View source: R/create_and_run_job.R
create_and_run_job | R Documentation |
Single function to both create a job and immediately run it. Each call
will register a new job in the Databricks Jobs UI, so for subsequent runs
it is best to submit the job_id to run_job
.
create_and_run_job( name = "R Job", file = NULL, notebook_path, job_config = "default", workspace, token = NULL, ... )
name |
A string representing the name of the job. It is encouraged to choose a unique name for each job. |
file |
The path to a local .R or .Rmd file. Will be imported to the workspace at the notebook_path. |
notebook_path |
A string representing the path to a Databricks notebook in the workspace. |
job_config |
A JSON formatted string or file specifying the details of the job, i.e., the name, cluster spec, and so on. |
workspace |
A string representing the web workspace of your Databricks instance. E.g., "https://eastus2.azuredatabricks.net" or "https://demo.cloud.databricks.com". |
token |
A valid authentication token generated via User Settings in Databricks or via the Databricks REST API 2.0. If none is provided, netrc will be used. |
... |
additional arguments to be passed, i.e., overwrite = 'false' when importing a file to run as a job. |
Uses '2.0/jobs/create', '2.0/jobs/run-now' and '2.0/runs/get' API endpoints. For all details on API calls please see the official documentation at https://docs.databricks.com/dev-tools/api/latest/.
A list with three elements containing the values of create_job
,
run_job
, and get_run_status
:
job - The full API response, including status code.
run - The JSON result.
run_status - The JSON result transformed into a list.
results <- create_and_run_job(name = "Forecasting Report", notebook_path = "/Shared/forecasting_report_notebook". workspace = "https://eastus2.azuredatabricks.net", token = "dapi2930482309ddavascscq") # Get each response job <- results$job run <- results$run run_status <- results$run_status
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