| :mod:`airflow.contrib.hooks.spark_submit_hook` |
| ============================================== |
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| .. py:module:: airflow.contrib.hooks.spark_submit_hook |
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| Module Contents |
| --------------- |
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| .. py:class:: SparkSubmitHook(conf=None, conn_id='spark_default', files=None, py_files=None, archives=None, driver_class_path=None, jars=None, java_class=None, packages=None, exclude_packages=None, repositories=None, total_executor_cores=None, executor_cores=None, executor_memory=None, driver_memory=None, keytab=None, principal=None, proxy_user=None, name='default-name', num_executors=None, status_poll_interval=1, application_args=None, env_vars=None, verbose=False, spark_binary=None) |
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| Bases: :class:`airflow.hooks.base_hook.BaseHook`, :class:`airflow.utils.log.logging_mixin.LoggingMixin` |
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| 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 to be |
| supplied. |
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| :param conf: Arbitrary Spark configuration properties |
| :type conf: dict |
| :param conn_id: The connection id as configured in Airflow administration. When an |
| invalid connection_id is supplied, it will default to yarn. |
| :type 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. |
| :type files: str |
| :param py_files: Additional python files used by the job, can be .zip, .egg or .py. |
| :type py_files: str |
| :param: archives: Archives that spark should unzip (and possibly tag with #ALIAS) into |
| the application working directory. |
| :param driver_class_path: Additional, driver-specific, classpath settings. |
| :type driver_class_path: str |
| :param jars: Submit additional jars to upload and place them in executor classpath. |
| :type jars: 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 |
| :type packages: str |
| :param exclude_packages: Comma-separated list of maven coordinates of jars to exclude |
| while resolving the dependencies provided in 'packages' |
| :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 and Kubernetes 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 |
| :type keytab: str |
| :param principal: The name of the kerberos principal used for keytab |
| :type principal: str |
| :param proxy_user: User to impersonate when submitting the application |
| :type proxy_user: str |
| :param name: Name of the job (default airflow-spark) |
| :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 |
| :type application_args: list |
| :param env_vars: Environment variables for spark-submit. It |
| supports yarn and k8s mode too. |
| :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 |
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| .. method:: _resolve_should_track_driver_status(self) |
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| Determines whether or not this hook should poll the spark driver status through |
| subsequent spark-submit status requests after the initial spark-submit request |
| :return: if the driver status should be tracked |
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| .. method:: _resolve_connection(self) |
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| .. method:: get_conn(self) |
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| .. method:: _get_spark_binary_path(self) |
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| .. method:: _mask_cmd(self, connection_cmd) |
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| .. method:: _build_spark_submit_command(self, application) |
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| Construct the spark-submit command to execute. |
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| :param application: command to append to the spark-submit command |
| :type application: str |
| :return: full command to be executed |
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| .. method:: _build_track_driver_status_command(self) |
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| Construct the command to poll the driver status. |
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| :return: full command to be executed |
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| .. method:: submit(self, application='', **kwargs) |
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| Remote Popen to execute the spark-submit job |
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| :param application: Submitted application, jar or py file |
| :type application: str |
| :param kwargs: extra arguments to Popen (see subprocess.Popen) |
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| .. method:: _process_spark_submit_log(self, itr) |
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| Processes the log files and extracts useful information out of it. |
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| If the deploy-mode is 'client', log the output of the submit command as those |
| are the output logs of the Spark worker directly. |
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| Remark: If the driver needs to be tracked for its status, the log-level of the |
| spark deploy needs to be at least INFO (log4j.logger.org.apache.spark.deploy=INFO) |
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| :param itr: An iterator which iterates over the input of the subprocess |
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| .. method:: _process_spark_status_log(self, itr) |
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| parses the logs of the spark driver status query process |
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| :param itr: An iterator which iterates over the input of the subprocess |
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| .. method:: _start_driver_status_tracking(self) |
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| Polls the driver based on self._driver_id to get the status. |
| Finish successfully when the status is FINISHED. |
| Finish failed when the status is ERROR/UNKNOWN/KILLED/FAILED. |
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| Possible status: |
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| SUBMITTED |
| Submitted but not yet scheduled on a worker |
| RUNNING |
| Has been allocated to a worker to run |
| FINISHED |
| Previously ran and exited cleanly |
| RELAUNCHING |
| Exited non-zero or due to worker failure, but has not yet |
| started running again |
| UNKNOWN |
| The status of the driver is temporarily not known due to |
| master failure recovery |
| KILLED |
| A user manually killed this driver |
| FAILED |
| The driver exited non-zero and was not supervised |
| ERROR |
| Unable to run or restart due to an unrecoverable error |
| (e.g. missing jar file) |
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| .. method:: _build_spark_driver_kill_command(self) |
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| Construct the spark-submit command to kill a driver. |
| :return: full command to kill a driver |
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| .. method:: on_kill(self) |
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