Google Cloud v8.21.0, Mar 5 25

Google Cloud v8.21.0 published on Wednesday, Mar 5, 2025 by Pulumi

gcp.dataproc.GdcSparkApplication

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Google Cloud v8.21.0 published on Wednesday, Mar 5, 2025 by Pulumi

pulumi/pulumi-gcp

Example Usage

Dataprocgdc Sparkapplication Basic

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-spark-app-basic",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    sparkApplicationConfig: {
        mainClass: "org.apache.spark.examples.SparkPi",
        jarFileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        args: ["10000"],
    },
});

import pulumi
import pulumi_gcp as gcp

spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-spark-app-basic",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    spark_application_config={
        "main_class": "org.apache.spark.examples.SparkPi",
        "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        "args": ["10000"],
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-spark-app-basic"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			SparkApplicationConfig: &dataproc.GdcSparkApplicationSparkApplicationConfigArgs{
				MainClass: pulumi.String("org.apache.spark.examples.SparkPi"),
				JarFileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
				Args: pulumi.StringArray{
					pulumi.String("10000"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-spark-app-basic",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        SparkApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkApplicationConfigArgs
        {
            MainClass = "org.apache.spark.examples.SparkPi",
            JarFileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
            Args = new[]
            {
                "10000",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkApplicationConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-spark-app-basic")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .sparkApplicationConfig(GdcSparkApplicationSparkApplicationConfigArgs.builder()
                .mainClass("org.apache.spark.examples.SparkPi")
                .jarFileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .args("10000")
                .build())
            .build());

    }
}

resources:
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-spark-app-basic
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      sparkApplicationConfig:
        mainClass: org.apache.spark.examples.SparkPi
        jarFileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar
        args:
          - '10000'

Dataprocgdc Sparkapplication

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const appEnv = new gcp.dataproc.GdcApplicationEnvironment("app_env", {
    applicationEnvironmentId: "tf-e2e-spark-app-env",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
});
const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-spark-app",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    labels: {
        "test-label": "label-value",
    },
    annotations: {
        an_annotation: "annotation_value",
    },
    properties: {
        "spark.executor.instances": "2",
    },
    applicationEnvironment: appEnv.name,
    version: "1.2",
    sparkApplicationConfig: {
        mainJarFileUri: "file:///usr/lib/spark/examples/jars/spark-examples.jar",
        jarFileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        archiveUris: ["file://usr/lib/spark/examples/spark-examples.jar"],
        fileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
    },
});

import pulumi
import pulumi_gcp as gcp

app_env = gcp.dataproc.GdcApplicationEnvironment("app_env",
    application_environment_id="tf-e2e-spark-app-env",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default")
spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-spark-app",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    labels={
        "test-label": "label-value",
    },
    annotations={
        "an_annotation": "annotation_value",
    },
    properties={
        "spark.executor.instances": "2",
    },
    application_environment=app_env.name,
    version="1.2",
    spark_application_config={
        "main_jar_file_uri": "file:///usr/lib/spark/examples/jars/spark-examples.jar",
        "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        "archive_uris": ["file://usr/lib/spark/examples/spark-examples.jar"],
        "file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		appEnv, err := dataproc.NewGdcApplicationEnvironment(ctx, "app_env", &dataproc.GdcApplicationEnvironmentArgs{
			ApplicationEnvironmentId: pulumi.String("tf-e2e-spark-app-env"),
			Serviceinstance:          pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:                  pulumi.String("my-project"),
			Location:                 pulumi.String("us-west2"),
			Namespace:                pulumi.String("default"),
		})
		if err != nil {
			return err
		}
		_, err = dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-spark-app"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			Labels: pulumi.StringMap{
				"test-label": pulumi.String("label-value"),
			},
			Annotations: pulumi.StringMap{
				"an_annotation": pulumi.String("annotation_value"),
			},
			Properties: pulumi.StringMap{
				"spark.executor.instances": pulumi.String("2"),
			},
			ApplicationEnvironment: appEnv.Name,
			Version:                pulumi.String("1.2"),
			SparkApplicationConfig: &dataproc.GdcSparkApplicationSparkApplicationConfigArgs{
				MainJarFileUri: pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				JarFileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
				ArchiveUris: pulumi.StringArray{
					pulumi.String("file://usr/lib/spark/examples/spark-examples.jar"),
				},
				FileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var appEnv = new Gcp.Dataproc.GdcApplicationEnvironment("app_env", new()
    {
        ApplicationEnvironmentId = "tf-e2e-spark-app-env",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
    });

    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-spark-app",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        Labels = 
        {
            { "test-label", "label-value" },
        },
        Annotations = 
        {
            { "an_annotation", "annotation_value" },
        },
        Properties = 
        {
            { "spark.executor.instances", "2" },
        },
        ApplicationEnvironment = appEnv.Name,
        Version = "1.2",
        SparkApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkApplicationConfigArgs
        {
            MainJarFileUri = "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            JarFileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
            ArchiveUris = new[]
            {
                "file://usr/lib/spark/examples/spark-examples.jar",
            },
            FileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcApplicationEnvironment;
import com.pulumi.gcp.dataproc.GdcApplicationEnvironmentArgs;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkApplicationConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var appEnv = new GdcApplicationEnvironment("appEnv", GdcApplicationEnvironmentArgs.builder()
            .applicationEnvironmentId("tf-e2e-spark-app-env")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .build());

        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-spark-app")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .labels(Map.of("test-label", "label-value"))
            .annotations(Map.of("an_annotation", "annotation_value"))
            .properties(Map.of("spark.executor.instances", "2"))
            .applicationEnvironment(appEnv.name())
            .version("1.2")
            .sparkApplicationConfig(GdcSparkApplicationSparkApplicationConfigArgs.builder()
                .mainJarFileUri("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .jarFileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .archiveUris("file://usr/lib/spark/examples/spark-examples.jar")
                .fileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .build())
            .build());

    }
}

resources:
  appEnv:
    type: gcp:dataproc:GdcApplicationEnvironment
    name: app_env
    properties:
      applicationEnvironmentId: tf-e2e-spark-app-env
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-spark-app
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      labels:
        test-label: label-value
      annotations:
        an_annotation: annotation_value
      properties:
        spark.executor.instances: '2'
      applicationEnvironment: ${appEnv.name}
      version: '1.2'
      sparkApplicationConfig:
        mainJarFileUri: file:///usr/lib/spark/examples/jars/spark-examples.jar
        jarFileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar
        archiveUris:
          - file://usr/lib/spark/examples/spark-examples.jar
        fileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar

Dataprocgdc Sparkapplication Pyspark

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-pyspark-app",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    displayName: "A Pyspark application for a Terraform create test",
    dependencyImages: ["gcr.io/some/image"],
    pysparkApplicationConfig: {
        mainPythonFileUri: "gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py",
        jarFileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        pythonFileUris: ["gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py"],
        fileUris: ["file://usr/lib/spark/examples/spark-examples.jar"],
        archiveUris: ["file://usr/lib/spark/examples/spark-examples.jar"],
        args: ["10"],
    },
});

import pulumi
import pulumi_gcp as gcp

spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-pyspark-app",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    display_name="A Pyspark application for a Terraform create test",
    dependency_images=["gcr.io/some/image"],
    pyspark_application_config={
        "main_python_file_uri": "gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py",
        "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        "python_file_uris": ["gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py"],
        "file_uris": ["file://usr/lib/spark/examples/spark-examples.jar"],
        "archive_uris": ["file://usr/lib/spark/examples/spark-examples.jar"],
        "args": ["10"],
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-pyspark-app"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			DisplayName:        pulumi.String("A Pyspark application for a Terraform create test"),
			DependencyImages: pulumi.StringArray{
				pulumi.String("gcr.io/some/image"),
			},
			PysparkApplicationConfig: &dataproc.GdcSparkApplicationPysparkApplicationConfigArgs{
				MainPythonFileUri: pulumi.String("gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py"),
				JarFileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
				PythonFileUris: pulumi.StringArray{
					pulumi.String("gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py"),
				},
				FileUris: pulumi.StringArray{
					pulumi.String("file://usr/lib/spark/examples/spark-examples.jar"),
				},
				ArchiveUris: pulumi.StringArray{
					pulumi.String("file://usr/lib/spark/examples/spark-examples.jar"),
				},
				Args: pulumi.StringArray{
					pulumi.String("10"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-pyspark-app",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        DisplayName = "A Pyspark application for a Terraform create test",
        DependencyImages = new[]
        {
            "gcr.io/some/image",
        },
        PysparkApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationPysparkApplicationConfigArgs
        {
            MainPythonFileUri = "gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py",
            JarFileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
            PythonFileUris = new[]
            {
                "gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py",
            },
            FileUris = new[]
            {
                "file://usr/lib/spark/examples/spark-examples.jar",
            },
            ArchiveUris = new[]
            {
                "file://usr/lib/spark/examples/spark-examples.jar",
            },
            Args = new[]
            {
                "10",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationPysparkApplicationConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-pyspark-app")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .displayName("A Pyspark application for a Terraform create test")
            .dependencyImages("gcr.io/some/image")
            .pysparkApplicationConfig(GdcSparkApplicationPysparkApplicationConfigArgs.builder()
                .mainPythonFileUri("gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py")
                .jarFileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .pythonFileUris("gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py")
                .fileUris("file://usr/lib/spark/examples/spark-examples.jar")
                .archiveUris("file://usr/lib/spark/examples/spark-examples.jar")
                .args("10")
                .build())
            .build());

    }
}

resources:
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-pyspark-app
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      displayName: A Pyspark application for a Terraform create test
      dependencyImages:
        - gcr.io/some/image
      pysparkApplicationConfig:
        mainPythonFileUri: gs://goog-dataproc-initialization-actions-us-west2/conda/test_conda.py
        jarFileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar
        pythonFileUris:
          - gs://goog-dataproc-initialization-actions-us-west2/conda/get-sys-exec.py
        fileUris:
          - file://usr/lib/spark/examples/spark-examples.jar
        archiveUris:
          - file://usr/lib/spark/examples/spark-examples.jar
        args:
          - '10'

Dataprocgdc Sparkapplication Sparkr

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-sparkr-app",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    displayName: "A SparkR application for a Terraform create test",
    sparkRApplicationConfig: {
        mainRFileUri: "gs://some-bucket/something.R",
        fileUris: ["file://usr/lib/spark/examples/spark-examples.jar"],
        archiveUris: ["file://usr/lib/spark/examples/spark-examples.jar"],
        args: ["10"],
    },
});

import pulumi
import pulumi_gcp as gcp

spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-sparkr-app",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    display_name="A SparkR application for a Terraform create test",
    spark_r_application_config={
        "main_r_file_uri": "gs://some-bucket/something.R",
        "file_uris": ["file://usr/lib/spark/examples/spark-examples.jar"],
        "archive_uris": ["file://usr/lib/spark/examples/spark-examples.jar"],
        "args": ["10"],
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-sparkr-app"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			DisplayName:        pulumi.String("A SparkR application for a Terraform create test"),
			SparkRApplicationConfig: &dataproc.GdcSparkApplicationSparkRApplicationConfigArgs{
				MainRFileUri: pulumi.String("gs://some-bucket/something.R"),
				FileUris: pulumi.StringArray{
					pulumi.String("file://usr/lib/spark/examples/spark-examples.jar"),
				},
				ArchiveUris: pulumi.StringArray{
					pulumi.String("file://usr/lib/spark/examples/spark-examples.jar"),
				},
				Args: pulumi.StringArray{
					pulumi.String("10"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-sparkr-app",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        DisplayName = "A SparkR application for a Terraform create test",
        SparkRApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkRApplicationConfigArgs
        {
            MainRFileUri = "gs://some-bucket/something.R",
            FileUris = new[]
            {
                "file://usr/lib/spark/examples/spark-examples.jar",
            },
            ArchiveUris = new[]
            {
                "file://usr/lib/spark/examples/spark-examples.jar",
            },
            Args = new[]
            {
                "10",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkRApplicationConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-sparkr-app")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .displayName("A SparkR application for a Terraform create test")
            .sparkRApplicationConfig(GdcSparkApplicationSparkRApplicationConfigArgs.builder()
                .mainRFileUri("gs://some-bucket/something.R")
                .fileUris("file://usr/lib/spark/examples/spark-examples.jar")
                .archiveUris("file://usr/lib/spark/examples/spark-examples.jar")
                .args("10")
                .build())
            .build());

    }
}

resources:
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-sparkr-app
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      displayName: A SparkR application for a Terraform create test
      sparkRApplicationConfig:
        mainRFileUri: gs://some-bucket/something.R
        fileUris:
          - file://usr/lib/spark/examples/spark-examples.jar
        archiveUris:
          - file://usr/lib/spark/examples/spark-examples.jar
        args:
          - '10'

Dataprocgdc Sparkapplication Sparksql

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-sparksql-app",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    displayName: "A SparkSql application for a Terraform create test",
    sparkSqlApplicationConfig: {
        jarFileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        queryList: {
            queries: ["show tables;"],
        },
        scriptVariables: {
            MY_VAR: "1",
        },
    },
});

import pulumi
import pulumi_gcp as gcp

spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-sparksql-app",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    display_name="A SparkSql application for a Terraform create test",
    spark_sql_application_config={
        "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        "query_list": {
            "queries": ["show tables;"],
        },
        "script_variables": {
            "MY_VAR": "1",
        },
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-sparksql-app"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			DisplayName:        pulumi.String("A SparkSql application for a Terraform create test"),
			SparkSqlApplicationConfig: &dataproc.GdcSparkApplicationSparkSqlApplicationConfigArgs{
				JarFileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
				QueryList: &dataproc.GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs{
					Queries: pulumi.StringArray{
						pulumi.String("show tables;"),
					},
				},
				ScriptVariables: pulumi.StringMap{
					"MY_VAR": pulumi.String("1"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-sparksql-app",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        DisplayName = "A SparkSql application for a Terraform create test",
        SparkSqlApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkSqlApplicationConfigArgs
        {
            JarFileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
            QueryList = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs
            {
                Queries = new[]
                {
                    "show tables;",
                },
            },
            ScriptVariables = 
            {
                { "MY_VAR", "1" },
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkSqlApplicationConfigArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-sparksql-app")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .displayName("A SparkSql application for a Terraform create test")
            .sparkSqlApplicationConfig(GdcSparkApplicationSparkSqlApplicationConfigArgs.builder()
                .jarFileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .queryList(GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs.builder()
                    .queries("show tables;")
                    .build())
                .scriptVariables(Map.of("MY_VAR", "1"))
                .build())
            .build());

    }
}

resources:
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-sparksql-app
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      displayName: A SparkSql application for a Terraform create test
      sparkSqlApplicationConfig:
        jarFileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar
        queryList:
          queries:
            - show tables;
        scriptVariables:
          MY_VAR: '1'

Dataprocgdc Sparkapplication Sparksql Query File

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const spark_application = new gcp.dataproc.GdcSparkApplication("spark-application", {
    sparkApplicationId: "tf-e2e-sparksql-app",
    serviceinstance: "do-not-delete-dataproc-gdc-instance",
    project: "my-project",
    location: "us-west2",
    namespace: "default",
    displayName: "A SparkSql application for a Terraform create test",
    sparkSqlApplicationConfig: {
        jarFileUris: ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        queryFileUri: "gs://some-bucket/something.sql",
        scriptVariables: {
            MY_VAR: "1",
        },
    },
});

import pulumi
import pulumi_gcp as gcp

spark_application = gcp.dataproc.GdcSparkApplication("spark-application",
    spark_application_id="tf-e2e-sparksql-app",
    serviceinstance="do-not-delete-dataproc-gdc-instance",
    project="my-project",
    location="us-west2",
    namespace="default",
    display_name="A SparkSql application for a Terraform create test",
    spark_sql_application_config={
        "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
        "query_file_uri": "gs://some-bucket/something.sql",
        "script_variables": {
            "MY_VAR": "1",
        },
    })

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := dataproc.NewGdcSparkApplication(ctx, "spark-application", &dataproc.GdcSparkApplicationArgs{
			SparkApplicationId: pulumi.String("tf-e2e-sparksql-app"),
			Serviceinstance:    pulumi.String("do-not-delete-dataproc-gdc-instance"),
			Project:            pulumi.String("my-project"),
			Location:           pulumi.String("us-west2"),
			Namespace:          pulumi.String("default"),
			DisplayName:        pulumi.String("A SparkSql application for a Terraform create test"),
			SparkSqlApplicationConfig: &dataproc.GdcSparkApplicationSparkSqlApplicationConfigArgs{
				JarFileUris: pulumi.StringArray{
					pulumi.String("file:///usr/lib/spark/examples/jars/spark-examples.jar"),
				},
				QueryFileUri: pulumi.String("gs://some-bucket/something.sql"),
				ScriptVariables: pulumi.StringMap{
					"MY_VAR": pulumi.String("1"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var spark_application = new Gcp.Dataproc.GdcSparkApplication("spark-application", new()
    {
        SparkApplicationId = "tf-e2e-sparksql-app",
        Serviceinstance = "do-not-delete-dataproc-gdc-instance",
        Project = "my-project",
        Location = "us-west2",
        Namespace = "default",
        DisplayName = "A SparkSql application for a Terraform create test",
        SparkSqlApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkSqlApplicationConfigArgs
        {
            JarFileUris = new[]
            {
                "file:///usr/lib/spark/examples/jars/spark-examples.jar",
            },
            QueryFileUri = "gs://some-bucket/something.sql",
            ScriptVariables = 
            {
                { "MY_VAR", "1" },
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.GdcSparkApplication;
import com.pulumi.gcp.dataproc.GdcSparkApplicationArgs;
import com.pulumi.gcp.dataproc.inputs.GdcSparkApplicationSparkSqlApplicationConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var spark_application = new GdcSparkApplication("spark-application", GdcSparkApplicationArgs.builder()
            .sparkApplicationId("tf-e2e-sparksql-app")
            .serviceinstance("do-not-delete-dataproc-gdc-instance")
            .project("my-project")
            .location("us-west2")
            .namespace("default")
            .displayName("A SparkSql application for a Terraform create test")
            .sparkSqlApplicationConfig(GdcSparkApplicationSparkSqlApplicationConfigArgs.builder()
                .jarFileUris("file:///usr/lib/spark/examples/jars/spark-examples.jar")
                .queryFileUri("gs://some-bucket/something.sql")
                .scriptVariables(Map.of("MY_VAR", "1"))
                .build())
            .build());

    }
}

resources:
  spark-application:
    type: gcp:dataproc:GdcSparkApplication
    properties:
      sparkApplicationId: tf-e2e-sparksql-app
      serviceinstance: do-not-delete-dataproc-gdc-instance
      project: my-project
      location: us-west2
      namespace: default
      displayName: A SparkSql application for a Terraform create test
      sparkSqlApplicationConfig:
        jarFileUris:
          - file:///usr/lib/spark/examples/jars/spark-examples.jar
        queryFileUri: gs://some-bucket/something.sql
        scriptVariables:
          MY_VAR: '1'

Create GdcSparkApplication Resource

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

Constructor syntax

new GdcSparkApplication(name: string, args: GdcSparkApplicationArgs, opts?: CustomResourceOptions);

@overload
def GdcSparkApplication(resource_name: str,
                        args: GdcSparkApplicationArgs,
                        opts: Optional[ResourceOptions] = None)

@overload
def GdcSparkApplication(resource_name: str,
                        opts: Optional[ResourceOptions] = None,
                        location: Optional[str] = None,
                        spark_application_id: Optional[str] = None,
                        serviceinstance: Optional[str] = None,
                        labels: Optional[Mapping[str, str]] = None,
                        annotations: Optional[Mapping[str, str]] = None,
                        display_name: Optional[str] = None,
                        namespace: Optional[str] = None,
                        project: Optional[str] = None,
                        properties: Optional[Mapping[str, str]] = None,
                        pyspark_application_config: Optional[GdcSparkApplicationPysparkApplicationConfigArgs] = None,
                        dependency_images: Optional[Sequence[str]] = None,
                        spark_application_config: Optional[GdcSparkApplicationSparkApplicationConfigArgs] = None,
                        application_environment: Optional[str] = None,
                        spark_r_application_config: Optional[GdcSparkApplicationSparkRApplicationConfigArgs] = None,
                        spark_sql_application_config: Optional[GdcSparkApplicationSparkSqlApplicationConfigArgs] = None,
                        version: Optional[str] = None)

func NewGdcSparkApplication(ctx *Context, name string, args GdcSparkApplicationArgs, opts ...ResourceOption) (*GdcSparkApplication, error)

public GdcSparkApplication(string name, GdcSparkApplicationArgs args, CustomResourceOptions? opts = null)

public GdcSparkApplication(String name, GdcSparkApplicationArgs args)
public GdcSparkApplication(String name, GdcSparkApplicationArgs args, CustomResourceOptions options)

type: gcp:dataproc:GdcSparkApplication
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 GdcSparkApplicationArgs: 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 GdcSparkApplicationArgs: 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 GdcSparkApplicationArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

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

name String: The unique name of the resource.
args GdcSparkApplicationArgs: 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 gdcSparkApplicationResource = new Gcp.Dataproc.GdcSparkApplication("gdcSparkApplicationResource", new()
{
    Location = "string",
    SparkApplicationId = "string",
    Serviceinstance = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Annotations = 
    {
        { "string", "string" },
    },
    DisplayName = "string",
    Namespace = "string",
    Project = "string",
    Properties = 
    {
        { "string", "string" },
    },
    PysparkApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationPysparkApplicationConfigArgs
    {
        MainPythonFileUri = "string",
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
        JarFileUris = new[]
        {
            "string",
        },
        PythonFileUris = new[]
        {
            "string",
        },
    },
    DependencyImages = new[]
    {
        "string",
    },
    SparkApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkApplicationConfigArgs
    {
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
        JarFileUris = new[]
        {
            "string",
        },
        MainClass = "string",
        MainJarFileUri = "string",
    },
    ApplicationEnvironment = "string",
    SparkRApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkRApplicationConfigArgs
    {
        MainRFileUri = "string",
        ArchiveUris = new[]
        {
            "string",
        },
        Args = new[]
        {
            "string",
        },
        FileUris = new[]
        {
            "string",
        },
    },
    SparkSqlApplicationConfig = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkSqlApplicationConfigArgs
    {
        JarFileUris = new[]
        {
            "string",
        },
        QueryFileUri = "string",
        QueryList = new Gcp.Dataproc.Inputs.GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs
        {
            Queries = new[]
            {
                "string",
            },
        },
        ScriptVariables = 
        {
            { "string", "string" },
        },
    },
    Version = "string",
});

example, err := dataproc.NewGdcSparkApplication(ctx, "gdcSparkApplicationResource", &dataproc.GdcSparkApplicationArgs{
	Location:           pulumi.String("string"),
	SparkApplicationId: pulumi.String("string"),
	Serviceinstance:    pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Annotations: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	DisplayName: pulumi.String("string"),
	Namespace:   pulumi.String("string"),
	Project:     pulumi.String("string"),
	Properties: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	PysparkApplicationConfig: &dataproc.GdcSparkApplicationPysparkApplicationConfigArgs{
		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"),
		},
	},
	DependencyImages: pulumi.StringArray{
		pulumi.String("string"),
	},
	SparkApplicationConfig: &dataproc.GdcSparkApplicationSparkApplicationConfigArgs{
		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"),
	},
	ApplicationEnvironment: pulumi.String("string"),
	SparkRApplicationConfig: &dataproc.GdcSparkApplicationSparkRApplicationConfigArgs{
		MainRFileUri: pulumi.String("string"),
		ArchiveUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		Args: pulumi.StringArray{
			pulumi.String("string"),
		},
		FileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
	SparkSqlApplicationConfig: &dataproc.GdcSparkApplicationSparkSqlApplicationConfigArgs{
		JarFileUris: pulumi.StringArray{
			pulumi.String("string"),
		},
		QueryFileUri: pulumi.String("string"),
		QueryList: &dataproc.GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs{
			Queries: pulumi.StringArray{
				pulumi.String("string"),
			},
		},
		ScriptVariables: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
	},
	Version: pulumi.String("string"),
})

var gdcSparkApplicationResource = new GdcSparkApplication("gdcSparkApplicationResource", GdcSparkApplicationArgs.builder()
    .location("string")
    .sparkApplicationId("string")
    .serviceinstance("string")
    .labels(Map.of("string", "string"))
    .annotations(Map.of("string", "string"))
    .displayName("string")
    .namespace("string")
    .project("string")
    .properties(Map.of("string", "string"))
    .pysparkApplicationConfig(GdcSparkApplicationPysparkApplicationConfigArgs.builder()
        .mainPythonFileUri("string")
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .jarFileUris("string")
        .pythonFileUris("string")
        .build())
    .dependencyImages("string")
    .sparkApplicationConfig(GdcSparkApplicationSparkApplicationConfigArgs.builder()
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .jarFileUris("string")
        .mainClass("string")
        .mainJarFileUri("string")
        .build())
    .applicationEnvironment("string")
    .sparkRApplicationConfig(GdcSparkApplicationSparkRApplicationConfigArgs.builder()
        .mainRFileUri("string")
        .archiveUris("string")
        .args("string")
        .fileUris("string")
        .build())
    .sparkSqlApplicationConfig(GdcSparkApplicationSparkSqlApplicationConfigArgs.builder()
        .jarFileUris("string")
        .queryFileUri("string")
        .queryList(GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs.builder()
            .queries("string")
            .build())
        .scriptVariables(Map.of("string", "string"))
        .build())
    .version("string")
    .build());

gdc_spark_application_resource = gcp.dataproc.GdcSparkApplication("gdcSparkApplicationResource",
    location="string",
    spark_application_id="string",
    serviceinstance="string",
    labels={
        "string": "string",
    },
    annotations={
        "string": "string",
    },
    display_name="string",
    namespace="string",
    project="string",
    properties={
        "string": "string",
    },
    pyspark_application_config={
        "main_python_file_uri": "string",
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
        "jar_file_uris": ["string"],
        "python_file_uris": ["string"],
    },
    dependency_images=["string"],
    spark_application_config={
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
        "jar_file_uris": ["string"],
        "main_class": "string",
        "main_jar_file_uri": "string",
    },
    application_environment="string",
    spark_r_application_config={
        "main_r_file_uri": "string",
        "archive_uris": ["string"],
        "args": ["string"],
        "file_uris": ["string"],
    },
    spark_sql_application_config={
        "jar_file_uris": ["string"],
        "query_file_uri": "string",
        "query_list": {
            "queries": ["string"],
        },
        "script_variables": {
            "string": "string",
        },
    },
    version="string")

const gdcSparkApplicationResource = new gcp.dataproc.GdcSparkApplication("gdcSparkApplicationResource", {
    location: "string",
    sparkApplicationId: "string",
    serviceinstance: "string",
    labels: {
        string: "string",
    },
    annotations: {
        string: "string",
    },
    displayName: "string",
    namespace: "string",
    project: "string",
    properties: {
        string: "string",
    },
    pysparkApplicationConfig: {
        mainPythonFileUri: "string",
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
        jarFileUris: ["string"],
        pythonFileUris: ["string"],
    },
    dependencyImages: ["string"],
    sparkApplicationConfig: {
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
        jarFileUris: ["string"],
        mainClass: "string",
        mainJarFileUri: "string",
    },
    applicationEnvironment: "string",
    sparkRApplicationConfig: {
        mainRFileUri: "string",
        archiveUris: ["string"],
        args: ["string"],
        fileUris: ["string"],
    },
    sparkSqlApplicationConfig: {
        jarFileUris: ["string"],
        queryFileUri: "string",
        queryList: {
            queries: ["string"],
        },
        scriptVariables: {
            string: "string",
        },
    },
    version: "string",
});

type: gcp:dataproc:GdcSparkApplication
properties:
    annotations:
        string: string
    applicationEnvironment: string
    dependencyImages:
        - string
    displayName: string
    labels:
        string: string
    location: string
    namespace: string
    project: string
    properties:
        string: string
    pysparkApplicationConfig:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        jarFileUris:
            - string
        mainPythonFileUri: string
        pythonFileUris:
            - string
    serviceinstance: string
    sparkApplicationConfig:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        jarFileUris:
            - string
        mainClass: string
        mainJarFileUri: string
    sparkApplicationId: string
    sparkRApplicationConfig:
        archiveUris:
            - string
        args:
            - string
        fileUris:
            - string
        mainRFileUri: string
    sparkSqlApplicationConfig:
        jarFileUris:
            - string
        queryFileUri: string
        queryList:
            queries:
                - string
        scriptVariables:
            string: string
    version: string

GdcSparkApplication 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 GdcSparkApplication resource accepts the following input properties:

Location string: The location of the spark application.
Serviceinstance string: The id of the service instance to which this spark application belongs.
SparkApplicationId string: The id of the application
Annotations Dictionary<string, string>: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
ApplicationEnvironment string: An ApplicationEnvironment from which to inherit configuration properties.
DependencyImages List<string>: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
DisplayName string: User-provided human-readable name to be used in user interfaces.
Labels Dictionary<string, string>: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
Namespace string: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
Project string: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
Properties Dictionary<string, string>: application-specific properties.
PysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig: Represents the PySparkApplicationConfig. Structure is documented below.
SparkApplicationConfig GdcSparkApplicationSparkApplicationConfig: Represents the SparkApplicationConfig. Structure is documented below.
SparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
SparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
Version string: The Dataproc version of this application.

Location string: The location of the spark application.
Serviceinstance string: The id of the service instance to which this spark application belongs.
SparkApplicationId string: The id of the application
Annotations map[string]string: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
ApplicationEnvironment string: An ApplicationEnvironment from which to inherit configuration properties.
DependencyImages []string: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
DisplayName string: User-provided human-readable name to be used in user interfaces.
Labels map[string]string: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
Namespace string: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
Project string: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
Properties map[string]string: application-specific properties.
PysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfigArgs: Represents the PySparkApplicationConfig. Structure is documented below.
SparkApplicationConfig GdcSparkApplicationSparkApplicationConfigArgs: Represents the SparkApplicationConfig. Structure is documented below.
SparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfigArgs: Represents the SparkRApplicationConfig. Structure is documented below.
SparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfigArgs: Represents the SparkRApplicationConfig. Structure is documented below.
Version string: The Dataproc version of this application.

location String: The location of the spark application.
serviceinstance String: The id of the service instance to which this spark application belongs.
sparkApplicationId String: The id of the application
annotations Map<String,String>: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
applicationEnvironment String: An ApplicationEnvironment from which to inherit configuration properties.
dependencyImages List<String>: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
displayName String: User-provided human-readable name to be used in user interfaces.
labels Map<String,String>: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
namespace String: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
project String: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
properties Map<String,String>: application-specific properties.
pysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig: Represents the PySparkApplicationConfig. Structure is documented below.
sparkApplicationConfig GdcSparkApplicationSparkApplicationConfig: Represents the SparkApplicationConfig. Structure is documented below.
sparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
sparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
version String: The Dataproc version of this application.

location string: The location of the spark application.
serviceinstance string: The id of the service instance to which this spark application belongs.
sparkApplicationId string: The id of the application
annotations {[key: string]: string}: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
applicationEnvironment string: An ApplicationEnvironment from which to inherit configuration properties.
dependencyImages string[]: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
displayName string: User-provided human-readable name to be used in user interfaces.
labels {[key: string]: string}: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
namespace string: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
project string: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
properties {[key: string]: string}: application-specific properties.
pysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig: Represents the PySparkApplicationConfig. Structure is documented below.
sparkApplicationConfig GdcSparkApplicationSparkApplicationConfig: Represents the SparkApplicationConfig. Structure is documented below.
sparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
sparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig: Represents the SparkRApplicationConfig. Structure is documented below.
version string: The Dataproc version of this application.

location str: The location of the spark application.
serviceinstance str: The id of the service instance to which this spark application belongs.
spark_application_id str: The id of the application
annotations Mapping[str, str]: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
application_environment str: An ApplicationEnvironment from which to inherit configuration properties.
dependency_images Sequence[str]: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
display_name str: User-provided human-readable name to be used in user interfaces.
labels Mapping[str, str]: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
namespace str: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
project str: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
properties Mapping[str, str]: application-specific properties.
pyspark_application_config GdcSparkApplicationPysparkApplicationConfigArgs: Represents the PySparkApplicationConfig. Structure is documented below.
spark_application_config GdcSparkApplicationSparkApplicationConfigArgs: Represents the SparkApplicationConfig. Structure is documented below.
spark_r_application_config GdcSparkApplicationSparkRApplicationConfigArgs: Represents the SparkRApplicationConfig. Structure is documented below.
spark_sql_application_config GdcSparkApplicationSparkSqlApplicationConfigArgs: Represents the SparkRApplicationConfig. Structure is documented below.
version str: The Dataproc version of this application.

location String: The location of the spark application.
serviceinstance String: The id of the service instance to which this spark application belongs.
sparkApplicationId String: The id of the application
annotations Map<String>: The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.
applicationEnvironment String: An ApplicationEnvironment from which to inherit configuration properties.
dependencyImages List<String>: List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.
displayName String: User-provided human-readable name to be used in user interfaces.
labels Map<String>: The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
namespace String: The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.
project String: The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
properties Map<String>: application-specific properties.
pysparkApplicationConfig Property Map: Represents the PySparkApplicationConfig. Structure is documented below.
sparkApplicationConfig Property Map: Represents the SparkApplicationConfig. Structure is documented below.
sparkRApplicationConfig Property Map: Represents the SparkRApplicationConfig. Structure is documented below.
sparkSqlApplicationConfig Property Map: Represents the SparkRApplicationConfig. Structure is documented below.
version String: The Dataproc version of this application.

Outputs

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

CreateTime string

The timestamp when the resource was created.

EffectiveAnnotations Dictionary<string, string>

EffectiveLabels Dictionary<string, string>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

Id string

The provider-assigned unique ID for this managed resource.

MonitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

Name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

OutputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

PulumiLabels Dictionary<string, string>

The combination of labels configured directly on the resource and default labels configured on the provider.

Reconciling bool

Whether the application is currently reconciling. True if the current state of the resource does not match the intended state, and the system is working to reconcile them, whether or not the change was user initiated.

State string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

StateMessage string

A message explaining the current state.

Uid string

System generated unique identifier for this application, formatted as UUID4.

UpdateTime string

The timestamp when the resource was most recently updated.

CreateTime string

The timestamp when the resource was created.

EffectiveAnnotations map[string]string

EffectiveLabels map[string]string

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

Id string

The provider-assigned unique ID for this managed resource.

MonitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

Name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

OutputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

PulumiLabels map[string]string

The combination of labels configured directly on the resource and default labels configured on the provider.

Reconciling bool

State string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

StateMessage string

A message explaining the current state.

Uid string

System generated unique identifier for this application, formatted as UUID4.

UpdateTime string

The timestamp when the resource was most recently updated.

createTime String

The timestamp when the resource was created.

effectiveAnnotations Map<String,String>

effectiveLabels Map<String,String>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

id String

The provider-assigned unique ID for this managed resource.

monitoringEndpoint String

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name String

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

outputUri String

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

pulumiLabels Map<String,String>

The combination of labels configured directly on the resource and default labels configured on the provider.

reconciling Boolean

state String

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage String

A message explaining the current state.

uid String

System generated unique identifier for this application, formatted as UUID4.

updateTime String

The timestamp when the resource was most recently updated.

createTime string

The timestamp when the resource was created.

effectiveAnnotations {[key: string]: string}

effectiveLabels {[key: string]: string}

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

id string

The provider-assigned unique ID for this managed resource.

monitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

outputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

pulumiLabels {[key: string]: string}

The combination of labels configured directly on the resource and default labels configured on the provider.

reconciling boolean

state string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage string

A message explaining the current state.

uid string

System generated unique identifier for this application, formatted as UUID4.

updateTime string

The timestamp when the resource was most recently updated.

create_time str

The timestamp when the resource was created.

effective_annotations Mapping[str, str]

effective_labels Mapping[str, str]

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

id str

The provider-assigned unique ID for this managed resource.

monitoring_endpoint str

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name str

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

output_uri str

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

pulumi_labels Mapping[str, str]

The combination of labels configured directly on the resource and default labels configured on the provider.

reconciling bool

state str

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

state_message str

A message explaining the current state.

uid str

System generated unique identifier for this application, formatted as UUID4.

update_time str

The timestamp when the resource was most recently updated.

createTime String

The timestamp when the resource was created.

effectiveAnnotations Map<String>

effectiveLabels Map<String>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

id String

The provider-assigned unique ID for this managed resource.

monitoringEndpoint String

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name String

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

outputUri String

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

pulumiLabels Map<String>

The combination of labels configured directly on the resource and default labels configured on the provider.

reconciling Boolean

state String

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage String

A message explaining the current state.

uid String

System generated unique identifier for this application, formatted as UUID4.

updateTime String

The timestamp when the resource was most recently updated.

Look up Existing GdcSparkApplication Resource

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

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

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        annotations: Optional[Mapping[str, str]] = None,
        application_environment: Optional[str] = None,
        create_time: Optional[str] = None,
        dependency_images: Optional[Sequence[str]] = None,
        display_name: Optional[str] = None,
        effective_annotations: Optional[Mapping[str, str]] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        labels: Optional[Mapping[str, str]] = None,
        location: Optional[str] = None,
        monitoring_endpoint: Optional[str] = None,
        name: Optional[str] = None,
        namespace: Optional[str] = None,
        output_uri: Optional[str] = None,
        project: Optional[str] = None,
        properties: Optional[Mapping[str, str]] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        pyspark_application_config: Optional[GdcSparkApplicationPysparkApplicationConfigArgs] = None,
        reconciling: Optional[bool] = None,
        serviceinstance: Optional[str] = None,
        spark_application_config: Optional[GdcSparkApplicationSparkApplicationConfigArgs] = None,
        spark_application_id: Optional[str] = None,
        spark_r_application_config: Optional[GdcSparkApplicationSparkRApplicationConfigArgs] = None,
        spark_sql_application_config: Optional[GdcSparkApplicationSparkSqlApplicationConfigArgs] = None,
        state: Optional[str] = None,
        state_message: Optional[str] = None,
        uid: Optional[str] = None,
        update_time: Optional[str] = None,
        version: Optional[str] = None) -> GdcSparkApplication

func GetGdcSparkApplication(ctx *Context, name string, id IDInput, state *GdcSparkApplicationState, opts ...ResourceOption) (*GdcSparkApplication, error)

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

public static GdcSparkApplication get(String name, Output<String> id, GdcSparkApplicationState state, CustomResourceOptions options)

resources:  _:    type: gcp:dataproc:GdcSparkApplication    get:      id: ${id}

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

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

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

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

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

The following state arguments are supported:

Annotations Dictionary<string, string>

The annotations to associate with this application. Annotations may be used to store client information, but are not used by the server. Note: This field is non-authoritative, and will only manage the annotations present in your configuration. Please refer to the field effective_annotations for all of the annotations present on the resource.

ApplicationEnvironment string

An ApplicationEnvironment from which to inherit configuration properties.

CreateTime string

The timestamp when the resource was created.

DependencyImages List<string>

List of container image uris for additional file dependencies. Dependent files are sequentially copied from each image. If a file with the same name exists in 2 images then the file from later image is used.

DisplayName string

User-provided human-readable name to be used in user interfaces.

EffectiveAnnotations Dictionary<string, string>

EffectiveLabels Dictionary<string, string>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

Labels Dictionary<string, string>

The labels to associate with this application. Labels may be used for filtering and billing tracking. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.

Location string

The location of the spark application.

MonitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

Name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

Namespace string

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

OutputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

Project string

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

Properties Dictionary<string, string>

application-specific properties.

PulumiLabels Dictionary<string, string>

The combination of labels configured directly on the resource and default labels configured on the provider.

PysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig

Represents the PySparkApplicationConfig. Structure is documented below.

Reconciling bool

Serviceinstance string

The id of the service instance to which this spark application belongs.

SparkApplicationConfig GdcSparkApplicationSparkApplicationConfig

Represents the SparkApplicationConfig. Structure is documented below.

SparkApplicationId string

The id of the application

SparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

SparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

State string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

StateMessage string

A message explaining the current state.

Uid string

System generated unique identifier for this application, formatted as UUID4.

UpdateTime string

The timestamp when the resource was most recently updated.

Version string

The Dataproc version of this application.

Annotations map[string]string

ApplicationEnvironment string

An ApplicationEnvironment from which to inherit configuration properties.

CreateTime string

The timestamp when the resource was created.

DependencyImages []string

DisplayName string

User-provided human-readable name to be used in user interfaces.

EffectiveAnnotations map[string]string

EffectiveLabels map[string]string

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

Labels map[string]string

Location string

The location of the spark application.

MonitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

Name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

Namespace string

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

OutputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

Project string

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

Properties map[string]string

application-specific properties.

PulumiLabels map[string]string

The combination of labels configured directly on the resource and default labels configured on the provider.

PysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfigArgs

Represents the PySparkApplicationConfig. Structure is documented below.

Reconciling bool

Serviceinstance string

The id of the service instance to which this spark application belongs.

SparkApplicationConfig GdcSparkApplicationSparkApplicationConfigArgs

Represents the SparkApplicationConfig. Structure is documented below.

SparkApplicationId string

The id of the application

SparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfigArgs

Represents the SparkRApplicationConfig. Structure is documented below.

SparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfigArgs

Represents the SparkRApplicationConfig. Structure is documented below.

State string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

StateMessage string

A message explaining the current state.

Uid string

System generated unique identifier for this application, formatted as UUID4.

UpdateTime string

The timestamp when the resource was most recently updated.

Version string

The Dataproc version of this application.

annotations Map<String,String>

applicationEnvironment String

An ApplicationEnvironment from which to inherit configuration properties.

createTime String

The timestamp when the resource was created.

dependencyImages List<String>

displayName String

User-provided human-readable name to be used in user interfaces.

effectiveAnnotations Map<String,String>

effectiveLabels Map<String,String>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

labels Map<String,String>

location String

The location of the spark application.

monitoringEndpoint String

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name String

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

namespace String

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

outputUri String

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

project String

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

properties Map<String,String>

application-specific properties.

pulumiLabels Map<String,String>

The combination of labels configured directly on the resource and default labels configured on the provider.

pysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig

Represents the PySparkApplicationConfig. Structure is documented below.

reconciling Boolean

serviceinstance String

The id of the service instance to which this spark application belongs.

sparkApplicationConfig GdcSparkApplicationSparkApplicationConfig

Represents the SparkApplicationConfig. Structure is documented below.

sparkApplicationId String

The id of the application

sparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

sparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

state String

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage String

A message explaining the current state.

uid String

System generated unique identifier for this application, formatted as UUID4.

updateTime String

The timestamp when the resource was most recently updated.

version String

The Dataproc version of this application.

annotations {[key: string]: string}

applicationEnvironment string

An ApplicationEnvironment from which to inherit configuration properties.

createTime string

The timestamp when the resource was created.

dependencyImages string[]

displayName string

User-provided human-readable name to be used in user interfaces.

effectiveAnnotations {[key: string]: string}

effectiveLabels {[key: string]: string}

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

labels {[key: string]: string}

location string

The location of the spark application.

monitoringEndpoint string

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name string

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

namespace string

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

outputUri string

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

project string

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

properties {[key: string]: string}

application-specific properties.

pulumiLabels {[key: string]: string}

The combination of labels configured directly on the resource and default labels configured on the provider.

pysparkApplicationConfig GdcSparkApplicationPysparkApplicationConfig

Represents the PySparkApplicationConfig. Structure is documented below.

reconciling boolean

serviceinstance string

The id of the service instance to which this spark application belongs.

sparkApplicationConfig GdcSparkApplicationSparkApplicationConfig

Represents the SparkApplicationConfig. Structure is documented below.

sparkApplicationId string

The id of the application

sparkRApplicationConfig GdcSparkApplicationSparkRApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

sparkSqlApplicationConfig GdcSparkApplicationSparkSqlApplicationConfig

Represents the SparkRApplicationConfig. Structure is documented below.

state string

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage string

A message explaining the current state.

uid string

System generated unique identifier for this application, formatted as UUID4.

updateTime string

The timestamp when the resource was most recently updated.

version string

The Dataproc version of this application.

annotations Mapping[str, str]

application_environment str

An ApplicationEnvironment from which to inherit configuration properties.

create_time str

The timestamp when the resource was created.

dependency_images Sequence[str]

display_name str

User-provided human-readable name to be used in user interfaces.

effective_annotations Mapping[str, str]

effective_labels Mapping[str, str]

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

labels Mapping[str, str]

location str

The location of the spark application.

monitoring_endpoint str

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name str

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

namespace str

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

output_uri str

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

project str

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

properties Mapping[str, str]

application-specific properties.

pulumi_labels Mapping[str, str]

The combination of labels configured directly on the resource and default labels configured on the provider.

pyspark_application_config GdcSparkApplicationPysparkApplicationConfigArgs

Represents the PySparkApplicationConfig. Structure is documented below.

reconciling bool

serviceinstance str

The id of the service instance to which this spark application belongs.

spark_application_config GdcSparkApplicationSparkApplicationConfigArgs

Represents the SparkApplicationConfig. Structure is documented below.

spark_application_id str

The id of the application

spark_r_application_config GdcSparkApplicationSparkRApplicationConfigArgs

Represents the SparkRApplicationConfig. Structure is documented below.

spark_sql_application_config GdcSparkApplicationSparkSqlApplicationConfigArgs

Represents the SparkRApplicationConfig. Structure is documented below.

state str

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

state_message str

A message explaining the current state.

uid str

System generated unique identifier for this application, formatted as UUID4.

update_time str

The timestamp when the resource was most recently updated.

version str

The Dataproc version of this application.

annotations Map<String>

applicationEnvironment String

An ApplicationEnvironment from which to inherit configuration properties.

createTime String

The timestamp when the resource was created.

dependencyImages List<String>

displayName String

User-provided human-readable name to be used in user interfaces.

effectiveAnnotations Map<String>

effectiveLabels Map<String>

All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.

labels Map<String>

location String

The location of the spark application.

monitoringEndpoint String

URL for a monitoring UI for this application (for eventual Spark PHS/UI support) Out of scope for private GA

name String

Identifier. The name of the application. Format: projects/{project}/locations/{location}/serviceInstances/{service_instance}/sparkApplications/{application}

namespace String

The Kubernetes namespace in which to create the application. This namespace must already exist on the cluster.

outputUri String

An HCFS URI pointing to the location of stdout and stdout of the application Mainly useful for Pantheon and gcloud Not in scope for private GA

project String

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

properties Map<String>

application-specific properties.

pulumiLabels Map<String>

The combination of labels configured directly on the resource and default labels configured on the provider.

pysparkApplicationConfig Property Map

Represents the PySparkApplicationConfig. Structure is documented below.

reconciling Boolean

serviceinstance String

The id of the service instance to which this spark application belongs.

sparkApplicationConfig Property Map

Represents the SparkApplicationConfig. Structure is documented below.

sparkApplicationId String

The id of the application

sparkRApplicationConfig Property Map

Represents the SparkRApplicationConfig. Structure is documented below.

sparkSqlApplicationConfig Property Map

Represents the SparkRApplicationConfig. Structure is documented below.

state String

The current state. Possible values:

STATE_UNSPECIFIED
PENDING
RUNNING
CANCELLING
CANCELLED
SUCCEEDED
FAILED

stateMessage String

A message explaining the current state.

uid String

System generated unique identifier for this application, formatted as UUID4.

updateTime String

The timestamp when the resource was most recently updated.

version String

The Dataproc version of this application.

Supporting Types

GdcSparkApplicationPysparkApplicationConfig, GdcSparkApplicationPysparkApplicationConfigArgs

MainPythonFileUri string: The HCFS URI of the main Python file to use as the driver. Must be a .py file.
ArchiveUris List<string>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
FileUris List<string>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
JarFileUris List<string>: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
PythonFileUris List<string>: 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 driver. Must be a .py file.
ArchiveUris []string: 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: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
FileUris []string: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
JarFileUris []string: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
PythonFileUris []string: 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 driver. Must be a .py file.
archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
jarFileUris List<String>: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
pythonFileUris List<String>: 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 driver. Must be a .py file.
archiveUris string[]: 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[]: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris string[]: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
jarFileUris string[]: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
pythonFileUris string[]: 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 driver. Must be a .py file.
archive_uris Sequence[str]: 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]: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
file_uris Sequence[str]: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
jar_file_uris Sequence[str]: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
python_file_uris Sequence[str]: 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 driver. Must be a .py file.
archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.
jarFileUris List<String>: HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.
pythonFileUris List<String>: HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.

GdcSparkApplicationSparkApplicationConfig, GdcSparkApplicationSparkApplicationConfigArgs

ArchiveUris List<string>: 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>: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
FileUris List<string>: HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris List<string>: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: 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: The HCFS URI of the jar file that contains the main class.

ArchiveUris []string: 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: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
FileUris []string: HCFS URIs of files to be placed in the working directory of each executor.
JarFileUris []string: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
MainClass string: 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: The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: 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: The HCFS URI of the jar file that contains the main class.

archiveUris string[]: 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[]: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
fileUris string[]: HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris string[]: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass string: 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: The HCFS URI of the jar file that contains the main class.

archive_uris Sequence[str]: 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]: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
file_uris Sequence[str]: HCFS URIs of files to be placed in the working directory of each executor.
jar_file_uris Sequence[str]: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
main_class str: 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: The HCFS URI of the jar file that contains the main class.

archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments that can be set as application properties, such as --conf, since a collision can occur that causes an incorrect application submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor.
jarFileUris List<String>: HCFS URIs of jar files to add to the classpath of the Spark driver and tasks.
mainClass String: 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: The HCFS URI of the jar file that contains the main class.

GdcSparkApplicationSparkRApplicationConfig, GdcSparkApplicationSparkRApplicationConfigArgs

MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R file.
ArchiveUris List<string>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
FileUris List<string>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

MainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R file.
ArchiveUris []string: 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: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
FileUris []string: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R file.
archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

mainRFileUri string: The HCFS URI of the main R file to use as the driver. Must be a .R file.
archiveUris string[]: 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[]: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris string[]: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

main_r_file_uri str: The HCFS URI of the main R file to use as the driver. Must be a .R file.
archive_uris Sequence[str]: 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]: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
file_uris Sequence[str]: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

mainRFileUri String: The HCFS URI of the main R file to use as the driver. Must be a .R file.
archiveUris List<String>: 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>: The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.
fileUris List<String>: HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

GdcSparkApplicationSparkSqlApplicationConfig, GdcSparkApplicationSparkSqlApplicationConfigArgs

JarFileUris List<string>: HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryFileUri string: The HCFS URI of the script that contains SQL queries.
QueryList GdcSparkApplicationSparkSqlApplicationConfigQueryList: Represents a list of queries. Structure is documented below.
ScriptVariables Dictionary<string, string>: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

JarFileUris []string: HCFS URIs of jar files to be added to the Spark CLASSPATH.
QueryFileUri string: The HCFS URI of the script that contains SQL queries.
QueryList GdcSparkApplicationSparkSqlApplicationConfigQueryList: Represents a list of queries. Structure is documented below.
ScriptVariables map[string]string: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris List<String>: HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri String: The HCFS URI of the script that contains SQL queries.
queryList GdcSparkApplicationSparkSqlApplicationConfigQueryList: Represents a list of queries. Structure is documented below.
scriptVariables Map<String,String>: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris string[]: HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri string: The HCFS URI of the script that contains SQL queries.
queryList GdcSparkApplicationSparkSqlApplicationConfigQueryList: Represents a list of queries. Structure is documented below.
scriptVariables {[key: string]: string}: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jar_file_uris Sequence[str]: HCFS URIs of jar files to be added to the Spark CLASSPATH.
query_file_uri str: The HCFS URI of the script that contains SQL queries.
query_list GdcSparkApplicationSparkSqlApplicationConfigQueryList: Represents a list of queries. Structure is documented below.
script_variables Mapping[str, str]: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

jarFileUris List<String>: HCFS URIs of jar files to be added to the Spark CLASSPATH.
queryFileUri String: The HCFS URI of the script that contains SQL queries.
queryList Property Map: Represents a list of queries. Structure is documented below.
scriptVariables Map<String>: Mapping of query variable names to values (equivalent to the Spark SQL command: SET name="value";).

GdcSparkApplicationSparkSqlApplicationConfigQueryList, GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs

Queries List<string>: The queries to run.

Queries []string: The queries to run.

queries List<String>: The queries to run.

queries string[]: The queries to run.

queries Sequence[str]: The queries to run.

queries List<String>: The queries to run.

Import

SparkApplication can be imported using any of these accepted formats:

projects/{{project}}/locations/{{location}}/serviceInstances/{{serviceinstance}}/sparkApplications/{{spark_application_id}}
{{project}}/{{location}}/{{serviceinstance}}/{{spark_application_id}}
{{location}}/{{serviceinstance}}/{{spark_application_id}}

When using the pulumi import command, SparkApplication can be imported using one of the formats above. For example:

$ pulumi import gcp:dataproc/gdcSparkApplication:GdcSparkApplication default projects/{{project}}/locations/{{location}}/serviceInstances/{{serviceinstance}}/sparkApplications/{{spark_application_id}}

$ pulumi import gcp:dataproc/gdcSparkApplication:GdcSparkApplication default {{project}}/{{location}}/{{serviceinstance}}/{{spark_application_id}}

$ pulumi import gcp:dataproc/gdcSparkApplication:GdcSparkApplication default {{location}}/{{serviceinstance}}/{{spark_application_id}}

To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository: Google Cloud (GCP) Classic pulumi/pulumi-gcp
License: Apache-2.0
Notes: This Pulumi package is based on the google-beta Terraform Provider.

Google Cloud v8.21.0 published on Wednesday, Mar 5, 2025 by Pulumi

pulumi/pulumi-gcp

gcp.dataproc.GdcSparkApplication

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Example Usage

Dataprocgdc Sparkapplication Basic

Dataprocgdc Sparkapplication

Dataprocgdc Sparkapplication Pyspark

Dataprocgdc Sparkapplication Sparkr

Dataprocgdc Sparkapplication Sparksql

Dataprocgdc Sparkapplication Sparksql Query File

Create GdcSparkApplication Resource

Constructor syntax

Parameters

Constructor example

GdcSparkApplication Resource Properties

Inputs

Outputs

Look up Existing GdcSparkApplication Resource

Supporting Types

GdcSparkApplicationPysparkApplicationConfig, GdcSparkApplicationPysparkApplicationConfigArgs

GdcSparkApplicationSparkApplicationConfig, GdcSparkApplicationSparkApplicationConfigArgs

GdcSparkApplicationSparkRApplicationConfig, GdcSparkApplicationSparkRApplicationConfigArgs

GdcSparkApplicationSparkSqlApplicationConfig, GdcSparkApplicationSparkSqlApplicationConfigArgs

GdcSparkApplicationSparkSqlApplicationConfigQueryList, GdcSparkApplicationSparkSqlApplicationConfigQueryListArgs

Import

Package Details

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