Jobs API
The Jobs API allows you to create, edit, and delete jobs. The maximum allowed size of a request to the Jobs API is 10MB. See Create a High Concurrency cluster for a how-to guide on this API.
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.
An example request for a job that runs at 10:15pm each night:
{
"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": 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"
}
}
And 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. |
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task | NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask | 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. |
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. |
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. |
List
Endpoint | HTTP Method |
---|---|
2.0/jobs/list |
GET |
List all jobs.
An example 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.
An example request:
{
"job_id": 1
}
Get
Endpoint | HTTP Method |
---|---|
2.0/jobs/get |
GET |
Retrieve information about a single job. An example request:
/jobs/get?job_id=1
An example 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": []
},
"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.
An example request that makes job 2 identical to job 1 in the create example:
{
"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": []
},
"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"
}
}
}
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 |
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.
An example request that removes libraries and adds email notification settings to job 1 defined in the create example:
{
"job_id": 1,
"new_settings": {
"existing_cluster_id": "1201-my-cluster",
"email_notifications": {
"on_start": ["donald@duck.com"],
"on_success": [],
"on_failure": []
}
},
"fields_to_remove": ["libraries"]
}
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. Any top-level fields specified in Changes to the field |
fields_to_remove | An array of STRING |
Remove top-level fields in the job settings. Removing nested fields is not supported. This field is optional. |
Run now
Important
- A workspace is limited to 1000 concurrent job runs. A
429 Too Many Requests
response is returned when you request a run that cannot be started immediately. - The number of jobs a workspace can create in an hour is limited to 5000 (includes “run now” and “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.
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"]
}
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.
If not specified upon You cannot specify notebook_params in conjunction with jar_params. The JSON representation of this field (i.e.
|
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. |
Runs submit
Important
- A workspace is limited to 1000 concurrent job runs. A
429 Too Many Requests
response is returned when you request a run that cannot be started immediately. - The number of jobs a workspace can create in an hour is limited to 5000 (includes “run now” and “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. Runs submitted using this endpoint don’t display in the UI. Use the jobs/runs/get
API to check the run state after the job is submitted.
An example request:
{
"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"
}
}
And 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. |
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task | NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask | 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. |
run_name | STRING |
An optional name for the run. 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. |
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 that can be used to guarantee the idempotency of job run requests. If an active run with the provided token already exists, the request will not create a new run, but will return the ID of the existing run instead. If you specify the idempotency token, upon failure you can retry until the request succeeds. Databricks guarantees that exactly one run will be launched with that idempotency token. This token should have at most 64 characters. |
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 Job API, see Runs export.
An example request:
/jobs/runs/list?job_id=1&active_only=false&offset=1&limit=1&run_type=JOB_RUN
And 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,
"trigger": "PERIODIC"
}
],
"has_more": true
}
Request structure
Field Name | Type | Description |
---|---|---|
active_only OR completed_only | BOOL OR BOOL |
If active_only is If completed_only is |
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 Job API, see Runs export.
An example request:
/jobs/runs/get?run_id=452
An example 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/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,
"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 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. |
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.
An example request:
/jobs/runs/export?run_id=452
An example 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 run. The run is canceled asynchronously, so when this request completes, the run may still be running. 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.
An example request:
{
"run_id": 453
}
Runs get output
Endpoint | HTTP Method |
---|---|
2.0/jobs/runs/get-output |
GET |
Retrieve the output and metadata of a 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 Job API, see Runs export.
An example request:
/jobs/runs/get-output?run_id=453
And 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/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,
"setup_duration": 259754,
"execution_duration": 3589020,
"cleanup_duration": 31038,
"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. 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
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.
An example request:
{
"run_id": 42
}
Data structures
In this section:
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 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 The response won’t include this field if the identifier is not available yet. |
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. |
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. |
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”. |
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. |
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 will be empty, and 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. |
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. |
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task | NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask | 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. |
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. |
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. |
JobTask
Field Name | Type | Description |
---|---|---|
notebook_task OR spark_jar_task OR spark_python_task OR spark_submit_task | NotebookTask OR SparkJarTask OR SparkPythonTask OR SparkSubmitTask | 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. |
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 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 Runtime versions API 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
Example Spark confs:
|
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 List node types API call. This field 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:
|
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.,
To specify an additional set of Example Spark environment variables:
|
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 Autoscaling local storage for details. |
instance_pool_id | STRING |
The optional ID of the instance pool to which the cluster belongs. Refer to 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 Use Task parameter variables to set parameters containing information about job runs. If the notebook takes a parameter that is not specified in the job’s 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. |
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.
|
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. |
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. Use Task parameter variables 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.
If not specified upon notebook_params cannot be specified in conjunction with jar_params. Use Task parameter variables to set parameters containing information about job runs. The JSON representation of this field (i.e.
|
python_params | An array of STRING |
A list of parameters for jobs with Python tasks, e.g. Use Task parameter variables 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.
Use Task parameter variables 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. |
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. |
state_message | STRING |
A descriptive message for the current state. This field is unstructured, and its exact format is subject to change. |
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 |
parameters | An array of STRING |
Parameters passed to the main method. Use Task parameter variables 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 Task parameter variables 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
andspark_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
, andexecutor-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 Task parameter variables to set parameters containing information about job runs. |
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, it would be the notebook’s name. In the case of dashboard view, it would be the dashboard’s name. |
type | ViewType | Type of the view item. |
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. |
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
, orSKIPPED
, 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. |
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. |
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. |