# Run Now

Launch stage: GA

`POST /api/2.2/jobs/run-now`

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

API scopes: jobs

## Request body

- `job_id` (int64, optional)
  The ID of the job to be executed
  Example: `11223344`
- `job_parameters` (object, optional)
  Job-level parameters used in the run. for example `"param": "overriding_val"`
- `idempotency_token` (string, optional)
  An optional token to guarantee the idempotency of job run requests. If a run with the provided token already exists,
   the request does not create a new run but returns the ID of the existing run instead. If a run with the provided token is deleted,
   an error is returned.
  
   If you specify the idempotency token, upon failure you can retry until the request succeeds. <Databricks> guarantees that exactly one run
   is launched with that idempotency token.
  
   This token must have at most 64 characters.
  Example: `8f018174-4792-40d5-bcbc-3e6a527352c8`
- `queue` (object, optional)
  The queue settings of the run.
  - `enabled` (boolean, optional)
    If true, enable queueing for the job. This is a required field.
    Default: `true`
    Example: `true`
- `only` (array of string, optional)
  A list of task keys to run inside of the job. If this field is not provided, all tasks in the job will be run.
  
   Prefix a task key with `+` to also run its upstream tasks, or suffix it with `+` to also run its downstream tasks.
   For example, `+my_task` runs `my_task` and everything upstream of it, `my_task+` runs `my_task` and everything
   downstream of it, and `+my_task+` runs both. A task key with no `+` runs only that task.
  Example: `notebook_task_1`
- `performance_target` (string, optional)
  The performance mode on a serverless job. The performance target determines the level of compute performance or cost-efficiency for the run. This field overrides the performance target defined on the job level.
  
   * `STANDARD`: Enables cost-efficient execution of serverless workloads.
   * `PERFORMANCE_OPTIMIZED`: Prioritizes fast startup and execution times through rapid scaling and optimized cluster performance.
  Possible values: `PERFORMANCE_TARGET_UNSPECIFIED`, `PERFORMANCE_OPTIMIZED`, `STANDARD`
- `pipeline_params` (object, optional)
  Controls whether the pipeline should perform a full refresh
  - `full_refresh` (boolean, optional)
    If true, triggers a full refresh on the spark declarative pipeline.
    Default: `false`
  - `refresh_selection` (array of string, optional, Beta)
    A list of tables to update without fullRefresh.
  - `full_refresh_selection` (array of string, optional, Beta)
    A list of tables to update with fullRefresh.
  - `reset_checkpoint_selection` (array of string, optional, Beta)
    A list of streaming flows to reset checkpoints without clearing data.
  - `refresh_flow_selection` (array of string, optional, Beta)
    Flow names to selectively refresh. These are unioned with other selective refresh
     options (refresh_selection, full_refresh_selection) to determine the final set of flows to refresh.

## Returns

- `run_id` (int64, optional)
  The globally unique ID of the newly triggered run.
  Example: `455644833`
- `number_in_job` (int64, optional)
  A unique identifier for this job run. This is set to the same value as `run_id`.
  Example: `455644833`

## Response

```json
{
  "run_id": 455644833,
  "number_in_job": 455644833
}
```