Delta Live Tables API guide

Important

This article’s content has been retired and might not be updated. See Delta Live Tables in the Databricks REST API Reference.

The Delta Live Tables API allows you to create, edit, delete, start, and view details about pipelines.

Important

To access Databricks REST APIs, you must authenticate.

Create a pipeline

Endpoint	HTTP Method
`2.0/pipelines`	`POST`

Creates a new Delta Live Tables pipeline.

Example

This example creates a new triggered pipeline.

Request

curl --netrc -X POST \
https://<databricks-instance>/api/2.0/pipelines \
--data @pipeline-settings.json

pipeline-settings.json:

{
  "name": "Wikipedia pipeline (SQL)",
  "storage": "/Users/username/data",
  "clusters": [
    {
      "label": "default",
      "autoscale": {
        "min_workers": 1,
        "max_workers": 5,
        "mode": "ENHANCED"
      }
    }
  ],
  "libraries": [
    {
      "notebook": {
        "path": "/Users/username/DLT Notebooks/Delta Live Tables quickstart (SQL)"
      }
    }
  ],
  "continuous": false
}

Replace:

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

This example uses a .netrc file.

Response

{
  "pipeline_id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5"
}

Request structure

See PipelineSettings.

Response structure

Field Name	Type	Description
pipeline_id	`STRING`	The unique identifier for the newly created pipeline.

Edit a pipeline

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}`	`PUT`

Updates the settings for an existing pipeline.

Example

This example adds a target parameter to the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X PUT \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5 \
--data @pipeline-settings.json

pipeline-settings.json

{
  "id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
  "name": "Wikipedia pipeline (SQL)",
  "storage": "/Users/username/data",
  "clusters": [
    {
      "label": "default",
      "autoscale": {
        "min_workers": 1,
        "max_workers": 5,
        "mode": "ENHANCED"
      }
    }
  ],
  "libraries": [
    {
      "notebook": {
        "path": "/Users/username/DLT Notebooks/Delta Live Tables quickstart (SQL)"
      }
    }
  ],
  "target": "wikipedia_quickstart_data",
  "continuous": false
}

Replace:

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

This example uses a .netrc file.

Request structure

See PipelineSettings.

Delete a pipeline

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}`	`DELETE`

Deletes a pipeline from the Delta Live Tables system.

Example

This example deletes the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X DELETE \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5

Replace:

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

This example uses a .netrc file.

Start a pipeline update

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}/updates`	`POST`

Starts an update for a pipeline. You can start an update for the entire pipeline graph, or a selective update of specific tables.

Examples

Start a full refresh

This example starts an update with full refresh for the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X POST \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/updates \
--data '{ "full_refresh": "true" }'

Replace:

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

This example uses a .netrc file.

Response

{
  "update_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8",
  "request_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8"
}

Start an update of selected tables

This example starts an update that refreshes the sales_orders_cleaned and sales_order_in_chicago tables in the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X POST \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/updates \
--data '{ "refresh_selection": ["sales_orders_cleaned", "sales_order_in_chicago"] }'

Replace:

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

This example uses a .netrc file.

Response

{
  "update_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8",
  "request_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8"
}

Start a full update of selected tables

This example starts an update of the sales_orders_cleaned and sales_order_in_chicago tables, and an update with full refresh of the customers and sales_orders_raw tables in the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5.

Request

curl --netrc -X POST \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/updates \
--data '{ "refresh_selection": ["sales_orders_cleaned", "sales_order_in_chicago"], "full_refresh_selection": ["customers", "sales_orders_raw"] }'

Replace:

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

This example uses a .netrc file.

Response

{
  "update_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8",
  "request_id": "a1b23c4d-5e6f-78gh-91i2-3j4k5lm67no8"
}

Request structure

Field Name

Type

Description

full_refresh

BOOLEAN

Whether to reprocess all data. If true, the Delta Live Tables system resets all tables that are resettable before running the pipeline.

This field is optional.

The default value is false.

An error is returned if full_refesh is true and either refresh_selection or full_refresh_selection is set.

refresh_selection

An array of STRING

A list of tables to update. Use refresh_selection to start a refresh of a selected set of tables in the pipeline graph.

This field is optional. If both refresh_selection and full_refresh_selection are empty, the entire pipeline graph is refreshed.

An error is returned if:

full_refesh is true and refresh_selection is set.
One or more of the specified tables does not exist in the pipeline graph.

full_refresh_selection

An array of STRING

A list of tables to update with full refresh. Use full_refresh_selection to start an update of a selected set of tables. The states of the specified tables are reset before the Delta Live Tables system starts the update.

This field is optional. If both refresh_selection and full_refresh_selection are empty, the entire pipeline graph is refreshed.

An error is returned if:

full_refesh is true and refresh_selection is set.
One or more of the specified tables does not exist in the pipeline graph.
One or more of the specified tables is not resettable.

Response structure

Field Name	Type	Description
`update_id`	`STRING`	The unique identifier of the newly created update.
`request_id`	`STRING`	The unique identifier of the request that started the update.

Get the status of a pipeline update request

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}/requests/{request_id}`	`GET`

Gets the status and information for the pipeline update associated with request_id, where request_id is a unique identifier for the request initiating the pipeline update. If the update is retried or restarted, then the new update inherits the request_id.

Example

For the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5, this example returns status and information for the update associated with request ID a83d9f7c-d798-4fd5-aa39-301b6e6f4429:

Request

curl --netrc -X GET \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/requests/a83d9f7c-d798-4fd5-aa39-301b6e6f4429

Replace:

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

This example uses a .netrc file.

Response

{
   "status": "TERMINATED",
   "latest_update":{
     "pipeline_id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
     "update_id": "90da8183-89de-4715-b5a9-c243e67f0093",
     "config":{
       "id": "aae89b88-e97e-40c4-8e1a-1b7ac76657e8",
       "name": "Retail sales (SQL)",
       "storage": "/Users/username/data",
       "configuration":{
         "pipelines.numStreamRetryAttempts": "5"
       },
       "clusters":[
         {
           "label": "default",
           "autoscale":{
             "min_workers": 1,
             "max_workers": 5,
             "mode": "ENHANCED"
           }
         }
       ],
       "libraries":[
         {
           "notebook":{
             "path": "/Users/username/DLT Notebooks/Delta Live Tables quickstart (SQL)"
           }
         }
       ],
       "continuous": false,
       "development": true,
       "photon": true,
       "edition": "advanced",
       "channel": "CURRENT"
     },
     "cause": "API_CALL",
     "state": "COMPLETED",
     "cluster_id": "1234-567891-abcde123",
     "creation_time": 1664304117145,
     "full_refresh": false,
     "request_id": "a83d9f7c-d798-4fd5-aa39-301b6e6f4429"
   }
}

Response structure

Field Name	Type	Description
`status`	`STRING`	The status of the pipeline update request. One of `ACTIVE`: An update for this request is actively running or may be retried in a new update. `TERMINATED`: The request is terminated and will not be retried or restarted.
`pipeline_id`	`STRING`	The unique identifier of the pipeline.
`update_id`	`STRING`	The unique identifier of the update.
`config`	PipelineSettings	The pipeline settings.
`cause`	`STRING`	The trigger for the update. One of `API_CALL`, `RETRY_ON_FAILURE`, `SERVICE_UPGRADE`, `SCHEMA_CHANGE`, `JOB_TASK`, or `USER_ACTION`.
`state`	`STRING`	The state of the update. One of `QUEUED`, `CREATED` `WAITING_FOR_RESOURCES`, `INITIALIZING`, `RESETTING`, `SETTING_UP_TABLES`, `RUNNING`, `STOPPING`, `COMPLETED`, `FAILED`, or `CANCELED`.
`cluster_id`	`STRING`	The identifier of the cluster running the update.
`creation_time`	`INT64`	The timestamp when the update was created.
`full_refresh`	`BOOLEAN`	Whether this update resets all tables before running
`refresh_selection`	An array of `STRING`	A list of tables to update without full refresh.
`full_refresh_selection`	An array of `STRING`	A list of tables to update with full refresh.
`request_id`	`STRING`	The unique identifier of the request that started the update. This is the value returned by the update request. If the update is retried or restarted, then the new update inherits the request_id. However, the `update_id` will be different.

Stop any active pipeline update

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}/stop`	`POST`

Stops any active pipeline update. If no update is running, this request is a no-op.

For a continuous pipeline, the pipeline execution is paused. Tables currently processing finish refreshing, but downstream tables are not refreshed. On the next pipeline update, Delta Live Tables performs a selected refresh of tables that did not complete processing, and resumes processing of the remaining pipeline DAG.

For a triggered pipeline, the pipeline execution is stopped. Tables currently processing finish refreshing, but downstream tables are not refreshed. On the next pipeline update, Delta Live Tables refreshes all tables.

Example

This example stops an update for the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X POST \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/stop

Replace:

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

This example uses a .netrc file.

List pipeline events

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}/events`	`GET`

Retrieves events for a pipeline.

Example

This example retrieves a maximum of 5 events for the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5.

Request

curl --netrc -X GET \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/events?max_results=5

Replace:

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

This example uses a .netrc file.

Request structure

Field Name	Type	Description
`page_token`	`STRING`	Page token returned by previous call. This field is mutually exclusive with all fields in this request except max_results. An error is returned if any fields other than max_results are set when this field is set. This field is optional.
`max_results`	`INT32`	The maximum number of entries to return in a single page. The system may return fewer than `max_results` events in a response, even if there are more events available. This field is optional. The default value is 25. The maximum value is 100. An error is returned if the value of `max_results` is greater than 100.
`order_by`	`STRING`	A string indicating a sort order by timestamp for the results, for example, `["timestamp asc"]`. The sort order can be ascending or descending. By default, events are returned in descending order by timestamp. This field is optional.
`filter`	`STRING`	Criteria to select a subset of results, expressed using a SQL-like syntax. The supported filters are: `level='INFO'` (or `WARN` or `ERROR`) `level in ('INFO', 'WARN')` `id='[event-id]'` `timestamp > 'TIMESTAMP'` (or `>=`,`<`,`<=`,`=`) Composite expressions are supported, for example: `level in ('ERROR', 'WARN') AND timestamp> '2021-07-22T06:37:33.083Z'` This field is optional.

Response structure

Field Name	Type	Description
`events`	An array of pipeline events.	The list of events matching the request criteria.
`next_page_token`	`STRING`	If present, a token to fetch the next page of events.
`prev_page_token`	`STRING`	If present, a token to fetch the previous page of events.

Get pipeline details

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}`	`GET`

Gets details about a pipeline, including the pipeline settings and recent updates.

Example

This example gets details for the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X GET \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5

Replace:

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

This example uses a .netrc file.

Response

{
  "pipeline_id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
  "spec": {
    "id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
    "name": "Wikipedia pipeline (SQL)",
    "storage": "/Users/username/data",
    "clusters": [
      {
        "label": "default",
        "autoscale": {
          "min_workers": 1,
          "max_workers": 5,
          "mode": "ENHANCED"
        }
      }
    ],
    "libraries": [
      {
        "notebook": {
          "path": "/Users/username/DLT Notebooks/Delta Live Tables quickstart (SQL)"
        }
      }
    ],
    "target": "wikipedia_quickstart_data",
    "continuous": false
  },
  "state": "IDLE",
  "cluster_id": "1234-567891-abcde123",
  "name": "Wikipedia pipeline (SQL)",
  "creator_user_name": "username",
  "latest_updates": [
    {
      "update_id": "8a0b6d02-fbd0-11eb-9a03-0242ac130003",
      "state": "COMPLETED",
      "creation_time": "2021-08-13T00:37:30.279Z"
    },
    {
      "update_id": "a72c08ba-fbd0-11eb-9a03-0242ac130003",
      "state": "CANCELED",
      "creation_time": "2021-08-13T00:35:51.902Z"
    },
    {
      "update_id": "ac37d924-fbd0-11eb-9a03-0242ac130003",
      "state": "FAILED",
      "creation_time": "2021-08-13T00:33:38.565Z"
    }
  ],
  "run_as_user_name": "username"
}

Response structure

Field Name	Type	Description
`pipeline_id`	`STRING`	The unique identifier of the pipeline.
`spec`	PipelineSettings	The pipeline settings.
`state`	`STRING`	The state of the pipeline. One of `IDLE` or `RUNNING`. If state = `RUNNING`, then there is at least one active update.
`cluster_id`	`STRING`	The identifier of the cluster running the pipeline.
`name`	`STRING`	The user-friendly name for this pipeline.
`creator_user_name`	`STRING`	The username of the pipeline creator.
`latest_updates`	An array of UpdateStateInfo	Status of the most recent updates for the pipeline, ordered with the newest update first.
`run_as_user_name`	`STRING`	The username that the pipeline runs as.

Get update details

Endpoint	HTTP Method
`2.0/pipelines/{pipeline_id}/updates/{update_id}`	`GET`

Gets details for a pipeline update.

Example

This example gets details for update 9a84f906-fc51-11eb-9a03-0242ac130003 for the pipeline with ID a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5:

Request

curl --netrc -X GET \
https://<databricks-instance>/api/2.0/pipelines/a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5/updates/9a84f906-fc51-11eb-9a03-0242ac130003

Replace:

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

This example uses a .netrc file.

Response

{
  "update": {
    "pipeline_id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
    "update_id": "9a84f906-fc51-11eb-9a03-0242ac130003",
    "config": {
      "id": "a12cd3e4-0ab1-1abc-1a2b-1a2bcd3e4fg5",
      "name": "Wikipedia pipeline (SQL)",
      "storage": "/Users/username/data",
      "configuration": {
        "pipelines.numStreamRetryAttempts": "5"
      },
      "clusters": [
        {
          "label": "default",
          "autoscale": {
            "min_workers": 1,
            "max_workers": 5,
            "mode": "ENHANCED"
          }
        }
      ],
      "libraries": [
        {
          "notebook": {
            "path": "/Users/username/DLT Notebooks/Delta Live Tables quickstart (SQL)"
          }
        }
      ],
      "target": "wikipedia_quickstart_data",
      "continuous": false,
      "development": false
    },
    "cause": "API_CALL",
    "state": "COMPLETED",
    "creation_time": 1628815050279,
    "full_refresh": true,
    "request_id": "a83d9f7c-d798-4fd5-aa39-301b6e6f4429"
  }
}

Response structure

Field Name	Type	Description
`pipeline_id`	`STRING`	The unique identifier of the pipeline.
`update_id`	`STRING`	The unique identifier of this update.
`config`	PipelineSettings	The pipeline settings.
`cause`	`STRING`	The trigger for the update. One of `API_CALL`, `RETRY_ON_FAILURE`, `SERVICE_UPGRADE`.
`state`	`STRING`	The state of the update. One of `QUEUED`, `CREATED` `WAITING_FOR_RESOURCES`, `INITIALIZING`, `RESETTING`, `SETTING_UP_TABLES`, `RUNNING`, `STOPPING`, `COMPLETED`, `FAILED`, or `CANCELED`.
`cluster_id`	`STRING`	The identifier of the cluster running the pipeline.
`creation_time`	`INT64`	The timestamp when the update was created.
`full_refresh`	`BOOLEAN`	Whether this was a full refresh. If true, all pipeline tables were reset before running the update.

List pipelines

Endpoint	HTTP Method
`2.0/pipelines/`	`GET`

Lists pipelines defined in the Delta Live Tables system.

Example

This example retrieves details for pipelines where the name contains quickstart:

Request

curl --netrc -X GET \
https://<databricks-instance>/api/2.0/pipelines?filter=name%20LIKE%20%27%25quickstart%25%27

Replace:

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

This example uses a .netrc file.

Response

{
  "statuses": [
    {
      "pipeline_id": "e0f01758-fc61-11eb-9a03-0242ac130003",
      "state": "IDLE",
      "name": "DLT quickstart (Python)",
      "latest_updates": [
        {
          "update_id": "ee9ae73e-fc61-11eb-9a03-0242ac130003",
          "state": "COMPLETED",
          "creation_time": "2021-08-13T00:34:21.871Z"
        }
      ],
      "creator_user_name": "username"
    },
    {
      "pipeline_id": "f4c82f5e-fc61-11eb-9a03-0242ac130003",
      "state": "IDLE",
      "name": "My DLT quickstart example",
      "creator_user_name": "username"
    }
  ],
  "next_page_token": "eyJ...==",
  "prev_page_token": "eyJ..x9"
}

Request structure

Field Name	Type	Description
`page_token`	`STRING`	Page token returned by previous call. This field is optional.
`max_results`	`INT32`	The maximum number of entries to return in a single page. The system may return fewer than `max_results` events in a response, even if there are more events available. This field is optional. The default value is 25. The maximum value is 100. An error is returned if the value of `max_results` is greater than 100.
`order_by`	An array of `STRING`	A list of strings specifying the order of results, for example, `["name asc"]`. Supported `order_by` fields are `id` and `name`. The default is `id asc`. This field is optional.
`filter`	`STRING`	Select a subset of results based on the specified criteria. The supported filters are: `"notebook='<path>'"` to select pipelines that reference the provided notebook path. `name LIKE '[pattern]'` to select pipelines with a name that matches `pattern`. Wildcards are supported, for example: `name LIKE '%shopping%'` Composite filters are not supported. This field is optional.

Response structure

Field Name	Type	Description
`statuses`	An array of PipelineStateInfo	The list of events matching the request criteria.
`next_page_token`	`STRING`	If present, a token to fetch the next page of events.
`prev_page_token`	`STRING`	If present, a token to fetch the previous page of events.

Data structures

In this section:

AwsAttributes
AwsAvailability
ClusterLogConf
DbfsStorageInfo
EbsVolumeType
FileStorageInfo
InitScriptInfo
KeyValue
NotebookLibrary
PipelinesAutoScale
PipelineLibrary
PipelinesNewCluster
PipelineSettings
PipelineStateInfo
S3StorageInfo
UpdateStateInfo
WorkspaceStorageInfo

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).

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" } }

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.

Important

Init scripts are not supported with Unity Catalog-enabled pipelines. See Limitations.

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" } }

KeyValue

A key-value pair that specifies configuration parameters.

Field Name	Type	Description
`key`	`STRING`	The configuration property name.
`value`	`STRING`	The configuration property value.

NotebookLibrary

A specification for a notebook containing pipeline code.

Field Name

Type

Description

path

STRING

The absolute path to the notebook.

This field is required.

PipelinesAutoScale

Attributes defining an autoscaling cluster.

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.

mode

STRING

The autoscaling mode for the cluster:

ENHANCED to use enhanced autoscaling.
LEGACY to use the cluster autoscaling functionality.

PipelineLibrary

A specification for pipeline dependencies.

Field Name	Type	Description
`notebook`	NotebookLibrary	The path to a notebook defining Delta Live Tables datasets. The path must be in the Databricks workspace, for example: `{ "notebook" : { "path" : "/my-pipeline-notebook-path" } }`.

PipelinesNewCluster

A pipeline cluster specification.

The Delta Live Tables system sets the following attributes. These attributes cannot be configured by users:

spark_version

Field Name	Type	Description
`label`	`STRING`	A label for the cluster specification, either `default` to configure the default cluster, or `maintenance` to configure the maintenance cluster. This field is optional. The default value is `default`.
`spark_conf`	KeyValue	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.
`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`	KeyValue	An object containing a set of tags for cluster resources. Databricks tags all cluster resources 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 this configuration is provided, 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`.
`spark_env_vars`	KeyValue	An object containing a set of optional, user-specified environment variable key-value pairs. Key-value pairs of the form (X,Y) are exported as is (that is, `export X='Y'`) while launching the driver and workers. In order to specify an additional set of `SPARK_DAEMON_JAVA_OPTS`, Databricks recommends 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"}`
`init_scripts`	An array of InitScriptInfo	The configuration for storing init scripts. Any number of destinations 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`.
`instance_pool_id`	`STRING`	The optional ID of the instance pool to which the cluster belongs. See Create a pool.
`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`. See Instance Pools API.
`policy_id`	`STRING`	A cluster policy ID.
`num_workers OR autoscale`	`INT32` OR InitScriptInfo	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 number of workers. For instance, if a cluster is resized from 5 to 10 workers, this field is updated to reflect the target size of 10 workers, whereas the workers listed in executors gradually increase from 5 to 10 as the new nodes are provisioned. If autoscale, parameters needed to automatically scale clusters up and down based on load. This field is optional.
`apply_policy_default_values`	`BOOLEAN`	Whether to use policy default values for missing cluster attributes.

PipelineSettings

The settings for a pipeline deployment.

Field Name	Type	Description
`id`	`STRING`	The unique identifier for this pipeline. The identifier is created by the Delta Live Tables system, and must not be provided when creating a pipeline.
`name`	`STRING`	A user-friendly name for this pipeline. This field is optional. By default, the pipeline name must be unique. To use a duplicate name, set `allow_duplicate_names` to `true` in the pipeline configuration.
`storage`	`STRING`	A path to a DBFS directory for storing checkpoints and tables created by the pipeline. This field is optional. The system uses a default location if this field is empty.
`configuration`	A map of `STRING:STRING`	A list of key-value pairs to add to the Spark configuration of the cluster that will run the pipeline. This field is optional. Elements must be formatted as key:value pairs.
`clusters`	An array of PipelinesNewCluster	An array of specifications for the clusters to run the pipeline. This field is optional. If this is not specified, the system will select a default cluster configuration for the pipeline.
`libraries`	An array of PipelineLibrary	The notebooks containing the pipeline code and any dependencies required to run the pipeline.
`target`	`STRING`	A database name for persisting pipeline output data. See Publish data from Delta Live Tables pipelines to the Hive metastore for more information.
`continuous`	`BOOLEAN`	Whether this is a continuous pipeline. This field is optional. The default value is `false`.
`development`	`BOOLEAN`	Whether to run the pipeline in development mode. This field is optional. The default value is `false`.
`photon`	`BOOLEAN`	Whether Photon acceleration is enabled for this pipeline. This field is optional. The default value is `false`.
`channel`	`STRING`	The Delta Live Tables release channel specifying the runtime version to use for this pipeline. Supported values are: `preview` to test the pipeline with upcoming changes to the Delta Live Tables runtime. `current` to use the current Delta Live Tables runtime version. This field is optional. The default value is `current`.
`edition`	`STRING`	The Delta Live Tables product edition to run the pipeline: `CORE` supports streaming ingest workloads. `PRO` also supports streaming ingest workloads and adds support for change data capture (CDC) processing. `ADVANCED` supports all the features of the `PRO` edition and adds support for workloads that require Delta Live Tables expectations to enforce data quality constraints. This field is optional. The default value is `advanced`.

PipelineStateInfo

The state of a pipeline, the status of the most recent updates, and information about associated resources.

Field Name	Type	Description
`state`	`STRING`	The state of the pipeline. One of `IDLE` or `RUNNING`.
`pipeline_id`	`STRING`	The unique identifier of the pipeline.
`cluster_id`	`STRING`	The unique identifier of the cluster running the pipeline.
`name`	`STRING`	The user-friendly name of the pipeline.
`latest_updates`	An array of UpdateStateInfo	Status of the most recent updates for the pipeline, ordered with the newest update first.
`creator_user_name`	`STRING`	The username of the pipeline creator.
`run_as_user_name`	`STRING`	The username that the pipeline runs as. This is a read only value derived from the pipeline owner.

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.

UpdateStateInfo

The current state of a pipeline update.

Field Name	Type	Description
`update_id`	`STRING`	The unique identifier for this update.
`state`	`STRING`	The state of the update. One of `QUEUED`, `CREATED`, `WAITING_FOR_RESOURCES`, `INITIALIZING`, `RESETTING`, `SETTING_UP_TABLES`, `RUNNING`, `STOPPING`, `COMPLETED`, `FAILED`, or `CANCELED`.
`creation_time`	`STRING`	Timestamp when this update was created.

WorkspaceStorageInfo

Workspace storage information.

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