databricks.Cluster

AwsAttributes ClusterAwsAttributes

Automatically terminate the cluster after being inactive for this time in minutes. If not set, Databricks won't automatically terminate an inactive cluster. If specified, the threshold must be between 10 and 10000 minutes. You can also set this value to 0 to explicitly disable automatic termination. We highly recommend having this setting present for Interactive/BI clusters.

AzureAttributes ClusterAzureAttributes

ClusterId string

ClusterLogConf ClusterClusterLogConf

ClusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

CustomTags Dictionary<string, object>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

DataSecurityMode string

Select the security features of the cluster. Unity Catalog requires SINGLE_USER or USER_ISOLATION mode. LEGACY_PASSTHROUGH for passthrough cluster and LEGACY_TABLE_ACL for Table ACL cluster. Default to NONE, i.e. no security feature enabled.

DockerImage ClusterDockerImage

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

DriverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

If you don’t want to allocate a fixed number of EBS volumes at cluster creation time, use autoscaling local storage. With autoscaling local storage, Databricks monitors the amount of free disk space available on your cluster’s Spark workers. If a worker begins to run too low on disk, Databricks automatically attaches a new EBS volume to the worker before it runs out of disk space. EBS volumes are attached up to a limit of 5 TB of total disk space per instance (including the instance’s local storage). To scale down EBS usage, make sure you have autotermination_minutes and autoscale attributes set. More documentation available at cluster configuration page.

GcpAttributes ClusterGcpAttributes

Some instance types you use to run clusters may have locally attached disks. Databricks may store shuffle data or temporary data on these locally attached disks. To ensure that all data at rest is encrypted for all storage types, including shuffle data stored temporarily on your cluster’s local disks, you can enable local disk encryption. When local disk encryption is enabled, Databricks generates an encryption key locally unique to each cluster node and encrypting all data stored on local disks. The scope of the key is local to each cluster node and is destroyed along with the cluster node itself. During its lifetime, the key resides in memory for encryption and decryption and is stored encrypted on the disk. Your workloads may run more slowly because of the performance impact of reading and writing encrypted data to and from local volumes. This feature is not available for all Azure Databricks subscriptions. Contact your Microsoft or Databricks account representative to request access.

IdempotencyToken string

An optional token to guarantee the idempotency of cluster creation requests. If an active cluster with the provided token already exists, the request will not create a new cluster, but it will return the existing running cluster's ID instead. If you specify the idempotency token, upon failure, you can retry until the request succeeds. Databricks platform guarantees to launch exactly one cluster with that idempotency token. This token should have at most 64 characters.

InitScripts List<ClusterInitScript>

InstancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

IsPinned bool

boolean value specifying if cluster is pinned (not pinned by default). You must be a Databricks administrator to use this. The pinned clusters' maximum number is limited to 70, so apply may fail if you have more than that.

Libraries List<ClusterLibrary>

NodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

Autoscale ClusterAutoscaleArgs

PolicyId string

Identifier of Cluster Policy to validate cluster and preset certain defaults. The primary use for cluster policies is to allow users to create policy-scoped clusters via UI rather than sharing configuration for API-created clusters. For example, when you specify policy_id of external metastore policy, you still have to fill in relevant keys for spark_conf.

SingleUserName string

The optional user name of the user to assign to an interactive cluster. This field is required when using standard AAD Passthrough for Azure Data Lake Storage (ADLS) with a single-user cluster (i.e., not high-concurrency clusters).

SparkConf Dictionary<string, object>

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

SparkEnvVars Dictionary<string, object>

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

SshPublicKeys List<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. You can specify up to 10 keys.

SparkVersion string

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

AwsAttributes ClusterAwsAttributesArgs

AzureAttributes ClusterAzureAttributesArgs

ClusterId string

ClusterLogConf ClusterClusterLogConfArgs

ClusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

CustomTags map[string]interface{}

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

DataSecurityMode string

DockerImage ClusterDockerImageArgs

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

DriverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

GcpAttributes ClusterGcpAttributesArgs

IdempotencyToken string

InitScripts []ClusterInitScriptArgs

InstancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

IsPinned bool

Libraries []ClusterLibraryArgs

NodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

PolicyId string

SingleUserName string

SparkConf map[string]interface{}

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

SparkEnvVars map[string]interface{}

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

SshPublicKeys []string

sparkVersion String

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

autoterminationMinutes Integer

clusterId String

clusterName String

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags Map<String,Object>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode String

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId String

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk Boolean

initScripts List<ClusterInitScript>

idempotencyToken String

instancePoolId String

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

isPinned Boolean

libraries List<ClusterLibrary>

nodeTypeId String

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

numWorkers Integer

policyId String

singleUserName String

sparkConf Map<String,Object>

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

sparkEnvVars Map<String,Object>

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

sshPublicKeys List<String>

sparkVersion string

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

autoterminationMinutes number

clusterId string

clusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags {[key: string]: any}

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode string

driverInstancePoolId string

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk boolean

enableLocalDiskEncryption boolean

initScripts ClusterInitScript[]

idempotencyToken string

instancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

isPinned boolean

libraries ClusterLibrary[]

nodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

numWorkers number

policyId string

singleUserName string

sparkConf {[key: string]: any}

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

sparkEnvVars {[key: string]: any}

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

sshPublicKeys string[]

spark_version str

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

autoscale ClusterAutoscaleArgs

autotermination_minutes int

aws_attributes ClusterAwsAttributesArgs

azure_attributes ClusterAzureAttributesArgs

cluster_id str

cluster_log_conf ClusterClusterLogConfArgs

cluster_name str

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

custom_tags Mapping[str, Any]

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

data_security_mode str

docker_image ClusterDockerImageArgs

driver_instance_pool_id str

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driver_node_type_id str

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enable_elastic_disk bool

enable_local_disk_encryption bool

gcp_attributes ClusterGcpAttributesArgs

idempotency_token str

init_scripts Sequence[ClusterInitScriptArgs]

instance_pool_id str

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

is_pinned bool

libraries Sequence[ClusterLibraryArgs]

node_type_id str

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

num_workers int

policy_id str

single_user_name str

spark_conf Mapping[str, Any]

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

spark_env_vars Mapping[str, Any]

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

ssh_public_keys Sequence[str]

sparkVersion String

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

autoscale Property Map

autoterminationMinutes Number

awsAttributes Property Map

azureAttributes Property Map

clusterId String

clusterLogConf Property Map

clusterName String

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags Map<Any>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode String

dockerImage Property Map

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId String

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk Boolean

gcpAttributes Property Map

idempotencyToken String

initScripts List<Property Map>

instancePoolId String

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

isPinned Boolean

libraries List<Property Map>

nodeTypeId String

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

numWorkers Number

policyId String

singleUserName String

sparkConf Map<Any>

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

sparkEnvVars Map<Any>

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

sshPublicKeys List<String>

Outputs

All input properties are implicitly available as output properties. Additionally, the Cluster resource produces the following output properties:

DefaultTags Dictionary<string, object>: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
Id string: The provider-assigned unique ID for this managed resource.
State string: (string) State of the cluster.
Url string

DefaultTags map[string]interface{}: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
Id string: The provider-assigned unique ID for this managed resource.
State string: (string) State of the cluster.
Url string

defaultTags Map<String,Object>: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
id String: The provider-assigned unique ID for this managed resource.
state String: (string) State of the cluster.
url String

defaultTags {[key: string]: any}: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
id string: The provider-assigned unique ID for this managed resource.
state string: (string) State of the cluster.
url string

default_tags Mapping[str, Any]: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
id str: The provider-assigned unique ID for this managed resource.
state str: (string) State of the cluster.
url str

defaultTags Map<Any>: (map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:
id String: The provider-assigned unique ID for this managed resource.
state String: (string) State of the cluster.
url String

Look up Existing Cluster Resource

Get an existing Cluster resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: ClusterState, opts?: CustomResourceOptions): Cluster

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        autoscale: Optional[ClusterAutoscaleArgs] = None,
        autotermination_minutes: Optional[int] = None,
        aws_attributes: Optional[ClusterAwsAttributesArgs] = None,
        azure_attributes: Optional[ClusterAzureAttributesArgs] = None,
        cluster_id: Optional[str] = None,
        cluster_log_conf: Optional[ClusterClusterLogConfArgs] = None,
        cluster_name: Optional[str] = None,
        custom_tags: Optional[Mapping[str, Any]] = None,
        data_security_mode: Optional[str] = None,
        default_tags: Optional[Mapping[str, Any]] = None,
        docker_image: Optional[ClusterDockerImageArgs] = None,
        driver_instance_pool_id: Optional[str] = None,
        driver_node_type_id: Optional[str] = None,
        enable_elastic_disk: Optional[bool] = None,
        enable_local_disk_encryption: Optional[bool] = None,
        gcp_attributes: Optional[ClusterGcpAttributesArgs] = None,
        idempotency_token: Optional[str] = None,
        init_scripts: Optional[Sequence[ClusterInitScriptArgs]] = None,
        instance_pool_id: Optional[str] = None,
        is_pinned: Optional[bool] = None,
        libraries: Optional[Sequence[ClusterLibraryArgs]] = None,
        node_type_id: Optional[str] = None,
        num_workers: Optional[int] = None,
        policy_id: Optional[str] = None,
        single_user_name: Optional[str] = None,
        spark_conf: Optional[Mapping[str, Any]] = None,
        spark_env_vars: Optional[Mapping[str, Any]] = None,
        spark_version: Optional[str] = None,
        ssh_public_keys: Optional[Sequence[str]] = None,
        state: Optional[str] = None,
        url: Optional[str] = None) -> Cluster

func GetCluster(ctx *Context, name string, id IDInput, state *ClusterState, opts ...ResourceOption) (*Cluster, error)

public static Cluster Get(string name, Input<string> id, ClusterState? state, CustomResourceOptions? opts = null)

public static Cluster get(String name, Output<String> id, ClusterState state, CustomResourceOptions options)

resources:  _:    type: databricks:Cluster    get:      id: ${id}

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

resource_name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

The following state arguments are supported:

Autoscale ClusterAutoscale

AwsAttributes ClusterAwsAttributes

AzureAttributes ClusterAzureAttributes

ClusterId string

ClusterLogConf ClusterClusterLogConf

ClusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

CustomTags Dictionary<string, object>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

DataSecurityMode string

DefaultTags Dictionary<string, object>

(map) Tags that are added by Databricks by default, regardless of any custom_tags that may have been added. These include: Vendor: Databricks, Creator: <username_of_creator>, ClusterName: <name_of_cluster>, ClusterId: <id_of_cluster>, Name:

DockerImage ClusterDockerImage

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

DriverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

GcpAttributes ClusterGcpAttributes

IdempotencyToken string

InitScripts List<ClusterInitScript>

InstancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

IsPinned bool

Libraries List<ClusterLibrary>

NodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

Autoscale ClusterAutoscaleArgs

PolicyId string

SingleUserName string

SparkConf Dictionary<string, object>

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

SparkEnvVars Dictionary<string, object>

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

SparkVersion string

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

SshPublicKeys List<string>

State string

(string) State of the cluster.

Url string

AwsAttributes ClusterAwsAttributesArgs

AzureAttributes ClusterAzureAttributesArgs

ClusterId string

ClusterLogConf ClusterClusterLogConfArgs

ClusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

CustomTags map[string]interface{}

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

DataSecurityMode string

DefaultTags map[string]interface{}

DockerImage ClusterDockerImageArgs

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

DriverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

GcpAttributes ClusterGcpAttributesArgs

IdempotencyToken string

InitScripts []ClusterInitScriptArgs

InstancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

IsPinned bool

Libraries []ClusterLibraryArgs

NodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

PolicyId string

SingleUserName string

SparkConf map[string]interface{}

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

SparkEnvVars map[string]interface{}

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

SparkVersion string

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

SshPublicKeys []string

State string

(string) State of the cluster.

Url string

autoterminationMinutes Integer

clusterId String

clusterName String

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags Map<String,Object>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode String

defaultTags Map<String,Object>

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId String

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk Boolean

initScripts List<ClusterInitScript>

idempotencyToken String

instancePoolId String

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

isPinned Boolean

libraries List<ClusterLibrary>

nodeTypeId String

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

numWorkers Integer

policyId String

singleUserName String

sparkConf Map<String,Object>

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

sparkEnvVars Map<String,Object>

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

sparkVersion String

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

sshPublicKeys List<String>

state String

(string) State of the cluster.

url String

autoterminationMinutes number

clusterId string

clusterName string

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags {[key: string]: any}

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode string

defaultTags {[key: string]: any}

driverInstancePoolId string

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId string

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk boolean

enableLocalDiskEncryption boolean

initScripts ClusterInitScript[]

idempotencyToken string

instancePoolId string

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

isPinned boolean

libraries ClusterLibrary[]

nodeTypeId string

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

numWorkers number

policyId string

singleUserName string

sparkConf {[key: string]: any}

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

sparkEnvVars {[key: string]: any}

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

sparkVersion string

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

sshPublicKeys string[]

state string

(string) State of the cluster.

url string

autoscale ClusterAutoscaleArgs

autotermination_minutes int

aws_attributes ClusterAwsAttributesArgs

azure_attributes ClusterAzureAttributesArgs

cluster_id str

cluster_log_conf ClusterClusterLogConfArgs

cluster_name str

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

custom_tags Mapping[str, Any]

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

data_security_mode str

default_tags Mapping[str, Any]

docker_image ClusterDockerImageArgs

driver_instance_pool_id str

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driver_node_type_id str

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enable_elastic_disk bool

enable_local_disk_encryption bool

gcp_attributes ClusterGcpAttributesArgs

idempotency_token str

init_scripts Sequence[ClusterInitScriptArgs]

instance_pool_id str

To reduce cluster start time, you can attach a cluster to a predefined pool of idle instances. When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to TERMINATED, the instances it used are returned to the pool and reused by a different cluster.

is_pinned bool

libraries Sequence[ClusterLibraryArgs]

node_type_id str

Any supported databricks.getNodeType id. If instance_pool_id is specified, this field is not needed.

num_workers int

policy_id str

single_user_name str

spark_conf Mapping[str, Any]

Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration.

spark_env_vars Mapping[str, Any]

Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers.

spark_version str

Runtime version of the cluster. Any supported databricks.getSparkVersion id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control.

ssh_public_keys Sequence[str]

state str

(string) State of the cluster.

url str

autoscale Property Map

autoterminationMinutes Number

awsAttributes Property Map

azureAttributes Property Map

clusterId String

clusterLogConf Property Map

clusterName String

Cluster name, which doesn’t have to be unique. If not specified at creation, the cluster name will be an empty string.

customTags Map<Any>

Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., AWS EC2 instances and EBS volumes) with these tags in addition to default_tags.

dataSecurityMode String

defaultTags Map<Any>

dockerImage Property Map

similar to instance_pool_id, but for driver node. If omitted, and instance_pool_id is specified, then driver will be allocated from that pool.

driverNodeTypeId String

The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node_type_id defined above.

enableElasticDisk Boolean