Google Cloud Native v0.31.1, Jul 20 23

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.31.1 published on Thursday, Jul 20, 2023 by Pulumi

pulumi/pulumi-google-native

google-native.dataproc/v1.getBatch

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.31.1 published on Thursday, Jul 20, 2023 by Pulumi

pulumi/pulumi-google-native

Using getBatch

Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

function getBatch(args: GetBatchArgs, opts?: InvokeOptions): Promise<GetBatchResult>
function getBatchOutput(args: GetBatchOutputArgs, opts?: InvokeOptions): Output<GetBatchResult>

def get_batch(batch_id: Optional[str] = None,
              location: Optional[str] = None,
              project: Optional[str] = None,
              opts: Optional[InvokeOptions] = None) -> GetBatchResult
def get_batch_output(batch_id: Optional[pulumi.Input[str]] = None,
              location: Optional[pulumi.Input[str]] = None,
              project: Optional[pulumi.Input[str]] = None,
              opts: Optional[InvokeOptions] = None) -> Output[GetBatchResult]

func LookupBatch(ctx *Context, args *LookupBatchArgs, opts ...InvokeOption) (*LookupBatchResult, error)
func LookupBatchOutput(ctx *Context, args *LookupBatchOutputArgs, opts ...InvokeOption) LookupBatchResultOutput

> Note: This function is named LookupBatch in the Go SDK.

public static class GetBatch 
{
    public static Task<GetBatchResult> InvokeAsync(GetBatchArgs args, InvokeOptions? opts = null)
    public static Output<GetBatchResult> Invoke(GetBatchInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetBatchResult> getBatch(GetBatchArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet

fn::invoke:
  function: google-native:dataproc/v1:getBatch
  arguments:
    # arguments dictionary

The following arguments are supported:

BatchId string
Location string
Project string

BatchId string
Location string
Project string

batchId String
location String
project String

batchId string
location string
project string

batch_id str
location str
project str

batchId String
location String
project String

getBatch Result

The following output properties are available:

CreateTime string: The time when the batch was created.
Creator string: The email address of the user who created the batch.
EnvironmentConfig Pulumi.GoogleNative.Dataproc.V1.Outputs.EnvironmentConfigResponse: 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.
Name string: The resource name of the batch.
Operation string: The resource name of the operation associated with this batch.
PysparkBatch Pulumi.GoogleNative.Dataproc.V1.Outputs.PySparkBatchResponse: Optional. PySpark batch config.
RuntimeConfig Pulumi.GoogleNative.Dataproc.V1.Outputs.RuntimeConfigResponse: Optional. Runtime configuration for the batch execution.
RuntimeInfo Pulumi.GoogleNative.Dataproc.V1.Outputs.RuntimeInfoResponse: Runtime information about batch execution.
SparkBatch Pulumi.GoogleNative.Dataproc.V1.Outputs.SparkBatchResponse: Optional. Spark batch config.
SparkRBatch Pulumi.GoogleNative.Dataproc.V1.Outputs.SparkRBatchResponse: Optional. SparkR batch config.
SparkSqlBatch Pulumi.GoogleNative.Dataproc.V1.Outputs.SparkSqlBatchResponse: Optional. SparkSql batch config.
State string: The state of the batch.
StateHistory List<Pulumi.GoogleNative.Dataproc.V1.Outputs.StateHistoryResponse>: Historical state information for the batch.
StateMessage string: Batch state details, such as a failure description if the state is FAILED.
StateTime string: The time when the batch entered a current state.
Uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

CreateTime string: The time when the batch was created.
Creator string: The email address of the user who created the batch.
EnvironmentConfig EnvironmentConfigResponse: 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.
Name string: The resource name of the batch.
Operation string: The resource name of the operation associated with this batch.
PysparkBatch PySparkBatchResponse: Optional. PySpark batch config.
RuntimeConfig RuntimeConfigResponse: Optional. Runtime configuration for the batch execution.
RuntimeInfo RuntimeInfoResponse: Runtime information about batch execution.
SparkBatch SparkBatchResponse: Optional. Spark batch config.
SparkRBatch SparkRBatchResponse: Optional. SparkR batch config.
SparkSqlBatch SparkSqlBatchResponse: Optional. SparkSql batch config.
State string: The state of the batch.
StateHistory []StateHistoryResponse: Historical state information for the batch.
StateMessage string: Batch state details, such as a failure description if the state is FAILED.
StateTime string: The time when the batch entered a current state.
Uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime String: The time when the batch was created.
creator String: The email address of the user who created the batch.
environmentConfig EnvironmentConfigResponse: 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.
name String: The resource name of the batch.
operation String: The resource name of the operation associated with this batch.
pysparkBatch PySparkBatchResponse: Optional. PySpark batch config.
runtimeConfig RuntimeConfigResponse: Optional. Runtime configuration for the batch execution.
runtimeInfo RuntimeInfoResponse: Runtime information about batch execution.
sparkBatch SparkBatchResponse: Optional. Spark batch config.
sparkRBatch SparkRBatchResponse: Optional. SparkR batch config.
sparkSqlBatch SparkSqlBatchResponse: Optional. SparkSql batch config.
state String: The state of the batch.
stateHistory List<StateHistoryResponse>: Historical state information for the batch.
stateMessage String: Batch state details, such as a failure description if the state is FAILED.
stateTime String: The time when the batch entered a current state.
uuid String: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime string: The time when the batch was created.
creator string: The email address of the user who created the batch.
environmentConfig EnvironmentConfigResponse: 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.
name string: The resource name of the batch.
operation string: The resource name of the operation associated with this batch.
pysparkBatch PySparkBatchResponse: Optional. PySpark batch config.
runtimeConfig RuntimeConfigResponse: Optional. Runtime configuration for the batch execution.
runtimeInfo RuntimeInfoResponse: Runtime information about batch execution.
sparkBatch SparkBatchResponse: Optional. Spark batch config.
sparkRBatch SparkRBatchResponse: Optional. SparkR batch config.
sparkSqlBatch SparkSqlBatchResponse: Optional. SparkSql batch config.
state string: The state of the batch.
stateHistory StateHistoryResponse[]: Historical state information for the batch.
stateMessage string: Batch state details, such as a failure description if the state is FAILED.
stateTime string: The time when the batch entered a current state.
uuid string: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

create_time str: The time when the batch was created.
creator str: The email address of the user who created the batch.
environment_config EnvironmentConfigResponse: 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.
name str: The resource name of the batch.
operation str: The resource name of the operation associated with this batch.
pyspark_batch PySparkBatchResponse: Optional. PySpark batch config.
runtime_config RuntimeConfigResponse: Optional. Runtime configuration for the batch execution.
runtime_info RuntimeInfoResponse: Runtime information about batch execution.
spark_batch SparkBatchResponse: Optional. Spark batch config.
spark_r_batch SparkRBatchResponse: Optional. SparkR batch config.
spark_sql_batch SparkSqlBatchResponse: Optional. SparkSql batch config.
state str: The state of the batch.
state_history Sequence[StateHistoryResponse]: Historical state information for the batch.
state_message str: Batch state details, such as a failure description if the state is FAILED.
state_time str: The time when the batch entered a current state.
uuid str: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

createTime String: The time when the batch was created.
creator String: The email address of the user who created the batch.
environmentConfig Property Map: Optional. Environment configuration for the batch execution.
labels Map<String>: Optional. The labels to associate with this batch. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a batch.
name String: The resource name of the batch.
operation String: The resource name of the operation associated with this batch.
pysparkBatch Property Map: Optional. PySpark batch config.
runtimeConfig Property Map: Optional. Runtime configuration for the batch execution.
runtimeInfo Property Map: Runtime information about batch execution.
sparkBatch Property Map: Optional. Spark batch config.
sparkRBatch Property Map: Optional. SparkR batch config.
sparkSqlBatch Property Map: Optional. SparkSql batch config.
state String: The state of the batch.
stateHistory List<Property Map>: Historical state information for the batch.
stateMessage String: Batch state details, such as a failure description if the state is FAILED.
stateTime String: The time when the batch entered a current state.
uuid String: A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

Supporting Types

EnvironmentConfigResponse

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

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

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

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

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

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

ExecutionConfigResponse

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

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

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

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

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

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

PeripheralsConfigResponse

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

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

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

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

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

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

PySparkBatchResponse

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

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

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

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

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

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

RuntimeConfigResponse

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

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

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

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

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

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

RuntimeInfoResponse

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

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

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

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

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

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

SparkBatchResponse

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

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

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

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

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

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

SparkHistoryServerConfigResponse

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

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

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

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

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

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

SparkRBatchResponse

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

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

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

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

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

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

SparkSqlBatchResponse

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

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

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

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

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

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

StateHistoryResponse

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

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

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

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

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

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

UsageMetricsResponse

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

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

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

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

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

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

UsageSnapshotResponse

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

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

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

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

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

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

Package Details

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

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.31.1 published on Thursday, Jul 20, 2023 by Pulumi

pulumi/pulumi-google-native

google-native.dataproc/v1.getBatch

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Using getBatch

getBatch Result

Supporting Types

EnvironmentConfigResponse

ExecutionConfigResponse

PeripheralsConfigResponse

PySparkBatchResponse

RuntimeConfigResponse

RuntimeInfoResponse

SparkBatchResponse

SparkHistoryServerConfigResponse

SparkRBatchResponse

SparkSqlBatchResponse

StateHistoryResponse

UsageMetricsResponse

UsageSnapshotResponse

Package Details

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