airflow.providers.apache.spark.operators.spark_submit¶
Module Contents¶
Classes¶
Wrap the spark-submit binary to kick off a spark-submit job; requires "spark-submit" binary in the PATH. |
- class airflow.providers.apache.spark.operators.spark_submit.SparkSubmitOperator(*, application='', 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='arrow-spark', num_executors=None, status_poll_interval=1, application_args=None, env_vars=None, verbose=False, spark_binary=None, properties_file=None, yarn_queue=None, deploy_mode=None, use_krb5ccache=False, **kwargs)[source]¶
Bases:
airflow.models.BaseOperatorWrap the spark-submit binary to kick off a spark-submit job; requires “spark-submit” binary in the PATH.
See also
For more information on how to use this operator, take a look at the guide: SparkSubmitOperator
- Parameters
application (str) – The application that submitted as a job, either jar or py file. (templated)
conf (dict[str, Any] | None) – Arbitrary Spark configuration properties (templated)
conn_id (str) – The spark connection id as configured in Airflow administration. When an invalid connection_id is supplied, it will default to yarn.
files (str | None) – 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)
py_files (str | None) – Additional python files used by the job, can be .zip, .egg or .py. (templated)
jars (str | None) – Submit additional jars to upload and place them in executor classpath. (templated)
driver_class_path (str | None) – Additional, driver-specific, classpath settings. (templated)
java_class (str | None) – the main class of the Java application
packages (str | None) – Comma-separated list of maven coordinates of jars to include on the driver and executor classpaths. (templated)
exclude_packages (str | None) – Comma-separated list of maven coordinates of jars to exclude while resolving the dependencies provided in ‘packages’ (templated)
repositories (str | None) – Comma-separated list of additional remote repositories to search for the maven coordinates given with ‘packages’
total_executor_cores (int | None) – (Standalone & Mesos only) Total cores for all executors (Default: all the available cores on the worker)
executor_cores (int | None) – (Standalone & YARN only) Number of cores per executor (Default: 2)
executor_memory (str | None) – Memory per executor (e.g. 1000M, 2G) (Default: 1G)
driver_memory (str | None) – Memory allocated to the driver (e.g. 1000M, 2G) (Default: 1G)
keytab (str | None) – Full path to the file that contains the keytab (templated) (will overwrite any keytab defined in the connection’s extra JSON)
principal (str | None) – The name of the kerberos principal used for keytab (templated) (will overwrite any principal defined in the connection’s extra JSON)
proxy_user (str | None) – User to impersonate when submitting the application (templated)
name (str) – Name of the job (default airflow-spark). (templated)
num_executors (int | None) – Number of executors to launch
status_poll_interval (int) – Seconds to wait between polls of driver status in cluster mode (Default: 1)
application_args (list[Any] | None) – Arguments for the application being submitted (templated)
env_vars (dict[str, Any] | None) – Environment variables for spark-submit. It supports yarn and k8s mode too. (templated)
verbose (bool) – Whether to pass the verbose flag to spark-submit process for debugging
spark_binary (str | None) – The command to use for spark submit. Some distros may use spark2-submit or spark3-submit. (will overwrite any spark_binary defined in the connection’s extra JSON)
properties_file (str | None) – Path to a file from which to load extra properties. If not specified, this will look for conf/spark-defaults.conf.
yarn_queue (str | None) – The name of the YARN queue to which the application is submitted. (will overwrite any yarn queue defined in the connection’s extra JSON)
deploy_mode (str | None) – Whether to deploy your driver on the worker nodes (cluster) or locally as a client. (will overwrite any deployment mode defined in the connection’s extra JSON)
use_krb5ccache (bool) – if True, configure spark to use ticket cache instead of relying on keytab for Kerberos login