| # |
| # 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. |
| # |
| from typing import Any, Dict, List, Optional |
| |
| from airflow.models import BaseOperator |
| from airflow.providers.apache.spark.hooks.spark_submit import SparkSubmitHook |
| from airflow.settings import WEB_COLORS |
| |
| |
| class SparkSubmitOperator(BaseOperator): |
| """ |
| This hook is a wrapper around the spark-submit binary to kick off a spark-submit job. |
| It requires that the "spark-submit" binary is in the PATH or the spark-home is set |
| in the extra on the connection. |
| |
| .. seealso:: |
| For more information on how to use this operator, take a look at the guide: |
| :ref:`howto/operator:SparkSubmitOperator` |
| |
| :param application: The application that submitted as a job, either jar or py file. (templated) |
| :type application: str |
| :param conf: Arbitrary Spark configuration properties (templated) |
| :type conf: dict |
| :param spark_conn_id: The :ref:`spark connection id <howto/connection:spark>` as configured |
| in Airflow administration. When an invalid connection_id is supplied, it will default to yarn. |
| :type spark_conn_id: str |
| :param files: Upload additional files to the executor running the job, separated by a |
| comma. Files will be placed in the working directory of each executor. |
| For example, serialized objects. (templated) |
| :type files: str |
| :param py_files: Additional python files used by the job, can be .zip, .egg or .py. (templated) |
| :type py_files: str |
| :param jars: Submit additional jars to upload and place them in executor classpath. (templated) |
| :type jars: str |
| :param driver_class_path: Additional, driver-specific, classpath settings. (templated) |
| :type driver_class_path: str |
| :param java_class: the main class of the Java application |
| :type java_class: str |
| :param packages: Comma-separated list of maven coordinates of jars to include on the |
| driver and executor classpaths. (templated) |
| :type packages: str |
| :param exclude_packages: Comma-separated list of maven coordinates of jars to exclude |
| while resolving the dependencies provided in 'packages' (templated) |
| :type exclude_packages: str |
| :param repositories: Comma-separated list of additional remote repositories to search |
| for the maven coordinates given with 'packages' |
| :type repositories: str |
| :param total_executor_cores: (Standalone & Mesos only) Total cores for all executors |
| (Default: all the available cores on the worker) |
| :type total_executor_cores: int |
| :param executor_cores: (Standalone & YARN only) Number of cores per executor (Default: 2) |
| :type executor_cores: int |
| :param executor_memory: Memory per executor (e.g. 1000M, 2G) (Default: 1G) |
| :type executor_memory: str |
| :param driver_memory: Memory allocated to the driver (e.g. 1000M, 2G) (Default: 1G) |
| :type driver_memory: str |
| :param keytab: Full path to the file that contains the keytab (templated) |
| :type keytab: str |
| :param principal: The name of the kerberos principal used for keytab (templated) |
| :type principal: str |
| :param proxy_user: User to impersonate when submitting the application (templated) |
| :type proxy_user: str |
| :param name: Name of the job (default airflow-spark). (templated) |
| :type name: str |
| :param num_executors: Number of executors to launch |
| :type num_executors: int |
| :param status_poll_interval: Seconds to wait between polls of driver status in cluster |
| mode (Default: 1) |
| :type status_poll_interval: int |
| :param application_args: Arguments for the application being submitted (templated) |
| :type application_args: list |
| :param env_vars: Environment variables for spark-submit. It supports yarn and k8s mode too. (templated) |
| :type env_vars: dict |
| :param verbose: Whether to pass the verbose flag to spark-submit process for debugging |
| :type verbose: bool |
| :param spark_binary: The command to use for spark submit. |
| Some distros may use spark2-submit. |
| :type spark_binary: str |
| """ |
| |
| template_fields = ( |
| '_application', |
| '_conf', |
| '_files', |
| '_py_files', |
| '_jars', |
| '_driver_class_path', |
| '_packages', |
| '_exclude_packages', |
| '_keytab', |
| '_principal', |
| '_proxy_user', |
| '_name', |
| '_application_args', |
| '_env_vars', |
| ) |
| ui_color = WEB_COLORS['LIGHTORANGE'] |
| |
| def __init__( |
| self, |
| *, |
| application: str = '', |
| conf: Optional[Dict[str, Any]] = None, |
| conn_id: str = 'spark_default', |
| files: Optional[str] = None, |
| py_files: Optional[str] = None, |
| archives: Optional[str] = None, |
| driver_class_path: Optional[str] = None, |
| jars: Optional[str] = None, |
| java_class: Optional[str] = None, |
| packages: Optional[str] = None, |
| exclude_packages: Optional[str] = None, |
| repositories: Optional[str] = None, |
| total_executor_cores: Optional[int] = None, |
| executor_cores: Optional[int] = None, |
| executor_memory: Optional[str] = None, |
| driver_memory: Optional[str] = None, |
| keytab: Optional[str] = None, |
| principal: Optional[str] = None, |
| proxy_user: Optional[str] = None, |
| name: str = 'arrow-spark', |
| num_executors: Optional[int] = None, |
| status_poll_interval: int = 1, |
| application_args: Optional[List[Any]] = None, |
| env_vars: Optional[Dict[str, Any]] = None, |
| verbose: bool = False, |
| spark_binary: Optional[str] = None, |
| **kwargs: Any, |
| ) -> None: |
| super().__init__(**kwargs) |
| self._application = application |
| self._conf = conf |
| self._files = files |
| self._py_files = py_files |
| self._archives = archives |
| self._driver_class_path = driver_class_path |
| self._jars = jars |
| self._java_class = java_class |
| self._packages = packages |
| self._exclude_packages = exclude_packages |
| self._repositories = repositories |
| self._total_executor_cores = total_executor_cores |
| self._executor_cores = executor_cores |
| self._executor_memory = executor_memory |
| self._driver_memory = driver_memory |
| self._keytab = keytab |
| self._principal = principal |
| self._proxy_user = proxy_user |
| self._name = name |
| self._num_executors = num_executors |
| self._status_poll_interval = status_poll_interval |
| self._application_args = application_args |
| self._env_vars = env_vars |
| self._verbose = verbose |
| self._spark_binary = spark_binary |
| self._hook: Optional[SparkSubmitHook] = None |
| self._conn_id = conn_id |
| |
| def execute(self, context: Dict[str, Any]) -> None: |
| """Call the SparkSubmitHook to run the provided spark job""" |
| if self._hook is None: |
| self._hook = self._get_hook() |
| self._hook.submit(self._application) |
| |
| def on_kill(self) -> None: |
| if self._hook is None: |
| self._hook = self._get_hook() |
| self._hook.on_kill() |
| |
| def _get_hook(self) -> SparkSubmitHook: |
| return SparkSubmitHook( |
| conf=self._conf, |
| conn_id=self._conn_id, |
| files=self._files, |
| py_files=self._py_files, |
| archives=self._archives, |
| driver_class_path=self._driver_class_path, |
| jars=self._jars, |
| java_class=self._java_class, |
| packages=self._packages, |
| exclude_packages=self._exclude_packages, |
| repositories=self._repositories, |
| total_executor_cores=self._total_executor_cores, |
| executor_cores=self._executor_cores, |
| executor_memory=self._executor_memory, |
| driver_memory=self._driver_memory, |
| keytab=self._keytab, |
| principal=self._principal, |
| proxy_user=self._proxy_user, |
| name=self._name, |
| num_executors=self._num_executors, |
| status_poll_interval=self._status_poll_interval, |
| application_args=self._application_args, |
| env_vars=self._env_vars, |
| verbose=self._verbose, |
| spark_binary=self._spark_binary, |
| ) |
