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google-native.dataproc/v1.Batch
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Google Cloud Native is in preview. Google Cloud Classic is fully supported.
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)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:
- Batch
Id 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]-/.
- Environment
Config Pulumi.Google Native. Dataproc. V1. Inputs. Environment Config 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
- Pyspark
Batch Pulumi.Google Native. Dataproc. V1. Inputs. Py Spark Batch Optional. PySpark batch config.
- Request
Id 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.
- Runtime
Config Pulumi.Google Native. Dataproc. V1. Inputs. Runtime Config Optional. Runtime configuration for the batch execution.
- Spark
Batch Pulumi.Google Native. Dataproc. V1. Inputs. Spark Batch Optional. Spark batch config.
- Spark
RBatch Pulumi.Google Native. Dataproc. V1. Inputs. Spark RBatch Optional. SparkR batch config.
- Spark
Sql Pulumi.Batch Google Native. Dataproc. V1. Inputs. Spark Sql Batch Optional. SparkSql batch config.
- Batch
Id 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]-/.
- Environment
Config EnvironmentConfig Args 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
- Pyspark
Batch PySpark Batch Args Optional. PySpark batch config.
- Request
Id 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.
- Runtime
Config RuntimeConfig Args Optional. Runtime configuration for the batch execution.
- Spark
Batch SparkBatch Args Optional. Spark batch config.
- Spark
RBatch SparkRBatch Args Optional. SparkR batch config.
- Spark
Sql SparkBatch Sql Batch Args Optional. SparkSql batch config.
- batch
Id 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]-/.
- environment
Config EnvironmentConfig 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
- pyspark
Batch PySpark Batch Optional. PySpark batch config.
- request
Id 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.
- runtime
Config RuntimeConfig Optional. Runtime configuration for the batch execution.
- spark
Batch SparkBatch Optional. Spark batch config.
- spark
RBatch SparkRBatch Optional. SparkR batch config.
- spark
Sql SparkBatch Sql Batch Optional. SparkSql batch config.
- batch
Id 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]-/.
- environment
Config EnvironmentConfig 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
- pyspark
Batch PySpark Batch Optional. PySpark batch config.
- request
Id 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.
- runtime
Config RuntimeConfig Optional. Runtime configuration for the batch execution.
- spark
Batch SparkBatch Optional. Spark batch config.
- spark
RBatch SparkRBatch Optional. SparkR batch config.
- spark
Sql SparkBatch Sql Batch 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 EnvironmentConfig Args 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 PySpark Batch Args 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 RuntimeConfig Args Optional. Runtime configuration for the batch execution.
- spark_
batch SparkBatch Args Optional. Spark batch config.
- spark_
r_ Sparkbatch RBatch Args Optional. SparkR batch config.
- spark_
sql_ Sparkbatch Sql Batch Args Optional. SparkSql batch config.
- batch
Id 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]-/.
- environment
Config 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
- pyspark
Batch Property Map Optional. PySpark batch config.
- request
Id 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.
- runtime
Config Property Map Optional. Runtime configuration for the batch execution.
- spark
Batch Property Map Optional. Spark batch config.
- spark
RBatch Property Map Optional. SparkR batch config.
- spark
Sql Property MapBatch Optional. SparkSql batch config.
Outputs
All input properties are implicitly available as output properties. Additionally, the Batch resource produces the following output properties:
- Create
Time 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.
- Runtime
Info Pulumi.Google Native. Dataproc. V1. Outputs. Runtime Info Response Runtime information about batch execution.
- State string
The state of the batch.
- State
History List<Pulumi.Google Native. Dataproc. V1. Outputs. State History Response> Historical state information for the batch.
- State
Message string Batch state details, such as a failure description if the state is FAILED.
- State
Time 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 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.
- Runtime
Info RuntimeInfo Response Runtime information about batch execution.
- State string
The state of the batch.
- State
History []StateHistory Response Historical state information for the batch.
- State
Message string Batch state details, such as a failure description if the state is FAILED.
- State
Time 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 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.
- runtime
Info RuntimeInfo Response Runtime information about batch execution.
- state String
The state of the batch.
- state
History List<StateHistory Response> Historical state information for the batch.
- state
Message String Batch state details, such as a failure description if the state is FAILED.
- state
Time 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 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.
- runtime
Info RuntimeInfo Response Runtime information about batch execution.
- state string
The state of the batch.
- state
History StateHistory Response[] Historical state information for the batch.
- state
Message string Batch state details, such as a failure description if the state is FAILED.
- state
Time 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 RuntimeInfo Response Runtime information about batch execution.
- state str
The state of the batch.
- state_
history Sequence[StateHistory Response] 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.
- create
Time 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.
- runtime
Info Property Map Runtime information about batch execution.
- state String
The state of the batch.
- state
History List<Property Map> Historical state information for the batch.
- state
Message String Batch state details, such as a failure description if the state is FAILED.
- state
Time 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, EnvironmentConfigArgs
- Execution
Config Pulumi.Google Native. Dataproc. V1. Inputs. Execution Config Optional. Execution configuration for a workload.
- Peripherals
Config Pulumi.Google Native. Dataproc. V1. Inputs. Peripherals Config 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.
- execution
Config ExecutionConfig Optional. Execution configuration for a workload.
- peripherals
Config 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.
- execution_
config ExecutionConfig Optional. Execution configuration for a workload.
- peripherals_
config PeripheralsConfig Optional. Peripherals configuration that workload has access to.
- execution
Config Property Map Optional. Execution configuration for a workload.
- peripherals
Config Property Map Optional. Peripherals configuration that workload has access to.
EnvironmentConfigResponse, EnvironmentConfigResponseArgs
- Execution
Config Pulumi.Google Native. Dataproc. V1. Inputs. Execution Config Response Optional. Execution configuration for a workload.
- Peripherals
Config Pulumi.Google Native. Dataproc. V1. Inputs. Peripherals Config Response Optional. Peripherals configuration that workload has access to.
- Execution
Config ExecutionConfig Response Optional. Execution configuration for a workload.
- Peripherals
Config PeripheralsConfig Response Optional. Peripherals configuration that workload has access to.
- execution
Config ExecutionConfig Response Optional. Execution configuration for a workload.
- peripherals
Config PeripheralsConfig Response Optional. Peripherals configuration that workload has access to.
- execution
Config ExecutionConfig Response Optional. Execution configuration for a workload.
- peripherals
Config PeripheralsConfig Response Optional. Peripherals configuration that workload has access to.
- execution_
config ExecutionConfig Response Optional. Execution configuration for a workload.
- peripherals_
config PeripheralsConfig Response Optional. Peripherals configuration that workload has access to.
- execution
Config Property Map Optional. Execution configuration for a workload.
- peripherals
Config Property Map Optional. Peripherals configuration that workload has access to.
ExecutionConfig, ExecutionConfigArgs
- Idle
Ttl string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- Kms
Key string Optional. The Cloud KMS key to use for encryption.
- List<string>
Optional. Tags used for network traffic control.
- Network
Uri string Optional. Network URI to connect workload to.
- Service
Account string Optional. Service account that used to execute workload.
- Staging
Bucket 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.
- Subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- Ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- Kms
Key string Optional. The Cloud KMS key to use for encryption.
- []string
Optional. Tags used for network traffic control.
- Network
Uri string Optional. Network URI to connect workload to.
- Service
Account string Optional. Service account that used to execute workload.
- Staging
Bucket 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.
- Subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- Ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 String Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key String Optional. The Cloud KMS key to use for encryption.
- List<String>
Optional. Tags used for network traffic control.
- network
Uri String Optional. Network URI to connect workload to.
- service
Account String Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri String Optional. Subnetwork URI to connect workload to.
- ttl String
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key string Optional. The Cloud KMS key to use for encryption.
- string[]
Optional. Tags used for network traffic control.
- network
Uri string Optional. Network URI to connect workload to.
- service
Account string Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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. Applies to sessions only. 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 1 hour if not set. 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.
- kms_
key str Optional. The Cloud KMS key to use for encryption.
- 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, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 String Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key String Optional. The Cloud KMS key to use for encryption.
- List<String>
Optional. Tags used for network traffic control.
- network
Uri String Optional. Network URI to connect workload to.
- service
Account String Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri String Optional. Subnetwork URI to connect workload to.
- ttl String
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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, ExecutionConfigResponseArgs
- Idle
Ttl string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- Kms
Key string Optional. The Cloud KMS key to use for encryption.
- List<string>
Optional. Tags used for network traffic control.
- Network
Uri string Optional. Network URI to connect workload to.
- Service
Account string Optional. Service account that used to execute workload.
- Staging
Bucket 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.
- Subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- Ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- Kms
Key string Optional. The Cloud KMS key to use for encryption.
- []string
Optional. Tags used for network traffic control.
- Network
Uri string Optional. Network URI to connect workload to.
- Service
Account string Optional. Service account that used to execute workload.
- Staging
Bucket 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.
- Subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- Ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 String Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key String Optional. The Cloud KMS key to use for encryption.
- List<String>
Optional. Tags used for network traffic control.
- network
Uri String Optional. Network URI to connect workload to.
- service
Account String Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri String Optional. Subnetwork URI to connect workload to.
- ttl String
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 string Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key string Optional. The Cloud KMS key to use for encryption.
- string[]
Optional. Tags used for network traffic control.
- network
Uri string Optional. Network URI to connect workload to.
- service
Account string Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri string Optional. Subnetwork URI to connect workload to.
- ttl string
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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. Applies to sessions only. 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 1 hour if not set. 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.
- kms_
key str Optional. The Cloud KMS key to use for encryption.
- 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, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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 String Optional. Applies to sessions only. 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 1 hour if not set. 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.
- kms
Key String Optional. The Cloud KMS key to use for encryption.
- List<String>
Optional. Tags used for network traffic control.
- network
Uri String Optional. Network URI to connect workload to.
- service
Account String Optional. Service account that used to execute workload.
- staging
Bucket 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.
- subnetwork
Uri String Optional. Subnetwork URI to connect workload to.
- ttl String
Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). 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 run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. 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, PeripheralsConfigArgs
- Metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- Spark
History Pulumi.Server Config Google Native. Dataproc. V1. Inputs. Spark History Server Config Optional. The Spark History Server configuration for the workload.
- Metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- Spark
History SparkServer Config History Server Config Optional. The Spark History Server configuration for the workload.
- metastore
Service String Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History SparkServer Config History Server Config Optional. The Spark History Server configuration for the workload.
- metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History SparkServer Config History Server Config 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_ Sparkserver_ config History Server Config Optional. The Spark History Server configuration for the workload.
- metastore
Service String Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History Property MapServer Config Optional. The Spark History Server configuration for the workload.
PeripheralsConfigResponse, PeripheralsConfigResponseArgs
- Metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- Spark
History Pulumi.Server Config Google Native. Dataproc. V1. Inputs. Spark History Server Config Response Optional. The Spark History Server configuration for the workload.
- Metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- Spark
History SparkServer Config History Server Config Response Optional. The Spark History Server configuration for the workload.
- metastore
Service String Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History SparkServer Config History Server Config Response Optional. The Spark History Server configuration for the workload.
- metastore
Service string Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History SparkServer Config History Server Config Response 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_ Sparkserver_ config History Server Config Response Optional. The Spark History Server configuration for the workload.
- metastore
Service String Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
- spark
History Property MapServer Config Optional. The Spark History Server configuration for the workload.
PyPiRepositoryConfig, PyPiRepositoryConfigArgs
- Pypi
Repository string Optional. PyPi repository address
- Pypi
Repository string Optional. PyPi repository address
- pypi
Repository String Optional. PyPi repository address
- pypi
Repository string Optional. PyPi repository address
- pypi_
repository str Optional. PyPi repository address
- pypi
Repository String Optional. PyPi repository address
PyPiRepositoryConfigResponse, PyPiRepositoryConfigResponseArgs
- Pypi
Repository string Optional. PyPi repository address
- Pypi
Repository string Optional. PyPi repository address
- pypi
Repository String Optional. PyPi repository address
- pypi
Repository string Optional. PyPi repository address
- pypi_
repository str Optional. PyPi repository address
- pypi
Repository String Optional. PyPi repository address
PySparkBatch, PySparkBatchArgs
- Main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Python
File List<string>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- Main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File []stringUris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Python
File []stringUris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- main
Python StringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- python
File List<String>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File string[]Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- python
File string[]Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- main_
python_ strfile_ uri 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_ Sequence[str]uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- python_
file_ Sequence[str]uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- main
Python StringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- python
File List<String>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
PySparkBatchResponse, PySparkBatchResponseArgs
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- Python
File List<string>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File []stringUris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- Python
File []stringUris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Python StringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- python
File List<String>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File string[]Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Python stringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- python
File string[]Uris 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_ Sequence[str]uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main_
python_ strfile_ uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- python_
file_ Sequence[str]uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Python StringFile Uri The HCFS URI of the main Python file to use as the Spark driver. Must be a .py file.
- python
File List<String>Uris Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
RepositoryConfig, RepositoryConfigArgs
- Pypi
Repository Pulumi.Config Google Native. Dataproc. V1. Inputs. Py Pi Repository Config Optional. Configuration for PyPi repository.
- Pypi
Repository PyConfig Pi Repository Config Optional. Configuration for PyPi repository.
- pypi
Repository PyConfig Pi Repository Config Optional. Configuration for PyPi repository.
- pypi
Repository PyConfig Pi Repository Config Optional. Configuration for PyPi repository.
- pypi_
repository_ Pyconfig Pi Repository Config Optional. Configuration for PyPi repository.
- pypi
Repository Property MapConfig Optional. Configuration for PyPi repository.
RepositoryConfigResponse, RepositoryConfigResponseArgs
- Pypi
Repository Pulumi.Config Google Native. Dataproc. V1. Inputs. Py Pi Repository Config Response Optional. Configuration for PyPi repository.
- Pypi
Repository PyConfig Pi Repository Config Response Optional. Configuration for PyPi repository.
- pypi
Repository PyConfig Pi Repository Config Response Optional. Configuration for PyPi repository.
- pypi
Repository PyConfig Pi Repository Config Response Optional. Configuration for PyPi repository.
- pypi_
repository_ Pyconfig Pi Repository Config Response Optional. Configuration for PyPi repository.
- pypi
Repository Property MapConfig Optional. Configuration for PyPi repository.
RuntimeConfig, RuntimeConfigArgs
- Container
Image 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.
- Repository
Config Pulumi.Google Native. Dataproc. V1. Inputs. Repository Config Optional. Dependency repository configuration.
- Version string
Optional. Version of the batch runtime.
- Container
Image 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.
- Repository
Config RepositoryConfig Optional. Dependency repository configuration.
- Version string
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config RepositoryConfig Optional. Dependency repository configuration.
- version String
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config RepositoryConfig Optional. Dependency repository configuration.
- 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.
- repository_
config RepositoryConfig Optional. Dependency repository configuration.
- version str
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config Property Map Optional. Dependency repository configuration.
- version String
Optional. Version of the batch runtime.
RuntimeConfigResponse, RuntimeConfigResponseArgs
- Container
Image 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.
- Repository
Config Pulumi.Google Native. Dataproc. V1. Inputs. Repository Config Response Optional. Dependency repository configuration.
- Version string
Optional. Version of the batch runtime.
- Container
Image 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.
- Repository
Config RepositoryConfig Response Optional. Dependency repository configuration.
- Version string
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config RepositoryConfig Response Optional. Dependency repository configuration.
- version String
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config RepositoryConfig Response Optional. Dependency repository configuration.
- 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.
- repository_
config RepositoryConfig Response Optional. Dependency repository configuration.
- version str
Optional. Version of the batch runtime.
- container
Image 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.
- repository
Config Property Map Optional. Dependency repository configuration.
- version String
Optional. Version of the batch runtime.
RuntimeInfoResponse, RuntimeInfoResponseArgs
- Approximate
Usage Pulumi.Google Native. Dataproc. V1. Inputs. Usage Metrics Response Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- Current
Usage Pulumi.Google Native. Dataproc. V1. Inputs. Usage Snapshot Response Snapshot of current workload resource usage.
- Diagnostic
Output stringUri 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.
- Output
Uri string A URI pointing to the location of the stdout and stderr of the workload.
- Approximate
Usage UsageMetrics Response Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- Current
Usage UsageSnapshot Response Snapshot of current workload resource usage.
- Diagnostic
Output stringUri 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.
- Output
Uri string A URI pointing to the location of the stdout and stderr of the workload.
- approximate
Usage UsageMetrics Response Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- current
Usage UsageSnapshot Response Snapshot of current workload resource usage.
- diagnostic
Output StringUri 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.
- output
Uri String A URI pointing to the location of the stdout and stderr of the workload.
- approximate
Usage UsageMetrics Response Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- current
Usage UsageSnapshot Response Snapshot of current workload resource usage.
- diagnostic
Output stringUri 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.
- output
Uri string A URI pointing to the location of the stdout and stderr of the workload.
- approximate_
usage UsageMetrics Response Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- current_
usage UsageSnapshot Response Snapshot of current workload resource usage.
- diagnostic_
output_ struri 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.
- approximate
Usage Property Map Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
- current
Usage Property Map Snapshot of current workload resource usage.
- diagnostic
Output StringUri 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.
- output
Uri String A URI pointing to the location of the stdout and stderr of the workload.
SparkBatch, SparkBatchArgs
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Class 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.
- Main
Jar stringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File []stringUris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Class 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.
- Main
Jar stringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar StringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File string[]Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar stringFile Uri 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_ Sequence[str]uris 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_ strfile_ uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar StringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
SparkBatchResponse, SparkBatchResponseArgs
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Class 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.
- Main
Jar stringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Jar
File []stringUris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- Main
Class 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.
- Main
Jar stringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar StringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File string[]Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar stringFile Uri 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_ Sequence[str]uris 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_ strfile_ uri Optional. The HCFS URI of the jar file that contains the main class.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
- main
Class 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.
- main
Jar StringFile Uri Optional. The HCFS URI of the jar file that contains the main class.
SparkHistoryServerConfig, SparkHistoryServerConfigArgs
- Dataproc
Cluster 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 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 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 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]
- dataproc
Cluster 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, SparkHistoryServerConfigResponseArgs
- Dataproc
Cluster 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 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 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 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]
- dataproc
Cluster 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, SparkRBatchArgs
- Main
RFile stringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Main
RFile stringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main
RFile StringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main
RFile stringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main_
r_ strfile_ uri 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
RFile StringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
SparkRBatchResponse, SparkRBatchResponseArgs
- Archive
Uris 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.
- File
Uris List<string> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Main
RFile stringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- Archive
Uris []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.
- File
Uris []string Optional. HCFS URIs of files to be placed in the working directory of each executor.
- Main
RFile stringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main
RFile StringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris string[] Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main
RFile stringUri 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_ strfile_ uri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
- archive
Uris 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.
- file
Uris List<String> Optional. HCFS URIs of files to be placed in the working directory of each executor.
- main
RFile StringUri The HCFS URI of the main R file to use as the driver. Must be a .R or .r file.
SparkSqlBatch, SparkSqlBatchArgs
- Query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- Query
Variables Dictionary<string, string> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- Query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- Jar
File []stringUris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- Query
Variables map[string]string Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- query
File StringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
Variables Map<String,String> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- jar
File string[]Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
Variables {[key: string]: string} Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- query_
file_ struri The HCFS URI of the script that contains Spark SQL queries to execute.
- jar_
file_ Sequence[str]uris 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";).
- query
File StringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- jar
File List<String>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
Variables Map<String> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
SparkSqlBatchResponse, SparkSqlBatchResponseArgs
- Jar
File List<string>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- Query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- Query
Variables Dictionary<string, string> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- Jar
File []stringUris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- Query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- Query
Variables map[string]string Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- jar
File List<String>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
File StringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- query
Variables Map<String,String> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- jar
File string[]Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
File stringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- query
Variables {[key: string]: string} Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
- jar_
file_ Sequence[str]uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query_
file_ struri 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";).
- jar
File List<String>Uris Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
- query
File StringUri The HCFS URI of the script that contains Spark SQL queries to execute.
- query
Variables Map<String> Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
StateHistoryResponse, StateHistoryResponseArgs
- State string
The state of the batch at this point in history.
- State
Message string Details about the state at this point in history.
- State
Start stringTime The time when the batch entered the historical state.
- State string
The state of the batch at this point in history.
- State
Message string Details about the state at this point in history.
- State
Start stringTime The time when the batch entered the historical state.
- state String
The state of the batch at this point in history.
- state
Message String Details about the state at this point in history.
- state
Start StringTime The time when the batch entered the historical state.
- state string
The state of the batch at this point in history.
- state
Message string Details about the state at this point in history.
- state
Start stringTime 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_ strtime The time when the batch entered the historical state.
- state String
The state of the batch at this point in history.
- state
Message String Details about the state at this point in history.
- state
Start StringTime The time when the batch entered the historical state.
UsageMetricsResponse, UsageMetricsResponseArgs
- Accelerator
Type string Optional. Accelerator type being used, if any
- Milli
Accelerator stringSeconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Milli
Dcu stringSeconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Shuffle
Storage stringGb Seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Accelerator
Type string Optional. Accelerator type being used, if any
- Milli
Accelerator stringSeconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Milli
Dcu stringSeconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Shuffle
Storage stringGb Seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- accelerator
Type String Optional. Accelerator type being used, if any
- milli
Accelerator StringSeconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- milli
Dcu StringSeconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage StringGb Seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- accelerator
Type string Optional. Accelerator type being used, if any
- milli
Accelerator stringSeconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- milli
Dcu stringSeconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage stringGb Seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- accelerator_
type str Optional. Accelerator type being used, if any
- milli_
accelerator_ strseconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- milli_
dcu_ strseconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle_
storage_ strgb_ seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- accelerator
Type String Optional. Accelerator type being used, if any
- milli
Accelerator StringSeconds Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- milli
Dcu StringSeconds Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage StringGb Seconds Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
UsageSnapshotResponse, UsageSnapshotResponseArgs
- Accelerator
Type string Optional. Accelerator type being used, if any
- Milli
Accelerator string Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- Milli
Dcu string Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- string
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Shuffle
Storage stringGb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- string
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- Snapshot
Time string Optional. The timestamp of the usage snapshot.
- Accelerator
Type string Optional. Accelerator type being used, if any
- Milli
Accelerator string Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- Milli
Dcu string Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- string
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- Shuffle
Storage stringGb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- string
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- Snapshot
Time string Optional. The timestamp of the usage snapshot.
- accelerator
Type String Optional. Accelerator type being used, if any
- milli
Accelerator String Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- milli
Dcu String Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- String
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage StringGb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- String
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- snapshot
Time String Optional. The timestamp of the usage snapshot.
- accelerator
Type string Optional. Accelerator type being used, if any
- milli
Accelerator string Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- milli
Dcu string Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- string
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage stringGb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- string
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- snapshot
Time string Optional. The timestamp of the usage snapshot.
- accelerator_
type str Optional. Accelerator type being used, if any
- milli_
accelerator str Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- milli_
dcu str Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- str
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle_
storage_ strgb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- str
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- snapshot_
time str Optional. The timestamp of the usage snapshot.
- accelerator
Type String Optional. Accelerator type being used, if any
- milli
Accelerator String Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- milli
Dcu String Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- String
Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
- shuffle
Storage StringGb Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- String
Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
- snapshot
Time String Optional. The timestamp of the usage snapshot.
Package Details
- Repository
- Google Cloud Native pulumi/pulumi-google-native
- License
- Apache-2.0
Google Cloud Native is in preview. Google Cloud Classic is fully supported.