Jobs API 2.0

Important

This article documents the 2.0 version of the Jobs API. However, Databricks recommends using Jobs API 2.1 for new and existing clients and scripts. For details on the changes from the 2.0 to 2.1 versions, see Updating from Jobs API 2.0 to 2.1.

The Jobs API allows you to create, edit, and delete jobs. The maximum allowed size of a request to the Jobs API is 10MB.

For details about updates to the Jobs API that support orchestration of multiple tasks with Databricks jobs, see Updating from Jobs API 2.0 to 2.1.

Warning

You should never hard code secrets or store them in plain text. Use the Secrets API to manage secrets in the Databricks CLI. Use the Secrets utility (dbutils.secrets) to reference secrets in notebooks and jobs.

Note

If you receive a 500-level error when making Jobs API requests, Databricks recommends retrying requests for up to 10 min (with a minimum 30 second interval between retries).

Important

To access Databricks REST APIs, you must authenticate.

Create

Endpoint	HTTP Method
2.0/jobs/create	POST

Create a new job.

Example

This example creates a job that runs a JAR task at 10:15pm each night.

Request

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/create \
--data @create-job.json \
| jq .

create-job.json:

{
  "name": "Nightly model training",
  "new_cluster": {
    "spark_version": "7.3.x-scala2.12",
    "node_type_id": "r3.xlarge",
    "aws_attributes": {
      "availability": "ON_DEMAND"
    },
    "num_workers": 10
  },
  "libraries": [
    {
      "jar": "dbfs:/my-jar.jar"
    },
    {
      "maven": {
        "coordinates": "org.jsoup:jsoup:1.7.2"
      }
    }
  ],
  "email_notifications": {
    "on_start": [],
    "on_success": [],
    "on_failure": []
  },
  "webhook_notifications": {
    "on_start": [
      {
        "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
      }
    ],
    "on_success": [
      {
        "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
      }
    ],
    "on_failure": []
  },
  "notification_settings": {
    "no_alert_for_skipped_runs": false,
    "no_alert_for_canceled_runs": false,
    "alert_on_last_attempt": false
  },
  "timeout_seconds": 3600,
  "max_retries": 1,
  "schedule": {
    "quartz_cron_expression": "0 15 22 * * ?",
    "timezone_id": "America/Los_Angeles"
  },
  "spark_jar_task": {
    "main_class_name": "com.databricks.ComputeModels"
  }
}

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• The contents of create-job.json with fields that are appropriate for your solution.

This example uses a .netrc file and jq.

Response

{
  "job_id": 1
}

Request structure

Important

• When you run a job on a new jobs cluster, the job is treated as a Jobs Compute (automated) workload subject to Jobs Compute pricing.

• When you run a job on an existing all-purpose cluster, it is treated as an All-Purpose Compute (interactive) workload subject to All-Purpose Compute pricing.

Field Name	Type	Description
existing_cluster_id OR new_cluster	STRING OR NewCluster	If existing_cluster_id, the ID of an existing cluster that will be used for all runs of this job. When running jobs on an existing cluster, you may need to manually restart the cluster if it stops responding. We suggest running jobs on new clusters for greater reliability. If new_cluster, a description of a cluster that will be created for each run. If specifying a PipelineTask, this field can be empty.
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task OR pipeline_task OR run_job_task	NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask OR PipelineTask OR RunJobTask	If notebook_task, indicates that this job should run a notebook. This field may not be specified in conjunction with spark_jar_task. If spark_jar_task, indicates that this job should run a JAR. If spark_python_task, indicates that this job should run a Python file. If spark_submit_task, indicates that this job should be launched by the spark submit script. If pipeline_task, indicates that this job should run a Delta Live Tables pipeline. If run_job_task, indicates that this job should run another job.
name	STRING	An optional name for the job. The default value is Untitled.
libraries	An array of Library	An optional list of libraries to be installed on the cluster that will execute the job. The default value is an empty list.
email_notifications	JobEmailNotifications	An optional set of email addresses notified when runs of this job begin and complete and when this job is deleted. The default behavior is to not send any emails.
webhook_notifications	WebhookNotifications	An optional set of system destinations to notify when runs of this job begin, complete, or fail.
notification_settings	JobNotificationSettings	Optional notification settings that are used when sending notifications to each of the email_notifications and webhook_notifications for this job.
timeout_seconds	INT32	An optional timeout applied to each run of this job. The default behavior is to have no timeout.
max_retries	INT32	An optional maximum number of times to retry an unsuccessful run. A run is considered to be unsuccessful if it completes with the FAILED result_state or INTERNAL_ERROR life_cycle_state. The value -1 means to retry indefinitely and the value 0 means to never retry. The default behavior is to never retry.
min_retry_interval_millis	INT32	An optional minimal interval in milliseconds between the start of the failed run and the subsequent retry run. The default behavior is that unsuccessful runs are immediately retried.
retry_on_timeout	BOOL	An optional policy to specify whether to retry a job when it times out. The default behavior is to not retry on timeout.
schedule	CronSchedule	An optional periodic schedule for this job. The default behavior is that the job runs when triggered by clicking Run Now in the Jobs UI or sending an API request to runNow.
max_concurrent_runs	INT32	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.

Response structure

Field Name	Type	Description
job_id	INT64	The canonical identifier for the newly created job.

List

Endpoint	HTTP Method
2.0/jobs/list	GET

List all jobs.

Example

Request

curl --netrc --request GET \
https://<databricks-instance>/api/2.0/jobs/list \
| jq .

Replace <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

This example uses a .netrc file and jq.

Response

{
  "jobs": [
    {
      "job_id": 1,
      "settings": {
        "name": "Nightly model training",
        "new_cluster": {
          "spark_version": "7.3.x-scala2.12",
          "node_type_id": "r3.xlarge",
          "aws_attributes": {
            "availability": "ON_DEMAND"
          },
          "num_workers": 10
        },
        "libraries": [
          {
            "jar": "dbfs:/my-jar.jar"
          },
          {
            "maven": {
              "coordinates": "org.jsoup:jsoup:1.7.2"
            }
          }
        ],
        "email_notifications": {
          "on_start": [],
          "on_success": [],
          "on_failure": []
        },
        "timeout_seconds": 100000000,
        "max_retries": 1,
        "schedule": {
          "quartz_cron_expression": "0 15 22 * * ?",
          "timezone_id": "America/Los_Angeles",
          "pause_status": "UNPAUSED"
        },
        "spark_jar_task": {
          "main_class_name": "com.databricks.ComputeModels"
        }
      },
      "created_time": 1457570074236
    }
  ]
}

Response structure

Field Name	Type	Description
jobs	An array of Job	The list of jobs.

Delete

Endpoint	HTTP Method
2.0/jobs/delete	POST

Delete a job and send an email to the addresses specified in JobSettings.email_notifications. No action occurs if the job has already been removed. After the job is removed, neither its details nor its run history is visible in the Jobs UI or API. The job is guaranteed to be removed upon completion of this request. However, runs that were active before the receipt of this request may still be active. They will be terminated asynchronously.

Example

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/delete \
--data '{ "job_id": <job-id> }'

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <job-id> with the ID of the job, for example 123.

This example uses a .netrc file.

Request structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job to delete. This field is required.

Get

Endpoint	HTTP Method
2.0/jobs/get	GET

Retrieve information about a single job.

Example

Request

curl --netrc --request GET \
'https://<databricks-instance>/api/2.0/jobs/get?job_id=<job-id>' \
| jq .

Or:

curl --netrc --get \
https://<databricks-instance>/api/2.0/jobs/get \
--data job_id=<job-id> \
| jq .

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <job-id> with the ID of the job, for example 123.

This example uses a .netrc file and jq.

Response

{
  "job_id": 1,
  "settings": {
    "name": "Nightly model training",
    "new_cluster": {
      "spark_version": "7.3.x-scala2.12",
      "node_type_id": "r3.xlarge",
      "aws_attributes": {
        "availability": "ON_DEMAND"
      },
      "num_workers": 10
    },
    "libraries": [
      {
        "jar": "dbfs:/my-jar.jar"
      },
      {
        "maven": {
          "coordinates": "org.jsoup:jsoup:1.7.2"
        }
      }
    ],
    "email_notifications": {
      "on_start": [],
      "on_success": [],
      "on_failure": []
    },
    "webhook_notifications": {
      "on_start": [
        {
          "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
        }
      ],
      "on_success": [
        {
          "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
        }
      ],
      "on_failure": []
    },
    "notification_settings": {
      "no_alert_for_skipped_runs": false,
      "no_alert_for_canceled_runs": false,
      "alert_on_last_attempt": false
    },
    "timeout_seconds": 100000000,
    "max_retries": 1,
    "schedule": {
      "quartz_cron_expression": "0 15 22 * * ?",
      "timezone_id": "America/Los_Angeles",
      "pause_status": "UNPAUSED"
    },
    "spark_jar_task": {
      "main_class_name": "com.databricks.ComputeModels"
    }
  },
  "created_time": 1457570074236
}

Request structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job to retrieve information about. This field is required.

Response structure

Field Name	Type	Description
job_id	INT64	The canonical identifier for this job.
creator_user_name	STRING	The creator user name. This field won’t be included in the response if the user has been deleted.
settings	JobSettings	Settings for this job and all of its runs. These settings can be updated using the Reset or Update endpoints.
created_time	INT64	The time at which this job was created in epoch milliseconds (milliseconds since 1/1/1970 UTC).

Reset

Endpoint	HTTP Method
2.0/jobs/reset	POST

Overwrite all settings for a specific job. Use the Update endpoint to update job settings partially.

Example

This example request makes job 2 identical to job 1 in the create example.

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/reset \
--data @reset-job.json \
| jq .

reset-job.json:

{
  "job_id": 2,
  "new_settings": {
    "name": "Nightly model training",
    "new_cluster": {
      "spark_version": "7.3.x-scala2.12",
      "node_type_id": "r3.xlarge",
      "aws_attributes": {
        "availability": "ON_DEMAND"
      },
      "num_workers": 10
    },
    "libraries": [
      {
        "jar": "dbfs:/my-jar.jar"
      },
      {
        "maven": {
          "coordinates": "org.jsoup:jsoup:1.7.2"
        }
      }
    ],
    "email_notifications": {
      "on_start": [],
      "on_success": [],
      "on_failure": []
    },
    "webhook_notifications": {
      "on_start": [
        {
          "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
        }
      ],
      "on_success": [
        {
          "id": "bf2fbd0a-4a05-4300-98a5-303fc8132233"
        }
      ],
      "on_failure": []
    },
    "notification_settings": {
      "no_alert_for_skipped_runs": false,
      "no_alert_for_canceled_runs": false,
      "alert_on_last_attempt": false
    },
    "timeout_seconds": 100000000,
    "max_retries": 1,
    "schedule": {
      "quartz_cron_expression": "0 15 22 * * ?",
      "timezone_id": "America/Los_Angeles",
      "pause_status": "UNPAUSED"
    },
    "spark_jar_task": {
      "main_class_name": "com.databricks.ComputeModels"
    }
  }
}

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• The contents of reset-job.json with fields that are appropriate for your solution.

This example uses a .netrc file and jq.

Request structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job to reset. This field is required.
new_settings	JobSettings	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.

Update

Endpoint	HTTP Method
2.0/jobs/update	POST

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

Example

This example request removes libraries and adds email notification settings to job 1 defined in the create example.

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/update \
--data @update-job.json \
| jq .

update-job.json:

{
  "job_id": 1,
  "new_settings": {
    "existing_cluster_id": "1201-my-cluster",
    "email_notifications": {
      "on_start": [ "someone@example.com" ],
      "on_success": [],
      "on_failure": []
    }
  },
  "fields_to_remove": ["libraries"]
}

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• The contents of update-job.json with fields that are appropriate for your solution.

This example uses a .netrc file and jq.

Request structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job to update. This field is required.
new_settings	JobSettings	The new settings for the job. Top-level fields specified in new_settings, except for arrays, are completely replaced. Arrays are merged based on the respective key fields, such as task_key or job_cluster_key, and array entries with the same key are completely replaced. Except for array merging, 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.
fields_to_remove	An array of STRING	Remove top-level fields in the job settings. Removing nested fields is not supported, except for entries from the tasks and job_clusters arrays. For example, the following is a valid argument for this field: ["libraries", "schedule", "tasks/task_1", "job_clusters/Default"] This field is optional.

Run now

Important

• A workspace is limited to 1000 concurrent task runs. A 429 Too Many Requests response is returned when you request a run that cannot start immediately.

• The number of jobs a workspace can create in an hour is limited to 10000 (includes “runs submit”). This limit also affects jobs created by the REST API and notebook workflows.

Endpoint	HTTP Method
2.0/jobs/run-now	POST

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

Tip

If you invoke Create together with Run now, you can use the Runs submit endpoint instead, which allows you to submit your workload directly without having to create a job.

Example

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/run-now \
--data @run-job.json \
| jq .

run-job.json:

An example request for a notebook job:

{
  "job_id": 1,
  "notebook_params": {
    "name": "john doe",
    "age": "35"
  }
}

An example request for a JAR job:

{
  "job_id": 2,
  "jar_params": [ "john doe", "35" ]
}

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• The contents of run-job.json with fields that are appropriate for your solution.

This example uses a .netrc file and jq.

Request structure

Field Name	Type	Description
job_id	INT64
jar_params	An array of STRING	A list of parameters for jobs with JAR tasks, e.g. "jar_params": ["john doe", "35"]. The parameters will be used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it will default to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (i.e. {"jar_params":["john doe","35"]}) cannot exceed 10,000 bytes.
notebook_params	A map of ParamPair	A map 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 is accessible through the dbutils.widgets.get function. If not specified upon run-now, the triggered run uses the job’s base parameters. You cannot specify notebook_params 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.
python_params	An array of STRING	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.
spark_submit_params	An array of STRING	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.
idempotency_token	STRING	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.

Response structure

Field Name	Type	Description
run_id	INT64	The globally unique ID of the newly triggered run.
number_in_job	INT64	The sequence number of this run among all runs of the job.

Runs submit

Important

• A workspace is limited to 1000 concurrent task runs. A 429 Too Many Requests response is returned when you request a run that cannot start immediately.

• The number of jobs a workspace can create in an hour is limited to 10000 (includes “runs submit”). This limit also affects jobs created by the REST API and notebook workflows.

Endpoint	HTTP Method
2.0/jobs/runs/submit	POST

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.

Example

Request

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/runs/submit \
--data @submit-job.json \
| jq .

submit-job.json:

{
  "run_name": "my spark task",
  "new_cluster": {
    "spark_version": "7.3.x-scala2.12",
    "node_type_id": "r3.xlarge",
    "aws_attributes": {
      "availability": "ON_DEMAND"
    },
    "num_workers": 10
  },
  "libraries": [
    {
      "jar": "dbfs:/my-jar.jar"
    },
    {
      "maven": {
        "coordinates": "org.jsoup:jsoup:1.7.2"
      }
    }
  ],
  "spark_jar_task": {
    "main_class_name": "com.databricks.ComputeModels"
  }
}

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• The contents of submit-job.json with fields that are appropriate for your solution.

This example uses a .netrc file and jq.

Response

{
  "run_id": 123
}

Request structure

Important

• When you run a job on a new jobs cluster, the job is treated as a Jobs Compute (automated) workload subject to Jobs Compute pricing.

• When you run a job on an existing all-purpose cluster, it is treated as an All-Purpose Compute (interactive) workload subject to All-Purpose Compute pricing.

Field Name	Type	Description
existing_cluster_id OR new_cluster	STRING OR NewCluster	If existing_cluster_id, the ID of an existing cluster that will be used for all runs of this job. When running jobs on an existing cluster, you may need to manually restart the cluster if it stops responding. We suggest running jobs on new clusters for greater reliability. If new_cluster, a description of a cluster that will be created for each run. If specifying a PipelineTask, then this field can be empty.
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task OR pipeline_task OR run_job_task	NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask OR PipelineTask OR RunJobTask	If notebook_task, indicates that this job should run a notebook. This field may not be specified in conjunction with spark_jar_task. If spark_jar_task, indicates that this job should run a JAR. If spark_python_task, indicates that this job should run a Python file. If spark_submit_task, indicates that this job should be launched by the spark submit script. If pipeline_task, indicates that this job should run a Delta Live Tables pipeline. If run_job_task, indicates that this job should run another job.
run_name	STRING	An optional name for the run. The default value is Untitled.
webhook_notifications	WebhookNotifications	An optional set of system destinations to notify when runs of this job begin, complete, or fail.
notification_settings	JobNotificationSettings	Optional notification settings that are used when sending notifications to each of the webhook_notifications for this run.
libraries	An array of Library	An optional list of libraries to be installed on the cluster that will execute the job. The default value is an empty list.
timeout_seconds	INT32	An optional timeout applied to each run of this job. The default behavior is to have no timeout.
idempotency_token	STRING	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.

Response structure

Field Name	Type	Description
run_id	INT64	The canonical identifier for the newly submitted run.

Runs list

Endpoint	HTTP Method
2.0/jobs/runs/list	GET

List runs in descending order by start time.

Note

Runs are automatically removed after 60 days. If you to want to reference them beyond 60 days, you should 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.

Example

Request

curl --netrc --request GET \
'https://<databricks-instance>/api/2.0/jobs/runs/list?job_id=<job-id>&active_only=<true-false>&offset=<offset>&limit=<limit>&run_type=<run-type>' \
| jq .

Or:

curl --netrc --get \
https://<databricks-instance>/api/2.0/jobs/runs/list \
--data 'job_id=<job-id>&active_only=<true-false>&offset=<offset>&limit=<limit>&run_type=<run-type>' \
| jq .

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <job-id> with the ID of the job, for example 123.

• <true-false> with true or false.

• <offset> with the offset value.

• <limit> with the limit value.

• <run-type> with the run_type value.

This example uses a .netrc file and jq.

Response

{
  "runs": [
    {
      "job_id": 1,
      "run_id": 452,
      "number_in_job": 5,
      "state": {
        "life_cycle_state": "RUNNING",
        "state_message": "Performing action"
      },
      "task": {
        "notebook_task": {
          "notebook_path": "/Users/donald@duck.com/my-notebook"
        }
      },
      "cluster_spec": {
        "existing_cluster_id": "1201-my-cluster"
      },
      "cluster_instance": {
        "cluster_id": "1201-my-cluster",
        "spark_context_id": "1102398-spark-context-id"
      },
      "overriding_parameters": {
        "jar_params": ["param1", "param2"]
      },
      "start_time": 1457570074236,
      "end_time": 1457570075149,
      "setup_duration": 259754,
      "execution_duration": 3589020,
      "cleanup_duration": 31038,
      "run_duration": 3879812,
      "trigger": "PERIODIC"
    }
  ],
  "has_more": true
}

Request structure

Field Name	Type	Description
active_only OR completed_only	BOOL OR BOOL	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 RunLifecycleState. This field cannot be true when completed_only is true. 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	INT64	The job for which to list runs. If omitted, the Jobs service will list runs from all jobs.
offset	INT32	The offset of the first run to return, relative to the most recent run.
limit	INT32	The number of runs to return. This value should be greater than 0 and less than 1000. The default value is 20. If a request specifies a limit of 0, the service will instead use the maximum limit.
run_type	STRING	The type of runs to return. For a description of run types, see Run.

Response structure

Field Name	Type	Description
runs	An array of Run	A list of runs, from most recently started to least.
has_more	BOOL	If true, additional runs matching the provided filter are available for listing.

Runs get

Endpoint	HTTP Method
2.0/jobs/runs/get	GET

Retrieve the metadata of a run.

Note

Runs are automatically removed after 60 days. If you to want to reference them beyond 60 days, you should 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.

Example

Request

curl --netrc --request GET \
'https://<databricks-instance>/api/2.0/jobs/runs/get?run_id=<run-id>' \
| jq .

Or:

curl --netrc --get \
https://<databricks-instance>/api/2.0/jobs/runs/get \
--data run_id=<run-id> \
| jq .

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <run-id> with the ID of the run, for example 123.

This example uses a .netrc file and jq.

Response

{
  "job_id": 1,
  "run_id": 452,
  "number_in_job": 5,
  "state": {
    "life_cycle_state": "RUNNING",
    "state_message": "Performing action"
  },
  "task": {
    "notebook_task": {
      "notebook_path": "/Users/someone@example.com/my-notebook"
    }
  },
  "cluster_spec": {
    "existing_cluster_id": "1201-my-cluster"
  },
  "cluster_instance": {
    "cluster_id": "1201-my-cluster",
    "spark_context_id": "1102398-spark-context-id"
  },
  "overriding_parameters": {
    "jar_params": ["param1", "param2"]
  },
  "start_time": 1457570074236,
  "end_time": 1457570075149,
  "setup_duration": 259754,
  "execution_duration": 3589020,
  "cleanup_duration": 31038,
  "run_duration": 3879812,
  "trigger": "PERIODIC"
}

Request structure

Field Name	Type	Description
run_id	INT64	The canonical identifier of the run for which to retrieve the metadata. This field is required.

Response structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job that contains this run.
run_id	INT64	The canonical identifier of the run. This ID is unique across all runs of all jobs.
number_in_job	INT64	The sequence number of this run among all runs of the job. This value starts at 1.
original_attempt_run_id	INT64	If this run is a retry of a prior run attempt, this field contains the run_id of the original attempt; otherwise, it is the same as the run_id.
state	RunState	The result and lifecycle states of the run.
schedule	CronSchedule	The cron schedule that triggered this run if it was triggered by the periodic scheduler.
task	JobTask	The task performed by the run, if any.
cluster_spec	ClusterSpec	A snapshot of the job’s cluster specification when this run was created.
cluster_instance	ClusterInstance	The cluster used for this run. If the run is specified to use a new cluster, this field will be set once the Jobs service has requested a cluster for the run.
overriding_parameters	RunParameters	The parameters used for this run.
start_time	INT64	The time at which this run was started in epoch milliseconds (milliseconds since 1/1/1970 UTC). This may not be the time when the job task starts executing, for example, if the job is scheduled to run on a new cluster, this is the time the cluster creation call is issued.
end_time	INT64	The time at which this run ended in epoch milliseconds (milliseconds since 1/1/1970 UTC). This field will be set to 0 if the job is still running.
setup_duration	INT64	The time in milliseconds it took to set up the cluster. For runs that run on new clusters this is the cluster creation time, for runs that run on existing clusters this time should be very short. The total duration of the run is the sum of the setup_duration, execution_duration, and the cleanup_duration. The setup_duration field is set to 0 for multitask job runs. The total duration of a multitask job run is the value of the run_duration field.
execution_duration	INT64	The time in milliseconds it took to execute the commands in the JAR or notebook until they completed, failed, timed out, were cancelled, or encountered an unexpected error. The total duration of the run is the sum of the setup_duration, execution_duration, and the cleanup_duration. The execution_duration field is set to 0 for multitask job runs. The total duration of a multitask job run is the value of the run_duration field.
cleanup_duration	INT64	The time in milliseconds it took to terminate the cluster and clean up any associated artifacts. The total duration of the run is the sum of the setup_duration, execution_duration, and the cleanup_duration. The cleanup_duration field is set to 0 for multitask job runs. The total duration of a multitask job run is the value of the run_duration field.
run_duration	INT64	The time in milliseconds it took the job run and all of its repairs to finish. This field is only set for multitask job runs and not task runs. The duration of a task run is the sum of the setup_duration, execution_duration, and the cleanup_duration.
trigger	TriggerType	The type of trigger that fired this run.
creator_user_name	STRING	The creator user name. This field won’t be included in the response if the user has been deleted
run_page_url	STRING	The URL to the detail page of the run.

Runs export

Endpoint	HTTP Method
2.0/jobs/runs/export	GET

Export and retrieve the job run task.

Note

Only notebook runs can be exported in HTML format. Exporting runs of other types will fail.

Example

Request

curl --netrc --request GET \
'https://<databricks-instance>/api/2.0/jobs/runs/export?run_id=<run-id>' \
| jq .

Or:

curl --netrc --get \
https://<databricks-instance>/api/2.0/jobs/runs/export \
--data run_id=<run-id> \
| jq .

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <run-id> with the ID of the run, for example 123.

This example uses a .netrc file and jq.

Response

{
  "views": [ {
    "content": "<!DOCTYPE html><html><head>Head</head><body>Body</body></html>",
    "name": "my-notebook",
    "type": "NOTEBOOK"
  } ]
}

To extract the HTML notebook from the JSON response, download and run this Python script.

Note

The notebook body in the __DATABRICKS_NOTEBOOK_MODEL object is encoded.

Request structure

Field Name	Type	Description
run_id	INT64	The canonical identifier for the run. This field is required.
views_to_export	ViewsToExport	Which views to export (CODE, DASHBOARDS, or ALL). Defaults to CODE.

Response structure

Field Name	Type	Description
views	An array of ViewItem	The exported content in HTML format (one for every view item).

Runs cancel

Endpoint	HTTP Method
2.0/jobs/runs/cancel	POST

Cancel a job run. Because the run is canceled asynchronously, the run may still be running when this request completes. The run will be terminated shortly. If the run is already in a terminal life_cycle_state, this method is a no-op.

This endpoint validates that the run_id parameter is valid and for invalid parameters returns HTTP status code 400.

Example

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/runs/cancel \
--data '{ "run_id": <run-id> }'

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <run-id> with the ID of the run, for example 123.

This example uses a .netrc file.

Request structure

Field Name	Type	Description
run_id	INT64	The canonical identifier of the run to cancel. This field is required.

Runs cancel all

Endpoint	HTTP Method
2.0/jobs/runs/cancel-all	POST

Cancel all active runs of a job. Because the run is canceled asynchronously, it doesn’t prevent new runs from being started.

This endpoint validates that the job_id parameter is valid and for invalid parameters returns HTTP status code 400.

Example

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/runs/cancel-all \
--data '{ "job_id": <job-id> }'

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <job-id> with the ID of the job, for example 123.

This example uses a .netrc file.

Request structure

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job to cancel all runs of. This field is required.

Runs get output

Endpoint	HTTP Method
2.0/jobs/runs/get-output	GET

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. For returning a larger result, you can store job results in a cloud storage service.

This endpoint validates that the run_id parameter is valid and for invalid parameters returns HTTP status code 400.

Runs are automatically removed after 60 days. If you to want to reference them beyond 60 days, you should 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.

Example

Request

curl --netrc --request GET \
'https://<databricks-instance>/api/2.0/jobs/runs/get-output?run_id=<run-id>' \
| jq .

Or:

curl --netrc --get \
https://<databricks-instance>/api/2.0/jobs/runs/get-output \
--data run_id=<run-id> \
| jq .

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <run-id> with the ID of the run, for example 123.

This example uses a .netrc file and jq.

Response

{
  "metadata": {
    "job_id": 1,
    "run_id": 452,
    "number_in_job": 5,
    "state": {
      "life_cycle_state": "TERMINATED",
      "result_state": "SUCCESS",
      "state_message": ""
    },
    "task": {
      "notebook_task": {
        "notebook_path": "/Users/someone@example.com/my-notebook"
      }
    },
    "cluster_spec": {
      "existing_cluster_id": "1201-my-cluster"
    },
    "cluster_instance": {
      "cluster_id": "1201-my-cluster",
      "spark_context_id": "1102398-spark-context-id"
    },
    "overriding_parameters": {
      "jar_params": ["param1", "param2"]
    },
    "start_time": 1457570074236,
    "setup_duration": 259754,
    "execution_duration": 3589020,
    "cleanup_duration": 31038,
    "run_duration": 3879812,
    "trigger": "PERIODIC"
  },
  "notebook_output": {
    "result": "the maybe truncated string passed to dbutils.notebook.exit()"
  }
}

Request structure

Field Name	Type	Description
run_id	INT64	The canonical identifier for the run. For a job with mulitple tasks, this is the run_id of a task run. See Runs get output. This field is required.

Response structure

Field Name	Type	Description
notebook_output OR error	NotebookOutput OR STRING	If notebook_output, the output of a notebook task, if available. A notebook task that terminates (either successfully or with a failure) without calling dbutils.notebook.exit() is considered to have an empty output. This field will be set but its result value will be empty. If error, an error message indicating why output is not available. The message is unstructured, and its exact format is subject to change.
metadata	Run	All details of the run except for its output.

Runs delete

Endpoint	HTTP Method
2.0/jobs/runs/delete	POST

Delete a non-active run. Returns an error if the run is active.

Example

curl --netrc --request POST \
https://<databricks-instance>/api/2.0/jobs/runs/delete \
--data '{ "run_id": <run-id> }'

Replace:

• <databricks-instance> with the Databricks workspace instance name, for example dbc-a1b2345c-d6e7.cloud.databricks.com.

• <run-id> with the ID of the run, for example 123.

This example uses a .netrc file.

Request structure

Field Name	Type	Description
run_id	INT64	The canonical identifier of the run for which to retrieve the metadata.

Data structures

AutoScale

Range defining the min and max number of cluster workers.

Field Name	Type	Description
min_workers	INT32	The minimum number of workers to which the cluster can scale down when underutilized. It is also the initial number of workers the cluster will have after creation.
max_workers	INT32	The maximum number of workers to which the cluster can scale up when overloaded. max_workers must be strictly greater than min_workers.

AwsAttributes

Attributes set during cluster creation related to Amazon Web Services.

Field Name	Type	Description
first_on_demand	INT32	The first first_on_demand nodes of the cluster will be placed on on-demand instances. If this value is greater than 0, the cluster driver node will be placed on an on-demand instance. If this value is greater than or equal to the current cluster size, all nodes will be placed on on-demand instances. If this value is less than the current cluster size, first_on_demand nodes will be placed on on-demand instances and the remainder will be placed on availability instances. This value does not affect cluster size and cannot be mutated over the lifetime of a cluster.
availability	AwsAvailability	Availability type used for all subsequent nodes past the first_on_demand ones. Note: If first_on_demand is zero, this availability type will be used for the entire cluster.
zone_id	STRING	Identifier for the availability zone (AZ) in which the cluster resides. By default, the setting has a value of auto, otherwise known as Auto-AZ. With Auto-AZ, Databricks selects the AZ based on available IPs in the workspace subnets and retries in other availability zones if AWS returns insufficient capacity errors. If you want, you can also specify an availability zone to use. This benefits accounts that have reserved instances in a specific AZ. Specify the AZ as a string (for example, "us-west-2a"). The provided availability zone must be in the same region as the Databricks deployment. For example, “us-west-2a” is not a valid zone ID if the Databricks deployment resides in the “us-east-1” region. The list of available zones as well as the default value can be found by using the GET /api/2.0/clusters/list-zones call.
instance_profile_arn	STRING	Nodes for this cluster will only be placed on AWS instances with this instance profile. If omitted, nodes will be placed on instances without an instance profile. The instance profile must have previously been added to the Databricks environment by an account administrator. This feature may only be available to certain customer plans.
spot_bid_price_percent	INT32	The max price for AWS spot instances, as a percentage of the corresponding instance type’s on-demand price. For example, if this field is set to 50, and the cluster needs a new i3.xlarge spot instance, then the max price is half of the price of on-demand i3.xlarge instances. Similarly, if this field is set to 200, the max price is twice the price of on-demand i3.xlarge instances. If not specified, the default value is 100. When spot instances are requested for this cluster, only spot instances whose max price percentage matches this field will be considered. For safety, we enforce this field to be no more than 10000.
ebs_volume_type	EbsVolumeType	The type of EBS volumes that will be launched with this cluster.
ebs_volume_count	INT32	The number of volumes launched for each instance. You can choose up to 10 volumes. This feature is only enabled for supported node types. Legacy node types cannot specify custom EBS volumes. For node types with no instance store, at least one EBS volume needs to be specified; otherwise, cluster creation will fail. These EBS volumes will be mounted at /ebs0, /ebs1, and etc. Instance store volumes will be mounted at /local_disk0, /local_disk1, and etc. If EBS volumes are attached, Databricks will configure Spark to use only the EBS volumes for scratch storage because heterogeneously sized scratch devices can lead to inefficient disk utilization. If no EBS volumes are attached, Databricks will configure Spark to use instance store volumes. If EBS volumes are specified, then the Spark configuration spark.local.dir will be overridden.
ebs_volume_size	INT32	The size of each EBS volume (in GiB) launched for each instance. For general purpose SSD, this value must be within the range 100 - 4096. For throughput optimized HDD, this value must be within the range 500 - 4096. Custom EBS volumes cannot be specified for the legacy node types (memory-optimized and compute-optimized).
ebs_volume_iops	INT32	The number of IOPS per EBS gp3 volume. This value must be between 3000 and 16000. The value of IOPS and throughput is calculated based on AWS documentation to match the maximum performance of a gp2 volume with the same volume size. For more information, see the EBS volume limit calculator.
ebs_volume_throughput	INT32	The throughput per EBS gp3 volume, in MiB per second. This value must be between 125 and 1000.

If neither ebs_volume_iops nor ebs_volume_throughput is specified, the values are inferred from the disk size:

Disk size	IOPS	Throughput
Greater than 1000	3 times the disk size, up to 16000	250
Between 170 and 1000	3000	250
Below 170	3000	125

AwsAvailability

The set of AWS availability types supported when setting up nodes for a cluster.

Type	Description
SPOT	Use spot instances.
ON_DEMAND	Use on-demand instances.
SPOT_WITH_FALLBACK	Preferably use spot instances, but fall back to on-demand instances if spot instances cannot be acquired (for example, if AWS spot prices are too high).

ClusterInstance

Identifiers for the cluster and Spark context used by a run. These two values together identify an execution context across all time.

Field Name	Type	Description
cluster_id	STRING	The canonical identifier for the cluster used by a run. This field is always available for runs on existing clusters. For runs on new clusters, it becomes available once the cluster is created. This value can be used to view logs by browsing to /#setting/sparkui/$cluster_id/driver-logs. The logs will continue to be available after the run completes. The response won’t include this field if the identifier is not available yet.
spark_context_id	STRING	The canonical identifier for the Spark context used by a run. This field will be filled in once the run begins execution. This value can be used to view the Spark UI by browsing to /#setting/sparkui/$cluster_id/$spark_context_id. The Spark UI will continue to be available after the run has completed. The response won’t include this field if the identifier is not available yet.

ClusterLogConf

Path to cluster log.

Field Name	Type	Description
dbfs OR s3	DbfsStorageInfo S3StorageInfo	DBFS location of cluster log. Destination must be provided. For example, { "dbfs" : { "destination" : "dbfs:/home/cluster_log" } } S3 location of cluster log. destination and either region or warehouse must be provided. For example, { "s3": { "destination" : "s3://cluster_log_bucket/prefix", "region" : "us-west-2" } }

ClusterSpec

Important

• When you run a job on a new jobs cluster, the job is treated as a Jobs Compute (automated) workload subject to Jobs Compute pricing.

• When you run a job on an existing all-purpose cluster, it is treated as an All-Purpose Compute (interactive) workload subject to All-Purpose Compute pricing.

Field Name	Type	Description
existing_cluster_id OR new_cluster	STRING OR NewCluster	If existing_cluster_id, the ID of an existing cluster that will be used for all runs of this job. When running jobs on an existing cluster, you may need to manually restart the cluster if it stops responding. We suggest running jobs on new clusters for greater reliability. If new_cluster, a description of a cluster that will be created for each run. If specifying a PipelineTask, then this field can be empty.
libraries	An array of Library	An optional list of libraries to be installed on the cluster that will execute the job. The default value is an empty list.

ClusterTag

Cluster tag definition.

Type	Description
STRING	The key of the tag. The key length must be between 1 and 127 UTF-8 characters, inclusive. For a list of all restrictions, see AWS Tag Restrictions: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/Using_Tags.html#tag-restrictions
STRING	The value of the tag. The value length must be less than or equal to 255 UTF-8 characters. For a list of all restrictions, see AWS Tag Restrictions: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/Using_Tags.html#tag-restrictions

CronSchedule

Field Name	Type	Description
quartz_cron_expression	STRING	A Cron expression using Quartz syntax that describes the schedule for a job. See Cron Trigger for details. This field is required.
timezone_id	STRING	A Java timezone ID. The schedule for a job will be resolved with respect to this timezone. See Java TimeZone for details. This field is required.
pause_status	STRING	Indicate whether this schedule is paused or not. Either “PAUSED” or “UNPAUSED”.

DbfsStorageInfo

DBFS storage information.

Field Name	Type	Description
destination	STRING	DBFS destination. Example: dbfs:/my/path

EbsVolumeType

Databricks supports gp2 and gp3 EBS volume types. Follow the instructions at Manage SSD storage to select gp2 or gp3 for your workspace.

Type	Description
GENERAL_PURPOSE_SSD	Provision extra storage using AWS EBS volumes.
THROUGHPUT_OPTIMIZED_HDD	Provision extra storage using AWS st1 volumes.

FileStorageInfo

File storage information.

Note

This location type is only available for clusters set up using Databricks Container Services.

Field Name	Type	Description
destination	STRING	File destination. Example: file:/my/file.sh

InitScriptInfo

Path to an init script.

For instructions on using init scripts with Databricks Container Services, see Use an init script.

Note

The file storage type (field name: file) is only available for clusters set up using Databricks Container Services. See FileStorageInfo.

Field Name	Type	Description
workspace OR dbfs (deprecated) OR S3	WorkspaceStorageInfo DbfsStorageInfo (deprecated) S3StorageInfo	Workspace location of init script. Destination must be provided. For example, { "workspace" : { "destination" : "/Users/someone@domain.com/init_script.sh" } } (Deprecated) DBFS location of init script. Destination must be provided. For example, { "dbfs" : { "destination" : "dbfs:/home/init_script" } } S3 location of init script. Destination and either region or warehouse must be provided. For example, { "s3": { "destination" : "s3://init_script_bucket/prefix", "region" : "us-west-2" } }

Job

Field Name	Type	Description
job_id	INT64	The canonical identifier for this job.
creator_user_name	STRING	The creator user name. This field won’t be included in the response if the user has already been deleted.
run_as	STRING	The user name that the job will run as. run_as is based on the current job settings, and is set to the creator of the job if job access control is disabled, or the is_owner permission if job access control is enabled.
settings	JobSettings	Settings for this job and all of its runs. These settings can be updated using the resetJob method.
created_time	INT64	The time at which this job was created in epoch milliseconds (milliseconds since 1/1/1970 UTC).

JobEmailNotifications

Important

The on_start, on_success, and on_failure fields accept only Latin characters (ASCII character set). Using non-ASCII characters will return an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis.

Field Name	Type	Description
on_start	An array of STRING	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.
on_success	An array of STRING	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.
on_failure	An array of STRING	A list of email addresses to be notified when a run unsuccessfully completes. A run is considered to have completed unsuccessfully if it ends with an INTERNAL_ERROR life_cycle_state or a SKIPPED, FAILED, or TIMED_OUT result_state. If this is not specified on job creation, reset, or update the list is empty, and notifications are not sent.
on_duration_warning_threshold_exceeded	An array of STRING	An list of email addresses to be notified when the duration of a run exceeds the threshold specified for the RUN_DURATION_SECONDS metric in the health field. If no rule for the RUN_DURATION_SECONDS metric is specified in the health field for the job, notifications are not sent.
no_alert_for_skipped_runs	BOOL	If true, do not send email to recipients specified in on_failure if the run is skipped.

Field Name	Type	Description
on_start	An array of Webhook	An optional list of system destinations 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. A maximum of 3 destinations can be specified for the on_start property.
on_success	An array of Webhook	An optional list of system destinations to be notified when a run completes successfully. 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. A maximum of 3 destinations can be specified for the on_success property.
on_failure	An array of Webhook	An optional list of system destinations to be notified when a run completes unsuccessfully. A run is considered to have completed unsuccessfully if it ends with an INTERNAL_ERROR life_cycle_state or a SKIPPED, FAILED, or TIMED_OUT result_state. If this is not specified on job creation, reset, or update the list is empty, and notifications are not sent. A maximum of 3 destinations can be specified for the on_failure property.
on_duration_warning_threshold_exceeded	An array of Webhook	An optional list of system destinations to be notified when the duration of a run exceeds the threshold specified for the RUN_DURATION_SECONDS metric in the health field. A maximum of 3 destinations can be specified for the on_duration_warning_threshold_exceeded property.

JobNotificationSettings

Field Name	Type	Description
no_alert_for_skipped_runs	BOOL	If true, do not send notifications to recipients specified in on_failure if the run is skipped.
no_alert_for_canceled_runs	BOOL	If true, do not send notifications to recipients specified in on_failure if the run is canceled.
alert_on_last_attempt	BOOL	If true, do not send notifications to recipients specified in on_start for the retried runs and do not send notifications to recipients specified in on_failure until the last retry of the run.

JobSettings

Important

• When you run a job on a new jobs cluster, the job is treated as a Jobs Compute (automated) workload subject to Jobs Compute pricing.

• When you run a job on an existing all-purpose cluster, it is treated as an All-Purpose Compute (interactive) workload subject to All-Purpose Compute pricing.

Settings for a job. These settings can be updated using the resetJob method.

Field Name	Type	Description
existing_cluster_id OR new_cluster	STRING OR NewCluster	If existing_cluster_id, the ID of an existing cluster that will be used for all runs of this job. When running jobs on an existing cluster, you may need to manually restart the cluster if it stops responding. We suggest running jobs on new clusters for greater reliability. If new_cluster, a description of a cluster that will be created for each run. If specifying a PipelineTask, then this field can be empty.
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task OR pipeline_task OR run_job_task	NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask OR PipelineTask OR RunJobTask	If notebook_task, indicates that this job should run a notebook. This field may not be specified in conjunction with spark_jar_task. If spark_jar_task, indicates that this job should run a JAR. If spark_python_task, indicates that this job should run a Python file. If spark_submit_task, indicates that this job should be launched by the spark submit script. If pipeline_task, indicates that this job should run a Delta Live Tables pipeline. If run_job_task, indicates that this job should run another job.
name	STRING	An optional name for the job. The default value is Untitled.
libraries	An array of Library	An optional list of libraries to be installed on the cluster that will execute the job. The default value is an empty list.
email_notifications	JobEmailNotifications	An optional set of email addresses that will be 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	WebhookNotifications	An optional set of system destinations to notify when runs of this job begin, complete, or fail.
notification_settings	JobNotificationSettings	Optional notification settings that are used when sending notifications to each of the email_notifications and webhook_notifications for this job.
timeout_seconds	INT32	An optional timeout applied to each run of this job. The default behavior is to have no timeout.
max_retries	INT32	An optional maximum number of times to retry an unsuccessful run. A run is considered to be unsuccessful if it completes with the FAILED result_state or INTERNAL_ERROR life_cycle_state. The value -1 means to retry indefinitely and the value 0 means to never retry. The default behavior is to never retry.
min_retry_interval_millis	INT32	An optional minimal interval in milliseconds between attempts. The default behavior is that unsuccessful runs are immediately retried.
retry_on_timeout	BOOL	An optional policy to specify whether to retry a job when it times out. The default behavior is to not retry on timeout.
schedule	CronSchedule	An optional periodic schedule for this job. The default behavior is that the job will only run when triggered by clicking “Run Now” in the Jobs UI or sending an API request to runNow.
max_concurrent_runs	INT32	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 will be 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.
health	JobsHealthRules	An optional set of health rules defined for the job.

JobTask

Field Name	Type	Description
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task OR pipeline_task OR run_job_task	NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask OR PipelineTask OR RunJobTask	If notebook_task, indicates that this job should run a notebook. This field may not be specified in conjunction with spark_jar_task. If spark_jar_task, indicates that this job should run a JAR. If spark_python_task, indicates that this job should run a Python file. If spark_submit_task, indicates that this job should be launched by the spark submit script. If pipeline_task, indicates that this job should run a Delta Live Tables pipeline. If run_job_task, indicates that this job should run another job.

JobsHealthRule

Field Name	Type	Description
metric	STRING	Specifies the health metric that is being evaluated for a particular health rule. Valid values are RUN_DURATION_SECONDS.
operator	STRING	Specifies the operator used to compare the health metric value with the specified threshold. Valid values are GREATER_THAN.
value	INT32	Specifies the threshold value that the health metric should meet to comply with the health rule.

JobsHealthRules

Field Name	Type	Description
rules	An array of JobsHealthRule	An optional set of health rules that can be defined for a job.

Library

Field Name	Type	Description
jar OR egg OR whl OR pypi OR maven OR cran	STRING OR STRING OR STRING OR PythonPyPiLibrary OR MavenLibrary OR RCranLibrary	If jar, URI of the JAR to be installed. DBFS and S3 URIs are supported. For example: { "jar": "dbfs:/mnt/databricks/library.jar" } or { "jar": "s3://my-bucket/library.jar" }. If S3 is used, make sure the cluster has read access on the library. You may need to launch the cluster with an instance profile to access the S3 URI. If egg, URI of the egg to be installed. DBFS and S3 URIs are supported. For example: { "egg": "dbfs:/my/egg" } or { "egg": "s3://my-bucket/egg" }. If S3 is used, make sure the cluster has read access on the library. You may need to launch the cluster with an instance profile to access the S3 URI. If whl, URI of the wheel or zipped wheels to be installed. DBFS and S3 URIs are supported. For example: { "whl": "dbfs:/my/whl" } or { "whl": "s3://my-bucket/whl" }. If S3 is used, make sure the cluster has read access on the library. You may need to launch the cluster with an instance profile to access the S3 URI. Also the wheel file name needs to use the correct convention. If zipped wheels are to be installed, the file name suffix should be .wheelhouse.zip. If pypi, specification of a PyPI library to be installed. Specifying the repo field is optional and if not specified, the default pip index is used. For example: { "package": "simplejson", "repo": "https://my-repo.com" } If maven, specification of a Maven library to be installed. For example: { "coordinates": "org.jsoup:jsoup:1.7.2" } If cran, specification of a CRAN library to be installed.

MavenLibrary

Field Name	Type	Description
coordinates	STRING	Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2. This field is required.
repo	STRING	Maven repo to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
exclusions	An array of STRING	List of dependences to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. Maven dependency exclusions: https://maven.apache.org/guides/introduction/introduction-to-optional-and-excludes-dependencies.html.

NewCluster

Field Name	Type	Description
num_workers OR autoscale	INT32 OR AutoScale	If num_workers, number of worker nodes that this cluster should have. A cluster has one Spark driver and num_workers executors for a total of num_workers + 1 Spark nodes. When reading the properties of a cluster, this field reflects the desired number of workers rather than the actual current number of workers. For example, if a cluster is resized from 5 to 10 workers, this field will immediately be updated to reflect the target size of 10 workers, whereas the workers listed in spark_info will gradually increase from 5 to 10 as the new nodes are provisioned. If autoscale, the required parameters to automatically scale clusters up and down based on load.
spark_version	STRING	The Spark version of the cluster. A list of available Spark versions can be retrieved by using the GET 2.0/clusters/spark-versions call. This field is required.
spark_conf	SparkConfPair	An object containing a set of optional, user-specified Spark configuration key-value pairs. You can also pass in a string of extra JVM options to the driver and the executors via spark.driver.extraJavaOptions and spark.executor.extraJavaOptions respectively. Example Spark confs: {"spark.speculation": true, "spark.streaming.ui.retainedBatches": 5} or {"spark.driver.extraJavaOptions": "-verbose:gc -XX:+PrintGCDetails"}
aws_attributes	AwsAttributes	Attributes related to clusters running on Amazon Web Services. If not specified at cluster creation, a set of default values will be used.
node_type_id	STRING	This field encodes, through a single value, the resources available to each of the Spark nodes in this cluster. For example, the Spark nodes can be provisioned and optimized for memory or compute intensive workloads A list of available node types can be retrieved by using the GET 2.0/clusters/list-node-types call. This field, the instance_pool_id field, or a cluster policy that specifies a node type ID or instance pool ID, is required.
driver_node_type_id	STRING	The node type of the Spark driver. This field is optional; if unset, the driver node type will be set as the same value as node_type_id defined above.
ssh_public_keys	An array of STRING	SSH public key contents that will be added to each Spark node in this cluster. The corresponding private keys can be used to login with the user name ubuntu on port 2200. Up to 10 keys can be specified.
custom_tags	ClusterTag	An object containing a set of tags for cluster resources. Databricks tags all cluster resources (such as AWS instances and EBS volumes) with these tags in addition to default_tags. Note: Tags are not supported on legacy node types such as compute-optimized and memory-optimized Databricks allows at most 45 custom tags
cluster_log_conf	ClusterLogConf	The configuration for delivering Spark logs to a long-term storage destination. Only one destination can be specified for one cluster. If the conf is given, the logs will be delivered to the destination every 5 mins. The destination of driver logs is <destination>/<cluster-id>/driver, while the destination of executor logs is <destination>/<cluster-id>/executor.
init_scripts	An array of InitScriptInfo	The configuration for storing init scripts. Any number of scripts can be specified. The scripts are executed sequentially in the order provided. If cluster_log_conf is specified, init script logs are sent to <destination>/<cluster-id>/init_scripts.
spark_env_vars	SparkEnvPair	An object containing a set of optional, user-specified environment variable key-value pairs. Key-value pair of the form (X,Y) are exported as is (i.e., export X='Y') while launching the driver and workers. To specify an additional set of SPARK_DAEMON_JAVA_OPTS, we recommend appending them to $SPARK_DAEMON_JAVA_OPTS as shown in the following example. This ensures that all default databricks managed environmental variables are included as well. Example Spark environment variables: {"SPARK_WORKER_MEMORY": "28000m", "SPARK_LOCAL_DIRS": "/local_disk0"} or {"SPARK_DAEMON_JAVA_OPTS": "$SPARK_DAEMON_JAVA_OPTS -Dspark.shuffle.service.enabled=true"}
enable_elastic_disk	BOOL	Autoscaling Local Storage: when enabled, this cluster dynamically acquires additional disk space when its Spark workers are running low on disk space. This feature requires specific AWS permissions to function correctly - refer to Enable autoscaling local storage for details.
driver_instance_pool_id	STRING	The optional ID of the instance pool to use for the driver node. You must also specify instance_pool_id. Refer to the Instance Pools API for details.
instance_pool_id	STRING	The optional ID of the instance pool to use for cluster nodes. If driver_instance_pool_id is present, instance_pool_id is used for worker nodes only. Otherwise, it is used for both the driver node and worker nodes. Refer to the Instance Pools API for details.

NotebookOutput

Field Name	Type	Description
result	STRING	The value passed to dbutils.notebook.exit(). Databricks restricts this API to return the first 1 MB of the value. For a larger result, your job can store the results in a cloud storage service. This field will be absent if dbutils.notebook.exit() was never called.
truncated	BOOLEAN	Whether or not the result was truncated.

NotebookTask

All the output cells are subject to the size of 8MB. If the output of a cell has a larger size, the rest of the run will be cancelled and the run will be marked as failed. In that case, some of the content output from other cells may also be missing.

If you need help finding the cell that is beyond the limit, run the notebook against an all-purpose cluster and use this notebook autosave technique.

Field Name	Type	Description
notebook_path	STRING	The absolute path of the notebook to be run in the Databricks workspace. This path must begin with a slash. This field is required.
revision_timestamp	LONG	The timestamp of the revision of the notebook.
base_parameters	A map of ParamPair	Base parameters to be used for each run of this job. If the run is initiated by a call to run-now with parameters specified, the two parameters maps will be merged. If the same key is specified in base_parameters and in run-now, the value from run-now will be used. Use Pass context about job runs into job tasks to set parameters containing information about job runs. If the notebook takes a parameter that is not specified in the job’s base_parameters or the run-now override parameters, the default value from the notebook will be used. Retrieve these parameters in a notebook using dbutils.widgets.get.

ParamPair

Name-based parameters for jobs running notebook tasks.

Important

The fields in this data structure accept only Latin characters (ASCII character set). Using non-ASCII characters will return an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis.

Type	Description
STRING	Parameter name. Pass to dbutils.widgets.get to retrieve the value.
STRING	Parameter value.

PipelineTask

Field Name	Type	Description
pipeline_id	STRING	The full name of the Delta Live Tables pipeline task to execute.

PythonPyPiLibrary

Field Name	Type	Description
package	STRING	The name of the PyPI package to install. An optional exact version specification is also supported. Examples: simplejson and simplejson==3.8.0. This field is required.
repo	STRING	The repository where the package can be found. If not specified, the default pip index is used.

RCranLibrary

Field Name	Type	Description
package	STRING	The name of the CRAN package to install. This field is required.
repo	STRING	The repository where the package can be found. If not specified, the default CRAN repo is used.

Run

All the information about a run except for its output. The output can be retrieved separately with the getRunOutput method.

Field Name	Type	Description
job_id	INT64	The canonical identifier of the job that contains this run.
run_id	INT64	The canonical identifier of the run. This ID is unique across all runs of all jobs.
creator_user_name	STRING	The creator user name. This field won’t be included in the response if the user has already been deleted.
number_in_job	INT64	The sequence number of this run among all runs of the job. This value starts at 1.
original_attempt_run_id	INT64	If this run is a retry of a prior run attempt, this field contains the run_id of the original attempt; otherwise, it is the same as the run_id.
state	RunState	The result and lifecycle states of the run.
schedule	CronSchedule	The cron schedule that triggered this run if it was triggered by the periodic scheduler.
task	JobTask	The task performed by the run, if any.
cluster_spec	ClusterSpec	A snapshot of the job’s cluster specification when this run was created.
cluster_instance	ClusterInstance	The cluster used for this run. If the run is specified to use a new cluster, this field will be set once the Jobs service has requested a cluster for the run.
overriding_parameters	RunParameters	The parameters used for this run.
start_time	INT64	The time at which this run was started in epoch milliseconds (milliseconds since 1/1/1970 UTC). This may not be the time when the job task starts executing, for example, if the job is scheduled to run on a new cluster, this is the time the cluster creation call is issued.
setup_duration	INT64	The time it took to set up the cluster in milliseconds. For runs that run on new clusters this is the cluster creation time, for runs that run on existing clusters this time should be very short.
execution_duration	INT64	The time in milliseconds it took to execute the commands in the JAR or notebook until they completed, failed, timed out, were cancelled, or encountered an unexpected error.
cleanup_duration	INT64	The time in milliseconds it took to terminate the cluster and clean up any associated artifacts. The total duration of the run is the sum of the setup_duration, the execution_duration, and the cleanup_duration.
end_time	INT64	The time at which this run ended in epoch milliseconds (milliseconds since 1/1/1970 UTC). This field will be set to 0 if the job is still running.
trigger	TriggerType	The type of trigger that fired this run.
run_name	STRING	An optional name for the run. The default value is Untitled. The maximum allowed length is 4096 bytes in UTF-8 encoding.
run_page_url	STRING	The URL to the detail page of the run.
run_type	STRING	The type of the run. JOB_RUN - Normal job run. A run created with Run now. WORKFLOW_RUN - Workflow run. A run created with dbutils.notebook.run. SUBMIT_RUN - Submit run. A run created with Run now.
attempt_number	INT32	The sequence number of this run attempt for a triggered job run. The initial attempt of a run has an attempt_number of 0. If the initial run attempt fails, and the job has a retry policy (max_retries > 0), subsequent runs are created with an original_attempt_run_id of the original attempt’s ID and an incrementing attempt_number. Runs are retried only until they succeed, and the maximum attempt_number is the same as the max_retries value for the job.

RunJobTask

Field Name	Type	Description
job_id	INT32	Unique identifier of the job to run. This field is required.

RunLifeCycleState

The life cycle state of a run. Allowed state transitions are:

• PENDING -> RUNNING -> TERMINATING -> TERMINATED

• PENDING -> SKIPPED

• PENDING -> INTERNAL_ERROR

• RUNNING -> INTERNAL_ERROR

• TERMINATING -> INTERNAL_ERROR

State	Description
PENDING	The run has been triggered. If there is not already an active run of the same job, the cluster and execution context are being prepared. If there is already an active run of the same job, the run will immediately transition into the SKIPPED state without preparing any resources.
RUNNING	The task of this run is being executed.
TERMINATING	The task of this run has completed, and the cluster and execution context are being cleaned up.
TERMINATED	The task of this run has completed, and the cluster and execution context have been cleaned up. This state is terminal.
SKIPPED	This run was aborted because a previous run of the same job was already active. This state is terminal.
INTERNAL_ERROR	An exceptional state that indicates a failure in the Jobs service, such as network failure over a long period. If a run on a new cluster ends in the INTERNAL_ERROR state, the Jobs service terminates the cluster as soon as possible. This state is terminal.

RunParameters

Parameters for this run. Only one of jar_params, python_params, or notebook_params should be specified in the run-now request, depending on the type of job task. Jobs with Spark JAR task or Python task take a list of position-based parameters, and jobs with notebook tasks take a key value map.

Field Name	Type	Description
jar_params	An array of STRING	A list of parameters for jobs with Spark JAR tasks, e.g. "jar_params": ["john doe", "35"]. The parameters will be used to invoke the main function of the main class specified in the Spark JAR task. If not specified upon run-now, it will default to an empty list. jar_params cannot be specified in conjunction with notebook_params. The JSON representation of this field (i.e. {"jar_params":["john doe","35"]}) cannot exceed 10,000 bytes. Use Pass context about job runs into job tasks to set parameters containing information about job runs.
notebook_params	A map of ParamPair	A map 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 is accessible through the dbutils.widgets.get 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 Pass context about job runs into job tasks to set parameters containing information about job runs. The JSON representation of this field (i.e. {"notebook_params":{"name":"john doe","age":"35"}}) cannot exceed 10,000 bytes.
python_params	An array of STRING	A list of parameters for jobs with Python tasks, e.g. "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 (i.e. {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes. Use Pass context about job runs into job tasks to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters will return an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis.
spark_submit_params	An array of STRING	A list of parameters for jobs with spark submit task, e.g. "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 (i.e. {"python_params":["john doe","35"]}) cannot exceed 10,000 bytes. Use Pass context about job runs into job tasks to set parameters containing information about job runs. Important These parameters accept only Latin characters (ASCII character set). Using non-ASCII characters will return an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis.

RunResultState

The result state of the run.

• If life_cycle_state = TERMINATED: if the run had a task, the result is guaranteed to be available, and it indicates the result of the task.

• If life_cycle_state = PENDING, RUNNING, or SKIPPED, the result state is not available.

• If life_cycle_state = TERMINATING or lifecyclestate = INTERNAL_ERROR: the result state is available if the run had a task and managed to start it.

Once available, the result state never changes.

State	Description
SUCCESS	The task completed successfully.
FAILED	The task completed with an error.
TIMEDOUT	The run was stopped after reaching the timeout.
CANCELED	The run was canceled at user request.

RunState

Field Name	Type	Description
life_cycle_state	RunLifeCycleState	A description of a run’s current location in the run lifecycle. This field is always available in the response.
result_state	RunResultState	The result state of a run. If it is not available, the response won’t include this field. See RunResultState for details about the availability of result_state.
user_cancelled_or_timedout	BOOLEAN	Whether a run was canceled manually by a user or by the scheduler because the run timed out.
state_message	STRING	A descriptive message for the current state. This field is unstructured, and its exact format is subject to change.

S3StorageInfo

S3 storage information.

Field Name	Type	Description
destination	STRING	S3 destination. For example: s3://my-bucket/some-prefix You must configure the cluster with an instance profile and the instance profile must have write access to the destination. You cannot use AWS keys.
region	STRING	S3 region. For example: us-west-2. Either region or warehouse must be set. If both are set, warehouse is used.
warehouse	STRING	S3 warehouse. For example: https://s3-us-west-2.amazonaws.com. Either region or warehouse must be set. If both are set, warehouse is used.
enable_encryption	BOOL	(Optional)Enable server side encryption, false by default.
encryption_type	STRING	(Optional) The encryption type, it could be sse-s3 or sse-kms. It is used only when encryption is enabled and the default type is sse-s3.
kms_key	STRING	(Optional) KMS key used if encryption is enabled and encryption type is set to sse-kms.
canned_acl	STRING	(Optional) Set canned access control list. For example: bucket-owner-full-control. If canned_acl is set, the cluster instance profile must have s3:PutObjectAcl permission on the destination bucket and prefix. The full list of possible canned ACLs can be found at https://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. By default only the object owner gets full control. If you are using cross account role for writing data, you may want to set bucket-owner-full-control to make bucket owner able to read the logs.

SparkConfPair

Spark configuration key-value pairs.

Type	Description
STRING	A configuration property name.
STRING	The configuration property value.

SparkEnvPair

Spark environment variable key-value pairs.

Important

When specifying environment variables in a job cluster, the fields in this data structure accept only Latin characters (ASCII character set). Using non-ASCII characters will return an error. Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis.

Type	Description
STRING	An environment variable name.
STRING	The environment variable value.

SparkJarTask

Field Name	Type	Description
jar_uri	STRING	Deprecated since 04/2016. Provide a jar through the libraries field instead. For an example, see Create.
main_class_name	STRING	The full name of the class containing the main method to be executed. This class must be contained in a JAR provided as a library. The code should use SparkContext.getOrCreate to obtain a Spark context; otherwise, runs of the job will fail.
parameters	An array of STRING	Parameters passed to the main method. Use Pass context about job runs into job tasks to set parameters containing information about job runs.

SparkPythonTask

Field Name	Type	Description
python_file	STRING	The URI of the Python file to be executed. DBFS and S3 paths are supported. This field is required.
parameters	An array of STRING	Command line parameters passed to the Python file. Use Pass context about job runs into job tasks to set parameters containing information about job runs.

SparkSubmitTask

Important

• You can invoke Spark submit tasks only on new clusters.

• In the new_cluster specification, libraries and spark_conf are not supported. Instead, use --jars and --py-files to add Java and Python libraries and --conf to set the Spark configuration.

• master, deploy-mode, and executor-cores are automatically configured by Databricks; you cannot specify them in parameters.

• By default, the Spark submit job uses all available memory (excluding reserved memory for Databricks services). You can set --driver-memory, and --executor-memory to a smaller value to leave some room for off-heap usage.

• The --jars, --py-files, --files arguments support DBFS and S3 paths.

For example, assuming the JAR is uploaded to DBFS, you can run SparkPi by setting the following parameters.

{
  "parameters": [
    "--class",
    "org.apache.spark.examples.SparkPi",
    "dbfs:/path/to/examples.jar",
    "10"
  ]
}

Field Name	Type	Description
parameters	An array of STRING	Command-line parameters passed to spark submit. Use Pass context about job runs into job tasks to set parameters containing information about job runs.

TriggerType

These are the type of triggers that can fire a run.

Type	Description
PERIODIC	Schedules that periodically trigger runs, such as a cron scheduler.
ONE_TIME	One time triggers that fire a single run. This occurs you triggered a single run on demand through the UI or the API.
RETRY	Indicates a run that is triggered as a retry of a previously failed run. This occurs when you request to re-run the job in case of failures.

ViewItem

The exported content is in HTML format. For example, if the view to export is dashboards, one HTML string is returned for every dashboard.

Field Name	Type	Description
content	STRING	Content of the view.
name	STRING	Name of the view item. In the case of code view, the notebook’s name. In the case of dashboard view, the dashboard’s name.
type	ViewType	Type of the view item.

ViewType

Type	Description
NOTEBOOK	Notebook view item.
DASHBOARD	Dashboard view item.

ViewsToExport

View to export: either code, all dashboards, or all.

Type	Description
CODE	Code view of the notebook.
DASHBOARDS	All dashboard views of the notebook.
ALL	All views of the notebook.

Webhook

Field Name	Type	Description
id	STRING	Identifier referencing a system notification destination. This field is required.

WebhookNotifications

Field Name	Type	Description
on_start	An array of Webhook	An optional list of system destinations 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. A maximum of 3 destinations can be specified for the on_start property.
on_success	An array of Webhook	An optional list of system destinations to be notified when a run completes successfully. 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. A maximum of 3 destinations can be specified for the on_success property.
on_failure	An array of Webhook	An optional list of system destinations to be notified when a run completes unsuccessfully. A run is considered to have completed unsuccessfully if it ends with an INTERNAL_ERROR life_cycle_state or a SKIPPED, FAILED, or TIMED_OUT result_state. If this is not specified on job creation, reset, or update the list is empty, and notifications are not sent. A maximum of 3 destinations can be specified for the on_failure property.
on_duration_warning_threshold_exceeded	An array of Webhook	An optional list of system destinations to be notified when the duration of a run exceeds the threshold specified for the RUN_DURATION_SECONDS metric in the health field. A maximum of 3 destinations can be specified for the on_duration_warning_threshold_exceeded property.

WorkspaceStorageInfo

Workspace storage information.

Field Name	Type	Description
destination	STRING	File destination. Example: /Users/someone@domain.com/init_script.sh