Trigger a new job run. — run_job

Run a job and return the run_id of the triggered run.

Usage

run_job_now(
  client,
  job_id,
  dbt_commands = NULL,
  idempotency_token = NULL,
  jar_params = NULL,
  job_parameters = NULL,
  notebook_params = NULL,
  pipeline_params = NULL,
  python_named_params = NULL,
  python_params = NULL,
  queue = NULL,
  spark_submit_params = NULL,
  sql_params = NULL
)

jobsRunNow(
  client,
  job_id,
  dbt_commands = NULL,
  idempotency_token = NULL,
  jar_params = NULL,
  job_parameters = NULL,
  notebook_params = NULL,
  pipeline_params = NULL,
  python_named_params = NULL,
  python_params = NULL,
  queue = NULL,
  spark_submit_params = NULL,
  sql_params = NULL
)

Arguments

client: Required. Instance of DatabricksClient()
job_id: Required. The ID of the job to be executed.
dbt_commands: An array of commands to execute for jobs with the dbt task, for example 'dbt_commands': ['dbt deps', 'dbt seed', 'dbt run'].
idempotency_token: An optional token to guarantee the idempotency of job run requests.
jar_params: A list of parameters for jobs with Spark JAR tasks, for example 'jar_params': ['john doe', '35'].
job_parameters: Job-level parameters used in the run.
notebook_params: A map from keys to values for jobs with notebook task, for example 'notebook_params': {'name': 'john doe', 'age': '35'}.
pipeline_params: This field has no description yet.
python_named_params: A map from keys to values for jobs with Python wheel task, for example 'python_named_params': {'name': 'task', 'data': 'dbfs:/path/to/data.json'}.
python_params: A list of parameters for jobs with Python tasks, for example 'python_params': ['john doe', '35'].
queue: The queue settings of the run.
spark_submit_params: A list of parameters for jobs with spark submit task, for example 'spark_submit_params': ['--class', 'org.apache.spark.examples.SparkPi'].
sql_params: A map from keys to values for jobs with SQL task, for example 'sql_params': {'name': 'john doe', 'age': '35'}.