airflow livy 源码

airflow livy 代码

文件路径：/airflow/providers/apache/livy/operators/livy.py

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
"""This module contains the Apache Livy operator."""
from __future__ import annotations

from time import sleep
from typing import TYPE_CHECKING, Any, Sequence

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.apache.livy.hooks.livy import BatchState, LivyHook

if TYPE_CHECKING:
    from airflow.utils.context import Context


class LivyOperator(BaseOperator):
    """
    This operator wraps the Apache Livy batch REST API, allowing to submit a Spark
    application to the underlying cluster.

    :param file: path of the file containing the application to execute (required).
    :param class_name: name of the application Java/Spark main class.
    :param args: application command line arguments.
    :param jars: jars to be used in this sessions.
    :param py_files: python files to be used in this session.
    :param files: files to be used in this session.
    :param driver_memory: amount of memory to use for the driver process.
    :param driver_cores: number of cores to use for the driver process.
    :param executor_memory: amount of memory to use per executor process.
    :param executor_cores: number of cores to use for each executor.
    :param num_executors: number of executors to launch for this session.
    :param archives: archives to be used in this session.
    :param queue: name of the YARN queue to which the application is submitted.
    :param name: name of this session.
    :param conf: Spark configuration properties.
    :param proxy_user: user to impersonate when running the job.
    :param livy_conn_id: reference to a pre-defined Livy Connection.
    :param livy_conn_auth_type: The auth type for the Livy Connection.
    :param polling_interval: time in seconds between polling for job completion. Don't poll for values >=0
    :param extra_options: A dictionary of options, where key is string and value
        depends on the option that's being modified.
    :param extra_headers: A dictionary of headers passed to the HTTP request to livy.
    :param retry_args: Arguments which define the retry behaviour.
            See Tenacity documentation at https://github.com/jd/tenacity
    """

    template_fields: Sequence[str] = ('spark_params',)

    def __init__(
        self,
        *,
        file: str,
        class_name: str | None = None,
        args: Sequence[str | int | float] | None = None,
        conf: dict[Any, Any] | None = None,
        jars: Sequence[str] | None = None,
        py_files: Sequence[str] | None = None,
        files: Sequence[str] | None = None,
        driver_memory: str | None = None,
        driver_cores: int | str | None = None,
        executor_memory: str | None = None,
        executor_cores: int | str | None = None,
        num_executors: int | str | None = None,
        archives: Sequence[str] | None = None,
        queue: str | None = None,
        name: str | None = None,
        proxy_user: str | None = None,
        livy_conn_id: str = 'livy_default',
        livy_conn_auth_type: Any | None = None,
        polling_interval: int = 0,
        extra_options: dict[str, Any] | None = None,
        extra_headers: dict[str, Any] | None = None,
        retry_args: dict[str, Any] | None = None,
        **kwargs: Any,
    ) -> None:

        super().__init__(**kwargs)

        self.spark_params = {
            'file': file,
            'class_name': class_name,
            'args': args,
            'jars': jars,
            'py_files': py_files,
            'files': files,
            'driver_memory': driver_memory,
            'driver_cores': driver_cores,
            'executor_memory': executor_memory,
            'executor_cores': executor_cores,
            'num_executors': num_executors,
            'archives': archives,
            'queue': queue,
            'name': name,
            'conf': conf,
            'proxy_user': proxy_user,
        }

        self._livy_conn_id = livy_conn_id
        self._livy_conn_auth_type = livy_conn_auth_type
        self._polling_interval = polling_interval
        self._extra_options = extra_options or {}
        self._extra_headers = extra_headers or {}

        self._livy_hook: LivyHook | None = None
        self._batch_id: int | str
        self.retry_args = retry_args

    def get_hook(self) -> LivyHook:
        """
        Get valid hook.

        :return: hook
        :rtype: LivyHook
        """
        if self._livy_hook is None or not isinstance(self._livy_hook, LivyHook):
            self._livy_hook = LivyHook(
                livy_conn_id=self._livy_conn_id,
                extra_headers=self._extra_headers,
                extra_options=self._extra_options,
                auth_type=self._livy_conn_auth_type,
            )
        return self._livy_hook

    def execute(self, context: Context) -> Any:
        self._batch_id = self.get_hook().post_batch(**self.spark_params)

        if self._polling_interval > 0:
            self.poll_for_termination(self._batch_id)

        return self._batch_id

    def poll_for_termination(self, batch_id: int | str) -> None:
        """
        Pool Livy for batch termination.

        :param batch_id: id of the batch session to monitor.
        """
        hook = self.get_hook()
        state = hook.get_batch_state(batch_id, retry_args=self.retry_args)
        while state not in hook.TERMINAL_STATES:
            self.log.debug('Batch with id %s is in state: %s', batch_id, state.value)
            sleep(self._polling_interval)
            state = hook.get_batch_state(batch_id, retry_args=self.retry_args)
        self.log.info("Batch with id %s terminated with state: %s", batch_id, state.value)
        hook.dump_batch_logs(batch_id)
        if state != BatchState.SUCCESS:
            raise AirflowException(f"Batch {batch_id} did not succeed")

    def on_kill(self) -> None:
        self.kill()

    def kill(self) -> None:
        """Delete the current batch session."""
        if self._batch_id is not None:
            self.get_hook().delete_batch(self._batch_id)

相关信息

airflow 源码目录

相关文章

airflow init 源码