DatabricksRunNowOperator¶

Use the DatabricksRunNowOperator to trigger a run of an existing Databricks job via api/2.1/jobs/run-now API endpoint.

Using the Operator¶

There are two ways to instantiate this operator. In the first way, you can take the JSON payload that you typically use to call the api/2.1/jobs/run-now endpoint and pass it directly to our DatabricksRunNowOperator through the json parameter.

Another way to accomplish the same thing is to use the named parameters of the DatabricksRunNowOperator directly. Note that there is exactly one named parameter for each top level parameter in the jobs/run-now endpoint.

Parameter	Input
job_id: str	ID of the existing Databricks jobs (required if `job_name` isn't provided).
job_name: str	Name of the existing Databricks job (required if `job_id` isn't provided). It will throw exception if job isn't found, of if there are multiple jobs with the same name.
jar_params: list[str]	A list of parameters for jobs with JAR tasks, e.g. `"jar_params": ["john doe", "35"]`. The parameters will be passed to JAR file as command line parameters. If specified upon run-now, it would overwrite the parameters specified in job setting. The json representation of this field (i.e. `{"jar_params":["john doe","35"]}`) cannot exceed 10,000 bytes. This field will be templated.
notebook_params: dict[str,str]	A dict from keys to values for jobs with notebook task, e.g.``"notebook_params": {"name": "john doe", "age": "35"}```. The map is passed to the notebook and will be accessible through the `dbutils.widgets.get function`. See Widgets for more information. If not specified upon run-now, the triggered run will use the job’s base parameters. `notebook_params` cannot be specified in conjunction with `jar_params`. The json representation of this field (i.e. `{"notebook_params":{"name":"john doe","age":"35"}}`) cannot exceed 10,000 bytes. This field will be templated.
python_params: list[str]	A list of parameters for jobs with python tasks, e.g. `"python_params": ["john doe", "35"]`. The parameters will be passed to python file as command line parameters. If specified upon run-now, it would overwrite the parameters specified in job setting. The json representation of this field (i.e. `{"python_params":["john doe","35"]}`) cannot exceed 10,000 bytes. This field will be templated.
spark_submit_params: list[str]	A list of parameters for jobs with spark submit task, e.g. `"spark_submit_params": ["--class", "org.apache.spark.examples.SparkPi"]`. The parameters will be passed to spark-submit script as command line parameters. If specified upon run-now, it would overwrite the parameters specified in job setting. The json representation of this field cannot exceed 10,000 bytes. This field will be templated.
timeout_seconds: int	The timeout for this run. By default a value of 0 is used which means to have no timeout. This field will be templated.
databricks_conn_id: string	the name of the Airflow connection to use
polling_period_seconds: integer	controls the rate which we poll for the result of this run
databricks_retry_limit: integer	amount of times retry if the Databricks backend is unreachable
databricks_retry_delay: decimal	number of seconds to wait between retries
databricks_retry_args: dict	An optional dictionary with arguments passed to `tenacity.Retrying` class.
do_xcom_push: boolean	whether we should push run_id and run_page_url to xcom