/protocols.html - http://boto3.readthedocs.io/en/latest/reference/services/batch.html """
[docs] def describe_jobs(self, jobs: List[str]) -> Dict: """ Get job descriptions from AWS batch :param jobs: a list of JobId to describe :type jobs: List[str] :return: an API response to describe jobs :rtype: Dict """ ...
[docs] def get_waiter(self, waiterName: str) -> botocore.waiter.Waiter: """ Get an AWS Batch service waiter :param waiterName: The name of the waiter. The name should match the name (including the casing) of the key name in the waiter model file (typically this is CamelCasing). :type waiterName: str :return: a waiter object for the named AWS batch service :rtype: botocore.waiter.Waiter .. note:: AWS batch might not have any waiters (until botocore PR-1307 is released). .. code-block:: python import boto3 boto3.client("batch").waiter_names == [] .. seealso:: - https://boto3.amazonaws.com/v1/documentation/api/latest/guide/clients.html#waiters - https://github.com/boto/botocore/pull/1307 """ ...
[docs] def submit_job( self, jobName: str, jobQueue: str, jobDefinition: str, arrayProperties: Dict, parameters: Dict, containerOverrides: Dict, tags: Dict, ) -> Dict: """ Submit a batch job :param jobName: the name for the AWS batch job :type jobName: str :param jobQueue: the queue name on AWS Batch :type jobQueue: str :param jobDefinition: the job definition name on AWS Batch :type jobDefinition: str :param arrayProperties: the same parameter that boto3 will receive :type arrayProperties: Dict :param parameters: the same parameter that boto3 will receive :type parameters: Dict :param containerOverrides: the same parameter that boto3 will receive :type containerOverrides: Dict :param tags: the same parameter that boto3 will receive :type tags: Dict :return: an API response :rtype: Dict """ ...
[docs] def terminate_job(self, jobId: str, reason: str) -> Dict: """ Terminate a batch job :param jobId: a job ID to terminate :type jobId: str :param reason: a reason to terminate job ID :type reason: str :return: an API response :rtype: Dict """ ...
# Note that the use of invalid-name parameters should be restricted to the boto3 mappings only; # all the Airflow wrappers of boto3 clients should not adopt invalid-names to match boto3.
[docs]class AwsBatchClientHook(AwsBaseHook): """ A client for AWS batch services. :param max_retries: exponential back-off retries, 4200 = 48 hours; polling is only used when waiters is None :type max_retries: Optional[int] :param status_retries: number of HTTP retries to get job status, 10; polling is only used when waiters is None :type status_retries: Optional[int] .. note:: Several methods use a default random delay to check or poll for job status, i.e. ``random.uniform(DEFAULT_DELAY_MIN, DEFAULT_DELAY_MAX)`` Using a random interval helps to avoid AWS API throttle limits when many concurrent tasks request job-descriptions. To modify the global defaults for the range of jitter allowed when a random delay is used to check batch job status, modify these defaults, e.g.: .. code-block:: AwsBatchClient.DEFAULT_DELAY_MIN = 0 AwsBatchClient.DEFAULT_DELAY_MAX = 5 When explicit delay values are used, a 1 second random jitter is applied to the delay (e.g. a delay of 0 sec will be a ``random.uniform(0, 1)`` delay. It is generally recommended that random jitter is added to API requests. A convenience method is provided for this, e.g. to get a random delay of 10 sec +/- 5 sec: ``delay = AwsBatchClient.add_jitter(10, width=5, minima=0)`` .. seealso:: - https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/batch.html - https://docs.aws.amazon.com/general/latest/gr/api-retries.html - https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/ """
[docs] MAX_RETRIES = 4200
[docs] STATUS_RETRIES = 10
# delays are in seconds
[docs] DEFAULT_DELAY_MIN = 1
[docs] DEFAULT_DELAY_MAX = 10
def __init__( self, *args, max_retries: Optional[int] = None, status_retries: Optional[int] = None, **kwargs ) -> None: # https://github.com/python/mypy/issues/6799 hence type: ignore super().__init__(client_type='batch', *args, **kwargs) # type: ignore self.max_retries = max_retries or self.MAX_RETRIES self.status_retries = status_retries or self.STATUS_RETRIES @property
[docs] def client(self) -> Union[AwsBatchProtocol, botocore.client.BaseClient]: """ An AWS API client for batch services. :return: a boto3 'batch' client for the ``.region_name`` :rtype: Union[AwsBatchProtocol, botocore.client.BaseClient] """ return self.conn
[docs] def terminate_job(self, job_id: str, reason: str) -> Dict: """ Terminate a batch job :param job_id: a job ID to terminate :type job_id: str :param reason: a reason to terminate job ID :type reason: str :return: an API response :rtype: Dict """ response = self.get_conn().terminate_job(jobId=job_id, reason=reason) self.log.info(response) return response
[docs] def check_job_success(self, job_id: str) -> bool: """ Check the final status of the batch job; return True if the job 'SUCCEEDED', else raise an AirflowException :param job_id: a batch job ID :type job_id: str :rtype: bool :raises: AirflowException """ job = self.get_job_description(job_id) job_status = job.get("status") if job_status == "SUCCEEDED": self.log.info("AWS batch job (%s) succeeded: %s", job_id, job) return True if job_status == "FAILED": raise AirflowException(f"AWS Batch job ({job_id}) failed: {job}") if job_status in ["SUBMITTED", "PENDING", "RUNNABLE", "STARTING", "RUNNING"]: raise AirflowException(f"AWS Batch job ({job_id}) is not complete: {job}") raise AirflowException(f"AWS Batch job ({job_id}) has unknown status: {job}")
[docs] def wait_for_job(self, job_id: str, delay: Union[int, float, None] = None) -> None: """ Wait for batch job to complete :param job_id: a batch job ID :type job_id: str :param delay: a delay before polling for job status :type delay: Optional[Union[int, float]] :raises: AirflowException """ self.delay(delay) self.poll_for_job_running(job_id, delay) self.poll_for_job_complete(job_id, delay) self.log.info("AWS Batch job (%s) has completed", job_id)
[docs] def poll_for_job_running(self, job_id: str, delay: Union[int, float, None] = None) -> None: """ Poll for job running. The status that indicates a job is running or already complete are: 'RUNNING'|'SUCCEEDED'|'FAILED'. So the status options that this will wait for are the transitions from: 'SUBMITTED'>'PENDING'>'RUNNABLE'>'STARTING'>'RUNNING'|'SUCCEEDED'|'FAILED' The completed status options are included for cases where the status changes too quickly for polling to detect a RUNNING status that moves quickly from STARTING to RUNNING to completed (often a failure). :param job_id: a batch job ID :type job_id: str :param delay: a delay before polling for job status :type delay: Optional[Union[int, float]] :raises: AirflowException """ self.delay(delay) running_status = ["RUNNING", "SUCCEEDED", "FAILED"] self.poll_job_status(job_id, running_status)
[docs] def poll_for_job_complete(self, job_id: str, delay: Union[int, float, None] = None) -> None: """ Poll for job completion. The status that indicates job completion are: 'SUCCEEDED'|'FAILED'. So the status options that this will wait for are the transitions from: 'SUBMITTED'>'PENDING'>'RUNNABLE'>'STARTING'>'RUNNING'>'SUCCEEDED'|'FAILED' :param job_id: a batch job ID :type job_id: str :param delay: a delay before polling for job status :type delay: Optional[Union[int, float]] :raises: AirflowException """ self.delay(delay) complete_status = ["SUCCEEDED", "FAILED"] self.poll_job_status(job_id, complete_status)
[docs] def poll_job_status(self, job_id: str, match_status: List[str]) -> bool: """ Poll for job status using an exponential back-off strategy (with max_retries). :param job_id: a batch job ID :type job_id: str :param match_status: a list of job status to match; the batch job status are: 'SUBMITTED'|'PENDING'|'RUNNABLE'|'STARTING'|'RUNNING'|'SUCCEEDED'|'FAILED' :type match_status: List[str] :rtype: bool :raises: AirflowException """ retries = 0 while True: job = self.get_job_description(job_id) job_status = job.get("status") self.log.info( "AWS Batch job (%s) check status (%s) in %s", job_id, job_status, match_status, ) if job_status in match_status: return True if retries >= self.max_retries: raise AirflowException(f"AWS Batch job ({job_id}) status checks exceed max_retries") retries += 1 pause = self.exponential_delay(retries) self.log.info( "AWS Batch job (%s) status check (%d of %d) in the next %.2f seconds", job_id, retries, self.max_retries, pause, ) self.delay(pause)
[docs] def get_job_description(self, job_id: str) -> Dict: """ Get job description (using status_retries). :param job_id: a batch job ID :type job_id: str :return: an API response for describe jobs :rtype: Dict :raises: AirflowException """ retries = 0 while True: try: response = self.get_conn().describe_jobs(jobs=[job_id]) return self.parse_job_description(job_id, response) except botocore.exceptions.ClientError as err: error = err.response.get("Error", {}) if error.get("Code") == "TooManyRequestsException": pass # allow it to retry, if possible else: raise AirflowException(f"AWS Batch job ({job_id}) description error: {err}") retries += 1 if retries >= self.status_retries: raise AirflowException( "AWS Batch job ({}) description error: exceeded " "status_retries ({})".format(job_id, self.status_retries) ) pause = self.exponential_delay(retries) self.log.info( "AWS Batch job (%s) description retry (%d of %d) in the next %.2f seconds", job_id, retries, self.status_retries, pause, ) self.delay(pause)
@staticmethod
[docs] def parse_job_description(job_id: str, response: Dict) -> Dict: """ Parse job description to extract description for job_id :param job_id: a batch job ID :type job_id: str :param response: an API response for describe jobs :type response: Dict :return: an API response to describe job_id :rtype: Dict :raises: AirflowException """ jobs = response.get("jobs", []) matching_jobs = [job for job in jobs if job.get("jobId") == job_id] if len(matching_jobs) != 1: raise AirflowException(f"AWS Batch job ({job_id}) description error: response: {response}") return matching_jobs[0]
@staticmethod
[docs] def add_jitter( delay: Union[int, float], width: Union[int, float] = 1, minima: Union[int, float] = 0 ) -> float: """ Use delay +/- width for random jitter Adding jitter to status polling can help to avoid AWS batch API limits for monitoring batch jobs with a high concurrency in Airflow tasks. :param delay: number of seconds to pause; delay is assumed to be a positive number :type delay: Union[int, float] :param width: delay +/- width for random jitter; width is assumed to be a positive number :type width: Union[int, float] :param minima: minimum delay allowed; minima is assumed to be a non-negative number :type minima: Union[int, float] :return: uniform(delay - width, delay + width) jitter and it is a non-negative number :rtype: float """ delay = abs(delay) width = abs(width) minima = abs(minima) lower = max(minima, delay - width) upper = delay + width return uniform(lower, upper)
@staticmethod
[docs] def delay(delay: Union[int, float, None] = None) -> None: """ Pause execution for ``delay`` seconds. :param delay: a delay to pause execution using ``time.sleep(delay)``; a small 1 second jitter is applied to the delay. :type delay: Optional[Union[int, float]] .. note:: This method uses a default random delay, i.e. ``random.uniform(DEFAULT_DELAY_MIN, DEFAULT_DELAY_MAX)``; using a random interval helps to avoid AWS API throttle limits when many concurrent tasks request job-descriptions. """ if delay is None: delay = uniform(AwsBatchClientHook.DEFAULT_DELAY_MIN, AwsBatchClientHook.DEFAULT_DELAY_MAX) else: delay = AwsBatchClientHook.add_jitter(delay) sleep(delay)
@staticmethod
[docs] def exponential_delay(tries: int) -> float: """ An exponential back-off delay, with random jitter. There is a maximum interval of 10 minutes (with random jitter between 3 and 10 minutes). This is used in the :py:meth:`.poll_for_job_status` method. :param tries: Number of tries :type tries: int :rtype: float Examples of behavior: .. code-block:: python def exp(tries): max_interval = 600.0 # 10 minutes in seconds delay = 1 + pow(tries * 0.6, 2) delay = min(max_interval, delay) print(delay / 3, delay) for tries in range(10): exp(tries) # 0.33 1.0 # 0.45 1.35 # 0.81 2.44 # 1.41 4.23 # 2.25 6.76 # 3.33 10.00 # 4.65 13.95 # 6.21 18.64 # 8.01 24.04 # 10.05 30.15 .. seealso:: - https://docs.aws.amazon.com/general/latest/gr/api-retries.html - https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/ """ max_interval = 600.0 # results in 3 to 10 minute delay delay = 1 + pow(tries * 0.6, 2) delay = min(max_interval, delay) return uniform(delay / 3, delay)

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