Source code for airflow.providers.apache.flink.sensors.flink_kubernetes

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from __future__ import annotations

from typing import TYPE_CHECKING, Sequence

from kubernetes import client

from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.providers.cncf.kubernetes.hooks.kubernetes import KubernetesHook
from airflow.sensors.base import BaseSensorOperator

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class FlinkKubernetesSensor(BaseSensorOperator):
    """
    Checks flinkDeployment object in kubernetes cluster.

    .. seealso::
        For more detail about Flink Deployment Object have a look at the reference:
        https://nightlies.apache.org/flink/flink-kubernetes-operator-docs-main/docs/custom-resource/reference/#flinkdeployment

    :param application_name: flink Application resource name
    :param namespace: the kubernetes namespace where the flinkDeployment reside in
    :param kubernetes_conn_id: The :ref:`kubernetes connection<howto/connection:kubernetes>`
        to Kubernetes cluster
    :param attach_log: determines whether logs for driver pod should be appended to the sensor log
    :param api_group: kubernetes api group of flinkDeployment
    :param api_version: kubernetes api version of flinkDeployment
    :param plural: kubernetes api custom object plural
    """

[docs]    template_fields: Sequence[str] = ("application_name", "namespace")
[docs]    FAILURE_STATES = ("MISSING", "ERROR")
[docs]    SUCCESS_STATES = ("READY",)

    def __init__(
        self,
        *,
        application_name: str,
        attach_log: bool = False,
        namespace: str | None = None,
        kubernetes_conn_id: str = "kubernetes_default",
        api_group: str = "flink.apache.org",
        api_version: str = "v1beta1",
        plural: str = "flinkdeployments",
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        self.application_name = application_name
        self.attach_log = attach_log
        self.namespace = namespace
        self.kubernetes_conn_id = kubernetes_conn_id
        self.hook = KubernetesHook(conn_id=self.kubernetes_conn_id)
        self.api_group = api_group
        self.api_version = api_version
        self.plural = plural

    def _log_driver(self, application_state: str, response: dict) -> None:
        log_method = self.log.error if application_state in self.FAILURE_STATES else self.log.info
        if not self.attach_log:
            return
        status_info = response["status"]
        if "jobStatus" in status_info:
            job_status = status_info["jobStatus"]
            job_state = job_status["state"] if "state" in job_status else "StateFetchError"
            self.log.info("Flink Job status is %s", job_state)
        else:
            return

        task_manager_labels = status_info["taskManager"]["labelSelector"]
        all_pods = self.hook.get_namespaced_pod_list(
            namespace="default", watch=False, label_selector=task_manager_labels
        )

        namespace = response["metadata"]["namespace"]
        for task_manager in all_pods.items:
            task_manager_pod_name = task_manager.metadata.name

            self.log.info("Starting logging of task manager pod %s ", task_manager_pod_name)
            try:
                log = ""
                for line in self.hook.get_pod_logs(task_manager_pod_name, namespace=namespace):
                    log += line.decode()
                log_method(log)
            except client.rest.ApiException as e:
                self.log.warning(
                    "Could not read logs for pod %s. It may have been disposed.\n"
                    "Make sure timeToLiveSeconds is set on your flinkDeployment spec.\n"
                    "underlying exception: %s",
                    task_manager_pod_name,
                    e,
                )

[docs]    def poke(self, context: Context) -> bool:
        self.log.info("Poking: %s", self.application_name)
        response = self.hook.get_custom_object(
            group=self.api_group,
            version=self.api_version,
            plural=self.plural,
            name=self.application_name,
            namespace=self.namespace,
        )
        try:
            application_state = response["status"]["jobManagerDeploymentStatus"]
        except KeyError:
            return False
        if self.attach_log and application_state in self.FAILURE_STATES + self.SUCCESS_STATES:
            self._log_driver(application_state, response)
        if application_state in self.FAILURE_STATES:
            # TODO: remove this if check when min_airflow_version is set to higher than 2.7.1
            message = f"Flink application failed with state: {application_state}"
            if self.soft_fail:
                raise AirflowSkipException(message)
            raise AirflowException(message)
        elif application_state in self.SUCCESS_STATES:
            self.log.info("Flink application ended successfully")
            return True
        else:
            self.log.info("Flink application is still in state: %s", application_state)
            return False