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from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
from kubernetes.watch import Watch
from airflow.models import BaseOperator
from airflow.providers.cncf.kubernetes.hooks.kubernetes import KubernetesHook, _load_body_to_dict
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class SparkKubernetesOperator(BaseOperator):
"""
Creates sparkApplication object in kubernetes cluster:
.. seealso::
For more detail about Spark Application Object have a look at the reference:
https://github.com/GoogleCloudPlatform/spark-on-k8s-operator/blob/v1beta2-1.1.0-2.4.5/docs/api-docs.md#sparkapplication
:param application_file: Defines Kubernetes 'custom_resource_definition' of 'sparkApplication' as either a
path to a '.yaml' file, '.json' file, YAML string or JSON string.
:param namespace: kubernetes namespace to put sparkApplication
:param kubernetes_conn_id: The :ref:`kubernetes connection id <howto/connection:kubernetes>`
for the to Kubernetes cluster.
:param api_group: kubernetes api group of sparkApplication
:param api_version: kubernetes api version of sparkApplication
"""
[docs] template_fields: Sequence[str] = ("application_file", "namespace")
[docs] template_ext: Sequence[str] = (".yaml", ".yml", ".json")
def __init__(
self,
*,
application_file: str,
namespace: str | None = None,
kubernetes_conn_id: str = "kubernetes_default",
api_group: str = "sparkoperator.k8s.io",
api_version: str = "v1beta2",
in_cluster: bool | None = None,
cluster_context: str | None = None,
config_file: str | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.namespace = namespace
self.kubernetes_conn_id = kubernetes_conn_id
self.api_group = api_group
self.api_version = api_version
self.plural = "sparkapplications"
self.application_file = application_file
self.in_cluster = in_cluster
self.cluster_context = cluster_context
self.config_file = config_file
self.hook = KubernetesHook(
conn_id=self.kubernetes_conn_id,
in_cluster=self.in_cluster,
config_file=self.config_file,
cluster_context=self.cluster_context,
)
[docs] def execute(self, context: Context):
body = _load_body_to_dict(self.application_file)
name = body["metadata"]["name"]
namespace = self.namespace or self.hook.get_namespace()
namespace_event_stream = Watch().stream(
self.hook.core_v1_client.list_namespaced_pod,
namespace=namespace,
_preload_content=False,
watch=True,
label_selector=f"sparkoperator.k8s.io/app-name={name},spark-role=driver",
field_selector="status.phase=Running",
)
self.hook.create_custom_object(
group=self.api_group,
version=self.api_version,
plural=self.plural,
body=body,
namespace=namespace,
)
for event in namespace_event_stream:
if event["type"] == "ADDED":
pod_log_stream = Watch().stream(
self.hook.core_v1_client.read_namespaced_pod_log,
name=f"{name}-driver",
namespace=namespace,
_preload_content=False,
timestamps=True,
)
for line in pod_log_stream:
self.log.info(line)
else:
break
[docs] def on_kill(self) -> None:
body = _load_body_to_dict(self.application_file)
name = body["metadata"]["name"]
namespace = self.namespace or self.hook.get_namespace()
self.hook.delete_custom_object(
group=self.api_group,
version=self.api_version,
plural=self.plural,
namespace=namespace,
name=name,
)
