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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.dataproc/v1.Batch

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

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

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

    Create Batch Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Batch(name: string, args?: BatchArgs, opts?: CustomResourceOptions);
    @overload
def Batch(resource_name: str,
          args: Optional[BatchArgs] = None,
          opts: Optional[ResourceOptions] = None)

@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)
    func NewBatch(ctx *Context, name string, args *BatchArgs, opts ...ResourceOption) (*Batch, error)
    public Batch(string name, BatchArgs? args = null, CustomResourceOptions? opts = null)
    public Batch(String name, BatchArgs args)
public Batch(String name, BatchArgs args, CustomResourceOptions options)

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

    Parameters

    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.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var batchResource = new GoogleNative.Dataproc.V1.Batch("batchResource", new()
{
    BatchId = "string",
    EnvironmentConfig = new GoogleNative.Dataproc.V1.Inputs.EnvironmentConfigArgs
    {
        ExecutionConfig = new GoogleNative.Dataproc.V1.Inputs.ExecutionConfigArgs
        {
            IdleTtl = "string",
            KmsKey = "string",
            NetworkTags = new[]
            {
                "string",
            },
            NetworkUri = "string",
            ServiceAccount = "string",
            StagingBucket = "string",
            SubnetworkUri = "string",
            Ttl = "string",
        },
        PeripheralsConfig = new GoogleNative.Dataproc.V1.Inputs.PeripheralsConfigArgs
        {
            MetastoreService = "string",
            SparkHistoryServerConfig = new GoogleNative.Dataproc.V1.Inputs.SparkHistoryServerConfigArgs
            {
                DataprocCluster = "string",
            },
        },
    },
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    Project = "string",
    PysparkBatch = new GoogleNative.Dataproc.V1.Inputs.PySparkBatchArgs
    {
        MainPythonFileUri = "string",
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
        JarFileUris = new[]
        {
            "string",
        },
        PythonFileUris = new[]
        {
            "string",
        },
    },
    RequestId = "string",
    RuntimeConfig = new GoogleNative.Dataproc.V1.Inputs.RuntimeConfigArgs
    {
        ContainerImage = "string",
        Properties = 
        {
            { "string", "string" },
        },
        RepositoryConfig = new GoogleNative.Dataproc.V1.Inputs.RepositoryConfigArgs
        {
            PypiRepositoryConfig = new GoogleNative.Dataproc.V1.Inputs.PyPiRepositoryConfigArgs
            {
                PypiRepository = "string",
            },
        },
        Version = "string",
    },
    SparkBatch = new GoogleNative.Dataproc.V1.Inputs.SparkBatchArgs
    {
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
        JarFileUris = new[]
        {
            "string",
        },
        MainClass = "string",
        MainJarFileUri = "string",
    },
    SparkRBatch = new GoogleNative.Dataproc.V1.Inputs.SparkRBatchArgs
    {
        MainRFileUri = "string",
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
    },
    SparkSqlBatch = new GoogleNative.Dataproc.V1.Inputs.SparkSqlBatchArgs
    {
        QueryFileUri = "string",
        JarFileUris = new[]
        {
            "string",
        },
        QueryVariables = 
        {
            { "string", "string" },
        },
    },
});

    example, err := dataproc.NewBatch(ctx, "batchResource", &dataproc.BatchArgs{
	BatchId: pulumi.String("string"),
	EnvironmentConfig: &dataproc.EnvironmentConfigArgs{
		ExecutionConfig: &dataproc.ExecutionConfigArgs{
			IdleTtl: pulumi.String("string"),
			KmsKey:  pulumi.String("string"),
			NetworkTags: pulumi.StringArray{
				pulumi.String("string"),
			},
			NetworkUri:     pulumi.String("string"),
			ServiceAccount: pulumi.String("string"),
			StagingBucket:  pulumi.String("string"),
			SubnetworkUri:  pulumi.String("string"),
			Ttl:            pulumi.String("string"),
		},
		PeripheralsConfig: &dataproc.PeripheralsConfigArgs{
			MetastoreService: pulumi.String("string"),
			SparkHistoryServerConfig: &dataproc.SparkHistoryServerConfigArgs{
				DataprocCluster: pulumi.String("string"),
			},
		},
	},
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Location: pulumi.String("string"),
	Project:  pulumi.String("string"),
	PysparkBatch: &dataproc.PySparkBatchArgs{
		MainPythonFileUri: pulumi.String("string"),
		ArchiveUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		Args: pulumi.StringArray{
			pulumi.String("string"),
		},
		FileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		JarFileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		PythonFileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
	RequestId: pulumi.String("string"),
	RuntimeConfig: &dataproc.RuntimeConfigArgs{
		ContainerImage: pulumi.String("string"),
		Properties: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
		RepositoryConfig: &dataproc.RepositoryConfigArgs{
			PypiRepositoryConfig: &dataproc.PyPiRepositoryConfigArgs{
				PypiRepository: pulumi.String("string"),
			},
		},
		Version: pulumi.String("string"),
	},
	SparkBatch: &dataproc.SparkBatchArgs{
		ArchiveUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		Args: pulumi.StringArray{
			pulumi.String("string"),
		},
		FileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		JarFileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		MainClass:      pulumi.String("string"),
		MainJarFileUri: pulumi.String("string"),
	},
	SparkRBatch: &dataproc.SparkRBatchArgs{
		MainRFileUri: pulumi.String("string"),
		ArchiveUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		Args: pulumi.StringArray{
			pulumi.String("string"),
		},
		FileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
	SparkSqlBatch: &dataproc.SparkSqlBatchArgs{
		QueryFileUri: pulumi.String("string"),
		JarFileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		QueryVariables: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
	},
})

    var batchResource = new Batch("batchResource", BatchArgs.builder()
    .batchId("string")
    .environmentConfig(EnvironmentConfigArgs.builder()
        .executionConfig(ExecutionConfigArgs.builder()
            .idleTtl("string")
            .kmsKey("string")
            .networkTags("string")
            .networkUri("string")
            .serviceAccount("string")
            .stagingBucket("string")
            .subnetworkUri("string")
            .ttl("string")
            .build())
        .peripheralsConfig(PeripheralsConfigArgs.builder()
            .metastoreService("string")
            .sparkHistoryServerConfig(SparkHistoryServerConfigArgs.builder()
                .dataprocCluster("string")
                .build())
            .build())
        .build())
    .labels(Map.of("string", "string"))
    .location("string")
    .project("string")
    .pysparkBatch(PySparkBatchArgs.builder()
        .mainPythonFileUri("string")
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .jarFileUris("string")
        .pythonFileUris("string")
        .build())
    .requestId("string")
    .runtimeConfig(RuntimeConfigArgs.builder()
        .containerImage("string")
        .properties(Map.of("string", "string"))
        .repositoryConfig(RepositoryConfigArgs.builder()
            .pypiRepositoryConfig(PyPiRepositoryConfigArgs.builder()
                .pypiRepository("string")
                .build())
            .build())
        .version("string")
        .build())
    .sparkBatch(SparkBatchArgs.builder()
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .jarFileUris("string")
        .mainClass("string")
        .mainJarFileUri("string")
        .build())
    .sparkRBatch(SparkRBatchArgs.builder()
        .mainRFileUri("string")
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .build())
    .sparkSqlBatch(SparkSqlBatchArgs.builder()
        .queryFileUri("string")
        .jarFileUris("string")
        .queryVariables(Map.of("string", "string"))
        .build())
    .build());

    batch_resource = google_native.dataproc.v1.Batch("batchResource",
    batch_id="string",
    environment_config={
        "execution_config": {
            "idle_ttl": "string",
            "kms_key": "string",
            "network_tags": ["string"],
            "network_uri": "string",
            "service_account": "string",
            "staging_bucket": "string",
            "subnetwork_uri": "string",
            "ttl": "string",
        },
        "peripherals_config": {
            "metastore_service": "string",
            "spark_history_server_config": {
                "dataproc_cluster": "string",
            },
        },
    },
    labels={
        "string": "string",
    },
    location="string",
    project="string",
    pyspark_batch={
        "main_python_file_uri": "string",
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
        "jar_file_uris": ["string"],
        "python_file_uris": ["string"],
    },
    request_id="string",
    runtime_config={
        "container_image": "string",
        "properties": {
            "string": "string",
        },
        "repository_config": {
            "pypi_repository_config": {
                "pypi_repository": "string",
            },
        },
        "version": "string",
    },
    spark_batch={
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
        "jar_file_uris": ["string"],
        "main_class": "string",
        "main_jar_file_uri": "string",
    },
    spark_r_batch={
        "main_r_file_uri": "string",
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
    },
    spark_sql_batch={
        "query_file_uri": "string",
        "jar_file_uris": ["string"],
        "query_variables": {
            "string": "string",
        },
    })

    const batchResource = new google_native.dataproc.v1.Batch("batchResource", {
    batchId: "string",
    environmentConfig: {
        executionConfig: {
            idleTtl: "string",
            kmsKey: "string",
            networkTags: ["string"],
            networkUri: "string",
            serviceAccount: "string",
            stagingBucket: "string",
            subnetworkUri: "string",
            ttl: "string",
        },
        peripheralsConfig: {
            metastoreService: "string",
            sparkHistoryServerConfig: {
                dataprocCluster: "string",
            },
        },
    },
    labels: {
        string: "string",
    },
    location: "string",
    project: "string",
    pysparkBatch: {
        mainPythonFileUri: "string",
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
        jarFileUris: ["string"],
        pythonFileUris: ["string"],
    },
    requestId: "string",
    runtimeConfig: {
        containerImage: "string",
        properties: {
            string: "string",
        },
        repositoryConfig: {
            pypiRepositoryConfig: {
                pypiRepository: "string",
            },
        },
        version: "string",
    },
    sparkBatch: {
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
        jarFileUris: ["string"],
        mainClass: "string",
        mainJarFileUri: "string",
    },
    sparkRBatch: {
        mainRFileUri: "string",
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
    },
    sparkSqlBatch: {
        queryFileUri: "string",
        jarFileUris: ["string"],
        queryVariables: {
            string: "string",
        },
    },
});

    type: google-native:dataproc/v1:Batch
properties:
    batchId: string
    environmentConfig:
        executionConfig:
            idleTtl: string
            kmsKey: string
            networkTags:
                - string
            networkUri: string
            serviceAccount: string
            stagingBucket: string
            subnetworkUri: string
            ttl: string
        peripheralsConfig:
            metastoreService: string
            sparkHistoryServerConfig:
                dataprocCluster: string
    labels:
        string: string
    location: string
    project: string
    pysparkBatch:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        jarFileUris:
            - string
        mainPythonFileUri: string
        pythonFileUris:
            - string
    requestId: string
    runtimeConfig:
        containerImage: string
        properties:
            string: string
        repositoryConfig:
            pypiRepositoryConfig:
                pypiRepository: string
        version: string
    sparkBatch:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        jarFileUris:
            - string
        mainClass: string
        mainJarFileUri: string
    sparkRBatch:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        mainRFileUri: string
    sparkSqlBatch:
        jarFileUris:
            - string
        queryFileUri: string
        queryVariables:
            string: string

    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

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Batch resource accepts the following input properties:

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

    Outputs

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

    CreateTime string
    The time when the batch was created.
    Creator string
    The email address of the user who created the batch.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    The resource name of the batch.
    Operation string
    The resource name of the operation associated with this batch.
    RuntimeInfo Pulumi.GoogleNative.Dataproc.V1.Outputs.RuntimeInfoResponse
    Runtime information about batch execution.
    State string
    The state of the batch.
    StateHistory List<Pulumi.GoogleNative.Dataproc.V1.Outputs.StateHistoryResponse>
    Historical state information for the batch.
    StateMessage string
    Batch state details, such as a failure description if the state is FAILED.
    StateTime string
    The time when the batch entered a current state.
    Uuid string
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.
    CreateTime string
    The time when the batch was created.
    Creator string
    The email address of the user who created the batch.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    The resource name of the batch.
    Operation string
    The resource name of the operation associated with this batch.
    RuntimeInfo RuntimeInfoResponse
    Runtime information about batch execution.
    State string
    The state of the batch.
    StateHistory []StateHistoryResponse
    Historical state information for the batch.
    StateMessage string
    Batch state details, such as a failure description if the state is FAILED.
    StateTime string
    The time when the batch entered a current state.
    Uuid string
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.
    createTime String
    The time when the batch was created.
    creator String
    The email address of the user who created the batch.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    The resource name of the batch.
    operation String
    The resource name of the operation associated with this batch.
    runtimeInfo RuntimeInfoResponse
    Runtime information about batch execution.
    state String
    The state of the batch.
    stateHistory List<StateHistoryResponse>
    Historical state information for the batch.
    stateMessage String
    Batch state details, such as a failure description if the state is FAILED.
    stateTime String
    The time when the batch entered a current state.
    uuid String
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.
    createTime string
    The time when the batch was created.
    creator string
    The email address of the user who created the batch.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    The resource name of the batch.
    operation string
    The resource name of the operation associated with this batch.
    runtimeInfo RuntimeInfoResponse
    Runtime information about batch execution.
    state string
    The state of the batch.
    stateHistory StateHistoryResponse[]
    Historical state information for the batch.
    stateMessage string
    Batch state details, such as a failure description if the state is FAILED.
    stateTime string
    The time when the batch entered a current state.
    uuid string
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.
    create_time str
    The time when the batch was created.
    creator str
    The email address of the user who created the batch.
    id str
    The provider-assigned unique ID for this managed resource.
    name str
    The resource name of the batch.
    operation str
    The resource name of the operation associated with this batch.
    runtime_info RuntimeInfoResponse
    Runtime information about batch execution.
    state str
    The state of the batch.
    state_history Sequence[StateHistoryResponse]
    Historical state information for the batch.
    state_message str
    Batch state details, such as a failure description if the state is FAILED.
    state_time str
    The time when the batch entered a current state.
    uuid str
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.
    createTime String
    The time when the batch was created.
    creator String
    The email address of the user who created the batch.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    The resource name of the batch.
    operation String
    The resource name of the operation associated with this batch.
    runtimeInfo Property Map
    Runtime information about batch execution.
    state String
    The state of the batch.
    stateHistory List<Property Map>
    Historical state information for the batch.
    stateMessage String
    Batch state details, such as a failure description if the state is FAILED.
    stateTime String
    The time when the batch entered a current state.
    uuid String
    A batch UUID (Unique Universal Identifier). The service generates this value when it creates the batch.

    Supporting Types

    EnvironmentConfig, EnvironmentConfigArgs

    ExecutionConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.ExecutionConfig
    Optional. Execution configuration for a workload.
    PeripheralsConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.PeripheralsConfig
    Optional. Peripherals configuration that workload has access to.
    ExecutionConfig ExecutionConfig
    Optional. Execution configuration for a workload.
    PeripheralsConfig PeripheralsConfig
    Optional. Peripherals configuration that workload has access to.
    executionConfig ExecutionConfig
    Optional. Execution configuration for a workload.
    peripheralsConfig PeripheralsConfig
    Optional. Peripherals configuration that workload has access to.
    executionConfig ExecutionConfig
    Optional. Execution configuration for a workload.
    peripheralsConfig PeripheralsConfig
    Optional. Peripherals configuration that workload has access to.
    execution_config ExecutionConfig
    Optional. Execution configuration for a workload.
    peripherals_config PeripheralsConfig
    Optional. Peripherals configuration that workload has access to.
    executionConfig Property Map
    Optional. Execution configuration for a workload.
    peripheralsConfig Property Map
    Optional. Peripherals configuration that workload has access to.

    EnvironmentConfigResponse, EnvironmentConfigResponseArgs

    ExecutionConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.ExecutionConfigResponse
    Optional. Execution configuration for a workload.
    PeripheralsConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.PeripheralsConfigResponse
    Optional. Peripherals configuration that workload has access to.
    ExecutionConfig ExecutionConfigResponse
    Optional. Execution configuration for a workload.
    PeripheralsConfig PeripheralsConfigResponse
    Optional. Peripherals configuration that workload has access to.
    executionConfig ExecutionConfigResponse
    Optional. Execution configuration for a workload.
    peripheralsConfig PeripheralsConfigResponse
    Optional. Peripherals configuration that workload has access to.
    executionConfig ExecutionConfigResponse
    Optional. Execution configuration for a workload.
    peripheralsConfig PeripheralsConfigResponse
    Optional. Peripherals configuration that workload has access to.
    execution_config ExecutionConfigResponse
    Optional. Execution configuration for a workload.
    peripherals_config PeripheralsConfigResponse
    Optional. Peripherals configuration that workload has access to.
    executionConfig Property Map
    Optional. Execution configuration for a workload.
    peripheralsConfig Property Map
    Optional. Peripherals configuration that workload has access to.

    ExecutionConfig, ExecutionConfigArgs

    IdleTtl 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.
    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, 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.
    IdleTtl 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.
    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, 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.
    idleTtl 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.
    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, 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.
    idleTtl 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.
    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, 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.
    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, 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.
    idleTtl 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.
    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, 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

    IdleTtl 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.
    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, 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.
    IdleTtl 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.
    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, 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.
    idleTtl 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.
    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, 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.
    idleTtl 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.
    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, 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.
    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, 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.
    idleTtl 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.
    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, 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

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

    PeripheralsConfigResponse, PeripheralsConfigResponseArgs

    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.

    PyPiRepositoryConfig, PyPiRepositoryConfigArgs

    PypiRepository string
    Optional. PyPi repository address
    PypiRepository string
    Optional. PyPi repository address
    pypiRepository String
    Optional. PyPi repository address
    pypiRepository string
    Optional. PyPi repository address
    pypi_repository str
    Optional. PyPi repository address
    pypiRepository String
    Optional. PyPi repository address

    PyPiRepositoryConfigResponse, PyPiRepositoryConfigResponseArgs

    PypiRepository string
    Optional. PyPi repository address
    PypiRepository string
    Optional. PyPi repository address
    pypiRepository String
    Optional. PyPi repository address
    pypiRepository string
    Optional. PyPi repository address
    pypi_repository str
    Optional. PyPi repository address
    pypiRepository String
    Optional. PyPi repository address

    PySparkBatch, PySparkBatchArgs

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

    PySparkBatchResponse, PySparkBatchResponseArgs

    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.

    RepositoryConfig, RepositoryConfigArgs

    PypiRepositoryConfig PyPiRepositoryConfig
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig PyPiRepositoryConfig
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig PyPiRepositoryConfig
    Optional. Configuration for PyPi repository.
    pypi_repository_config PyPiRepositoryConfig
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig Property Map
    Optional. Configuration for PyPi repository.

    RepositoryConfigResponse, RepositoryConfigResponseArgs

    PypiRepositoryConfig PyPiRepositoryConfigResponse
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig PyPiRepositoryConfigResponse
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig PyPiRepositoryConfigResponse
    Optional. Configuration for PyPi repository.
    pypi_repository_config PyPiRepositoryConfigResponse
    Optional. Configuration for PyPi repository.
    pypiRepositoryConfig Property Map
    Optional. Configuration for PyPi repository.

    RuntimeConfig, RuntimeConfigArgs

    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.
    RepositoryConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.RepositoryConfig
    Optional. Dependency repository configuration.
    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.
    RepositoryConfig RepositoryConfig
    Optional. Dependency repository configuration.
    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.
    repositoryConfig RepositoryConfig
    Optional. Dependency repository configuration.
    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.
    repositoryConfig 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.
    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.
    repositoryConfig Property Map
    Optional. Dependency repository configuration.
    version String
    Optional. Version of the batch runtime.

    RuntimeConfigResponse, RuntimeConfigResponseArgs

    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.
    RepositoryConfig Pulumi.GoogleNative.Dataproc.V1.Inputs.RepositoryConfigResponse
    Optional. Dependency repository configuration.
    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.
    RepositoryConfig RepositoryConfigResponse
    Optional. Dependency repository configuration.
    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.
    repositoryConfig RepositoryConfigResponse
    Optional. Dependency repository configuration.
    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.
    repositoryConfig RepositoryConfigResponse
    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 RepositoryConfigResponse
    Optional. Dependency repository configuration.
    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.
    repositoryConfig Property Map
    Optional. Dependency repository configuration.
    version String
    Optional. Version of the batch runtime.

    RuntimeInfoResponse, RuntimeInfoResponseArgs

    ApproximateUsage Pulumi.GoogleNative.Dataproc.V1.Inputs.UsageMetricsResponse
    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).
    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 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).
    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 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).
    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 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).
    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 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 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 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).
    currentUsage Property Map
    Snapshot of current workload resource usage.
    diagnosticOutputUri String
    A URI pointing to the location of the diagnostics tarball.
    endpoints Map<String>
    Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
    outputUri String
    A URI pointing to the location of the stdout and stderr of the workload.

    SparkBatch, SparkBatchArgs

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

    SparkBatchResponse, SparkBatchResponseArgs

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

    SparkHistoryServerConfig, SparkHistoryServerConfigArgs

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

    SparkHistoryServerConfigResponse, SparkHistoryServerConfigResponseArgs

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

    SparkRBatch, SparkRBatchArgs

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

    SparkRBatchResponse, SparkRBatchResponseArgs

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

    SparkSqlBatch, SparkSqlBatchArgs

    QueryFileUri string
    The HCFS URI of the script that contains Spark SQL queries to execute.
    JarFileUris List<string>
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    QueryVariables Dictionary<string, string>
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
    QueryFileUri string
    The HCFS URI of the script that contains Spark SQL queries to execute.
    JarFileUris []string
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    QueryVariables map[string]string
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
    queryFileUri String
    The HCFS URI of the script that contains Spark SQL queries to execute.
    jarFileUris List<String>
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    queryVariables Map<String,String>
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
    queryFileUri string
    The HCFS URI of the script that contains Spark SQL queries to execute.
    jarFileUris string[]
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    queryVariables {[key: string]: string}
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
    query_file_uri str
    The HCFS URI of the script that contains Spark SQL queries to execute.
    jar_file_uris Sequence[str]
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    query_variables Mapping[str, str]
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).
    queryFileUri String
    The HCFS URI of the script that contains Spark SQL queries to execute.
    jarFileUris List<String>
    Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.
    queryVariables Map<String>
    Optional. Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

    SparkSqlBatchResponse, SparkSqlBatchResponseArgs

    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, StateHistoryResponseArgs

    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, UsageMetricsResponseArgs

    AcceleratorType string
    Optional. Accelerator type being used, if any
    MilliAcceleratorSeconds string
    Optional. Accelerator usage in (milliAccelerator 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)).
    AcceleratorType string
    Optional. Accelerator type being used, if any
    MilliAcceleratorSeconds string
    Optional. Accelerator usage in (milliAccelerator 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)).
    acceleratorType String
    Optional. Accelerator type being used, if any
    milliAcceleratorSeconds String
    Optional. Accelerator usage in (milliAccelerator 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)).
    acceleratorType string
    Optional. Accelerator type being used, if any
    milliAcceleratorSeconds string
    Optional. Accelerator usage in (milliAccelerator 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)).
    accelerator_type str
    Optional. Accelerator type being used, if any
    milli_accelerator_seconds str
    Optional. Accelerator usage in (milliAccelerator 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)).
    acceleratorType String
    Optional. Accelerator type being used, if any
    milliAcceleratorSeconds String
    Optional. Accelerator usage in (milliAccelerator 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, UsageSnapshotResponseArgs

    AcceleratorType string
    Optional. Accelerator type being used, if any
    MilliAccelerator string
    Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    MilliDcu string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
    MilliDcuPremium string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (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))
    ShuffleStorageGbPremium string
    Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    SnapshotTime string
    Optional. The timestamp of the usage snapshot.
    AcceleratorType string
    Optional. Accelerator type being used, if any
    MilliAccelerator string
    Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    MilliDcu string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
    MilliDcuPremium string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (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))
    ShuffleStorageGbPremium string
    Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    SnapshotTime string
    Optional. The timestamp of the usage snapshot.
    acceleratorType String
    Optional. Accelerator type being used, if any
    milliAccelerator String
    Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    milliDcu String
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
    milliDcuPremium String
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (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))
    shuffleStorageGbPremium String
    Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    snapshotTime String
    Optional. The timestamp of the usage snapshot.
    acceleratorType string
    Optional. Accelerator type being used, if any
    milliAccelerator string
    Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    milliDcu string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
    milliDcuPremium string
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (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))
    shuffleStorageGbPremium string
    Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    snapshotTime 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)).
    milli_dcu_premium 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_gb str
    Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    shuffle_storage_gb_premium 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.
    acceleratorType String
    Optional. Accelerator type being used, if any
    milliAccelerator String
    Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
    milliDcu String
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
    milliDcuPremium String
    Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (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))
    shuffleStorageGbPremium String
    Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (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-native logo

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

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native