pankajastro commented on code in PR #40013:
URL: https://github.com/apache/airflow/pull/40013#discussion_r1624117127
##########
airflow/providers/databricks/operators/databricks.py:
##########
@@ -1178,10 +1118,250 @@ def execute(self, context: Context) -> None:
self.databricks_run_id = workflow_run_metadata.run_id
self.databricks_conn_id = workflow_run_metadata.conn_id
else:
- self.launch_notebook_job()
+ self.launch_job()
if self.wait_for_termination:
self.monitor_databricks_job()
def execute_complete(self, context: dict | None, event: dict) -> None:
run_state = RunState.from_json(event["run_state"])
self._handle_terminal_run_state(run_state)
+
+
+class DatabricksNotebookOperator(DatabricksTaskBaseOperator):
+ """
+ Runs a notebook on Databricks using an Airflow operator.
+
+ The DatabricksNotebookOperator allows users to launch and monitor notebook
job runs on Databricks as
+ Airflow tasks. It can be used as a part of a DatabricksWorkflowTaskGroup
to take advantage of job
+ clusters, which allows users to run their tasks on cheaper clusters that
can be shared between tasks.
+
+ .. seealso::
+ For more information on how to use this operator, take a look at the
guide:
+ :ref:`howto/operator:DatabricksNotebookOperator`
+
+ :param notebook_path: The path to the notebook in Databricks.
+ :param source: Optional location type of the notebook. When set to
WORKSPACE, the notebook will be retrieved
+ from the local Databricks workspace. When set to GIT, the notebook
will be retrieved from a Git repository
+ defined in git_source. If the value is empty, the task will use
GIT if git_source is defined
+ and WORKSPACE otherwise. For more information please visit
+
https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsCreate
+ :param databricks_conn_id: The name of the Airflow connection to use.
+ :param databricks_retry_args: An optional dictionary with arguments passed
to ``tenacity.Retrying`` class.
+ :param databricks_retry_delay: Number of seconds to wait between retries.
+ :param databricks_retry_limit: Amount of times to retry if the Databricks
backend is unreachable.
+ :param deferrable: Whether to run the operator in the deferrable mode.
+ :param existing_cluster_id: ID for existing cluster on which to run this
task.
+ :param job_cluster_key: The key for the job cluster.
+ :param new_cluster: Specs for a new cluster on which this task will be run.
+ :param notebook_packages: A list of the Python libraries to be installed
on the cluster running the
+ notebook.
+ :param notebook_params: A dict of key-value pairs to be passed as optional
params to the notebook task.
+ :param polling_period_seconds: Controls the rate which we poll for the
result of this notebook job run.
+ :param wait_for_termination: if we should wait for termination of the job
run. ``True`` by default.
+ """
+
+ template_fields = (
+ "notebook_params",
+ "workflow_run_metadata",
+ )
+ CALLER = "DatabricksNotebookOperator"
+
+ def __init__(
+ self,
+ notebook_path: str,
+ source: str,
+ databricks_conn_id: str = "databricks_default",
+ databricks_retry_args: dict[Any, Any] | None = None,
+ databricks_retry_delay: int = 1,
+ databricks_retry_limit: int = 3,
+ deferrable: bool = conf.getboolean("operators", "default_deferrable",
fallback=False),
+ existing_cluster_id: str = "",
+ job_cluster_key: str = "",
+ new_cluster: dict[str, Any] | None = None,
+ notebook_packages: list[dict[str, Any]] | None = None,
+ notebook_params: dict | None = None,
+ polling_period_seconds: int = 5,
+ wait_for_termination: bool = True,
+ workflow_run_metadata: dict | None = None,
+ **kwargs: Any,
+ ):
+ self.notebook_path = notebook_path
+ self.source = source
+ self.databricks_conn_id = databricks_conn_id
+ self.databricks_retry_args = databricks_retry_args
+ self.databricks_retry_delay = databricks_retry_delay
+ self.databricks_retry_limit = databricks_retry_limit
+ self.databricks_run_id: int | None = None
+ self.deferrable = deferrable
Review Comment:
wondering if we can avoid setting these param here since anyway you are
setting in supper class?
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