DatabricksRunNowOperator

Databricks

Runs an existing Spark job run to Databricks using the api/2.0/jobs/run-now API endpoint.

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Last Updated: Apr. 29, 2021

Access Instructions

Install the Databricks provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.

Parameters

job_idstrthe job_id of the existing Databricks job. This field will be templated.
jsondictA JSON object containing API parameters which will be passed directly to the api/2.0/jobs/run-now endpoint. The other named parameters (i.e. notebook_params, spark_submit_params..) to this operator will be merged with this json dictionary if they are provided. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys. (templated)
notebook_paramsdictA 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_paramslist[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_paramslist[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_secondsint32The 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_idstrThe name of the Airflow connection to use. By default and in the common case this will be databricks_default. To use token based authentication, provide the key token in the extra field for the connection and create the key host and leave the host field empty.
polling_period_secondsintControls the rate which we poll for the result of this run. By default the operator will poll every 30 seconds.
databricks_retry_limitintAmount of times retry if the Databricks backend is unreachable. Its value must be greater than or equal to 1.
do_xcom_pushboolWhether we should push run_id and run_page_url to xcom.

Documentation

Runs an existing Spark job run to Databricks using the api/2.0/jobs/run-now API endpoint.

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/2.0/jobs/run-now endpoint and pass it directly to our DatabricksRunNowOperator through the json parameter. For example

json = {
"job_id": 42,
"notebook_params": {
"dry-run": "true",
"oldest-time-to-consider": "1457570074236"
}
}
notebook_run = DatabricksRunNowOperator(task_id='notebook_run', json=json)

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 run-now endpoint. In this method, your code would look like this:

job_id=42
notebook_params = {
"dry-run": "true",
"oldest-time-to-consider": "1457570074236"
}
python_params = ["douglas adams", "42"]
spark_submit_params = ["--class", "org.apache.spark.examples.SparkPi"]
notebook_run = DatabricksRunNowOperator(
job_id=job_id,
notebook_params=notebook_params,
python_params=python_params,
spark_submit_params=spark_submit_params
)

In the case where both the json parameter AND the named parameters are provided, they will be merged together. If there are conflicts during the merge, the named parameters will take precedence and override the top level json keys.

Currently the named parameters that DatabricksRunNowOperator supports are
  • job_id

  • json

  • notebook_params

  • python_params

  • spark_submit_params

Example DAGs

Improve this module by creating an example DAG.

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  1. Add an `example_dags` directory to the top-level source of the provider package with an empty `__init__.py` file.
  2. Add your DAG to this directory. Be sure to include a well-written and descriptive docstring
  3. Create a pull request against the source code. Once the package gets released, your DAG will show up on the Registry.

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