Source code for airflow.example_dags.example_kubernetes_executor

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This is an example dag for using a Kubernetes Executor Configuration.

from __future__ import annotations

import logging
import os

import pendulum

from airflow.configuration import conf
from airflow.decorators import task
from airflow.example_dags.libs.helper import print_stuff
from airflow.models.dag import DAG

[docs]log = logging.getLogger(__name__)
try: from kubernetes.client import models as k8s except ImportError: log.warning( "The example_kubernetes_executor example DAG requires the kubernetes provider." " Please install it with: pip install apache-airflow[cncf.kubernetes]" )
[docs] k8s = None
if k8s: with DAG( dag_id="example_kubernetes_executor", schedule=None, start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), catchup=False, tags=["example3"], ) as dag: # You can use annotations on your kubernetes pods!
[docs] start_task_executor_config = { "pod_override": k8s.V1Pod(metadata=k8s.V1ObjectMeta(annotations={"test": "annotation"})) }
@task(executor_config=start_task_executor_config) def start_task(): print_stuff() # [START task_with_volume] executor_config_volume_mount = { "pod_override": k8s.V1Pod( spec=k8s.V1PodSpec( containers=[ k8s.V1Container( name="base", volume_mounts=[ k8s.V1VolumeMount(mount_path="/foo/", name="example-kubernetes-test-volume") ], ) ], volumes=[ k8s.V1Volume( name="example-kubernetes-test-volume", host_path=k8s.V1HostPathVolumeSource(path="/tmp/"), ) ], ) ), } @task(executor_config=executor_config_volume_mount) def test_volume_mount(): """ Tests whether the volume has been mounted. """ with open("/foo/volume_mount_test.txt", "w") as foo: foo.write("Hello") return_code = os.system("cat /foo/volume_mount_test.txt") if return_code != 0: raise ValueError(f"Error when checking volume mount. Return code {return_code}") volume_task = test_volume_mount() # [END task_with_volume] # [START task_with_sidecar] executor_config_sidecar = { "pod_override": k8s.V1Pod( spec=k8s.V1PodSpec( containers=[ k8s.V1Container( name="base", volume_mounts=[k8s.V1VolumeMount(mount_path="/shared/", name="shared-empty-dir")], ), k8s.V1Container( name="sidecar", image="ubuntu", args=['echo "retrieved from mount" > /shared/test.txt'], command=["bash", "-cx"], volume_mounts=[k8s.V1VolumeMount(mount_path="/shared/", name="shared-empty-dir")], ), ], volumes=[ k8s.V1Volume(name="shared-empty-dir", empty_dir=k8s.V1EmptyDirVolumeSource()), ], ) ), } @task(executor_config=executor_config_sidecar) def test_sharedvolume_mount(): """ Tests whether the volume has been mounted. """ for i in range(5): try: return_code = os.system("cat /shared/test.txt") if return_code != 0: raise ValueError(f"Error when checking volume mount. Return code {return_code}") except ValueError as e: if i > 4: raise e sidecar_task = test_sharedvolume_mount() # [END task_with_sidecar] # You can add labels to pods executor_config_non_root = { "pod_override": k8s.V1Pod(metadata=k8s.V1ObjectMeta(labels={"release": "stable"})) } @task(executor_config=executor_config_non_root) def non_root_task(): print_stuff() third_task = non_root_task() executor_config_other_ns = { "pod_override": k8s.V1Pod( metadata=k8s.V1ObjectMeta(namespace="test-namespace", labels={"release": "stable"}) ) } @task(executor_config=executor_config_other_ns) def other_namespace_task(): print_stuff() other_ns_task = other_namespace_task() worker_container_repository = conf.get("kubernetes_executor", "worker_container_repository") worker_container_tag = conf.get("kubernetes_executor", "worker_container_tag") # You can also change the base image, here we used the worker image for demonstration. # Note that the image must have the same configuration as the # worker image. Could be that you want to run this task in a special docker image that has a zip # library built-in. You build the special docker image on top your worker image. kube_exec_config_special = { "pod_override": k8s.V1Pod( spec=k8s.V1PodSpec( containers=[ k8s.V1Container( name="base", image=f"{worker_container_repository}:{worker_container_tag}" ), ] ) ) } @task(executor_config=kube_exec_config_special) def base_image_override_task(): print_stuff() base_image_task = base_image_override_task() # Use k8s_client.V1Affinity to define node affinity k8s_affinity = k8s.V1Affinity( pod_anti_affinity=k8s.V1PodAntiAffinity( required_during_scheduling_ignored_during_execution=[ k8s.V1PodAffinityTerm( label_selector=k8s.V1LabelSelector( match_expressions=[ k8s.V1LabelSelectorRequirement(key="app", operator="In", values=["airflow"]) ] ), topology_key="", ) ] ) ) # Use k8s_client.V1Toleration to define node tolerations k8s_tolerations = [k8s.V1Toleration(key="dedicated", operator="Equal", value="airflow")] # Use k8s_client.V1ResourceRequirements to define resource limits k8s_resource_requirements = k8s.V1ResourceRequirements( requests={"memory": "512Mi"}, limits={"memory": "512Mi"} ) kube_exec_config_resource_limits = { "pod_override": k8s.V1Pod( spec=k8s.V1PodSpec( containers=[ k8s.V1Container( name="base", resources=k8s_resource_requirements, ) ], affinity=k8s_affinity, tolerations=k8s_tolerations, ) ) } @task(executor_config=kube_exec_config_resource_limits) def task_with_resource_limits(): print_stuff() four_task = task_with_resource_limits() ( start_task() >> [volume_task, other_ns_task, sidecar_task] >> third_task >> [base_image_task, four_task] )

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