This hook is a wrapper around the spark-submit binary to kick off a spark-submit job.
- class airflow.providers.apache.spark.hooks.spark_submit.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)¶
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.
conf (Optional[Dict[str, Any]]) – Arbitrary Spark configuration properties
spark_conn_id – The spark connection id as configured in Airflow administration. When an invalid connection_id is supplied, it will default to yarn.
files (Optional[str]) – 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.
py_files (Optional[str]) – Additional python files used by the job, can be .zip, .egg or .py.
archives (Optional[str]) – Archives that spark should unzip (and possibly tag with #ALIAS) into the application working directory.
driver_class_path (Optional[str]) – Additional, driver-specific, classpath settings.
jars (Optional[str]) – Submit additional jars to upload and place them in executor classpath.
java_class (Optional[str]) – the main class of the Java application
packages (Optional[str]) – Comma-separated list of maven coordinates of jars to include on the driver and executor classpaths
exclude_packages (Optional[str]) – Comma-separated list of maven coordinates of jars to exclude while resolving the dependencies provided in ‘packages’
repositories (Optional[str]) – Comma-separated list of additional remote repositories to search for the maven coordinates given with ‘packages’
total_executor_cores (Optional[int]) – (Standalone & Mesos only) Total cores for all executors (Default: all the available cores on the worker)
executor_cores (Optional[int]) – (Standalone, YARN and Kubernetes only) Number of cores per executor (Default: 2)
executor_memory (Optional[str]) – Memory per executor (e.g. 1000M, 2G) (Default: 1G)
driver_memory (Optional[str]) – Memory allocated to the driver (e.g. 1000M, 2G) (Default: 1G)
keytab (Optional[str]) – Full path to the file that contains the keytab
principal (Optional[str]) – The name of the kerberos principal used for keytab
proxy_user (Optional[str]) – User to impersonate when submitting the application
name (str) – Name of the job (default airflow-spark)
num_executors (Optional[int]) – Number of executors to launch
status_poll_interval (int) – Seconds to wait between polls of driver status in cluster mode (Default: 1)
application_args (Optional[List[Any]]) – Arguments for the application being submitted
env_vars (Optional[Dict[str, Any]]) – Environment variables for spark-submit. It supports yarn and k8s mode too.
verbose (bool) – Whether to pass the verbose flag to spark-submit process for debugging
spark_binary (Optional[str]) – The command to use for spark submit. Some distros may use spark2-submit.
- conn_name_attr = conn_id¶
- default_conn_name = spark_default¶
- conn_type = spark¶
- hook_name = Spark¶
- static get_ui_field_behaviour()¶
Returns custom field behaviour
Returns connection for the hook.
- submit(self, application='', **kwargs)¶
Remote Popen to execute the spark-submit job
application (str) – Submitted application, jar or py file
kwargs (Any) – extra arguments to Popen (see subprocess.Popen)
Kill Spark submit command