Google Cloud v8.36.0, Jun 27 25

Google Cloud v8.36.0 published on Friday, Jun 27, 2025 by Pulumi

gcp.dataproc.SessionTemplate

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Google Cloud v8.36.0 published on Friday, Jun 27, 2025 by Pulumi

pulumi/pulumi-gcp

Example Usage

Dataproc Session Templates Jupyter

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

const exampleSessionTemplatesJupyter = new gcp.dataproc.SessionTemplate("example_session_templates_jupyter", {
    name: "projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
    location: "us-central1",
    labels: {
        session_template_test: "terraform",
    },
    runtimeConfig: {
        properties: {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
    },
    environmentConfig: {
        executionConfig: {
            subnetworkUri: "default",
            ttl: "3600s",
            networkTags: ["tag1"],
        },
    },
    jupyterSession: {
        kernel: "PYTHON",
        displayName: "tf python kernel",
    },
});

import pulumi
import pulumi_gcp as gcp

example_session_templates_jupyter = gcp.dataproc.SessionTemplate("example_session_templates_jupyter",
    name="projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
    location="us-central1",
    labels={
        "session_template_test": "terraform",
    },
    runtime_config={
        "properties": {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
    },
    environment_config={
        "execution_config": {
            "subnetwork_uri": "default",
            "ttl": "3600s",
            "network_tags": ["tag1"],
        },
    },
    jupyter_session={
        "kernel": "PYTHON",
        "display_name": "tf python kernel",
    })

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.NewSessionTemplate(ctx, "example_session_templates_jupyter", &dataproc.SessionTemplateArgs{
			Name:     pulumi.String("projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template"),
			Location: pulumi.String("us-central1"),
			Labels: pulumi.StringMap{
				"session_template_test": pulumi.String("terraform"),
			},
			RuntimeConfig: &dataproc.SessionTemplateRuntimeConfigArgs{
				Properties: pulumi.StringMap{
					"spark.dynamicAllocation.enabled": pulumi.String("false"),
					"spark.executor.instances":        pulumi.String("2"),
				},
			},
			EnvironmentConfig: &dataproc.SessionTemplateEnvironmentConfigArgs{
				ExecutionConfig: &dataproc.SessionTemplateEnvironmentConfigExecutionConfigArgs{
					SubnetworkUri: pulumi.String("default"),
					Ttl:           pulumi.String("3600s"),
					NetworkTags: pulumi.StringArray{
						pulumi.String("tag1"),
					},
				},
			},
			JupyterSession: &dataproc.SessionTemplateJupyterSessionArgs{
				Kernel:      pulumi.String("PYTHON"),
				DisplayName: pulumi.String("tf python kernel"),
			},
		})
		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 exampleSessionTemplatesJupyter = new Gcp.Dataproc.SessionTemplate("example_session_templates_jupyter", new()
    {
        Name = "projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
        Location = "us-central1",
        Labels = 
        {
            { "session_template_test", "terraform" },
        },
        RuntimeConfig = new Gcp.Dataproc.Inputs.SessionTemplateRuntimeConfigArgs
        {
            Properties = 
            {
                { "spark.dynamicAllocation.enabled", "false" },
                { "spark.executor.instances", "2" },
            },
        },
        EnvironmentConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigArgs
        {
            ExecutionConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs
            {
                SubnetworkUri = "default",
                Ttl = "3600s",
                NetworkTags = new[]
                {
                    "tag1",
                },
            },
        },
        JupyterSession = new Gcp.Dataproc.Inputs.SessionTemplateJupyterSessionArgs
        {
            Kernel = "PYTHON",
            DisplayName = "tf python kernel",
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.SessionTemplate;
import com.pulumi.gcp.dataproc.SessionTemplateArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateRuntimeConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateJupyterSessionArgs;
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 exampleSessionTemplatesJupyter = new SessionTemplate("exampleSessionTemplatesJupyter", SessionTemplateArgs.builder()
            .name("projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template")
            .location("us-central1")
            .labels(Map.of("session_template_test", "terraform"))
            .runtimeConfig(SessionTemplateRuntimeConfigArgs.builder()
                .properties(Map.ofEntries(
                    Map.entry("spark.dynamicAllocation.enabled", "false"),
                    Map.entry("spark.executor.instances", "2")
                ))
                .build())
            .environmentConfig(SessionTemplateEnvironmentConfigArgs.builder()
                .executionConfig(SessionTemplateEnvironmentConfigExecutionConfigArgs.builder()
                    .subnetworkUri("default")
                    .ttl("3600s")
                    .networkTags("tag1")
                    .build())
                .build())
            .jupyterSession(SessionTemplateJupyterSessionArgs.builder()
                .kernel("PYTHON")
                .displayName("tf python kernel")
                .build())
            .build());

    }
}

resources:
  exampleSessionTemplatesJupyter:
    type: gcp:dataproc:SessionTemplate
    name: example_session_templates_jupyter
    properties:
      name: projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template
      location: us-central1
      labels:
        session_template_test: terraform
      runtimeConfig:
        properties:
          spark.dynamicAllocation.enabled: 'false'
          spark.executor.instances: '2'
      environmentConfig:
        executionConfig:
          subnetworkUri: default
          ttl: 3600s
          networkTags:
            - tag1
      jupyterSession:
        kernel: PYTHON
        displayName: tf python kernel

Dataproc Session Templates Jupyter Full

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

const project = gcp.organizations.getProject({});
const gcsAccount = gcp.storage.getProjectServiceAccount({});
const bucket = new gcp.storage.Bucket("bucket", {
    uniformBucketLevelAccess: true,
    name: "dataproc-bucket",
    location: "US",
    forceDestroy: true,
});
const cryptoKeyMember1 = new gcp.kms.CryptoKeyIAMMember("crypto_key_member_1", {
    cryptoKeyId: "example-key",
    role: "roles/cloudkms.cryptoKeyEncrypterDecrypter",
    member: project.then(project => `serviceAccount:service-${project.number}@dataproc-accounts.iam.gserviceaccount.com`),
});
const ms = new gcp.dataproc.MetastoreService("ms", {
    serviceId: "jupyter-session-template",
    location: "us-central1",
    port: 9080,
    tier: "DEVELOPER",
    maintenanceWindow: {
        hourOfDay: 2,
        dayOfWeek: "SUNDAY",
    },
    hiveMetastoreConfig: {
        version: "3.1.2",
    },
    networkConfig: {
        consumers: [{
            subnetwork: "projects/my-project-name/regions/us-central1/subnetworks/default",
        }],
    },
});
const basic = new gcp.dataproc.Cluster("basic", {
    name: "jupyter-session-template",
    region: "us-central1",
    clusterConfig: {
        softwareConfig: {
            overrideProperties: {
                "dataproc:dataproc.allow.zero.workers": "true",
                "spark:spark.history.fs.logDirectory": pulumi.interpolate`gs://${bucket.name}/*/spark-job-history`,
            },
        },
        gceClusterConfig: {
            subnetwork: "default",
        },
        endpointConfig: {
            enableHttpPortAccess: true,
        },
        masterConfig: {
            numInstances: 1,
            machineType: "e2-standard-2",
            diskConfig: {
                bootDiskSizeGb: 35,
            },
        },
        metastoreConfig: {
            dataprocMetastoreService: ms.name,
        },
    },
});
const dataprocSessionTemplatesJupyterFull = new gcp.dataproc.SessionTemplate("dataproc_session_templates_jupyter_full", {
    name: "projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
    location: "us-central1",
    labels: {
        session_template_test: "terraform",
    },
    runtimeConfig: {
        properties: {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
        version: "2.2",
        containerImage: "us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest",
    },
    environmentConfig: {
        executionConfig: {
            ttl: "3600s",
            networkTags: ["tag1"],
            kmsKey: "example-key",
            subnetworkUri: "default",
            serviceAccount: project.then(project => `${project.number}-compute@developer.gserviceaccount.com`),
            stagingBucket: bucket.name,
        },
        peripheralsConfig: {
            metastoreService: ms.name,
            sparkHistoryServerConfig: {
                dataprocCluster: basic.id,
            },
        },
    },
    jupyterSession: {
        kernel: "PYTHON",
        displayName: "tf python kernel",
    },
}, {
    dependsOn: [cryptoKeyMember1],
});

import pulumi
import pulumi_gcp as gcp

project = gcp.organizations.get_project()
gcs_account = gcp.storage.get_project_service_account()
bucket = gcp.storage.Bucket("bucket",
    uniform_bucket_level_access=True,
    name="dataproc-bucket",
    location="US",
    force_destroy=True)
crypto_key_member1 = gcp.kms.CryptoKeyIAMMember("crypto_key_member_1",
    crypto_key_id="example-key",
    role="roles/cloudkms.cryptoKeyEncrypterDecrypter",
    member=f"serviceAccount:service-{project.number}@dataproc-accounts.iam.gserviceaccount.com")
ms = gcp.dataproc.MetastoreService("ms",
    service_id="jupyter-session-template",
    location="us-central1",
    port=9080,
    tier="DEVELOPER",
    maintenance_window={
        "hour_of_day": 2,
        "day_of_week": "SUNDAY",
    },
    hive_metastore_config={
        "version": "3.1.2",
    },
    network_config={
        "consumers": [{
            "subnetwork": "projects/my-project-name/regions/us-central1/subnetworks/default",
        }],
    })
basic = gcp.dataproc.Cluster("basic",
    name="jupyter-session-template",
    region="us-central1",
    cluster_config={
        "software_config": {
            "override_properties": {
                "dataproc:dataproc.allow.zero.workers": "true",
                "spark:spark.history.fs.logDirectory": bucket.name.apply(lambda name: f"gs://{name}/*/spark-job-history"),
            },
        },
        "gce_cluster_config": {
            "subnetwork": "default",
        },
        "endpoint_config": {
            "enable_http_port_access": True,
        },
        "master_config": {
            "num_instances": 1,
            "machine_type": "e2-standard-2",
            "disk_config": {
                "boot_disk_size_gb": 35,
            },
        },
        "metastore_config": {
            "dataproc_metastore_service": ms.name,
        },
    })
dataproc_session_templates_jupyter_full = gcp.dataproc.SessionTemplate("dataproc_session_templates_jupyter_full",
    name="projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
    location="us-central1",
    labels={
        "session_template_test": "terraform",
    },
    runtime_config={
        "properties": {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
        "version": "2.2",
        "container_image": "us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest",
    },
    environment_config={
        "execution_config": {
            "ttl": "3600s",
            "network_tags": ["tag1"],
            "kms_key": "example-key",
            "subnetwork_uri": "default",
            "service_account": f"{project.number}-compute@developer.gserviceaccount.com",
            "staging_bucket": bucket.name,
        },
        "peripherals_config": {
            "metastore_service": ms.name,
            "spark_history_server_config": {
                "dataproc_cluster": basic.id,
            },
        },
    },
    jupyter_session={
        "kernel": "PYTHON",
        "display_name": "tf python kernel",
    },
    opts = pulumi.ResourceOptions(depends_on=[crypto_key_member1]))

package main

import (
	"fmt"

	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/dataproc"
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/kms"
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/organizations"
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/storage"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		project, err := organizations.LookupProject(ctx, &organizations.LookupProjectArgs{}, nil)
		if err != nil {
			return err
		}
		_, err = storage.GetProjectServiceAccount(ctx, &storage.GetProjectServiceAccountArgs{}, nil)
		if err != nil {
			return err
		}
		bucket, err := storage.NewBucket(ctx, "bucket", &storage.BucketArgs{
			UniformBucketLevelAccess: pulumi.Bool(true),
			Name:                     pulumi.String("dataproc-bucket"),
			Location:                 pulumi.String("US"),
			ForceDestroy:             pulumi.Bool(true),
		})
		if err != nil {
			return err
		}
		cryptoKeyMember1, err := kms.NewCryptoKeyIAMMember(ctx, "crypto_key_member_1", &kms.CryptoKeyIAMMemberArgs{
			CryptoKeyId: pulumi.String("example-key"),
			Role:        pulumi.String("roles/cloudkms.cryptoKeyEncrypterDecrypter"),
			Member:      pulumi.Sprintf("serviceAccount:service-%v@dataproc-accounts.iam.gserviceaccount.com", project.Number),
		})
		if err != nil {
			return err
		}
		ms, err := dataproc.NewMetastoreService(ctx, "ms", &dataproc.MetastoreServiceArgs{
			ServiceId: pulumi.String("jupyter-session-template"),
			Location:  pulumi.String("us-central1"),
			Port:      pulumi.Int(9080),
			Tier:      pulumi.String("DEVELOPER"),
			MaintenanceWindow: &dataproc.MetastoreServiceMaintenanceWindowArgs{
				HourOfDay: pulumi.Int(2),
				DayOfWeek: pulumi.String("SUNDAY"),
			},
			HiveMetastoreConfig: &dataproc.MetastoreServiceHiveMetastoreConfigArgs{
				Version: pulumi.String("3.1.2"),
			},
			NetworkConfig: &dataproc.MetastoreServiceNetworkConfigArgs{
				Consumers: dataproc.MetastoreServiceNetworkConfigConsumerArray{
					&dataproc.MetastoreServiceNetworkConfigConsumerArgs{
						Subnetwork: pulumi.String("projects/my-project-name/regions/us-central1/subnetworks/default"),
					},
				},
			},
		})
		if err != nil {
			return err
		}
		basic, err := dataproc.NewCluster(ctx, "basic", &dataproc.ClusterArgs{
			Name:   pulumi.String("jupyter-session-template"),
			Region: pulumi.String("us-central1"),
			ClusterConfig: &dataproc.ClusterClusterConfigArgs{
				SoftwareConfig: &dataproc.ClusterClusterConfigSoftwareConfigArgs{
					OverrideProperties: pulumi.StringMap{
						"dataproc:dataproc.allow.zero.workers": pulumi.String("true"),
						"spark:spark.history.fs.logDirectory": bucket.Name.ApplyT(func(name string) (string, error) {
							return fmt.Sprintf("gs://%v/*/spark-job-history", name), nil
						}).(pulumi.StringOutput),
					},
				},
				GceClusterConfig: &dataproc.ClusterClusterConfigGceClusterConfigArgs{
					Subnetwork: pulumi.String("default"),
				},
				EndpointConfig: &dataproc.ClusterClusterConfigEndpointConfigArgs{
					EnableHttpPortAccess: pulumi.Bool(true),
				},
				MasterConfig: &dataproc.ClusterClusterConfigMasterConfigArgs{
					NumInstances: pulumi.Int(1),
					MachineType:  pulumi.String("e2-standard-2"),
					DiskConfig: &dataproc.ClusterClusterConfigMasterConfigDiskConfigArgs{
						BootDiskSizeGb: pulumi.Int(35),
					},
				},
				MetastoreConfig: &dataproc.ClusterClusterConfigMetastoreConfigArgs{
					DataprocMetastoreService: ms.Name,
				},
			},
		})
		if err != nil {
			return err
		}
		_, err = dataproc.NewSessionTemplate(ctx, "dataproc_session_templates_jupyter_full", &dataproc.SessionTemplateArgs{
			Name:     pulumi.String("projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template"),
			Location: pulumi.String("us-central1"),
			Labels: pulumi.StringMap{
				"session_template_test": pulumi.String("terraform"),
			},
			RuntimeConfig: &dataproc.SessionTemplateRuntimeConfigArgs{
				Properties: pulumi.StringMap{
					"spark.dynamicAllocation.enabled": pulumi.String("false"),
					"spark.executor.instances":        pulumi.String("2"),
				},
				Version:        pulumi.String("2.2"),
				ContainerImage: pulumi.String("us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest"),
			},
			EnvironmentConfig: &dataproc.SessionTemplateEnvironmentConfigArgs{
				ExecutionConfig: &dataproc.SessionTemplateEnvironmentConfigExecutionConfigArgs{
					Ttl: pulumi.String("3600s"),
					NetworkTags: pulumi.StringArray{
						pulumi.String("tag1"),
					},
					KmsKey:         pulumi.String("example-key"),
					SubnetworkUri:  pulumi.String("default"),
					ServiceAccount: pulumi.Sprintf("%v-compute@developer.gserviceaccount.com", project.Number),
					StagingBucket:  bucket.Name,
				},
				PeripheralsConfig: &dataproc.SessionTemplateEnvironmentConfigPeripheralsConfigArgs{
					MetastoreService: ms.Name,
					SparkHistoryServerConfig: &dataproc.SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs{
						DataprocCluster: basic.ID(),
					},
				},
			},
			JupyterSession: &dataproc.SessionTemplateJupyterSessionArgs{
				Kernel:      pulumi.String("PYTHON"),
				DisplayName: pulumi.String("tf python kernel"),
			},
		}, pulumi.DependsOn([]pulumi.Resource{
			cryptoKeyMember1,
		}))
		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 project = Gcp.Organizations.GetProject.Invoke();

    var gcsAccount = Gcp.Storage.GetProjectServiceAccount.Invoke();

    var bucket = new Gcp.Storage.Bucket("bucket", new()
    {
        UniformBucketLevelAccess = true,
        Name = "dataproc-bucket",
        Location = "US",
        ForceDestroy = true,
    });

    var cryptoKeyMember1 = new Gcp.Kms.CryptoKeyIAMMember("crypto_key_member_1", new()
    {
        CryptoKeyId = "example-key",
        Role = "roles/cloudkms.cryptoKeyEncrypterDecrypter",
        Member = $"serviceAccount:service-{project.Apply(getProjectResult => getProjectResult.Number)}@dataproc-accounts.iam.gserviceaccount.com",
    });

    var ms = new Gcp.Dataproc.MetastoreService("ms", new()
    {
        ServiceId = "jupyter-session-template",
        Location = "us-central1",
        Port = 9080,
        Tier = "DEVELOPER",
        MaintenanceWindow = new Gcp.Dataproc.Inputs.MetastoreServiceMaintenanceWindowArgs
        {
            HourOfDay = 2,
            DayOfWeek = "SUNDAY",
        },
        HiveMetastoreConfig = new Gcp.Dataproc.Inputs.MetastoreServiceHiveMetastoreConfigArgs
        {
            Version = "3.1.2",
        },
        NetworkConfig = new Gcp.Dataproc.Inputs.MetastoreServiceNetworkConfigArgs
        {
            Consumers = new[]
            {
                new Gcp.Dataproc.Inputs.MetastoreServiceNetworkConfigConsumerArgs
                {
                    Subnetwork = "projects/my-project-name/regions/us-central1/subnetworks/default",
                },
            },
        },
    });

    var basic = new Gcp.Dataproc.Cluster("basic", new()
    {
        Name = "jupyter-session-template",
        Region = "us-central1",
        ClusterConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigArgs
        {
            SoftwareConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigSoftwareConfigArgs
            {
                OverrideProperties = 
                {
                    { "dataproc:dataproc.allow.zero.workers", "true" },
                    { "spark:spark.history.fs.logDirectory", bucket.Name.Apply(name => $"gs://{name}/*/spark-job-history") },
                },
            },
            GceClusterConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigGceClusterConfigArgs
            {
                Subnetwork = "default",
            },
            EndpointConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigEndpointConfigArgs
            {
                EnableHttpPortAccess = true,
            },
            MasterConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigMasterConfigArgs
            {
                NumInstances = 1,
                MachineType = "e2-standard-2",
                DiskConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigMasterConfigDiskConfigArgs
                {
                    BootDiskSizeGb = 35,
                },
            },
            MetastoreConfig = new Gcp.Dataproc.Inputs.ClusterClusterConfigMetastoreConfigArgs
            {
                DataprocMetastoreService = ms.Name,
            },
        },
    });

    var dataprocSessionTemplatesJupyterFull = new Gcp.Dataproc.SessionTemplate("dataproc_session_templates_jupyter_full", new()
    {
        Name = "projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template",
        Location = "us-central1",
        Labels = 
        {
            { "session_template_test", "terraform" },
        },
        RuntimeConfig = new Gcp.Dataproc.Inputs.SessionTemplateRuntimeConfigArgs
        {
            Properties = 
            {
                { "spark.dynamicAllocation.enabled", "false" },
                { "spark.executor.instances", "2" },
            },
            Version = "2.2",
            ContainerImage = "us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest",
        },
        EnvironmentConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigArgs
        {
            ExecutionConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs
            {
                Ttl = "3600s",
                NetworkTags = new[]
                {
                    "tag1",
                },
                KmsKey = "example-key",
                SubnetworkUri = "default",
                ServiceAccount = $"{project.Apply(getProjectResult => getProjectResult.Number)}-compute@developer.gserviceaccount.com",
                StagingBucket = bucket.Name,
            },
            PeripheralsConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigPeripheralsConfigArgs
            {
                MetastoreService = ms.Name,
                SparkHistoryServerConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs
                {
                    DataprocCluster = basic.Id,
                },
            },
        },
        JupyterSession = new Gcp.Dataproc.Inputs.SessionTemplateJupyterSessionArgs
        {
            Kernel = "PYTHON",
            DisplayName = "tf python kernel",
        },
    }, new CustomResourceOptions
    {
        DependsOn =
        {
            cryptoKeyMember1,
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.organizations.OrganizationsFunctions;
import com.pulumi.gcp.organizations.inputs.GetProjectArgs;
import com.pulumi.gcp.storage.StorageFunctions;
import com.pulumi.gcp.storage.inputs.GetProjectServiceAccountArgs;
import com.pulumi.gcp.storage.Bucket;
import com.pulumi.gcp.storage.BucketArgs;
import com.pulumi.gcp.kms.CryptoKeyIAMMember;
import com.pulumi.gcp.kms.CryptoKeyIAMMemberArgs;
import com.pulumi.gcp.dataproc.MetastoreService;
import com.pulumi.gcp.dataproc.MetastoreServiceArgs;
import com.pulumi.gcp.dataproc.inputs.MetastoreServiceMaintenanceWindowArgs;
import com.pulumi.gcp.dataproc.inputs.MetastoreServiceHiveMetastoreConfigArgs;
import com.pulumi.gcp.dataproc.inputs.MetastoreServiceNetworkConfigArgs;
import com.pulumi.gcp.dataproc.Cluster;
import com.pulumi.gcp.dataproc.ClusterArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigSoftwareConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigGceClusterConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigEndpointConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigMasterConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigMasterConfigDiskConfigArgs;
import com.pulumi.gcp.dataproc.inputs.ClusterClusterConfigMetastoreConfigArgs;
import com.pulumi.gcp.dataproc.SessionTemplate;
import com.pulumi.gcp.dataproc.SessionTemplateArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateRuntimeConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigPeripheralsConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateJupyterSessionArgs;
import com.pulumi.resources.CustomResourceOptions;
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) {
        final var project = OrganizationsFunctions.getProject(GetProjectArgs.builder()
            .build());

        final var gcsAccount = StorageFunctions.getProjectServiceAccount(GetProjectServiceAccountArgs.builder()
            .build());

        var bucket = new Bucket("bucket", BucketArgs.builder()
            .uniformBucketLevelAccess(true)
            .name("dataproc-bucket")
            .location("US")
            .forceDestroy(true)
            .build());

        var cryptoKeyMember1 = new CryptoKeyIAMMember("cryptoKeyMember1", CryptoKeyIAMMemberArgs.builder()
            .cryptoKeyId("example-key")
            .role("roles/cloudkms.cryptoKeyEncrypterDecrypter")
            .member(String.format("serviceAccount:service-%s@dataproc-accounts.iam.gserviceaccount.com", project.number()))
            .build());

        var ms = new MetastoreService("ms", MetastoreServiceArgs.builder()
            .serviceId("jupyter-session-template")
            .location("us-central1")
            .port(9080)
            .tier("DEVELOPER")
            .maintenanceWindow(MetastoreServiceMaintenanceWindowArgs.builder()
                .hourOfDay(2)
                .dayOfWeek("SUNDAY")
                .build())
            .hiveMetastoreConfig(MetastoreServiceHiveMetastoreConfigArgs.builder()
                .version("3.1.2")
                .build())
            .networkConfig(MetastoreServiceNetworkConfigArgs.builder()
                .consumers(MetastoreServiceNetworkConfigConsumerArgs.builder()
                    .subnetwork("projects/my-project-name/regions/us-central1/subnetworks/default")
                    .build())
                .build())
            .build());

        var basic = new Cluster("basic", ClusterArgs.builder()
            .name("jupyter-session-template")
            .region("us-central1")
            .clusterConfig(ClusterClusterConfigArgs.builder()
                .softwareConfig(ClusterClusterConfigSoftwareConfigArgs.builder()
                    .overrideProperties(Map.ofEntries(
                        Map.entry("dataproc:dataproc.allow.zero.workers", "true"),
                        Map.entry("spark:spark.history.fs.logDirectory", bucket.name().applyValue(_name -> String.format("gs://%s/*/spark-job-history", _name)))
                    ))
                    .build())
                .gceClusterConfig(ClusterClusterConfigGceClusterConfigArgs.builder()
                    .subnetwork("default")
                    .build())
                .endpointConfig(ClusterClusterConfigEndpointConfigArgs.builder()
                    .enableHttpPortAccess(true)
                    .build())
                .masterConfig(ClusterClusterConfigMasterConfigArgs.builder()
                    .numInstances(1)
                    .machineType("e2-standard-2")
                    .diskConfig(ClusterClusterConfigMasterConfigDiskConfigArgs.builder()
                        .bootDiskSizeGb(35)
                        .build())
                    .build())
                .metastoreConfig(ClusterClusterConfigMetastoreConfigArgs.builder()
                    .dataprocMetastoreService(ms.name())
                    .build())
                .build())
            .build());

        var dataprocSessionTemplatesJupyterFull = new SessionTemplate("dataprocSessionTemplatesJupyterFull", SessionTemplateArgs.builder()
            .name("projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template")
            .location("us-central1")
            .labels(Map.of("session_template_test", "terraform"))
            .runtimeConfig(SessionTemplateRuntimeConfigArgs.builder()
                .properties(Map.ofEntries(
                    Map.entry("spark.dynamicAllocation.enabled", "false"),
                    Map.entry("spark.executor.instances", "2")
                ))
                .version("2.2")
                .containerImage("us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest")
                .build())
            .environmentConfig(SessionTemplateEnvironmentConfigArgs.builder()
                .executionConfig(SessionTemplateEnvironmentConfigExecutionConfigArgs.builder()
                    .ttl("3600s")
                    .networkTags("tag1")
                    .kmsKey("example-key")
                    .subnetworkUri("default")
                    .serviceAccount(String.format("%s-compute@developer.gserviceaccount.com", project.number()))
                    .stagingBucket(bucket.name())
                    .build())
                .peripheralsConfig(SessionTemplateEnvironmentConfigPeripheralsConfigArgs.builder()
                    .metastoreService(ms.name())
                    .sparkHistoryServerConfig(SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs.builder()
                        .dataprocCluster(basic.id())
                        .build())
                    .build())
                .build())
            .jupyterSession(SessionTemplateJupyterSessionArgs.builder()
                .kernel("PYTHON")
                .displayName("tf python kernel")
                .build())
            .build(), CustomResourceOptions.builder()
                .dependsOn(cryptoKeyMember1)
                .build());

    }
}

resources:
  dataprocSessionTemplatesJupyterFull:
    type: gcp:dataproc:SessionTemplate
    name: dataproc_session_templates_jupyter_full
    properties:
      name: projects/my-project-name/locations/us-central1/sessionTemplates/jupyter-session-template
      location: us-central1
      labels:
        session_template_test: terraform
      runtimeConfig:
        properties:
          spark.dynamicAllocation.enabled: 'false'
          spark.executor.instances: '2'
        version: '2.2'
        containerImage: us-docker.pkg.dev/my-project-name/s8s-spark-test-images/s8s-spark:latest
      environmentConfig:
        executionConfig:
          ttl: 3600s
          networkTags:
            - tag1
          kmsKey: example-key
          subnetworkUri: default
          serviceAccount: ${project.number}-compute@developer.gserviceaccount.com
          stagingBucket: ${bucket.name}
        peripheralsConfig:
          metastoreService: ${ms.name}
          sparkHistoryServerConfig:
            dataprocCluster: ${basic.id}
      jupyterSession:
        kernel: PYTHON
        displayName: tf python kernel
    options:
      dependsOn:
        - ${cryptoKeyMember1}
  bucket:
    type: gcp:storage:Bucket
    properties:
      uniformBucketLevelAccess: true
      name: dataproc-bucket
      location: US
      forceDestroy: true
  cryptoKeyMember1:
    type: gcp:kms:CryptoKeyIAMMember
    name: crypto_key_member_1
    properties:
      cryptoKeyId: example-key
      role: roles/cloudkms.cryptoKeyEncrypterDecrypter
      member: serviceAccount:service-${project.number}@dataproc-accounts.iam.gserviceaccount.com
  basic:
    type: gcp:dataproc:Cluster
    properties:
      name: jupyter-session-template
      region: us-central1
      clusterConfig:
        softwareConfig:
          overrideProperties:
            dataproc:dataproc.allow.zero.workers: 'true'
            spark:spark.history.fs.logDirectory: gs://${bucket.name}/*/spark-job-history
        gceClusterConfig:
          subnetwork: default
        endpointConfig:
          enableHttpPortAccess: true
        masterConfig:
          numInstances: 1
          machineType: e2-standard-2
          diskConfig:
            bootDiskSizeGb: 35
        metastoreConfig:
          dataprocMetastoreService: ${ms.name}
  ms:
    type: gcp:dataproc:MetastoreService
    properties:
      serviceId: jupyter-session-template
      location: us-central1
      port: 9080
      tier: DEVELOPER
      maintenanceWindow:
        hourOfDay: 2
        dayOfWeek: SUNDAY
      hiveMetastoreConfig:
        version: 3.1.2
      networkConfig:
        consumers:
          - subnetwork: projects/my-project-name/regions/us-central1/subnetworks/default
variables:
  project:
    fn::invoke:
      function: gcp:organizations:getProject
      arguments: {}
  gcsAccount:
    fn::invoke:
      function: gcp:storage:getProjectServiceAccount
      arguments: {}

Dataproc Session Templates Spark Connect

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

const exampleSessionTemplatesSparkConnect = new gcp.dataproc.SessionTemplate("example_session_templates_spark_connect", {
    name: "projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template",
    location: "us-central1",
    labels: {
        session_template_test: "terraform",
    },
    runtimeConfig: {
        properties: {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
    },
    environmentConfig: {
        executionConfig: {
            subnetworkUri: "default",
            ttl: "3600s",
            networkTags: ["tag1"],
        },
    },
});

import pulumi
import pulumi_gcp as gcp

example_session_templates_spark_connect = gcp.dataproc.SessionTemplate("example_session_templates_spark_connect",
    name="projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template",
    location="us-central1",
    labels={
        "session_template_test": "terraform",
    },
    runtime_config={
        "properties": {
            "spark.dynamicAllocation.enabled": "false",
            "spark.executor.instances": "2",
        },
    },
    environment_config={
        "execution_config": {
            "subnetwork_uri": "default",
            "ttl": "3600s",
            "network_tags": ["tag1"],
        },
    })

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.NewSessionTemplate(ctx, "example_session_templates_spark_connect", &dataproc.SessionTemplateArgs{
			Name:     pulumi.String("projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template"),
			Location: pulumi.String("us-central1"),
			Labels: pulumi.StringMap{
				"session_template_test": pulumi.String("terraform"),
			},
			RuntimeConfig: &dataproc.SessionTemplateRuntimeConfigArgs{
				Properties: pulumi.StringMap{
					"spark.dynamicAllocation.enabled": pulumi.String("false"),
					"spark.executor.instances":        pulumi.String("2"),
				},
			},
			EnvironmentConfig: &dataproc.SessionTemplateEnvironmentConfigArgs{
				ExecutionConfig: &dataproc.SessionTemplateEnvironmentConfigExecutionConfigArgs{
					SubnetworkUri: pulumi.String("default"),
					Ttl:           pulumi.String("3600s"),
					NetworkTags: pulumi.StringArray{
						pulumi.String("tag1"),
					},
				},
			},
		})
		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 exampleSessionTemplatesSparkConnect = new Gcp.Dataproc.SessionTemplate("example_session_templates_spark_connect", new()
    {
        Name = "projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template",
        Location = "us-central1",
        Labels = 
        {
            { "session_template_test", "terraform" },
        },
        RuntimeConfig = new Gcp.Dataproc.Inputs.SessionTemplateRuntimeConfigArgs
        {
            Properties = 
            {
                { "spark.dynamicAllocation.enabled", "false" },
                { "spark.executor.instances", "2" },
            },
        },
        EnvironmentConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigArgs
        {
            ExecutionConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs
            {
                SubnetworkUri = "default",
                Ttl = "3600s",
                NetworkTags = new[]
                {
                    "tag1",
                },
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.dataproc.SessionTemplate;
import com.pulumi.gcp.dataproc.SessionTemplateArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateRuntimeConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigArgs;
import com.pulumi.gcp.dataproc.inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs;
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 exampleSessionTemplatesSparkConnect = new SessionTemplate("exampleSessionTemplatesSparkConnect", SessionTemplateArgs.builder()
            .name("projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template")
            .location("us-central1")
            .labels(Map.of("session_template_test", "terraform"))
            .runtimeConfig(SessionTemplateRuntimeConfigArgs.builder()
                .properties(Map.ofEntries(
                    Map.entry("spark.dynamicAllocation.enabled", "false"),
                    Map.entry("spark.executor.instances", "2")
                ))
                .build())
            .environmentConfig(SessionTemplateEnvironmentConfigArgs.builder()
                .executionConfig(SessionTemplateEnvironmentConfigExecutionConfigArgs.builder()
                    .subnetworkUri("default")
                    .ttl("3600s")
                    .networkTags("tag1")
                    .build())
                .build())
            .build());

    }
}

resources:
  exampleSessionTemplatesSparkConnect:
    type: gcp:dataproc:SessionTemplate
    name: example_session_templates_spark_connect
    properties:
      name: projects/my-project-name/locations/us-central1/sessionTemplates/sc-session-template
      location: us-central1
      labels:
        session_template_test: terraform
      runtimeConfig:
        properties:
          spark.dynamicAllocation.enabled: 'false'
          spark.executor.instances: '2'
      environmentConfig:
        executionConfig:
          subnetworkUri: default
          ttl: 3600s
          networkTags:
            - tag1

Create SessionTemplate Resource

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

Constructor syntax

new SessionTemplate(name: string, args?: SessionTemplateArgs, opts?: CustomResourceOptions);

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

@overload
def SessionTemplate(resource_name: str,
                    opts: Optional[ResourceOptions] = None,
                    environment_config: Optional[SessionTemplateEnvironmentConfigArgs] = None,
                    jupyter_session: Optional[SessionTemplateJupyterSessionArgs] = None,
                    labels: Optional[Mapping[str, str]] = None,
                    location: Optional[str] = None,
                    name: Optional[str] = None,
                    project: Optional[str] = None,
                    runtime_config: Optional[SessionTemplateRuntimeConfigArgs] = None,
                    spark_connect_session: Optional[SessionTemplateSparkConnectSessionArgs] = None)

func NewSessionTemplate(ctx *Context, name string, args *SessionTemplateArgs, opts ...ResourceOption) (*SessionTemplate, error)

public SessionTemplate(string name, SessionTemplateArgs? args = null, CustomResourceOptions? opts = null)

public SessionTemplate(String name, SessionTemplateArgs args)
public SessionTemplate(String name, SessionTemplateArgs args, CustomResourceOptions options)

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

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

name String: The unique name of the resource.
args SessionTemplateArgs: 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 sessionTemplateResource = new Gcp.Dataproc.SessionTemplate("sessionTemplateResource", new()
{
    EnvironmentConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigArgs
    {
        ExecutionConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigExecutionConfigArgs
        {
            KmsKey = "string",
            NetworkTags = new[]
            {
                "string",
            },
            ServiceAccount = "string",
            StagingBucket = "string",
            SubnetworkUri = "string",
            Ttl = "string",
        },
        PeripheralsConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigPeripheralsConfigArgs
        {
            MetastoreService = "string",
            SparkHistoryServerConfig = new Gcp.Dataproc.Inputs.SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs
            {
                DataprocCluster = "string",
            },
        },
    },
    JupyterSession = new Gcp.Dataproc.Inputs.SessionTemplateJupyterSessionArgs
    {
        DisplayName = "string",
        Kernel = "string",
    },
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    Name = "string",
    Project = "string",
    RuntimeConfig = new Gcp.Dataproc.Inputs.SessionTemplateRuntimeConfigArgs
    {
        ContainerImage = "string",
        EffectiveProperties = 
        {
            { "string", "string" },
        },
        Properties = 
        {
            { "string", "string" },
        },
        Version = "string",
    },
    SparkConnectSession = null,
});

example, err := dataproc.NewSessionTemplate(ctx, "sessionTemplateResource", &dataproc.SessionTemplateArgs{
	EnvironmentConfig: &dataproc.SessionTemplateEnvironmentConfigArgs{
		ExecutionConfig: &dataproc.SessionTemplateEnvironmentConfigExecutionConfigArgs{
			KmsKey: pulumi.String("string"),
			NetworkTags: pulumi.StringArray{
				pulumi.String("string"),
			},
			ServiceAccount: pulumi.String("string"),
			StagingBucket:  pulumi.String("string"),
			SubnetworkUri:  pulumi.String("string"),
			Ttl:            pulumi.String("string"),
		},
		PeripheralsConfig: &dataproc.SessionTemplateEnvironmentConfigPeripheralsConfigArgs{
			MetastoreService: pulumi.String("string"),
			SparkHistoryServerConfig: &dataproc.SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs{
				DataprocCluster: pulumi.String("string"),
			},
		},
	},
	JupyterSession: &dataproc.SessionTemplateJupyterSessionArgs{
		DisplayName: pulumi.String("string"),
		Kernel:      pulumi.String("string"),
	},
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Location: pulumi.String("string"),
	Name:     pulumi.String("string"),
	Project:  pulumi.String("string"),
	RuntimeConfig: &dataproc.SessionTemplateRuntimeConfigArgs{
		ContainerImage: pulumi.String("string"),
		EffectiveProperties: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
		Properties: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
		Version: pulumi.String("string"),
	},
	SparkConnectSession: &dataproc.SessionTemplateSparkConnectSessionArgs{},
})

var sessionTemplateResource = new SessionTemplate("sessionTemplateResource", SessionTemplateArgs.builder()
    .environmentConfig(SessionTemplateEnvironmentConfigArgs.builder()
        .executionConfig(SessionTemplateEnvironmentConfigExecutionConfigArgs.builder()
            .kmsKey("string")
            .networkTags("string")
            .serviceAccount("string")
            .stagingBucket("string")
            .subnetworkUri("string")
            .ttl("string")
            .build())
        .peripheralsConfig(SessionTemplateEnvironmentConfigPeripheralsConfigArgs.builder()
            .metastoreService("string")
            .sparkHistoryServerConfig(SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs.builder()
                .dataprocCluster("string")
                .build())
            .build())
        .build())
    .jupyterSession(SessionTemplateJupyterSessionArgs.builder()
        .displayName("string")
        .kernel("string")
        .build())
    .labels(Map.of("string", "string"))
    .location("string")
    .name("string")
    .project("string")
    .runtimeConfig(SessionTemplateRuntimeConfigArgs.builder()
        .containerImage("string")
        .effectiveProperties(Map.of("string", "string"))
        .properties(Map.of("string", "string"))
        .version("string")
        .build())
    .sparkConnectSession(SessionTemplateSparkConnectSessionArgs.builder()
        .build())
    .build());

session_template_resource = gcp.dataproc.SessionTemplate("sessionTemplateResource",
    environment_config={
        "execution_config": {
            "kms_key": "string",
            "network_tags": ["string"],
            "service_account": "string",
            "staging_bucket": "string",
            "subnetwork_uri": "string",
            "ttl": "string",
        },
        "peripherals_config": {
            "metastore_service": "string",
            "spark_history_server_config": {
                "dataproc_cluster": "string",
            },
        },
    },
    jupyter_session={
        "display_name": "string",
        "kernel": "string",
    },
    labels={
        "string": "string",
    },
    location="string",
    name="string",
    project="string",
    runtime_config={
        "container_image": "string",
        "effective_properties": {
            "string": "string",
        },
        "properties": {
            "string": "string",
        },
        "version": "string",
    },
    spark_connect_session={})

const sessionTemplateResource = new gcp.dataproc.SessionTemplate("sessionTemplateResource", {
    environmentConfig: {
        executionConfig: {
            kmsKey: "string",
            networkTags: ["string"],
            serviceAccount: "string",
            stagingBucket: "string",
            subnetworkUri: "string",
            ttl: "string",
        },
        peripheralsConfig: {
            metastoreService: "string",
            sparkHistoryServerConfig: {
                dataprocCluster: "string",
            },
        },
    },
    jupyterSession: {
        displayName: "string",
        kernel: "string",
    },
    labels: {
        string: "string",
    },
    location: "string",
    name: "string",
    project: "string",
    runtimeConfig: {
        containerImage: "string",
        effectiveProperties: {
            string: "string",
        },
        properties: {
            string: "string",
        },
        version: "string",
    },
    sparkConnectSession: {},
});

type: gcp:dataproc:SessionTemplate
properties:
    environmentConfig:
        executionConfig:
            kmsKey: string
            networkTags:
                - string
            serviceAccount: string
            stagingBucket: string
            subnetworkUri: string
            ttl: string
        peripheralsConfig:
            metastoreService: string
            sparkHistoryServerConfig:
                dataprocCluster: string
    jupyterSession:
        displayName: string
        kernel: string
    labels:
        string: string
    location: string
    name: string
    project: string
    runtimeConfig:
        containerImage: string
        effectiveProperties:
            string: string
        properties:
            string: string
        version: string
    sparkConnectSession: {}

SessionTemplate 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 SessionTemplate resource accepts the following input properties:

EnvironmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

JupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

Labels Dictionary<string, string>

The labels to associate with this session template.

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 in which the session template will be created in.

Name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

Project string

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

RuntimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

SparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

EnvironmentConfig SessionTemplateEnvironmentConfigArgs

Environment configuration for the session execution. Structure is documented below.

JupyterSession SessionTemplateJupyterSessionArgs

Jupyter configuration for an interactive session. Structure is documented below.

Labels map[string]string

The labels to associate with this session template.

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 in which the session template will be created in.

Name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

Project string

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

RuntimeConfig SessionTemplateRuntimeConfigArgs

Runtime configuration for the session template. Structure is documented below.

SparkConnectSession SessionTemplateSparkConnectSessionArgs

Spark connect configuration for an interactive session.

environmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

jupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

labels Map<String,String>

The labels to associate with this session template.

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 in which the session template will be created in.

name String

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project String

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

runtimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

environmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

jupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

labels {[key: string]: string}

The labels to associate with this session template.

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 in which the session template will be created in.

name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project string

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

runtimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

environment_config SessionTemplateEnvironmentConfigArgs

Environment configuration for the session execution. Structure is documented below.

jupyter_session SessionTemplateJupyterSessionArgs

Jupyter configuration for an interactive session. Structure is documented below.

labels Mapping[str, str]

The labels to associate with this session template.

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 str

The location in which the session template will be created in.

name str

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project str

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

runtime_config SessionTemplateRuntimeConfigArgs

Runtime configuration for the session template. Structure is documented below.

spark_connect_session SessionTemplateSparkConnectSessionArgs

Spark connect configuration for an interactive session.

environmentConfig Property Map

Environment configuration for the session execution. Structure is documented below.

jupyterSession Property Map

Jupyter configuration for an interactive session. Structure is documented below.

labels Map<String>

The labels to associate with this session template.

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 in which the session template will be created in.

name String

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project String

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

runtimeConfig Property Map

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession Property Map

Spark connect configuration for an interactive session.

Outputs

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

CreateTime string: The time when the session template was created.
Creator string: The email address of the user who created the session template.
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.
PulumiLabels Dictionary<string, string>: The combination of labels configured directly on the resource and default labels configured on the provider.
UpdateTime string: The time when the session template was updated.
Uuid string: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

CreateTime string: The time when the session template was created.
Creator string: The email address of the user who created the session template.
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.
PulumiLabels map[string]string: The combination of labels configured directly on the resource and default labels configured on the provider.
UpdateTime string: The time when the session template was updated.
Uuid string: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime String: The time when the session template was created.
creator String: The email address of the user who created the session template.
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.
pulumiLabels Map<String,String>: The combination of labels configured directly on the resource and default labels configured on the provider.
updateTime String: The time when the session template was updated.
uuid String: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime string: The time when the session template was created.
creator string: The email address of the user who created the session template.
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.
pulumiLabels {[key: string]: string}: The combination of labels configured directly on the resource and default labels configured on the provider.
updateTime string: The time when the session template was updated.
uuid string: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

create_time str: The time when the session template was created.
creator str: The email address of the user who created the session template.
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.
pulumi_labels Mapping[str, str]: The combination of labels configured directly on the resource and default labels configured on the provider.
update_time str: The time when the session template was updated.
uuid str: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime String: The time when the session template was created.
creator String: The email address of the user who created the session template.
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.
pulumiLabels Map<String>: The combination of labels configured directly on the resource and default labels configured on the provider.
updateTime String: The time when the session template was updated.
uuid String: A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

Look up Existing SessionTemplate Resource

Get an existing SessionTemplate 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?: SessionTemplateState, opts?: CustomResourceOptions): SessionTemplate

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        create_time: Optional[str] = None,
        creator: Optional[str] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        environment_config: Optional[SessionTemplateEnvironmentConfigArgs] = None,
        jupyter_session: Optional[SessionTemplateJupyterSessionArgs] = None,
        labels: Optional[Mapping[str, str]] = None,
        location: Optional[str] = None,
        name: Optional[str] = None,
        project: Optional[str] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        runtime_config: Optional[SessionTemplateRuntimeConfigArgs] = None,
        spark_connect_session: Optional[SessionTemplateSparkConnectSessionArgs] = None,
        update_time: Optional[str] = None,
        uuid: Optional[str] = None) -> SessionTemplate

func GetSessionTemplate(ctx *Context, name string, id IDInput, state *SessionTemplateState, opts ...ResourceOption) (*SessionTemplate, error)

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

public static SessionTemplate get(String name, Output<String> id, SessionTemplateState state, CustomResourceOptions options)

resources:  _:    type: gcp:dataproc:SessionTemplate    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:

CreateTime string

The time when the session template was created.

Creator string

The email address of the user who created the session template.

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.

EnvironmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

JupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

Labels Dictionary<string, string>

The labels to associate with this session template.

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 in which the session template will be created in.

Name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

Project string

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

PulumiLabels Dictionary<string, string>

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

RuntimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

SparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

UpdateTime string

The time when the session template was updated.

Uuid string

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

CreateTime string

The time when the session template was created.

Creator string

The email address of the user who created the session template.

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.

EnvironmentConfig SessionTemplateEnvironmentConfigArgs

Environment configuration for the session execution. Structure is documented below.

JupyterSession SessionTemplateJupyterSessionArgs

Jupyter configuration for an interactive session. Structure is documented below.

Labels map[string]string

The labels to associate with this session template.

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 in which the session template will be created in.

Name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

Project string

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

PulumiLabels map[string]string

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

RuntimeConfig SessionTemplateRuntimeConfigArgs

Runtime configuration for the session template. Structure is documented below.

SparkConnectSession SessionTemplateSparkConnectSessionArgs

Spark connect configuration for an interactive session.

UpdateTime string

The time when the session template was updated.

Uuid string

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime String

The time when the session template was created.

creator String

The email address of the user who created the session template.

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.

environmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

jupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

labels Map<String,String>

The labels to associate with this session template.

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 in which the session template will be created in.

name String

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project String

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

pulumiLabels Map<String,String>

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

runtimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

updateTime String

The time when the session template was updated.

uuid String

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime string

The time when the session template was created.

creator string

The email address of the user who created the session template.

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.

environmentConfig SessionTemplateEnvironmentConfig

Environment configuration for the session execution. Structure is documented below.

jupyterSession SessionTemplateJupyterSession

Jupyter configuration for an interactive session. Structure is documented below.

labels {[key: string]: string}

The labels to associate with this session template.

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 in which the session template will be created in.

name string

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project string

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

pulumiLabels {[key: string]: string}

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

runtimeConfig SessionTemplateRuntimeConfig

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession SessionTemplateSparkConnectSession

Spark connect configuration for an interactive session.

updateTime string

The time when the session template was updated.

uuid string

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

create_time str

The time when the session template was created.

creator str

The email address of the user who created the session template.

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.

environment_config SessionTemplateEnvironmentConfigArgs

Environment configuration for the session execution. Structure is documented below.

jupyter_session SessionTemplateJupyterSessionArgs

Jupyter configuration for an interactive session. Structure is documented below.

labels Mapping[str, str]

The labels to associate with this session template.

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 str

The location in which the session template will be created in.

name str

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project str

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

pulumi_labels Mapping[str, str]

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

runtime_config SessionTemplateRuntimeConfigArgs

Runtime configuration for the session template. Structure is documented below.

spark_connect_session SessionTemplateSparkConnectSessionArgs

Spark connect configuration for an interactive session.

update_time str

The time when the session template was updated.

uuid str

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

createTime String

The time when the session template was created.

creator String

The email address of the user who created the session template.

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.

environmentConfig Property Map

Environment configuration for the session execution. Structure is documented below.

jupyterSession Property Map

Jupyter configuration for an interactive session. Structure is documented below.

labels Map<String>

The labels to associate with this session template.

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 in which the session template will be created in.

name String

The resource name of the session template in the following format: projects/{project}/locations/{location}/sessionTemplates/{template_id}

project String

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

pulumiLabels Map<String>

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

runtimeConfig Property Map

Runtime configuration for the session template. Structure is documented below.

sparkConnectSession Property Map

Spark connect configuration for an interactive session.

updateTime String

The time when the session template was updated.

uuid String

A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.

Supporting Types

SessionTemplateEnvironmentConfig, SessionTemplateEnvironmentConfigArgs

ExecutionConfig SessionTemplateEnvironmentConfigExecutionConfig: Execution configuration for a workload. Structure is documented below.
PeripheralsConfig SessionTemplateEnvironmentConfigPeripheralsConfig: Peripherals configuration that workload has access to. Structure is documented below.

ExecutionConfig SessionTemplateEnvironmentConfigExecutionConfig: Execution configuration for a workload. Structure is documented below.
PeripheralsConfig SessionTemplateEnvironmentConfigPeripheralsConfig: Peripherals configuration that workload has access to. Structure is documented below.

executionConfig SessionTemplateEnvironmentConfigExecutionConfig: Execution configuration for a workload. Structure is documented below.
peripheralsConfig SessionTemplateEnvironmentConfigPeripheralsConfig: Peripherals configuration that workload has access to. Structure is documented below.

executionConfig SessionTemplateEnvironmentConfigExecutionConfig: Execution configuration for a workload. Structure is documented below.
peripheralsConfig SessionTemplateEnvironmentConfigPeripheralsConfig: Peripherals configuration that workload has access to. Structure is documented below.

execution_config SessionTemplateEnvironmentConfigExecutionConfig: Execution configuration for a workload. Structure is documented below.
peripherals_config SessionTemplateEnvironmentConfigPeripheralsConfig: Peripherals configuration that workload has access to. Structure is documented below.

executionConfig Property Map: Execution configuration for a workload. Structure is documented below.
peripheralsConfig Property Map: Peripherals configuration that workload has access to. Structure is documented below.

SessionTemplateEnvironmentConfigExecutionConfig, SessionTemplateEnvironmentConfigExecutionConfigArgs

KmsKey string: The Cloud KMS key to use for encryption.
NetworkTags List<string>: Tags used for network traffic control.
ServiceAccount string: Service account that used to execute workload.
StagingBucket string: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Subnetwork configuration for workload execution.
Ttl string: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

KmsKey string: The Cloud KMS key to use for encryption.
NetworkTags []string: Tags used for network traffic control.
ServiceAccount string: Service account that used to execute workload.
StagingBucket string: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
SubnetworkUri string: Subnetwork configuration for workload execution.
Ttl string: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

kmsKey String: The Cloud KMS key to use for encryption.
networkTags List<String>: Tags used for network traffic control.
serviceAccount String: Service account that used to execute workload.
stagingBucket String: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Subnetwork configuration for workload execution.
ttl String: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

kmsKey string: The Cloud KMS key to use for encryption.
networkTags string[]: Tags used for network traffic control.
serviceAccount string: Service account that used to execute workload.
stagingBucket string: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri string: Subnetwork configuration for workload execution.
ttl string: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

kms_key str: The Cloud KMS key to use for encryption.
network_tags Sequence[str]: Tags used for network traffic control.
service_account str: Service account that used to execute workload.
staging_bucket str: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetwork_uri str: Subnetwork configuration for workload execution.
ttl str: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

kmsKey String: The Cloud KMS key to use for encryption.
networkTags List<String>: Tags used for network traffic control.
serviceAccount String: Service account that used to execute workload.
stagingBucket String: A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
subnetworkUri String: Subnetwork configuration for workload execution.
ttl String: The duration after which the workload will be terminated. When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a session workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idleTtl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idleTtl or when ttl has been exceeded, whichever occurs first.

SessionTemplateEnvironmentConfigPeripheralsConfig, SessionTemplateEnvironmentConfigPeripheralsConfigArgs

MetastoreService string: Resource name of an existing Dataproc Metastore service.
SparkHistoryServerConfig SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig: The Spark History Server configuration for the workload. Structure is documented below.

MetastoreService string: Resource name of an existing Dataproc Metastore service.
SparkHistoryServerConfig SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig: The Spark History Server configuration for the workload. Structure is documented below.

metastoreService String: Resource name of an existing Dataproc Metastore service.
sparkHistoryServerConfig SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig: The Spark History Server configuration for the workload. Structure is documented below.

metastoreService string: Resource name of an existing Dataproc Metastore service.
sparkHistoryServerConfig SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig: The Spark History Server configuration for the workload. Structure is documented below.

metastore_service str: Resource name of an existing Dataproc Metastore service.
spark_history_server_config SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig: The Spark History Server configuration for the workload. Structure is documented below.

metastoreService String: Resource name of an existing Dataproc Metastore service.
sparkHistoryServerConfig Property Map: The Spark History Server configuration for the workload. Structure is documented below.

SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig, SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs

DataprocCluster string: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

DataprocCluster string: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

dataprocCluster String: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

dataprocCluster string: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

dataproc_cluster str: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

dataprocCluster String: Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.

SessionTemplateJupyterSession, SessionTemplateJupyterSessionArgs

DisplayName string: Display name, shown in the Jupyter kernelspec card.
Kernel string: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

DisplayName string: Display name, shown in the Jupyter kernelspec card.
Kernel string: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

displayName String: Display name, shown in the Jupyter kernelspec card.
kernel String: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

displayName string: Display name, shown in the Jupyter kernelspec card.
kernel string: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

display_name str: Display name, shown in the Jupyter kernelspec card.
kernel str: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

displayName String: Display name, shown in the Jupyter kernelspec card.
kernel String: Kernel to be used with Jupyter interactive session. Possible values are: PYTHON, SCALA.

SessionTemplateRuntimeConfig, SessionTemplateRuntimeConfigArgs

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

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

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

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

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

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

Import

SessionTemplate can be imported using any of these accepted formats:

{{name}}

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

$ pulumi import gcp:dataproc/sessionTemplate:SessionTemplate default {{name}}

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 v8.36.0 published on Friday, Jun 27, 2025 by Pulumi

pulumi/pulumi-gcp

gcp.dataproc.SessionTemplate

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Example Usage

Dataproc Session Templates Jupyter

Dataproc Session Templates Jupyter Full

Dataproc Session Templates Spark Connect

Create SessionTemplate Resource

Constructor syntax

Parameters

Constructor example

SessionTemplate Resource Properties

Inputs

Outputs

Look up Existing SessionTemplate Resource

Supporting Types

SessionTemplateEnvironmentConfig, SessionTemplateEnvironmentConfigArgs

SessionTemplateEnvironmentConfigExecutionConfig, SessionTemplateEnvironmentConfigExecutionConfigArgs

SessionTemplateEnvironmentConfigPeripheralsConfig, SessionTemplateEnvironmentConfigPeripheralsConfigArgs

SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfig, SessionTemplateEnvironmentConfigPeripheralsConfigSparkHistoryServerConfigArgs

SessionTemplateJupyterSession, SessionTemplateJupyterSessionArgs

SessionTemplateRuntimeConfig, SessionTemplateRuntimeConfigArgs

Import

Package Details

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