Google Cloud Native v0.30.0, Apr 14 23

google-native.dataproc/v1.Batch

Explore with Pulumi AI

Creates a batch workload that executes asynchronously. Auto-naming is currently not supported for this resource.

Create Batch Resource

new Batch(name: string, args?: BatchArgs, opts?: CustomResourceOptions);

@overload
def Batch(resource_name: str,
          opts: Optional[ResourceOptions] = None,
          batch_id: Optional[str] = None,
          environment_config: Optional[EnvironmentConfigArgs] = None,
          labels: Optional[Mapping[str, str]] = None,
          location: Optional[str] = None,
          project: Optional[str] = None,
          pyspark_batch: Optional[PySparkBatchArgs] = None,
          request_id: Optional[str] = None,
          runtime_config: Optional[RuntimeConfigArgs] = None,
          spark_batch: Optional[SparkBatchArgs] = None,
          spark_r_batch: Optional[SparkRBatchArgs] = None,
          spark_sql_batch: Optional[SparkSqlBatchArgs] = None)
@overload
def Batch(resource_name: str,
          args: Optional[BatchArgs] = None,
          opts: Optional[ResourceOptions] = None)

func NewBatch(ctx *Context, name string, args *BatchArgs, opts ...ResourceOption) (*Batch, error)

public Batch(string name, BatchArgs? args = null, CustomResourceOptions? opts = null)

public Batch(String name, BatchArgs args)
public Batch(String name, BatchArgs args, CustomResourceOptions options)

type: google-native:dataproc/v1:Batch
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

name string: The unique name of the resource.
args BatchArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args BatchArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args BatchArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args BatchArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args BatchArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Batch Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

The Batch resource accepts the following input properties:

BatchId string: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
EnvironmentConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.EnvironmentConfigArgs: Optional. Environment configuration for the batch execution.
Labels Dictionary<string, string>: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
Location string
Project string
PysparkBatch Pulumi.GoogleNative.Dataproc.V1.Inputs.PySparkBatchArgs: Optional. PySpark batch config.
RequestId string: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
RuntimeConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.RuntimeConfigArgs: Optional. Runtime configuration for the batch execution.
SparkBatch Pulumi.GoogleNative.Dataproc.V1.Inputs.SparkBatchArgs: Optional. Spark batch config.
SparkRBatch Pulumi.GoogleNative.Dataproc.V1.Inputs.SparkRBatchArgs: Optional. SparkR batch config.
SparkSqlBatch Pulumi.GoogleNative.Dataproc.V1.Inputs.SparkSqlBatchArgs: Optional. SparkSql batch config.

BatchId string: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
EnvironmentConfig EnvironmentConfigArgs: Optional. Environment configuration for the batch execution.
Labels map[string]string: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
Location string
Project string
PysparkBatch PySparkBatchArgs: Optional. PySpark batch config.
RequestId string: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
RuntimeConfig RuntimeConfigArgs: Optional. Runtime configuration for the batch execution.
SparkBatch SparkBatchArgs: Optional. Spark batch config.
SparkRBatch SparkRBatchArgs: Optional. SparkR batch config.
SparkSqlBatch SparkSqlBatchArgs: Optional. SparkSql batch config.

batchId String: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
environmentConfig EnvironmentConfigArgs: Optional. Environment configuration for the batch execution.
labels Map<String,String>: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
location String
project String
pysparkBatch PySparkBatchArgs: Optional. PySpark batch config.
requestId String: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
runtimeConfig RuntimeConfigArgs: Optional. Runtime configuration for the batch execution.
sparkBatch SparkBatchArgs: Optional. Spark batch config.
sparkRBatch SparkRBatchArgs: Optional. SparkR batch config.
sparkSqlBatch SparkSqlBatchArgs: Optional. SparkSql batch config.

batchId string: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
environmentConfig EnvironmentConfigArgs: Optional. Environment configuration for the batch execution.
labels {[key: string]: string}: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
location string
project string
pysparkBatch PySparkBatchArgs: Optional. PySpark batch config.
requestId string: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
runtimeConfig RuntimeConfigArgs: Optional. Runtime configuration for the batch execution.
sparkBatch SparkBatchArgs: Optional. Spark batch config.
sparkRBatch SparkRBatchArgs: Optional. SparkR batch config.
sparkSqlBatch SparkSqlBatchArgs: Optional. SparkSql batch config.

batch_id str: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
environment_config EnvironmentConfigArgs: Optional. Environment configuration for the batch execution.
labels Mapping[str, str]: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
location str
project str
pyspark_batch PySparkBatchArgs: Optional. PySpark batch config.
request_id str: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
runtime_config RuntimeConfigArgs: Optional. Runtime configuration for the batch execution.
spark_batch SparkBatchArgs: Optional. Spark batch config.
spark_r_batch SparkRBatchArgs: Optional. SparkR batch config.
spark_sql_batch SparkSqlBatchArgs: Optional. SparkSql batch config.

batchId String: Optional. The ID to use for the batch, which will become the final component of the batch's resource name.This value must be 4-63 characters. Valid characters are /[a-z][0-9]-/.
environmentConfig Property Map: Optional. Environment configuration for the batch execution.
labels Map<String>: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
location String
project String
pysparkBatch Property Map: Optional. PySpark batch config.
requestId String: Optional. A unique ID used to identify the request. If the service receives two CreateBatchRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateBatchRequest)s with the same request_id, the second request is ignored and the Operation that corresponds to the first Batch created and stored in the backend is returned.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
runtimeConfig Property Map: Optional. Runtime configuration for the batch execution.
sparkBatch Property Map: Optional. Spark batch config.
sparkRBatch Property Map: Optional. SparkR batch config.
sparkSqlBatch Property Map: Optional. SparkSql batch config.

Outputs

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

CreateTime string: The time when the batch was created.
Creator string: The email address of the user who created the batch.
Id string: The provider-assigned unique ID for this managed resource.
Name string: The resource name of the batch.
Operation string: The resource name of the operation associated with this batch.
RuntimeInfo Pulumi.GoogleNative.Dataproc.V1.Outputs.RuntimeInfoResponse: Runtime information about batch execution.
State string: The state of the batch.
StateHistory List<Pulumi.GoogleNative.Dataproc.V1.Outputs.StateHistoryResponse>: Historical state information for the batch.
StateMessage string: Batch state details, such as a failure description if the state is FAILED.
StateTime string: The time when the batch entered a current state.
Uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

CreateTime string: The time when the batch was created.
Creator string: The email address of the user who created the batch.
Id string: The provider-assigned unique ID for this managed resource.
Name string: The resource name of the batch.
Operation string: The resource name of the operation associated with this batch.
RuntimeInfo RuntimeInfoResponse: Runtime information about batch execution.
State string: The state of the batch.
StateHistory []StateHistoryResponse: Historical state information for the batch.
StateMessage string: Batch state details, such as a failure description if the state is FAILED.
StateTime string: The time when the batch entered a current state.
Uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime String: The time when the batch was created.
creator String: The email address of the user who created the batch.
id String: The provider-assigned unique ID for this managed resource.
name String: The resource name of the batch.
operation String: The resource name of the operation associated with this batch.
runtimeInfo RuntimeInfoResponse: Runtime information about batch execution.
state String: The state of the batch.
stateHistory List<StateHistoryResponse>: Historical state information for the batch.
stateMessage String: Batch state details, such as a failure description if the state is FAILED.
stateTime String: The time when the batch entered a current state.
uuid String: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime string: The time when the batch was created.
creator string: The email address of the user who created the batch.
id string: The provider-assigned unique ID for this managed resource.
name string: The resource name of the batch.
operation string: The resource name of the operation associated with this batch.
runtimeInfo RuntimeInfoResponse: Runtime information about batch execution.
state string: The state of the batch.
stateHistory StateHistoryResponse[]: Historical state information for the batch.
stateMessage string: Batch state details, such as a failure description if the state is FAILED.
stateTime string: The time when the batch entered a current state.
uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

create_time str: The time when the batch was created.
creator str: The email address of the user who created the batch.
id str: The provider-assigned unique ID for this managed resource.
name str: The resource name of the batch.
operation str: The resource name of the operation associated with this batch.
runtime_info RuntimeInfoResponse: Runtime information about batch execution.
state str: The state of the batch.
state_history Sequence[StateHistoryResponse]: Historical state information for the batch.
state_message str: Batch state details, such as a failure description if the state is FAILED.
state_time str: The time when the batch entered a current state.
uuid str: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime String: The time when the batch was created.
creator String: The email address of the user who created the batch.
id String: The provider-assigned unique ID for this managed resource.
name String: The resource name of the batch.
operation String: The resource name of the operation associated with this batch.
runtimeInfo Property Map: Runtime information about batch execution.
state String: The state of the batch.
stateHistory List<Property Map>: Historical state information for the batch.
stateMessage String: Batch state details, such as a failure description if the state is FAILED.
stateTime String: The time when the batch entered a current state.
uuid String: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

Supporting Types

EnvironmentConfig

ExecutionConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.ExecutionConfig: Optional. Execution configuration for a workload.
PeripheralsConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.PeripheralsConfig: Optional. Peripherals configuration that workload has access to.

ExecutionConfig ExecutionConfig: Optional. Execution configuration for a workload.
PeripheralsConfig PeripheralsConfig: Optional. Peripherals configuration that workload has access to.

executionConfig ExecutionConfig: Optional. Execution configuration for a workload.
peripheralsConfig PeripheralsConfig: Optional. Peripherals configuration that workload has access to.

executionConfig ExecutionConfig: Optional. Execution configuration for a workload.
peripheralsConfig PeripheralsConfig: Optional. Peripherals configuration that workload has access to.

execution_config ExecutionConfig: Optional. Execution configuration for a workload.
peripherals_config PeripheralsConfig: Optional. Peripherals configuration that workload has access to.

executionConfig Property Map: Optional. Execution configuration for a workload.
peripheralsConfig Property Map: Optional. Peripherals configuration that workload has access to.

EnvironmentConfigResponse

ExecutionConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.ExecutionConfigResponse: Optional. Execution configuration for a workload.
PeripheralsConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.PeripheralsConfigResponse: Optional. Peripherals configuration that workload has access to.

ExecutionConfig ExecutionConfigResponse: Optional. Execution configuration for a workload.
PeripheralsConfig PeripheralsConfigResponse: Optional. Peripherals configuration that workload has access to.

executionConfig ExecutionConfigResponse: Optional. Execution configuration for a workload.
peripheralsConfig PeripheralsConfigResponse: Optional. Peripherals configuration that workload has access to.

executionConfig ExecutionConfigResponse: Optional. Execution configuration for a workload.
peripheralsConfig PeripheralsConfigResponse: Optional. Peripherals configuration that workload has access to.

execution_config ExecutionConfigResponse: Optional. Execution configuration for a workload.
peripherals_config PeripheralsConfigResponse: Optional. Peripherals configuration that workload has access to.

executionConfig Property Map: Optional. Execution configuration for a workload.
peripheralsConfig Property Map: Optional. Peripherals configuration that workload has access to.

ExecutionConfig

IdleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
KmsKey string: Optional. The Cloud KMS key to use for encryption.
NetworkTags List<string>: Optional. Tags used for network traffic control.
NetworkUri string: Optional. Network URI to connect workload to.
ServiceAccount string: Optional. Service account that used to execute workload.
StagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Optional. Subnetwork URI to connect workload to.
Ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

IdleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
KmsKey string: Optional. The Cloud KMS key to use for encryption.
NetworkTags []string: Optional. Tags used for network traffic control.
NetworkUri string: Optional. Network URI to connect workload to.
ServiceAccount string: Optional. Service account that used to execute workload.
StagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Optional. Subnetwork URI to connect workload to.
Ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl String: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey String: Optional. The Cloud KMS key to use for encryption.
networkTags List<String>: Optional. Tags used for network traffic control.
networkUri String: Optional. Network URI to connect workload to.
serviceAccount String: Optional. Service account that used to execute workload.
stagingBucket String: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Optional. Subnetwork URI to connect workload to.
ttl String: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey string: Optional. The Cloud KMS key to use for encryption.
networkTags string[]: Optional. Tags used for network traffic control.
networkUri string: Optional. Network URI to connect workload to.
serviceAccount string: Optional. Service account that used to execute workload.
stagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri string: Optional. Subnetwork URI to connect workload to.
ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idle_ttl str: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kms_key str: Optional. The Cloud KMS key to use for encryption.
network_tags Sequence[str]: Optional. Tags used for network traffic control.
network_uri str: Optional. Network URI to connect workload to.
service_account str: Optional. Service account that used to execute workload.
staging_bucket str: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetwork_uri str: Optional. Subnetwork URI to connect workload to.
ttl str: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl String: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey String: Optional. The Cloud KMS key to use for encryption.
networkTags List<String>: Optional. Tags used for network traffic control.
networkUri String: Optional. Network URI to connect workload to.
serviceAccount String: Optional. Service account that used to execute workload.
stagingBucket String: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Optional. Subnetwork URI to connect workload to.
ttl String: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

ExecutionConfigResponse

IdleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
KmsKey string: Optional. The Cloud KMS key to use for encryption.
NetworkTags List<string>: Optional. Tags used for network traffic control.
NetworkUri string: Optional. Network URI to connect workload to.
ServiceAccount string: Optional. Service account that used to execute workload.
StagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Optional. Subnetwork URI to connect workload to.
Ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

IdleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
KmsKey string: Optional. The Cloud KMS key to use for encryption.
NetworkTags []string: Optional. Tags used for network traffic control.
NetworkUri string: Optional. Network URI to connect workload to.
ServiceAccount string: Optional. Service account that used to execute workload.
StagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Optional. Subnetwork URI to connect workload to.
Ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl String: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey String: Optional. The Cloud KMS key to use for encryption.
networkTags List<String>: Optional. Tags used for network traffic control.
networkUri String: Optional. Network URI to connect workload to.
serviceAccount String: Optional. Service account that used to execute workload.
stagingBucket String: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Optional. Subnetwork URI to connect workload to.
ttl String: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl string: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey string: Optional. The Cloud KMS key to use for encryption.
networkTags string[]: Optional. Tags used for network traffic control.
networkUri string: Optional. Network URI to connect workload to.
serviceAccount string: Optional. Service account that used to execute workload.
stagingBucket string: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri string: Optional. Subnetwork URI to connect workload to.
ttl string: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idle_ttl str: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kms_key str: Optional. The Cloud KMS key to use for encryption.
network_tags Sequence[str]: Optional. Tags used for network traffic control.
network_uri str: Optional. Network URI to connect workload to.
service_account str: Optional. Service account that used to execute workload.
staging_bucket str: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetwork_uri str: Optional. Subnetwork URI to connect workload to.
ttl str: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

idleTtl String: Optional. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 4 hours if not set. If both ttl and idle_ttl are specified, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceed, whichever occurs first.
kmsKey String: Optional. The Cloud KMS key to use for encryption.
networkTags List<String>: Optional. Tags used for network traffic control.
networkUri String: Optional. Network URI to connect workload to.
serviceAccount String: Optional. Service account that used to execute workload.
stagingBucket String: Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Optional. Subnetwork URI to connect workload to.
ttl String: Optional. The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or runs forever without exiting). If ttl is not specified for an interactive session, it defaults to 24h. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.

PeripheralsConfig

MetastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
SparkHistoryServerConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.SparkHistoryServerConfig: Optional. The Spark History Server configuration for the workload.

MetastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
SparkHistoryServerConfig SparkHistoryServerConfig: Optional. The Spark History Server configuration for the workload.

metastoreService String: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig SparkHistoryServerConfig: Optional. The Spark History Server configuration for the workload.

metastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig SparkHistoryServerConfig: Optional. The Spark History Server configuration for the workload.

metastore_service str: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
spark_history_server_config SparkHistoryServerConfig: Optional. The Spark History Server configuration for the workload.

metastoreService String: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig Property Map: Optional. The Spark History Server configuration for the workload.

PeripheralsConfigResponse

MetastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
SparkHistoryServerConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.SparkHistoryServerConfigResponse: Optional. The Spark History Server configuration for the workload.

MetastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
SparkHistoryServerConfig SparkHistoryServerConfigResponse: Optional. The Spark History Server configuration for the workload.

metastoreService String: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig SparkHistoryServerConfigResponse: Optional. The Spark History Server configuration for the workload.

metastoreService string: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig SparkHistoryServerConfigResponse: Optional. The Spark History Server configuration for the workload.

metastore_service str: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
spark_history_server_config SparkHistoryServerConfigResponse: Optional. The Spark History Server configuration for the workload.

metastoreService String: Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
sparkHistoryServerConfig Property Map: Optional. The Spark History Server configuration for the workload.

PySparkBatch

MainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris List<string>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
PythonFileUris List<string>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

MainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris []string: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
PythonFileUris []string: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

mainPythonFileUri String: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
pythonFileUris List<String>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

mainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris string[]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
pythonFileUris string[]: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

main_python_file_uri str: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
python_file_uris Sequence[str]: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

mainPythonFileUri String: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
pythonFileUris List<String>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

PySparkBatchResponse

ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris List<string>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
PythonFileUris List<string>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris []string: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
PythonFileUris []string: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainPythonFileUri String: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
pythonFileUris List<String>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris string[]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainPythonFileUri string: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
pythonFileUris string[]: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
main_python_file_uri str: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
python_file_uris Sequence[str]: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainPythonFileUri String: The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
pythonFileUris List<String>: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

RuntimeConfig

ContainerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
Properties Dictionary<string, string>: Optional. A mapping of property names to values, which are used to configure workload execution.
Version string: Optional. Version of the batch runtime.

ContainerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
Properties map[string]string: Optional. A mapping of property names to values, which are used to configure workload execution.
Version string: Optional. Version of the batch runtime.

containerImage String: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Map<String,String>: Optional. A mapping of property names to values, which are used to configure workload execution.
version String: Optional. Version of the batch runtime.

containerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties {[key: string]: string}: Optional. A mapping of property names to values, which are used to configure workload execution.
version string: Optional. Version of the batch runtime.

container_image str: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Mapping[str, str]: Optional. A mapping of property names to values, which are used to configure workload execution.
version str: Optional. Version of the batch runtime.

containerImage String: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Map<String>: Optional. A mapping of property names to values, which are used to configure workload execution.
version String: Optional. Version of the batch runtime.

RuntimeConfigResponse

ContainerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
Properties Dictionary<string, string>: Optional. A mapping of property names to values, which are used to configure workload execution.
Version string: Optional. Version of the batch runtime.

ContainerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
Properties map[string]string: Optional. A mapping of property names to values, which are used to configure workload execution.
Version string: Optional. Version of the batch runtime.

containerImage String: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Map<String,String>: Optional. A mapping of property names to values, which are used to configure workload execution.
version String: Optional. Version of the batch runtime.

containerImage string: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties {[key: string]: string}: Optional. A mapping of property names to values, which are used to configure workload execution.
version string: Optional. Version of the batch runtime.

container_image str: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Mapping[str, str]: Optional. A mapping of property names to values, which are used to configure workload execution.
version str: Optional. Version of the batch runtime.

containerImage String: Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
properties Map<String>: Optional. A mapping of property names to values, which are used to configure workload execution.
version String: Optional. Version of the batch runtime.

RuntimeInfoResponse

ApproximateUsage Pulumi.GoogleNative.Dataproc.V1.Inputs.UsageMetricsResponse: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
CurrentUsage Pulumi.GoogleNative.Dataproc.V1.Inputs.UsageSnapshotResponse: Snapshot of current workload resource usage.
DiagnosticOutputUri string: A URI pointing to the location of the diagnostics tarball.
Endpoints Dictionary<string, string>: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
OutputUri string: A URI pointing to the location of the stdout and stderr of the workload.

ApproximateUsage UsageMetricsResponse: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
CurrentUsage UsageSnapshotResponse: Snapshot of current workload resource usage.
DiagnosticOutputUri string: A URI pointing to the location of the diagnostics tarball.
Endpoints map[string]string: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
OutputUri string: A URI pointing to the location of the stdout and stderr of the workload.

approximateUsage UsageMetricsResponse: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
currentUsage UsageSnapshotResponse: Snapshot of current workload resource usage.
diagnosticOutputUri String: A URI pointing to the location of the diagnostics tarball.
endpoints Map<String,String>: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
outputUri String: A URI pointing to the location of the stdout and stderr of the workload.

approximateUsage UsageMetricsResponse: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
currentUsage UsageSnapshotResponse: Snapshot of current workload resource usage.
diagnosticOutputUri string: A URI pointing to the location of the diagnostics tarball.
endpoints {[key: string]: string}: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
outputUri string: A URI pointing to the location of the stdout and stderr of the workload.

approximate_usage UsageMetricsResponse: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
current_usage UsageSnapshotResponse: Snapshot of current workload resource usage.
diagnostic_output_uri str: A URI pointing to the location of the diagnostics tarball.
endpoints Mapping[str, str]: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
output_uri str: A URI pointing to the location of the stdout and stderr of the workload.

approximateUsage Property Map: Approximate workload resource usage calculated after workload finishes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
currentUsage Property Map: Snapshot of current workload resource usage.
diagnosticOutputUri String: A URI pointing to the location of the diagnostics tarball.
endpoints Map<String>: Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
outputUri String: A URI pointing to the location of the stdout and stderr of the workload.

SparkBatch

ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris List<string>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
MainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris []string: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
MainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri String: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris string[]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
main_class str: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
main_jar_file_uri str: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri String: Optional. The HCFS URI of the jar file that contains the main class.

SparkBatchResponse

ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris List<string>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
MainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris []string: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
MainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri String: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris string[]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass string: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri string: Optional. The HCFS URI of the jar file that contains the main class.

archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
main_class str: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
main_jar_file_uri str: Optional. The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: Optional. The name of the driver main class. The jar file that contains the class must be in the classpath or specified in jar_file_uris.
mainJarFileUri String: Optional. The HCFS URI of the jar file that contains the main class.

SparkHistoryServerConfig

DataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

DataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster String: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataproc_cluster str: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster String: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

SparkHistoryServerConfigResponse

DataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

DataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster String: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster string: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataproc_cluster str: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

dataprocCluster String: Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]

SparkRBatch

MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.

MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.

mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.

mainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.

main_r_file_uri str: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.

mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.

SparkRBatchResponse

ArchiveUris List<string>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args List<string>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris List<string>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

ArchiveUris []string: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
Args []string: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
FileUris []string: Optional. HCFS URIs of files to be placed in the working directory of each executor.
MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

archiveUris string[]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args string[]: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris string[]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
mainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

archive_uris Sequence[str]: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args Sequence[str]: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
file_uris Sequence[str]: Optional. HCFS URIs of files to be placed in the working directory of each executor.
main_r_file_uri str: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

archiveUris List<String>: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
args List<String>: Optional. The arguments to pass to the Spark driver. Do not include arguments that can be set as batch properties, such as --conf, since a collision can occur that causes an incorrect batch submission.
fileUris List<String>: Optional. HCFS URIs of files to be placed in the working directory of each executor.
mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.

SparkSqlBatch

QueryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
JarFileUris List<string>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryVariables Dictionary<string, string>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

QueryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
JarFileUris []string: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryVariables map[string]string: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

queryFileUri String: The HCFS URI of the script that contains Spark SQL queries to execute.
jarFileUris List<String>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryVariables Map<String,String>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

queryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
jarFileUris string[]: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryVariables {[key: string]: string}: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

query_file_uri str: The HCFS URI of the script that contains Spark SQL queries to execute.
jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
query_variables Mapping[str, str]: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

queryFileUri String: The HCFS URI of the script that contains Spark SQL queries to execute.
jarFileUris List<String>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryVariables Map<String>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

SparkSqlBatchResponse

JarFileUris List<string>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
QueryVariables Dictionary<string, string>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

JarFileUris []string: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
QueryVariables map[string]string: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris List<String>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri String: The HCFS URI of the script that contains Spark SQL queries to execute.
queryVariables Map<String,String>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris string[]: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri string: The HCFS URI of the script that contains Spark SQL queries to execute.
queryVariables {[key: string]: string}: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jar_file_uris Sequence[str]: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
query_file_uri str: The HCFS URI of the script that contains Spark SQL queries to execute.
query_variables Mapping[str, str]: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris List<String>: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri String: The HCFS URI of the script that contains Spark SQL queries to execute.
queryVariables Map<String>: Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

StateHistoryResponse

State string: The state of the batch at this point in history.
StateMessage string: Details about the state at this point in history.
StateStartTime string: The time when the batch entered the historical state.

State string: The state of the batch at this point in history.
StateMessage string: Details about the state at this point in history.
StateStartTime string: The time when the batch entered the historical state.

state String: The state of the batch at this point in history.
stateMessage String: Details about the state at this point in history.
stateStartTime String: The time when the batch entered the historical state.

state string: The state of the batch at this point in history.
stateMessage string: Details about the state at this point in history.
stateStartTime string: The time when the batch entered the historical state.

state str: The state of the batch at this point in history.
state_message str: Details about the state at this point in history.
state_start_time str: The time when the batch entered the historical state.

state String: The state of the batch at this point in history.
stateMessage String: Details about the state at this point in history.
stateStartTime String: The time when the batch entered the historical state.

UsageMetricsResponse

MilliDcuSeconds string: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
ShuffleStorageGbSeconds string: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

MilliDcuSeconds string: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
ShuffleStorageGbSeconds string: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

milliDcuSeconds String: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGbSeconds String: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

milliDcuSeconds string: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGbSeconds string: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

milli_dcu_seconds str: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffle_storage_gb_seconds str: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

milliDcuSeconds String: Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGbSeconds String: Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).

UsageSnapshotResponse

MilliDcu string: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
ShuffleStorageGb string: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
SnapshotTime string: Optional. The timestamp of the usage snapshot.

MilliDcu string: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
ShuffleStorageGb string: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
SnapshotTime string: Optional. The timestamp of the usage snapshot.

milliDcu String: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGb String: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
snapshotTime String: Optional. The timestamp of the usage snapshot.

milliDcu string: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGb string: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
snapshotTime string: Optional. The timestamp of the usage snapshot.

milli_dcu str: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffle_storage_gb str: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
snapshot_time str: Optional. The timestamp of the usage snapshot.

milliDcu String: Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
shuffleStorageGb String: Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
snapshotTime String: Optional. The timestamp of the usage snapshot.

Package Details

Repository: Google Cloud Native pulumi/pulumi-google-native
License: Apache-2.0