`prefect_databricks.jobs`

This is a module containing tasks for interacting with: Databricks jobs

Functions

`jobs_runs_export`

jobs_runs_export(run_id: int, databricks_credentials: 'DatabricksCredentials', views_to_export: Optional['models.ViewsToExport'] = None) -> Dict[str, Any]

Export and retrieve the job run task. Args:

run_id: The canonical identifier for the run. This field is required.
databricks_credentials: Credentials to use for authentication with Databricks.
views_to_export: Which views to export (CODE, DASHBOARDS, or ALL). Defaults to CODE.

Returns:

Upon success, a dict of the response.
views: List["models.ViewItem"]

API Endpoint:

/2.0/jobs/runs/export

API Responses:

Response	Description
200	Run was exported successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_create`

jobs_create(databricks_credentials: 'DatabricksCredentials', name: str = 'Untitled', tags: Dict = None, tasks: Optional[List['models.JobTaskSettings']] = None, job_clusters: Optional[List['models.JobCluster']] = None, email_notifications: 'models.JobEmailNotifications' = None, webhook_notifications: 'models.WebhookNotifications' = None, timeout_seconds: Optional[int] = None, schedule: 'models.CronSchedule' = None, max_concurrent_runs: Optional[int] = None, git_source: 'models.GitSource' = None, format: Optional[str] = None, access_control_list: Optional[List['models.AccessControlRequest']] = None, parameters: Optional[List['models.JobParameter']] = None) -> Dict[str, Any]

Create a new job. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
name: An optional name for the job, e.g. A multitask job.
tags: A map of tags associated with the job. These are forwarded to the cluster as cluster tags for jobs clusters, and are subject to the same limitations as cluster tags. A maximum of 25 tags can be added to the job, e.g.

{"cost-center"\: "engineering", "team"\: "jobs"}

tasks: A list of task specifications to be executed by this job, e.g.

[
    {
        "task_key"\: "Sessionize",
        "description"\: "Extracts session data from events",
        "depends_on"\: [],
        "existing_cluster_id"\: "0923-164208-meows279",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.Sessionize",
            "parameters"\: ["--data", "dbfs\:/path/to/data.json"],
        },
        "libraries"\: [{"jar"\: "dbfs\:/mnt/databricks/Sessionize.jar"}],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Orders_Ingest",
        "description"\: "Ingests order data",
        "depends_on"\: [],
        "job_cluster_key"\: "auto_scaling_cluster",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.OrdersIngest",
            "parameters"\: ["--data", "dbfs\:/path/to/order-data.json"],
        },
        "libraries"\: [{"jar"\: "dbfs\:/mnt/databricks/OrderIngest.jar"}],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Match",
        "description"\: "Matches orders with user sessions",
        "depends_on"\: [
            {"task_key"\: "Orders_Ingest"},
            {"task_key"\: "Sessionize"},
        ],
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {"min_workers"\: 2, "max_workers"\: 16},
        },
        "notebook_task"\: {
            "notebook_path"\: "/Users/user.name@databricks.com/Match",
            "source"\: "WORKSPACE",
            "base_parameters"\: {"name"\: "John Doe", "age"\: "35"},
        },
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
]

job_clusters: A list of job cluster specifications that can be shared and reused by tasks of this job. Libraries cannot be declared in a shared job cluster. You must declare dependent libraries in task settings, e.g.

[
    {
        "job_cluster_key"\: "auto_scaling_cluster",
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {"min_workers"\: 2, "max_workers"\: 16},
        },
    }
]

email_notifications: An optional set of email addresses that is notified when runs of this job begin or complete as well as when this job is deleted. The default behavior is to not send any emails. Key-values:
on_start: A list of email addresses to be notified when a run begins. If not specified on job creation, reset, or update, the list is empty, and notifications are not sent, e.g.
```
["user.name@databricks.com"]
```
on_success: A list of email addresses to be notified when a run successfully completes. A run is considered to have completed successfully if it ends with a TERMINATED life_cycle_state and a SUCCESSFUL result_state. If not specified on job creation, reset, or update, the list is empty, and notifications are not sent, e.g.
```
["user.name@databricks.com"]
```
on_failure: A list of email addresses to notify when a run completes unsuccessfully. A run is considered unsuccessful if it ends with an INTERNAL_ERROR life_cycle_state or a SKIPPED, FAILED, or TIMED_OUT result_state. If not specified on job creation, reset, or update, or the list is empty, then notifications are not sent. Job-level failure notifications are sent only once after the entire job run (including all of its retries) has failed. Notifications are not sent when failed job runs are retried. To receive a failure notification after every failed task (including every failed retry), use task-level notifications instead, e.g.
```
["user.name@databricks.com"]
```
no_alert_for_skipped_runs: If true, do not send email to recipients specified in on_failure if the run is skipped.
webhook_notifications: A collection of system notification IDs to notify when runs of this job begin or complete. The default behavior is to not send any system notifications. Key-values:
on_start: An optional list of notification IDs to call when the run starts. A maximum of 3 destinations can be specified for the on_start property, e.g.
```
[
    {"id"\: "03dd86e4-57ef-4818-a950-78e41a1d71ab"},
    {"id"\: "0481e838-0a59-4eff-9541-a4ca6f149574"},
]
```
on_success: An optional list of notification IDs to call when the run completes successfully. A maximum of 3 destinations can be specified for the on_success property, e.g.
```
[{"id"\: "03dd86e4-57ef-4818-a950-78e41a1d71ab"}]
```
on_failure: An optional list of notification IDs to call when the run fails. A maximum of 3 destinations can be specified for the on_failure property, e.g.
```
[{"id"\: "0481e838-0a59-4eff-9541-a4ca6f149574"}]
```
timeout_seconds: An optional timeout applied to each run of this job. The default behavior is to have no timeout, e.g. 86400.
schedule: An optional periodic schedule for this job. The default behavior is that the job only runs when triggered by clicking “Run Now” in the Jobs UI or sending an API request to runNow. Key-values:
quartz_cron_expression: A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron Trigger](http://www.quartz- scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) for details. This field is required, e.g. 20 30 * * * ?.
timezone_id: A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See Java TimeZone for details. This field is required, e.g. Europe/London.
pause_status: Indicate whether this schedule is paused or not, e.g. PAUSED.
max_concurrent_runs: An optional maximum allowed number of concurrent runs of the job. Set this value if you want to be able to execute multiple runs of the same job concurrently. This is useful for example if you trigger your job on a frequent schedule and want to allow consecutive runs to overlap with each other, or if you want to trigger multiple runs which differ by their input parameters. This setting affects only new runs. For example, suppose the job’s concurrency is 4 and there are 4 concurrent active runs. Then setting the concurrency to 3 won’t kill any of the active runs. However, from then on, new runs are skipped unless there are fewer than 3 active runs. This value cannot exceed 1000. Setting this value to 0 causes all new runs to be skipped. The default behavior is to allow only 1 concurrent run, e.g. 10.
git_source: This functionality is in Public Preview. An optional specification for a remote repository containing the notebooks used by this job’s notebook tasks, e.g.

{
    "git_url"\: "https\://github.com/databricks/databricks-cli",
    "git_branch"\: "main",
    "git_provider"\: "gitHub",
}
``` Key-values\:
- git_url\:
    URL of the repository to be cloned by this job. The maximum
    length is 300 characters, e.g.
    `https\://github.com/databricks/databricks-cli`.
- git_provider\:
    Unique identifier of the service used to host the Git
    repository. The value is case insensitive, e.g. `github`.
- git_branch\:
    Name of the branch to be checked out and used by this job.
    This field cannot be specified in conjunction with git_tag
    or git_commit. The maximum length is 255 characters, e.g.
    `main`.
- git_tag\:
    Name of the tag to be checked out and used by this job. This
    field cannot be specified in conjunction with git_branch or
    git_commit. The maximum length is 255 characters, e.g.
    `release-1.0.0`.
- git_commit\:
    Commit to be checked out and used by this job. This field
    cannot be specified in conjunction with git_branch or
    git_tag. The maximum length is 64 characters, e.g.
    `e0056d01`.
- git_snapshot\:
    Read-only state of the remote repository at the time the job was run.
                This field is only included on job runs.
- `format`: 
Used to tell what is the format of the job. This field is ignored in
Create/Update/Reset calls. When using the Jobs API 2.1 this
value is always set to `'MULTI_TASK'`, e.g. `MULTI_TASK`.
- `access_control_list`: 
List of permissions to set on the job.
- `parameters`: 
Job-level parameter definitions.

**Returns:**
- Upon success, a dict of the response. 
- `job_id: int`

#### API Endpoint:
`/2.1/jobs/create`

#### API Responses:
| Response | Description |
| --- | --- |
| 200 | Job was created successfully. |
| 400 | The request was malformed. See JSON response for error details. |
| 401 | The request was unauthorized. |
| 500 | The request was not handled correctly due to a server error. |


### `jobs_delete` <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/integrations/prefect-databricks/prefect_databricks/jobs.py#L393" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python
jobs_delete(databricks_credentials: 'DatabricksCredentials', job_id: Optional[int] = None) -> Dict[str, Any]

Deletes a job. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
job_id: The canonical identifier of the job to delete. This field is required, e.g. 11223344.

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/delete

API Responses:

Response	Description
200	Job was deleted successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_get`

jobs_get(job_id: int, databricks_credentials: 'DatabricksCredentials') -> Dict[str, Any]

Retrieves the details for a single job. Args:

job_id: The canonical identifier of the job to retrieve information about. This field is required.
databricks_credentials: Credentials to use for authentication with Databricks.

Returns:

Upon success, a dict of the response.
job_id: int
creator_user_name: str
run_as_user_name: str
settings: "models.JobSettings"
created_time: int

API Endpoint:

/2.1/jobs/get

API Responses:

Response	Description
200	Job was retrieved successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_list`

jobs_list(databricks_credentials: 'DatabricksCredentials', limit: int = 20, offset: int = 0, name: Optional[str] = None, expand_tasks: bool = False) -> Dict[str, Any]

Retrieves a list of jobs. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
limit: The number of jobs to return. This value must be greater than 0 and less or equal to 25. The default value is 20.
offset: The offset of the first job to return, relative to the most recently created job.
name: A filter on the list based on the exact (case insensitive) job name.
expand_tasks: Whether to include task and cluster details in the response.

Returns:

Upon success, a dict of the response.
jobs: List["models.Job"]
has_more: bool

API Endpoint:

/2.1/jobs/list

API Responses:

Response	Description
200	List of jobs was retrieved successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_reset`

jobs_reset(databricks_credentials: 'DatabricksCredentials', job_id: Optional[int] = None, new_settings: 'models.JobSettings' = None) -> Dict[str, Any]

Overwrites all the settings for a specific job. Use the Update endpoint to update job settings partially. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
job_id: The canonical identifier of the job to reset. This field is required, e.g. 11223344.
new_settings: The new settings of the job. These settings completely replace the old settings. Changes to the field JobSettings.timeout_seconds are applied to active runs. Changes to other fields are applied to future runs only. Key-values:
name: An optional name for the job, e.g. A multitask job.
tags: A map of tags associated with the job. These are forwarded to the cluster as cluster tags for jobs clusters, and are subject to the same limitations as cluster tags. A maximum of 25 tags can be added to the job, e.g.
```
{"cost-center"\: "engineering", "team"\: "jobs"}
```

tasks: A list of task specifications to be executed by this job, e.g.

[
    {
        "task_key"\: "Sessionize",
        "description"\: "Extracts session data from events",
        "depends_on"\: [],
        "existing_cluster_id"\: "0923-164208-meows279",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.Sessionize",
            "parameters"\: [
                "--data",
                "dbfs\:/path/to/data.json",
            ],
        },
        "libraries"\: [
            {"jar"\: "dbfs\:/mnt/databricks/Sessionize.jar"}
        ],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Orders_Ingest",
        "description"\: "Ingests order data",
        "depends_on"\: [],
        "job_cluster_key"\: "auto_scaling_cluster",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.OrdersIngest",
            "parameters"\: [
                "--data",
                "dbfs\:/path/to/order-data.json",
            ],
        },
        "libraries"\: [
            {"jar"\: "dbfs\:/mnt/databricks/OrderIngest.jar"}
        ],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Match",
        "description"\: "Matches orders with user sessions",
        "depends_on"\: [
            {"task_key"\: "Orders_Ingest"},
            {"task_key"\: "Sessionize"},
        ],
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {
                "min_workers"\: 2,
                "max_workers"\: 16,
            },
        },
        "notebook_task"\: {
            "notebook_path"\: "/Users/user.name@databricks.com/Match",
            "source"\: "WORKSPACE",
            "base_parameters"\: {
                "name"\: "John Doe",
                "age"\: "35",
            },
        },
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
]

job_clusters: A list of job cluster specifications that can be shared and reused by tasks of this job. Libraries cannot be declared in a shared job cluster. You must declare dependent libraries in task settings, e.g.

[
    {
        "job_cluster_key"\: "auto_scaling_cluster",
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {
                "min_workers"\: 2,
                "max_workers"\: 16,
            },
        },
    }
]

email_notifications: An optional set of email addresses that is notified when runs of this job begin or complete as well as when this job is deleted. The default behavior is to not send any emails.
webhook_notifications: A collection of system notification IDs to notify when runs of this job begin or complete. The default behavior is to not send any system notifications.
timeout_seconds: An optional timeout applied to each run of this job. The default behavior is to have no timeout, e.g. 86400.
schedule: An optional periodic schedule for this job. The default behavior is that the job only runs when triggered by clicking “Run Now” in the Jobs UI or sending an API request to runNow.
max_concurrent_runs: An optional maximum allowed number of concurrent runs of the job. Set this value if you want to be able to execute multiple runs of the same job concurrently. This is useful for example if you trigger your job on a frequent schedule and want to allow consecutive runs to overlap with each other, or if you want to trigger multiple runs which differ by their input parameters. This setting affects only new runs. For example, suppose the job’s concurrency is 4 and there are 4 concurrent active runs. Then setting the concurrency to 3 won’t kill any of the active runs. However, from then on, new runs are skipped unless there are fewer than 3 active runs. This value cannot exceed 1000. Setting this value to 0 causes all new runs to be skipped. The default behavior is to allow only 1 concurrent run, e.g. 10.
git_source: This functionality is in Public Preview. An optional specification for a remote repository containing the notebooks used by this job’s notebook tasks, e.g.
```
{
    "git_url"\: "https\://github.com/databricks/databricks-cli",
    "git_branch"\: "main",
    "git_provider"\: "gitHub",
}
```
format: Used to tell what is the format of the job. This field is ignored in Create/Update/Reset calls. When using the Jobs API 2.1 this value is always set to 'MULTI_TASK', e.g. MULTI_TASK.
job_settings: Job-level parameter definitions.

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/reset

API Responses:

Response	Description
200	Job was overwritten successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_run_now`

jobs_run_now(databricks_credentials: 'DatabricksCredentials', job_id: Optional[int] = None, idempotency_token: Optional[str] = None, jar_params: Optional[List[str]] = None, notebook_params: Optional[Dict] = None, python_params: Optional[List[str]] = None, spark_submit_params: Optional[List[str]] = None, python_named_params: Optional[Dict] = None, pipeline_params: Optional[str] = None, sql_params: Optional[Dict] = None, dbt_commands: Optional[List] = None, job_parameters: Optional[Dict] = None) -> Dict[str, Any]

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

databricks_credentials: Credentials to use for authentication with Databricks.
job_id: The ID of the job to be executed, e.g. 11223344.
idempotency_token: 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. For more information, see [How to ensure idempotency for jobs](https://kb.databricks.com/jobs/jobs- idempotency.html), e.g. 8f018174-4792-40d5-bcbc-3e6a527352c8.
jar_params: A list of parameters for jobs with Spark JAR tasks, for example 'jar_params'\: ['john doe', '35']. The parameters are used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it defaults to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (for example {'jar_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs, e.g.

["john", "doe", "35"]

notebook_params: A map from keys to values for jobs with notebook task, for example 'notebook_params'\: {'name'\: 'john doe', 'age'\: '35'}. The map is passed to the notebook and is accessible through the [dbutils.widgets.get](https://docs.databricks.com/dev- tools/databricks-utils.html dbutils-widgets) function. If not specified upon run-now, the triggered run uses the job’s base parameters. notebook_params cannot be specified in conjunction with jar_params. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. The JSON representation of this field (for example {'notebook_params'\:{'name'\:'john doe','age'\:'35'}}) cannot exceed 10,000 bytes, e.g.

{"name"\: "john doe", "age"\: "35"}

python_params: A list of parameters for jobs with Python tasks, for example 'python_params'\: ['john doe', '35']. The parameters are 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 (for example {'python_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis, e.g.

["john doe", "35"]

spark_submit_params: A list of parameters for jobs with spark submit task, for example 'spark_submit_params'\: ['--class', 'org.apache.spark.examples.SparkPi']. The parameters are 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 (for example {'python_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis, e.g.

["--class", "org.apache.spark.examples.SparkPi"]

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'}, e.g.

{"name"\: "task", "data"\: "dbfs\:/path/to/data.json"}

pipeline_params:
sql_params: A map from keys to values for SQL tasks, for example 'sql_params'\: {'name'\: 'john doe', 'age'\: '35'}. The SQL alert task does not support custom parameters, e.g.

{"name"\: "john doe", "age"\: "35"}

dbt_commands: An array of commands to execute for jobs with the dbt task, for example 'dbt_commands'\: ['dbt deps', 'dbt seed', 'dbt run'], e.g.

["dbt deps", "dbt seed", "dbt run"]

job_parameters: A map from keys to values for job-level parameters used in the run, for example 'job_parameters'\: {'param'\: 'overriding_val'}, e.g.

{"param"\: "overriding_val"}

Returns:

Upon success, a dict of the response.
run_id: int
number_in_job: int

API Endpoint:

/2.1/jobs/run-now

API Responses:

Response	Description
200	Run was started successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_cancel`

jobs_runs_cancel(databricks_credentials: 'DatabricksCredentials', run_id: Optional[int] = None) -> Dict[str, Any]

Cancels a job run. The run is canceled asynchronously, so it may still be running when this request completes. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
run_id: This field is required, e.g. 455644833.

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/runs/cancel

API Responses:

Response	Description
200	Run was cancelled successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_cancel_all`

jobs_runs_cancel_all(databricks_credentials: 'DatabricksCredentials', job_id: Optional[int] = None) -> Dict[str, Any]

Cancels all active runs of a job. The runs are canceled asynchronously, so it doesn’t prevent new runs from being started. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
job_id: The canonical identifier of the job to cancel all runs of. This field is required, e.g. 11223344.

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/runs/cancel-all

API Responses:

Response	Description
200	All runs were cancelled successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_delete`

jobs_runs_delete(databricks_credentials: 'DatabricksCredentials', run_id: Optional[int] = None) -> Dict[str, Any]

Deletes a non-active run. Returns an error if the run is active. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
run_id: The canonical identifier of the run for which to retrieve the metadata, e.g. 455644833.

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/runs/delete

API Responses:

Response	Description
200	Run was deleted successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_get`

jobs_runs_get(run_id: int, databricks_credentials: 'DatabricksCredentials', include_history: Optional[bool] = None) -> Dict[str, Any]

Retrieve the metadata of a run. Args:

run_id: The canonical identifier of the run for which to retrieve the metadata. This field is required.
databricks_credentials: Credentials to use for authentication with Databricks.
include_history: Whether to include the repair history in the response.

Returns:

Upon success, a dict of the response.
job_id: int
run_id: int
number_in_job: int
creator_user_name: str
original_attempt_run_id: int
state: "models.RunState"
schedule: "models.CronSchedule"
tasks: List["models.RunTask"]
job_clusters: List["models.JobCluster"]
cluster_spec: "models.ClusterSpec"
cluster_instance: "models.ClusterInstance"
git_source: "models.GitSource"
overriding_parameters: "models.RunParameters"
start_time: int
setup_duration: int
execution_duration: int
cleanup_duration: int
end_time: int
trigger: "models.TriggerType"
run_name: str
run_page_url: str
run_type: "models.RunType"
attempt_number: int
repair_history: List["models.RepairHistoryItem"]
job_parameters: List["models.RunJobParameter]"

API Endpoint:

/2.1/jobs/runs/get

API Responses:

Response	Description
200	Run was retrieved successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_get_output`

jobs_runs_get_output(run_id: int, databricks_credentials: 'DatabricksCredentials') -> Dict[str, Any]

Retrieve the output and metadata of a single task run. When a notebook task returns a value through the dbutils.notebook.exit() call, you can use this endpoint to retrieve that value. Databricks restricts this API to return the first 5 MB of the output. To return a larger result, you can store job results in a cloud storage service. This endpoint validates that the run_id parameter is valid and returns an HTTP status code 400 if the run_id parameter is invalid. Runs are automatically removed after 60 days. If you to want to reference them beyond 60 days, you must save old run results before they expire. To export using the UI, see Export job run results. To export using the Jobs API, see Runs export. Args:

run_id: The canonical identifier for the run. This field is required.
databricks_credentials: Credentials to use for authentication with Databricks.

Returns:

Upon success, a dict of the response.
notebook_output: "models.NotebookOutput"
sql_output: "models.SqlOutput"
dbt_output: "models.DbtOutput"
logs: str
logs_truncated: bool
error: str
error_trace: str
metadata: "models.Run"

API Endpoint:

/2.1/jobs/runs/get-output

API Responses:

Response	Description
200	Run output was retrieved successfully.
400	A job run with multiple tasks was provided.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_list`

jobs_runs_list(databricks_credentials: 'DatabricksCredentials', active_only: bool = False, completed_only: bool = False, job_id: Optional[int] = None, offset: int = 0, limit: int = 25, run_type: Optional[str] = None, expand_tasks: bool = False, start_time_from: Optional[int] = None, start_time_to: Optional[int] = None) -> Dict[str, Any]

List runs in descending order by start time. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
active_only: If active_only is true, only active runs are included in the results; otherwise, lists both active and completed runs. An active run is a run in the PENDING, RUNNING, or TERMINATING. This field cannot be true when completed_only is true.
completed_only: If completed_only is true, only completed runs are included in the results; otherwise, lists both active and completed runs. This field cannot be true when active_only is true.
job_id: The job for which to list runs. If omitted, the Jobs service lists runs from all jobs.
offset: The offset of the first run to return, relative to the most recent run.
limit: The number of runs to return. This value must be greater than 0 and less than 25. The default value is 25. If a request specifies a limit of 0, the service instead uses the maximum limit.
run_type: The type of runs to return. For a description of run types, see [Run](https://docs.databricks.com/dev- tools/api/latest/jobs.html operation/JobsRunsGet).
expand_tasks: Whether to include task and cluster details in the response.
start_time_from: Show runs that started at or after this value. The value must be a UTC timestamp in milliseconds. Can be combined with start_time_to to filter by a time range.
start_time_to: Show runs that started at or before this value. The value must be a UTC timestamp in milliseconds. Can be combined with start_time_from to filter by a time range.

Returns:

Upon success, a dict of the response.
runs: List["models.Run"]
has_more: bool

API Endpoint:

/2.1/jobs/runs/list

API Responses:

Response	Description
200	List of runs was retrieved successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_repair`

jobs_runs_repair(databricks_credentials: 'DatabricksCredentials', run_id: Optional[int] = None, rerun_tasks: Optional[List[str]] = None, latest_repair_id: Optional[int] = None, rerun_all_failed_tasks: bool = False, jar_params: Optional[List[str]] = None, notebook_params: Optional[Dict] = None, python_params: Optional[List[str]] = None, spark_submit_params: Optional[List[str]] = None, python_named_params: Optional[Dict] = None, pipeline_params: Optional[str] = None, sql_params: Optional[Dict] = None, dbt_commands: Optional[List] = None, job_parameters: Optional[Dict] = None) -> Dict[str, Any]

Re-run one or more tasks. Tasks are re-run as part of the original job run, use the current job and task settings, and can be viewed in the history for the original job run. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
run_id: The job run ID of the run to repair. The run must not be in progress, e.g. 455644833.
rerun_tasks: The task keys of the task runs to repair, e.g.

["task0", "task1"]

latest_repair_id: The ID of the latest repair. This parameter is not required when repairing a run for the first time, but must be provided on subsequent requests to repair the same run, e.g. 734650698524280.
rerun_all_failed_tasks: If true, repair all failed tasks. Only one of rerun_tasks or rerun_all_failed_tasks can be used.
jar_params: A list of parameters for jobs with Spark JAR tasks, for example 'jar_params'\: ['john doe', '35']. The parameters are used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it defaults to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (for example {'jar_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs, e.g.

["john", "doe", "35"]

notebook_params: A map from keys to values for jobs with notebook task, for example 'notebook_params'\: {'name'\: 'john doe', 'age'\: '35'}. The map is passed to the notebook and is accessible through the [dbutils.widgets.get](https://docs.databricks.com/dev- tools/databricks-utils.html dbutils-widgets) function. If not specified upon run-now, the triggered run uses the job’s base parameters. notebook_params cannot be specified in conjunction with jar_params. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. The JSON representation of this field (for example {'notebook_params'\:{'name'\:'john doe','age'\:'35'}}) cannot exceed 10,000 bytes, e.g.

{"name"\: "john doe", "age"\: "35"}

python_params: A list of parameters for jobs with Python tasks, for example 'python_params'\: ['john doe', '35']. The parameters are 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 (for example {'python_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis, e.g.

["john doe", "35"]

spark_submit_params: A list of parameters for jobs with spark submit task, for example 'spark_submit_params'\: ['--class', 'org.apache.spark.examples.SparkPi']. The parameters are 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 (for example {'python_params'\:['john doe','35']}) cannot exceed 10,000 bytes. Use [Task parameter variables](https://docs.databricks.com/jobs.html parameter-variables) to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters returns an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis, e.g.

["--class", "org.apache.spark.examples.SparkPi"]

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'}, e.g.

{"name"\: "task", "data"\: "dbfs\:/path/to/data.json"}

pipeline_params:
sql_params: A map from keys to values for SQL tasks, for example 'sql_params'\: {'name'\: 'john doe', 'age'\: '35'}. The SQL alert task does not support custom parameters, e.g.

{"name"\: "john doe", "age"\: "35"}

dbt_commands: An array of commands to execute for jobs with the dbt task, for example 'dbt_commands'\: ['dbt deps', 'dbt seed', 'dbt run'], e.g.

["dbt deps", "dbt seed", "dbt run"]

job_parameters: A map from keys to values for job-level parameters used in the run, for example 'job_parameters'\: {'param'\: 'overriding_val'}, e.g.

{"param"\: "overriding_val"}

Returns:

Upon success, a dict of the response.
repair_id: int

API Endpoint:

/2.1/jobs/runs/repair

API Responses:

Response	Description
200	Run repair was initiated.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

`jobs_runs_submit`

jobs_runs_submit(databricks_credentials: 'DatabricksCredentials', tasks: Optional[List['models.RunSubmitTaskSettings']] = None, run_name: Optional[str] = None, webhook_notifications: 'models.WebhookNotifications' = None, git_source: 'models.GitSource' = None, timeout_seconds: Optional[int] = None, idempotency_token: Optional[str] = None, access_control_list: Optional[List['models.AccessControlRequest']] = None) -> Dict[str, Any]

Submit a one-time run. This endpoint allows you to submit a workload directly without creating a job. Use the jobs/runs/get API to check the run state after the job is submitted. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
tasks: , e.g.

[
    {
        "task_key"\: "Sessionize",
        "description"\: "Extracts session data from events",
        "depends_on"\: [],
        "existing_cluster_id"\: "0923-164208-meows279",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.Sessionize",
            "parameters"\: ["--data", "dbfs\:/path/to/data.json"],
        },
        "libraries"\: [{"jar"\: "dbfs\:/mnt/databricks/Sessionize.jar"}],
        "timeout_seconds"\: 86400,
    },
    {
        "task_key"\: "Orders_Ingest",
        "description"\: "Ingests order data",
        "depends_on"\: [],
        "existing_cluster_id"\: "0923-164208-meows279",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.OrdersIngest",
            "parameters"\: ["--data", "dbfs\:/path/to/order-data.json"],
        },
        "libraries"\: [{"jar"\: "dbfs\:/mnt/databricks/OrderIngest.jar"}],
        "timeout_seconds"\: 86400,
    },
    {
        "task_key"\: "Match",
        "description"\: "Matches orders with user sessions",
        "depends_on"\: [
            {"task_key"\: "Orders_Ingest"},
            {"task_key"\: "Sessionize"},
        ],
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {"min_workers"\: 2, "max_workers"\: 16},
        },
        "notebook_task"\: {
            "notebook_path"\: "/Users/user.name@databricks.com/Match",
            "source"\: "WORKSPACE",
            "base_parameters"\: {"name"\: "John Doe", "age"\: "35"},
        },
        "timeout_seconds"\: 86400,
    },
]

run_name: An optional name for the run. The default value is Untitled, e.g. A multitask job run.
webhook_notifications: A collection of system notification IDs to notify when runs of this job begin or complete. The default behavior is to not send any system notifications. Key-values:
on_start: An optional list of notification IDs to call when the run starts. A maximum of 3 destinations can be specified for the on_start property, e.g.
```
[
    {"id"\: "03dd86e4-57ef-4818-a950-78e41a1d71ab"},
    {"id"\: "0481e838-0a59-4eff-9541-a4ca6f149574"},
]
```
on_success: An optional list of notification IDs to call when the run completes successfully. A maximum of 3 destinations can be specified for the on_success property, e.g.
```
[{"id"\: "03dd86e4-57ef-4818-a950-78e41a1d71ab"}]
```
on_failure: An optional list of notification IDs to call when the run fails. A maximum of 3 destinations can be specified for the on_failure property, e.g.
```
[{"id"\: "0481e838-0a59-4eff-9541-a4ca6f149574"}]
```
git_source: This functionality is in Public Preview. An optional specification for a remote repository containing the notebooks used by this job’s notebook tasks, e.g.

{
    "git_url"\: "https\://github.com/databricks/databricks-cli",
    "git_branch"\: "main",
    "git_provider"\: "gitHub",
}
``` Key-values\:
- git_url\:
    URL of the repository to be cloned by this job. The maximum
    length is 300 characters, e.g.
    `https\://github.com/databricks/databricks-cli`.
- git_provider\:
    Unique identifier of the service used to host the Git
    repository. The value is case insensitive, e.g. `github`.
- git_branch\:
    Name of the branch to be checked out and used by this job.
    This field cannot be specified in conjunction with git_tag
    or git_commit. The maximum length is 255 characters, e.g.
    `main`.
- git_tag\:
    Name of the tag to be checked out and used by this job. This
    field cannot be specified in conjunction with git_branch or
    git_commit. The maximum length is 255 characters, e.g.
    `release-1.0.0`.
- git_commit\:
    Commit to be checked out and used by this job. This field
    cannot be specified in conjunction with git_branch or
    git_tag. The maximum length is 64 characters, e.g.
    `e0056d01`.
- git_snapshot\:
    Read-only state of the remote repository at the time the job was run.
                This field is only included on job runs.
- `timeout_seconds`: 
An optional timeout applied to each run of this job. The default
behavior is to have no timeout, e.g. `86400`.
- `idempotency_token`: 
An optional token that can be used 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.  For more
information, see [How to ensure idempotency for
jobs](https\://kb.databricks.com/jobs/jobs-idempotency.html),
e.g. `8f018174-4792-40d5-bcbc-3e6a527352c8`.
- `access_control_list`: 
List of permissions to set on the job.

**Returns:**
- Upon success, a dict of the response. 
- `run_id: int`

#### API Endpoint:
`/2.1/jobs/runs/submit`

#### API Responses:
| Response | Description |
| --- | --- |
| 200 | Run was created and started successfully. |
| 400 | The request was malformed. See JSON response for error details. |
| 401 | The request was unauthorized. |
| 500 | The request was not handled correctly due to a server error. |


### `jobs_update` <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/integrations/prefect-databricks/prefect_databricks/jobs.py#L1745" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python
jobs_update(databricks_credentials: 'DatabricksCredentials', job_id: Optional[int] = None, new_settings: 'models.JobSettings' = None, fields_to_remove: Optional[List[str]] = None) -> Dict[str, Any]

Add, update, or remove specific settings of an existing job. Use the Reset endpoint to overwrite all job settings. Args:

databricks_credentials: Credentials to use for authentication with Databricks.
job_id: The canonical identifier of the job to update. This field is required, e.g. 11223344.
new_settings: The new settings for the job. Any top-level fields specified in new_settings are completely replaced. Partially updating nested fields is not supported. Changes to the field JobSettings.timeout_seconds are applied to active runs. Changes to other fields are applied to future runs only. Key-values:
name: An optional name for the job, e.g. A multitask job.
tags: A map of tags associated with the job. These are forwarded to the cluster as cluster tags for jobs clusters, and are subject to the same limitations as cluster tags. A maximum of 25 tags can be added to the job, e.g.
```
{"cost-center"\: "engineering", "team"\: "jobs"}
```

tasks: A list of task specifications to be executed by this job, e.g.

[
    {
        "task_key"\: "Sessionize",
        "description"\: "Extracts session data from events",
        "depends_on"\: [],
        "existing_cluster_id"\: "0923-164208-meows279",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.Sessionize",
            "parameters"\: [
                "--data",
                "dbfs\:/path/to/data.json",
            ],
        },
        "libraries"\: [
            {"jar"\: "dbfs\:/mnt/databricks/Sessionize.jar"}
        ],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Orders_Ingest",
        "description"\: "Ingests order data",
        "depends_on"\: [],
        "job_cluster_key"\: "auto_scaling_cluster",
        "spark_jar_task"\: {
            "main_class_name"\: "com.databricks.OrdersIngest",
            "parameters"\: [
                "--data",
                "dbfs\:/path/to/order-data.json",
            ],
        },
        "libraries"\: [
            {"jar"\: "dbfs\:/mnt/databricks/OrderIngest.jar"}
        ],
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
    {
        "task_key"\: "Match",
        "description"\: "Matches orders with user sessions",
        "depends_on"\: [
            {"task_key"\: "Orders_Ingest"},
            {"task_key"\: "Sessionize"},
        ],
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {
                "min_workers"\: 2,
                "max_workers"\: 16,
            },
        },
        "notebook_task"\: {
            "notebook_path"\: "/Users/user.name@databricks.com/Match",
            "source"\: "WORKSPACE",
            "base_parameters"\: {
                "name"\: "John Doe",
                "age"\: "35",
            },
        },
        "timeout_seconds"\: 86400,
        "max_retries"\: 3,
        "min_retry_interval_millis"\: 2000,
        "retry_on_timeout"\: False,
    },
]

[
    {
        "job_cluster_key"\: "auto_scaling_cluster",
        "new_cluster"\: {
            "spark_version"\: "7.3.x-scala2.12",
            "node_type_id"\: "i3.xlarge",
            "spark_conf"\: {"spark.speculation"\: True},
            "aws_attributes"\: {
                "availability"\: "SPOT",
                "zone_id"\: "us-west-2a",
            },
            "autoscale"\: {
                "min_workers"\: 2,
                "max_workers"\: 16,
            },
        },
    }
]

email_notifications: An optional set of email addresses that is notified when runs of this job begin or complete as well as when this job is deleted. The default behavior is to not send any emails.
webhook_notifications: A collection of system notification IDs to notify when runs of this job begin or complete. The default behavior is to not send any system notifications.
timeout_seconds: An optional timeout applied to each run of this job. The default behavior is to have no timeout, e.g. 86400.
schedule: An optional periodic schedule for this job. The default behavior is that the job only runs when triggered by clicking “Run Now” in the Jobs UI or sending an API request to runNow.
max_concurrent_runs: An optional maximum allowed number of concurrent runs of the job. Set this value if you want to be able to execute multiple runs of the same job concurrently. This is useful for example if you trigger your job on a frequent schedule and want to allow consecutive runs to overlap with each other, or if you want to trigger multiple runs which differ by their input parameters. This setting affects only new runs. For example, suppose the job’s concurrency is 4 and there are 4 concurrent active runs. Then setting the concurrency to 3 won’t kill any of the active runs. However, from then on, new runs are skipped unless there are fewer than 3 active runs. This value cannot exceed 1000. Setting this value to 0 causes all new runs to be skipped. The default behavior is to allow only 1 concurrent run, e.g. 10.
git_source: This functionality is in Public Preview. An optional specification for a remote repository containing the notebooks used by this job’s notebook tasks, e.g.
```
{
    "git_url"\: "https\://github.com/databricks/databricks-cli",
    "git_branch"\: "main",
    "git_provider"\: "gitHub",
}
```
format: Used to tell what is the format of the job. This field is ignored in Create/Update/Reset calls. When using the Jobs API 2.1 this value is always set to 'MULTI_TASK', e.g. MULTI_TASK.
parameters: Job-level parameter definitions.
fields_to_remove: Remove top-level fields in the job settings. Removing nested fields is not supported. This field is optional, e.g.

["libraries", "schedule"]

Returns:

Upon success, an empty dict.

API Endpoint:

/2.1/jobs/update

API Responses:

Response	Description
200	Job was updated successfully.
400	The request was malformed. See JSON response for error details.
401	The request was unauthorized.
500	The request was not handled correctly due to a server error.

Integrations

​prefect_databricks.jobs

​Functions

​jobs_runs_export

​API Endpoint:

​API Responses:

​jobs_create

​API Endpoint:

​API Responses:

​jobs_get

​API Endpoint:

​API Responses:

​jobs_list

​API Endpoint:

​API Responses:

​jobs_reset

​API Endpoint:

​API Responses:

​jobs_run_now

​API Endpoint:

​API Responses:

​jobs_runs_cancel

​API Endpoint:

​API Responses:

​jobs_runs_cancel_all

​API Endpoint:

​API Responses:

​jobs_runs_delete

​API Endpoint:

​API Responses:

​jobs_runs_get

​API Endpoint:

​API Responses:

​jobs_runs_get_output

​API Endpoint:

​API Responses:

​jobs_runs_list

​API Endpoint:

​API Responses:

​jobs_runs_repair

​API Endpoint:

​API Responses:

​jobs_runs_submit

​API Endpoint:

​API Responses:

`prefect_databricks.jobs`

Functions

`jobs_runs_export`

API Endpoint:

API Responses:

`jobs_create`

API Endpoint:

API Responses:

`jobs_get`

API Endpoint:

API Responses:

`jobs_list`

API Endpoint:

API Responses:

`jobs_reset`

API Endpoint:

API Responses:

`jobs_run_now`

API Endpoint:

API Responses:

`jobs_runs_cancel`

API Endpoint:

API Responses:

`jobs_runs_cancel_all`

API Endpoint:

API Responses:

`jobs_runs_delete`

API Endpoint:

API Responses:

`jobs_runs_get`

API Endpoint:

API Responses:

`jobs_runs_get_output`

API Endpoint:

API Responses:

`jobs_runs_list`

API Endpoint:

API Responses:

`jobs_runs_repair`

API Endpoint:

API Responses:

`jobs_runs_submit`

API Endpoint:

API Responses: