Package google.cloud.dataproc.v1

Index

AutoscalingPolicyService

The API interface for managing autoscaling policies in the Dataproc API.

CreateAutoscalingPolicy

rpc CreateAutoscalingPolicy(CreateAutoscalingPolicyRequest) returns (AutoscalingPolicy)

Creates new autoscaling policy.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

DeleteAutoscalingPolicy

rpc DeleteAutoscalingPolicy(DeleteAutoscalingPolicyRequest) returns (Empty)

Deletes an autoscaling policy. It is an error to delete an autoscaling policy that is in use by one or more clusters.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

GetAutoscalingPolicy

rpc GetAutoscalingPolicy(GetAutoscalingPolicyRequest) returns (AutoscalingPolicy)

Retrieves autoscaling policy.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ListAutoscalingPolicies

rpc ListAutoscalingPolicies(ListAutoscalingPoliciesRequest) returns (ListAutoscalingPoliciesResponse)

Lists autoscaling policies in the project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

UpdateAutoscalingPolicy

rpc UpdateAutoscalingPolicy(UpdateAutoscalingPolicyRequest) returns (AutoscalingPolicy)

Updates (replaces) autoscaling policy.

Disabled check for update_mask, because all updates will be full replacements.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ClusterController

The ClusterControllerService provides methods to manage clusters of Compute Engine instances.

CreateCluster

rpc CreateCluster(CreateClusterRequest) returns (Operation)

Creates a cluster in a project. The returned Operation.metadata will be ClusterOperationMetadata.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

DeleteCluster

rpc DeleteCluster(DeleteClusterRequest) returns (Operation)

Deletes a cluster in a project. The returned Operation.metadata will be ClusterOperationMetadata.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

DiagnoseCluster

rpc DiagnoseCluster(DiagnoseClusterRequest) returns (Operation)

Gets cluster diagnostic information. The returned Operation.metadata will be ClusterOperationMetadata. After the operation completes, Operation.response contains DiagnoseClusterResults.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

GetCluster

rpc GetCluster(GetClusterRequest) returns (Cluster)

Gets the resource representation for a cluster in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ListClusters

rpc ListClusters(ListClustersRequest) returns (ListClustersResponse)

Lists all regions/{region}/clusters in a project alphabetically.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

StartCluster

rpc StartCluster(StartClusterRequest) returns (Operation)

Starts a cluster in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

StopCluster

rpc StopCluster(StopClusterRequest) returns (Operation)

Stops a cluster in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

UpdateCluster

rpc UpdateCluster(UpdateClusterRequest) returns (Operation)

Updates a cluster in a project. The returned Operation.metadata will be ClusterOperationMetadata. The cluster must be in a RUNNING state or an error is returned.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

JobController

The JobController provides methods to manage jobs.

CancelJob

rpc CancelJob(CancelJobRequest) returns (Job)

Starts a job cancellation request. To access the job resource after cancellation, call regions/{region}/jobs.list or regions/{region}/jobs.get.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

DeleteJob

rpc DeleteJob(DeleteJobRequest) returns (Empty)

Deletes the job from the project. If the job is active, the delete fails, and the response returns FAILED_PRECONDITION.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

GetJob

rpc GetJob(GetJobRequest) returns (Job)

Gets the resource representation for a job in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ListJobs

rpc ListJobs(ListJobsRequest) returns (ListJobsResponse)

Lists regions/{region}/jobs in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

SubmitJob

rpc SubmitJob(SubmitJobRequest) returns (Job)

Submits a job to a cluster.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

SubmitJobAsOperation

rpc SubmitJobAsOperation(SubmitJobRequest) returns (Operation)

Submits job to a cluster.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

UpdateJob

rpc UpdateJob(UpdateJobRequest) returns (Job)

Updates a job in a project.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

NodeGroupController

The NodeGroupControllerService provides methods to manage node groups of Compute Engine managed instances.

GetNodeGroup

rpc GetNodeGroup(GetNodeGroupRequest) returns (NodeGroup)

Gets the resource representation for a node group in a cluster.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ResizeNodeGroup

rpc ResizeNodeGroup(ResizeNodeGroupRequest) returns (Operation)

Resizes a node group in a cluster. The returned Operation.metadata is NodeGroupOperationMetadata.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

WorkflowTemplateService

The API interface for managing Workflow Templates in the Dataproc API.

CreateWorkflowTemplate

rpc CreateWorkflowTemplate(CreateWorkflowTemplateRequest) returns (WorkflowTemplate)

Creates new workflow template.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

DeleteWorkflowTemplate

rpc DeleteWorkflowTemplate(DeleteWorkflowTemplateRequest) returns (Empty)

Deletes a workflow template. It does not cancel in-progress workflows.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

GetWorkflowTemplate

rpc GetWorkflowTemplate(GetWorkflowTemplateRequest) returns (WorkflowTemplate)

Retrieves the latest workflow template.

Can retrieve previously instantiated template by specifying optional version parameter.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

InstantiateInlineWorkflowTemplate

rpc InstantiateInlineWorkflowTemplate(InstantiateInlineWorkflowTemplateRequest) returns (Operation)

Instantiates a template and begins execution.

This method is equivalent to executing the sequence CreateWorkflowTemplate, InstantiateWorkflowTemplate, DeleteWorkflowTemplate.

The returned Operation can be used to track execution of workflow by polling operations.get. The Operation will complete when entire workflow is finished.

The running workflow can be aborted via operations.cancel. This will cause any inflight jobs to be cancelled and workflow-owned clusters to be deleted.

The Operation.metadata will be WorkflowMetadata. Also see Using WorkflowMetadata.

On successful completion, Operation.response will be Empty.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

InstantiateWorkflowTemplate

rpc InstantiateWorkflowTemplate(InstantiateWorkflowTemplateRequest) returns (Operation)

Instantiates a template and begins execution.

The returned Operation can be used to track execution of workflow by polling operations.get. The Operation will complete when entire workflow is finished.

The running workflow can be aborted via operations.cancel. This will cause any inflight jobs to be cancelled and workflow-owned clusters to be deleted.

The Operation.metadata will be WorkflowMetadata. Also see Using WorkflowMetadata.

On successful completion, Operation.response will be Empty.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

ListWorkflowTemplates

rpc ListWorkflowTemplates(ListWorkflowTemplatesRequest) returns (ListWorkflowTemplatesResponse)

Lists workflows that match the specified filter in the request.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

UpdateWorkflowTemplate

rpc UpdateWorkflowTemplate(UpdateWorkflowTemplateRequest) returns (WorkflowTemplate)

Updates (replaces) workflow template. The updated template must contain version that matches the current server version.

Authorization scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

AcceleratorConfig

Specifies the type and number of accelerator cards attached to the instances of an instance. See GPUs on Compute Engine.

Fields
accelerator_type_uri

string

Full URL, partial URI, or short name of the accelerator type resource to expose to this instance. See Compute Engine AcceleratorTypes.

Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-k80
  • projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-k80
  • nvidia-tesla-k80

Auto Zone Exception: If you are using the Dataproc Auto Zone Placement feature, you must use the short name of the accelerator type resource, for example, nvidia-tesla-k80.

accelerator_count

int32

The number of the accelerator cards of this type exposed to this instance.

AutoscalingConfig

Autoscaling Policy config associated with the cluster.

Fields
policy_uri

string

Optional. The autoscaling policy used by the cluster.

Only resource names including projectid and location (region) are valid. Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/locations/[dataproc_region]/autoscalingPolicies/[policy_id]
  • projects/[project_id]/locations/[dataproc_region]/autoscalingPolicies/[policy_id]

Note that the policy must be in the same project and Dataproc region.

AutoscalingPolicy

Describes an autoscaling policy for Dataproc cluster autoscaler.

Fields
id

string

Required. The policy id.

The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.

name

string

Output only. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id}

  • For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}

worker_config

InstanceGroupAutoscalingPolicyConfig

Required. Describes how the autoscaler will operate for primary workers.

secondary_worker_config

InstanceGroupAutoscalingPolicyConfig

Optional. Describes how the autoscaler will operate for secondary workers.

Union field algorithm. Autoscaling algorithm for policy. algorithm can be only one of the following:
basic_algorithm

BasicAutoscalingAlgorithm

AuxiliaryNodeGroup

Node group identification and configuration information.

Fields
node_group

NodeGroup

Required. Node group configuration.

node_group_id

string

Optional. A node group ID. Generated if not specified.

The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of from 3 to 33 characters.

AuxiliaryServicesConfig

Auxiliary services configuration for a Cluster.

Fields
metastore_config

MetastoreConfig

Optional. The Hive Metastore configuration for this workload.

spark_history_server_config

SparkHistoryServerConfig

Optional. The Spark History Server configuration for the workload.

BasicAutoscalingAlgorithm

Basic algorithm for autoscaling.

Fields
cooldown_period

Duration

Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.

Bounds: [2m, 1d]. Default: 2m.

Union field config.

config can be only one of the following:

yarn_config

BasicYarnAutoscalingConfig

Optional. YARN autoscaling configuration.

BasicYarnAutoscalingConfig

Basic autoscaling configurations for YARN.

Fields
graceful_decommission_timeout

Duration

Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.

Bounds: [0s, 1d].

scale_up_factor

double

Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.

Bounds: [0.0, 1.0].

scale_down_factor

double

Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.

Bounds: [0.0, 1.0].

scale_up_min_worker_fraction

double

Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.

Bounds: [0.0, 1.0]. Default: 0.0.

scale_down_min_worker_fraction

double

Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.

Bounds: [0.0, 1.0]. Default: 0.0.

CancelJobRequest

A request to cancel a job.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the job belongs to.

region

string

Required. The Dataproc region in which to handle the request.

job_id

string

Required. The job ID.

Authorization requires the following IAM permission on the specified resource jobId:

  • dataproc.jobs.cancel

Cluster

Describes the identifying information, config, and status of a Dataproc cluster

Fields
project_id

string

Required. The Google Cloud Platform project ID that the cluster belongs to.

cluster_name

string

Required. The cluster name, which must be unique within a project. The name must start with a lowercase letter, and can contain up to 51 lowercase letters, numbers, and hyphens. It cannot end with a hyphen. The name of a deleted cluster can be reused.

config

ClusterConfig

Optional. The cluster config for a cluster of Compute Engine Instances. Note that Dataproc may set default values, and values may change when clusters are updated.

Exactly one of ClusterConfig or VirtualClusterConfig must be specified.

virtual_cluster_config

VirtualClusterConfig

Optional. The virtual cluster config is used when creating a Dataproc cluster that does not directly control the underlying compute resources, for example, when creating a Dataproc-on-GKE cluster. Dataproc may set default values, and values may change when clusters are updated. Exactly one of config or virtual_cluster_config must be specified.

labels

map<string, string>

Optional. The labels to associate with this cluster. Label keys must contain 1 to 63 characters, and must conform to RFC 1035. Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035. No more than 32 labels can be associated with a cluster.

status

ClusterStatus

Output only. Cluster status.

status_history[]

ClusterStatus

Output only. The previous cluster status.

cluster_uuid

string

Output only. A cluster UUID (Unique Universal Identifier). Dataproc generates this value when it creates the cluster.

metrics

ClusterMetrics

Output only. Contains cluster daemon metrics such as HDFS and YARN stats.

Beta Feature: This report is available for testing purposes only. It may be changed before final release.

ClusterConfig

The cluster config.

Fields
config_bucket

string

Optional. A Cloud Storage bucket used to stage job dependencies, config files, and job driver console output. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's staging bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

temp_bucket

string

Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket. The default bucket has a TTL of 90 days, but you can use any TTL (or none) if you specify a bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

gce_cluster_config

GceClusterConfig

Optional. The shared Compute Engine config settings for all instances in a cluster.

master_config

InstanceGroupConfig

Optional. The Compute Engine config settings for the cluster's master instance.

worker_config

InstanceGroupConfig

Optional. The Compute Engine config settings for the cluster's worker instances.

secondary_worker_config

InstanceGroupConfig

Optional. The Compute Engine config settings for a cluster's secondary worker instances

software_config

SoftwareConfig

Optional. The config settings for cluster software.

initialization_actions[]

NodeInitializationAction

Optional. Commands to execute on each node after config is completed. By default, executables are run on master and all worker nodes. You can test a node's role metadata to run an executable on a master or worker node, as shown below using curl (you can also use wget):

ROLE=$(curl -H Metadata-Flavor:Google
http://metadata/computeMetadata/v1/instance/attributes/dataproc-role)
if [[ "${ROLE}" == 'Master' ]]; then
  ... master specific actions ...
else
  ... worker specific actions ...
fi
encryption_config

EncryptionConfig

Optional. Encryption settings for the cluster.

autoscaling_config

AutoscalingConfig

Optional. Autoscaling config for the policy associated with the cluster. Cluster does not autoscale if this field is unset.

security_config

SecurityConfig

Optional. Security settings for the cluster.

lifecycle_config

LifecycleConfig

Optional. Lifecycle setting for the cluster.

endpoint_config

EndpointConfig

Optional. Port/endpoint configuration for this cluster

metastore_config

MetastoreConfig

Optional. Metastore configuration.

dataproc_metric_config

DataprocMetricConfig

Optional. The config for Dataproc metrics.

auxiliary_node_groups[]

AuxiliaryNodeGroup

Optional. The node group settings.

ClusterMetrics

Contains cluster daemon metrics, such as HDFS and YARN stats.

Beta Feature: This report is available for testing purposes only. It may be changed before final release.

Fields
hdfs_metrics

map<string, int64>

The HDFS metrics.

yarn_metrics

map<string, int64>

YARN metrics.

ClusterOperation

The cluster operation triggered by a workflow.

Fields
operation_id

string

Output only. The id of the cluster operation.

error

string

Output only. Error, if operation failed.

done

bool

Output only. Indicates the operation is done.

ClusterOperationMetadata

Metadata describing the operation.

Fields
cluster_name

string

Output only. Name of the cluster for the operation.

cluster_uuid

string

Output only. Cluster UUID for the operation.

status

ClusterOperationStatus

Output only. Current operation status.

status_history[]

ClusterOperationStatus

Output only. The previous operation status.

operation_type

string

Output only. The operation type.

description

string

Output only. Short description of operation.

labels

map<string, string>

Output only. Labels associated with the operation

warnings[]

string

Output only. Errors encountered during operation execution.

child_operation_ids[]

string

Output only. Child operation ids

ClusterOperationStatus

The status of the operation.

Fields
state

State

Output only. A message containing the operation state.

inner_state

string

Output only. A message containing the detailed operation state.

details

string

Output only. A message containing any operation metadata details.

state_start_time

Timestamp

Output only. The time this state was entered.

State

The operation state.

Enums
UNKNOWN Unused.
PENDING The operation has been created.
RUNNING The operation is running.
DONE The operation is done; either cancelled or completed.

ClusterSelector

A selector that chooses target cluster for jobs based on metadata.

Fields
zone

string

Optional. The zone where workflow process executes. This parameter does not affect the selection of the cluster.

If unspecified, the zone of the first cluster matching the selector is used.

cluster_labels

map<string, string>

Required. The cluster labels. Cluster must have all labels to match.

ClusterStatus

The status of a cluster and its instances.

Fields
state

State

Output only. The cluster's state.

detail

string

Optional. Output only. Details of cluster's state.

state_start_time

Timestamp

Output only. Time when this state was entered (see JSON representation of Timestamp).

substate

Substate

Output only. Additional state information that includes status reported by the agent.

State

The cluster state.

Enums
UNKNOWN The cluster state is unknown.
CREATING The cluster is being created and set up. It is not ready for use.
RUNNING

The cluster is currently running and healthy. It is ready for use.

Note: The cluster state changes from "creating" to "running" status after the master node(s), first two primary worker nodes (and the last primary worker node if primary workers > 2) are running.

ERROR The cluster encountered an error. It is not ready for use.
ERROR_DUE_TO_UPDATE The cluster has encountered an error while being updated. Jobs can be submitted to the cluster, but the cluster cannot be updated.
DELETING The cluster is being deleted. It cannot be used.
UPDATING The cluster is being updated. It continues to accept and process jobs.
STOPPING The cluster is being stopped. It cannot be used.
STOPPED The cluster is currently stopped. It is not ready for use.
STARTING The cluster is being started. It is not ready for use.

Substate

The cluster substate.

Enums
UNSPECIFIED The cluster substate is unknown.
UNHEALTHY

The cluster is known to be in an unhealthy state (for example, critical daemons are not running or HDFS capacity is exhausted).

Applies to RUNNING state.

STALE_STATUS

The agent-reported status is out of date (may occur if Dataproc loses communication with Agent).

Applies to RUNNING state.

Component

Cluster components that can be activated.

Enums
COMPONENT_UNSPECIFIED Unspecified component. Specifying this will cause Cluster creation to fail.
ANACONDA The Anaconda python distribution. The Anaconda component is not supported in the Dataproc 2.0 image. The 2.0 image is pre-installed with Miniconda.
DOCKER Docker
DRUID The Druid query engine. (alpha)
HBASE HBase. (beta)
HIVE_WEBHCAT The Hive Web HCatalog (the REST service for accessing HCatalog).
HUDI Hudi.
JUPYTER The Jupyter Notebook.
PRESTO The Presto query engine.
RANGER The Ranger service.
SOLR The Solr service.
ZEPPELIN The Zeppelin notebook.
ZOOKEEPER The Zookeeper service.

ConfidentialInstanceConfig

Confidential Instance Config for clusters using Confidential VMs

Fields
enable_confidential_compute

bool

Optional. Defines whether the instance should have confidential compute enabled.

CreateAutoscalingPolicyRequest

A request to create an autoscaling policy.

Fields
parent

string

Required. The "resource name" of the region or location, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.autoscalingPolicies.create, the resource name of the region has the following format: projects/{project_id}/regions/{region}

  • For projects.locations.autoscalingPolicies.create, the resource name of the location has the following format: projects/{project_id}/locations/{location}

Authorization requires the following IAM permission on the specified resource parent:

  • dataproc.autoscalingPolicies.create
policy

AutoscalingPolicy

Required. The autoscaling policy to create.

CreateClusterRequest

A request to create a cluster.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the cluster belongs to.

Authorization requires the following IAM permission on the specified resource projectId:

  • dataproc.clusters.create
region

string

Required. The Dataproc region in which to handle the request.

cluster

Cluster

Required. The cluster to create.

request_id

string

Optional. A unique ID used to identify the request. If the server receives two CreateClusterRequests with the same id, then the second request will be ignored and the first google.longrunning.Operation created and stored in the backend is returned.

It is recommended to always set this value to a UUID.

The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.

action_on_failed_primary_workers

FailureAction

Optional. Failure action when primary worker creation fails.

CreateWorkflowTemplateRequest

A request to create a workflow template.

Fields
parent

string

Required. The resource name of the region or location, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.workflowTemplates.create, the resource name of the region has the following format: projects/{project_id}/regions/{region}

  • For projects.locations.workflowTemplates.create, the resource name of the location has the following format: projects/{project_id}/locations/{location}

Authorization requires the following IAM permission on the specified resource parent:

  • dataproc.workflowTemplates.create
template

WorkflowTemplate

Required. The Dataproc workflow template to create.

DataprocMetricConfig

Dataproc metric config.

Fields
metrics[]

Metric

Required. Metrics sources to enable.

Metric

A Dataproc custom metric.

Fields
metric_source

MetricSource

Required. A standard set of metrics is collected unless metricOverrides are specified for the metric source (see Custom metrics for more information).

metric_overrides[]

string

Optional. Specify one or more Custom metrics to collect for the metric course (for the SPARK metric source (any Spark metric can be specified).

Provide metrics in the following format:

METRIC_SOURCE:INSTANCE:GROUP:METRIC

Use camelcase as appropriate.

Examples:

yarn:ResourceManager:QueueMetrics:AppsCompleted
spark:driver:DAGScheduler:job.allJobs
sparkHistoryServer:JVM:Memory:NonHeapMemoryUsage.committed
hiveserver2:JVM:Memory:NonHeapMemoryUsage.used

Notes:

  • Only the specified overridden metrics are collected for the metric source. For example, if one or more spark:executive metrics are listed as metric overrides, other SPARK metrics are not collected. The collection of the metrics for other enabled custom metric sources is unaffected. For example, if both SPARK andd YARN metric sources are enabled, and overrides are provided for Spark metrics only, all YARN metrics are collected.

MetricSource

A source for the collection of Dataproc custom metrics (see Custom metrics).

Enums
METRIC_SOURCE_UNSPECIFIED Required unspecified metric source.
MONITORING_AGENT_DEFAULTS Monitoring agent metrics. If this source is enabled, Dataproc enables the monitoring agent in Compute Engine, and collects monitoring agent metrics, which are published with an agent.googleapis.com prefix.
HDFS HDFS metric source.
SPARK Spark metric source.
YARN YARN metric source.
SPARK_HISTORY_SERVER Spark History Server metric source.
HIVESERVER2 Hiveserver2 metric source.
HIVEMETASTORE hivemetastore metric source

DeleteAutoscalingPolicyRequest

A request to delete an autoscaling policy.

Autoscaling policies in use by one or more clusters will not be deleted.

Fields
name

string

Required. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.autoscalingPolicies.delete, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id}

  • For projects.locations.autoscalingPolicies.delete, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}

Authorization requires the following IAM permission on the specified resource name:

  • dataproc.autoscalingPolicies.delete

DeleteClusterRequest

A request to delete a cluster.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the cluster belongs to.

region

string

Required. The Dataproc region in which to handle the request.

cluster_name

string

Required. The cluster name.

Authorization requires the following IAM permission on the specified resource clusterName:

  • dataproc.clusters.delete
cluster_uuid

string

Optional. Specifying the cluster_uuid means the RPC should fail (with error NOT_FOUND) if cluster with specified UUID does not exist.

request_id

string

Optional. A unique ID used to identify the request. If the server receives two DeleteClusterRequests with the same id, then the second request will be ignored and the first google.longrunning.Operation created and stored in the backend is returned.

It is recommended to always set this value to a UUID.

The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.

graceful_termination_timeout

Duration

Optional. The graceful termination timeout for the deletion of the cluster. Indicate the time the request will wait to complete the running jobs on the cluster before its forceful deletion. Default value is 0 indicating that the user has not enabled the graceful termination. Value can be between 60 second and 6 Hours, in case the graceful termination is enabled. (There is no separate flag to check the enabling or disabling of graceful termination, it can be checked by the values in the field).

DeleteJobRequest

A request to delete a job.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the job belongs to.

region

string

Required. The Dataproc region in which to handle the request.

job_id

string

Required. The job ID.

Authorization requires the following IAM permission on the specified resource jobId:

  • dataproc.jobs.delete

DeleteWorkflowTemplateRequest

A request to delete a workflow template.

Currently started workflows will remain running.

Fields
name

string

Required. The resource name of the workflow template, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.workflowTemplates.delete, the resource name of the template has the following format: projects/{project_id}/regions/{region}/workflowTemplates/{template_id}

  • For projects.locations.workflowTemplates.instantiate, the resource name of the template has the following format: projects/{project_id}/locations/{location}/workflowTemplates/{template_id}

Authorization requires the following IAM permission on the specified resource name:

  • dataproc.workflowTemplates.delete
version

int32

Optional. The version of workflow template to delete. If specified, will only delete the template if the current server version matches specified version.

DiagnoseClusterRequest

A request to collect cluster diagnostic information.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the cluster belongs to.

region

string

Required. The Dataproc region in which to handle the request.

cluster_name

string

Required. The cluster name.

Authorization requires the following IAM permission on the specified resource clusterName:

  • dataproc.clusters.diagnose
tarball_gcs_dir

string

Optional. (Optional) The output Cloud Storage directory for the diagnostic tarball. If not specified, a task-specific directory in the cluster's staging bucket will be used.

Authorization requires the following IAM permission on the specified resource tarballGcsDir:

  • dataproc.clusters.diagnose
tarball_access

TarballAccess

Optional. (Optional) The access type to the diagnostic tarball. If not specified, falls back to default access of the bucket

Authorization requires the following IAM permission on the specified resource tarballAccess:

  • dataproc.clusters.diagnose
diagnosis_interval

Interval

Optional. Time interval in which diagnosis should be carried out on the cluster.

jobs[]

string

Optional. Specifies a list of jobs on which diagnosis is to be performed. Format: projects/{project}/regions/{region}/jobs/{job}

yarn_application_ids[]

string

Optional. Specifies a list of yarn applications on which diagnosis is to be performed.

TarballAccess

Defines who has access to the diagnostic tarball

Enums
TARBALL_ACCESS_UNSPECIFIED Tarball Access unspecified. Falls back to default access of the bucket
GOOGLE_CLOUD_SUPPORT Google Cloud Support group has read access to the diagnostic tarball
GOOGLE_DATAPROC_DIAGNOSE Google Cloud Dataproc Diagnose service account has read access to the diagnostic tarball

DiagnoseClusterResults

The location of diagnostic output.

Fields
output_uri

string

Output only. The Cloud Storage URI of the diagnostic output. The output report is a plain text file with a summary of collected diagnostics.

DiskConfig

Specifies the config of disk options for a group of VM instances.

Fields
boot_disk_type

string

Optional. Type of the boot disk (default is "pd-standard"). Valid values: "pd-balanced" (Persistent Disk Balanced Solid State Drive), "pd-ssd" (Persistent Disk Solid State Drive), or "pd-standard" (Persistent Disk Hard Disk Drive). See Disk types.

boot_disk_size_gb

int32

Optional. Size in GB of the boot disk (default is 500GB).

num_local_ssds

int32

Optional. Number of attached SSDs, from 0 to 8 (default is 0). If SSDs are not attached, the boot disk is used to store runtime logs and HDFS data. If one or more SSDs are attached, this runtime bulk data is spread across them, and the boot disk contains only basic config and installed binaries.

Note: Local SSD options may vary by machine type and number of vCPUs selected.

local_ssd_interface

string

Optional. Interface type of local SSDs (default is "scsi"). Valid values: "scsi" (Small Computer System Interface), "nvme" (Non-Volatile Memory Express). See local SSD performance.

DriverSchedulingConfig

Driver scheduling configuration.

Fields
memory_mb

int32

Required. The amount of memory in MB the driver is requesting.

vcores

int32

Required. The number of vCPUs the driver is requesting.

EncryptionConfig

Encryption settings for the cluster.

Fields
gce_pd_kms_key_name

string

Optional. The Cloud KMS key resource name to use for persistent disk encryption for all instances in the cluster. See Use CMEK with cluster data for more information.

kms_key

string

Optional. The Cloud KMS key resource name to use for cluster persistent disk and job argument encryption. See Use CMEK with cluster data for more information.

When this key resource name is provided, the following job arguments of the following job types submitted to the cluster are encrypted using CMEK:

EndpointConfig

Endpoint config for this cluster

Fields
http_ports

map<string, string>

Output only. The map of port descriptions to URLs. Will only be populated if enable_http_port_access is true.

enable_http_port_access

bool

Optional. If true, enable http access to specific ports on the cluster from external sources. Defaults to false.

FailureAction

Actions in response to failure of a resource associated with a cluster.

Enums
FAILURE_ACTION_UNSPECIFIED When FailureAction is unspecified, failure action defaults to NO_ACTION.
NO_ACTION Take no action on failure to create a cluster resource. NO_ACTION is the default.
DELETE Delete the failed cluster resource.

FlinkJob

A Dataproc job for running Apache Flink applications on YARN.

Fields
args[]

string

Optional. The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision might occur that causes an incorrect job submission.

jar_file_uris[]

string

Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Flink driver and tasks.

savepoint_uri

string

Optional. HCFS URI of the savepoint, which contains the last saved progress for starting the current job.

properties

map<string, string>

Optional. A mapping of property names to values, used to configure Flink. Properties that conflict with values set by the Dataproc API might be

logging_config

LoggingConfig

Optional. The runtime log config for job execution.

Union field driver. Required. The specification of the main method to call to drive the job. Specify either the jar file that contains the main class or the main class name. To pass both a main jar and a main class in the jar, add the jar to jarFileUris, and then specify the main class name in mainClass. driver can be only one of the following:
main_jar_file_uri

string

The HCFS URI of the jar file that contains the main class.

main_class

string

The name of the driver's main class. The jar file that contains the class must be in the default CLASSPATH or specified in jarFileUris.

GceClusterConfig

Common config settings for resources of Compute Engine cluster instances, applicable to all instances in the cluster.

Fields
zone_uri

string

Optional. The Compute Engine zone where the Dataproc cluster will be located. If omitted, the service will pick a zone in the cluster's Compute Engine region. On a get request, zone will always be present.

A full URL, partial URI, or short name are valid. Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]
  • projects/[project_id]/zones/[zone]
  • [zone]
network_uri

string

Optional. The Compute Engine network to be used for machine communications. Cannot be specified with subnetwork_uri. If neither network_uri nor subnetwork_uri is specified, the "default" network of the project is used, if it exists. Cannot be a "Custom Subnet Network" (see Using Subnetworks for more information).

A full URL, partial URI, or short name are valid. Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/global/networks/default
  • projects/[project_id]/global/networks/default
  • default
subnetwork_uri

string

Optional. The Compute Engine subnetwork to be used for machine communications. Cannot be specified with network_uri.

A full URL, partial URI, or short name are valid. Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/regions/[region]/subnetworks/sub0
  • projects/[project_id]/regions/[region]/subnetworks/sub0
  • sub0
private_ipv6_google_access

PrivateIpv6GoogleAccess

Optional. The type of IPv6 access for a cluster.

service_account

string

Optional. The Dataproc service account (also see VM Data Plane identity) used by Dataproc cluster VM instances to access Google Cloud Platform services.

If not specified, the Compute Engine default service account is used.

service_account_scopes[]

string

Optional. The URIs of service account scopes to be included in Compute Engine instances. The following base set of scopes is always included:

If no scopes are specified, the following defaults are also provided:

tags[]

string

The Compute Engine tags to add to all instances (see Tagging instances).

metadata

map<string, string>

Optional. The Compute Engine metadata entries to add to all instances (see Project and instance metadata).

reservation_affinity

ReservationAffinity

Optional. Reservation Affinity for consuming Zonal reservation.

node_group_affinity

NodeGroupAffinity

Optional. Node Group Affinity for sole-tenant clusters.

shielded_instance_config

ShieldedInstanceConfig

Optional. Shielded Instance Config for clusters using Compute Engine Shielded VMs.

confidential_instance_config

ConfidentialInstanceConfig

Optional. Confidential Instance Config for clusters using Confidential VMs.

internal_ip_only

bool

Optional. If true, all instances in the cluster will only have internal IP addresses. By default, clusters are not restricted to internal IP addresses, and will have ephemeral external IP addresses assigned to each instance. This internal_ip_only restriction can only be enabled for subnetwork enabled networks, and all off-cluster dependencies must be configured to be accessible without external IP addresses.

PrivateIpv6GoogleAccess

PrivateIpv6GoogleAccess controls whether and how Dataproc cluster nodes can communicate with Google Services through gRPC over IPv6. These values are directly mapped to corresponding values in the Compute Engine Instance fields.

Enums
PRIVATE_IPV6_GOOGLE_ACCESS_UNSPECIFIED If unspecified, Compute Engine default behavior will apply, which is the same as INHERIT_FROM_SUBNETWORK.
INHERIT_FROM_SUBNETWORK Private access to and from Google Services configuration inherited from the subnetwork configuration. This is the default Compute Engine behavior.
OUTBOUND Enables outbound private IPv6 access to Google Services from the Dataproc cluster.
BIDIRECTIONAL Enables bidirectional private IPv6 access between Google Services and the Dataproc cluster.

GetAutoscalingPolicyRequest

A request to fetch an autoscaling policy.

Fields
name

string

Required. The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.autoscalingPolicies.get, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id}

  • For projects.locations.autoscalingPolicies.get, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}

Authorization requires the following IAM permission on the specified resource name:

  • dataproc.autoscalingPolicies.get

GetClusterRequest

Request to get the resource representation for a cluster in a project.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the cluster belongs to.

region

string

Required. The Dataproc region in which to handle the request.

cluster_name

string

Required. The cluster name.

Authorization requires the following IAM permission on the specified resource clusterName:

  • dataproc.clusters.get

GetJobRequest

A request to get the resource representation for a job in a project.

Fields
project_id

string

Required. The ID of the Google Cloud Platform project that the job belongs to.

region

string

Required. The Dataproc region in which to handle the request.

job_id

string

Required. The job ID.

Authorization requires the following IAM permission on the specified resource jobId:

  • dataproc.jobs.get

GetNodeGroupRequest

A request to get a node group .

Fields
name

string

Required. The name of the node group to retrieve. Format: projects/{project}/regions/{region}/clusters/{cluster}/nodeGroups/{nodeGroup}

GetWorkflowTemplateRequest

A request to fetch a workflow template.

Fields
name

string

Required. The resource name of the workflow template, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.workflowTemplates.get, the resource name of the template has the following format: projects/{project_id}/regions/{region}/workflowTemplates/{template_id}

  • For projects.locations.workflowTemplates.get, the resource name of the template has the following format: projects/{project_id}/locations/{location}/workflowTemplates/{template_id}

Authorization requires the following IAM permission on the specified resource name:

  • dataproc.workflowTemplates.get
version

int32

Optional. The version of workflow template to retrieve. Only previously instantiated versions can be retrieved.

If unspecified, retrieves the current version.

GkeClusterConfig

The cluster's GKE config.

Fields
namespaced_gke_deployment_target
(deprecated)

NamespacedGkeDeploymentTarget

Optional. Deprecated. Use gkeClusterTarget. Used only for the deprecated beta. A target for the deployment.

gke_cluster_target

string

Optional. A target GKE cluster to deploy to. It must be in the same project and region as the Dataproc cluster (the GKE cluster can be zonal or regional). Format: 'projects/{project}/locations/{location}/clusters/{cluster_id}'

node_pool_target[]

GkeNodePoolTarget

Optional. GKE node pools where workloads will be scheduled. At least one node pool must be assigned the DEFAULT GkeNodePoolTarget.Role. If a GkeNodePoolTarget is not specified, Dataproc constructs a DEFAULT GkeNodePoolTarget. Each role can be given to only one GkeNodePoolTarget. All node pools must have the same location settings.

NamespacedGkeDeploymentTarget

Deprecated. Used only for the deprecated beta. A full, namespace-isolated deployment target for an existing GKE cluster.

Fields
target_gke_cluster

string

Optional. The target GKE cluster to deploy to. Format: 'projects/{project}/locations/{location}/clusters/{cluster_id}'

cluster_namespace

string

Optional. A namespace within the GKE cluster to deploy into.

GkeNodePoolConfig

The configuration of a GKE node pool used by a Dataproc-on-GKE cluster.

Fields
config

GkeNodeConfig

Optional. The node pool configuration.

locations[]

string

Optional. The list of Compute Engine zones where node pool nodes associated with a Dataproc on GKE virtual cluster will be located.

Note: All node pools associated with a virtual cluster must be located in the same region as the virtual cluster, and they must be located in the same zone within that region.

If a location is not specified during node pool creation, Dataproc on GKE will choose the zone.

autoscaling

GkeNodePoolAutoscalingConfig

Optional. The autoscaler configuration for this node pool. The autoscaler is enabled only when a valid configuration is present.

GkeNodeConfig

Parameters that describe cluster nodes.

Fields
machine_type

string

Optional. The name of a Compute Engine machine type.

local_ssd_count

int32

Optional. The number of local SSD disks to attach to the node, which is limited by the maximum number of disks allowable per zone (see Adding Local SSDs).

preemptible

bool

Optional. Whether the nodes are created as legacy preemptible VM instances. Also see Spot VMs, preemptible VM instances without a maximum lifetime. Legacy and Spot preemptible nodes cannot be used in a node pool with the CONTROLLER role or in the DEFAULT node pool if the CONTROLLER role is not assigned (the DEFAULT node pool will assume the CONTROLLER role).

accelerators[]

GkeNodePoolAcceleratorConfig

Optional. A list of hardware accelerators to attach to each node.

min_cpu_platform

string

Optional. Minimum CPU platform to be used by this instance. The instance may be scheduled on the specified or a newer CPU platform. Specify the friendly names of CPU platforms, such as "Intel Haswell"` or Intel Sandy Bridge".

spot

bool

Optional. Whether the nodes are created as Spot VM instances. Spot VMs are the latest update to legacy preemptible VMs. Spot VMs do not have a maximum lifetime. Legacy and Spot preemptible nodes cannot be used in a node pool with the CONTROLLER role or in the DEFAULT node pool if the CONTROLLER role is not assigned (the DEFAULT node pool will assume the CONTROLLER role).

GkeNodePoolAcceleratorConfig

A GkeNodeConfigAcceleratorConfig represents a Hardware Accelerator request for a node pool.

Fields
accelerator_count

int64

The number of accelerator cards exposed to an instance.

accelerator_type

string

The accelerator type resource namename (see GPUs on Compute Engine).

gpu_partition_size

string

Size of partitions to create on the GPU. Valid values are described in the NVIDIA mig user guide.

GkeNodePoolAutoscalingConfig

GkeNodePoolAutoscaling contains information the cluster autoscaler needs to adjust the size of the node pool to the current cluster usage.

Fields
min_node_count

int32

The minimum number of nodes in the node pool. Must be >= 0 and <= max_node_count.

max_node_count

int32

The maximum number of nodes in the node pool. Must be >= min_node_count, and must be > 0. Note: Quota must be sufficient to scale up the cluster.

GkeNodePoolTarget

GKE node pools that Dataproc workloads run on.

Fields
node_pool

string

Required. The target GKE node pool. Format: 'projects/{project}/locations/{location}/clusters/{cluster}/nodePools/{node_pool}'

roles[]

Role

Required. The roles associated with the GKE node pool.

node_pool_config

GkeNodePoolConfig

Input only. The configuration for the GKE node pool.

If specified, Dataproc attempts to create a node pool with the specified shape. If one with the same name already exists, it is verified against all specified fields. If a field differs, the virtual cluster creation will fail.

If omitted, any node pool with the specified name is used. If a node pool with the specified name does not exist, Dataproc create a node pool with default values.

This is an input only field. It will not be returned by the API.

Role

Role specifies the tasks that will run on the node pool. Roles can be specific to workloads. Exactly one GkeNodePoolTarget within the virtual cluster must have the DEFAULT role, which is used to run all workloads that are not associated with a node pool.

Enums
ROLE_UNSPECIFIED Role is unspecified.
DEFAULT At least one node pool must have the DEFAULT role. Work assigned to a role that is not associated with a node pool is assigned to the node pool with the DEFAULT role. For example, work assigned to the CONTROLLER role will be assigned to the node pool with the DEFAULT role if no node pool has the CONTROLLER role.
CONTROLLER Run work associated with the Dataproc control plane (for example, controllers and webhooks). Very low resource requirements.
SPARK_DRIVER Run work associated with a Spark driver of a job.
SPARK_EXECUTOR Run work associated with a Spark executor of a job.

HadoopJob

A Dataproc job for running Apache Hadoop MapReduce jobs on Apache Hadoop YARN.

Fields
args[]

string

Optional. The arguments to pass to the driver. Do not include arguments, such as -libjars or -Dfoo=bar, that can be set as job properties, since a collision might occur that causes an incorrect job submission.

jar_file_uris[]

string

Optional. Jar file URIs to add to the CLASSPATHs of the Hadoop driver and tasks.

file_uris[]

string

Optional. HCFS (Hadoop Compatible Filesystem) URIs of files to be copied to the working directory of Hadoop drivers and distributed tasks. Useful for naively parallel tasks.

archive_uris[]

string

Optional. HCFS URIs of archives to be extracted in the working directory of Hadoop drivers and tasks. Supported file types: .jar, .tar, .tar.gz, .tgz, or .zip.

properties

map<string, string>

Optional. A mapping of property names to values, used to configure Hadoop. Properties that conflict with values set by the Dataproc API might be overwritten. Can include properties set in /etc/hadoop/conf/*-site and classes in user code.

logging_config

LoggingConfig

Optional. The runtime log config for job execution.

Union field driver. Required. Indicates the location of the driver's main class. Specify either the jar file that contains the main class or the main class name. To specify both, add the jar file to jar_file_uris, and then specify the main class name in this property. driver can be only one of the following:
main_jar_file_uri

string

The HCFS URI of the jar file containing the main class. Examples: 'gs://foo-bucket/analytics-binaries/extract-useful-metrics-mr.jar' 'hdfs:/tmp/test-samples/custom-wordcount.jar' 'file:///home/usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar'

main_class

string

The name of the driver's main class. The jar file containing the class must be in the default CLASSPATH or specified in jar_file_uris.

HiveJob

A Dataproc job for running Apache Hive queries on YARN.

Fields
continue_on_failure

bool

Optional. Whether to continue executing queries if a query fails. The default value is false. Setting to true can be useful when executing independent parallel queries.

script_variables

map<string, string>

Optional. Mapping of query variable names to values (equivalent to the Hive command: SET name="value";).

properties

map<string, string>

Optional. A mapping of property names and values, used to configure Hive. Properties that conflict with values set by the Dataproc API might be overwritten. Can include properties set in /etc/hadoop/conf/*-site.xml, /etc/hive/conf/hive-site.xml, and classes in user code.

jar_file_uris[]

string

Optional. HCFS URIs of jar files to add to the CLASSPATH of the Hive server and Hadoop MapReduce (MR) tasks. Can contain Hive SerDes and UDFs.

Union field queries. Required. The sequence of Hive queries to execute, specified as either an HCFS file URI or a list of queries. queries can be only one of the following:
query_file_uri

string

The HCFS URI of the script that contains Hive queries.

query_list

QueryList

A list of queries.

IdentityConfig

Identity related configuration, including service account based secure multi-tenancy user mappings.

Fields
user_service_account_mapping

map<string, string>

Required. Map of user to service account.

InstanceFlexibilityPolicy

Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.

Fields
instance_selection_list[]

InstanceSelection

Optional. List of instance selection options that the group will use when creating new VMs.

instance_selection_results[]

InstanceSelectionResult

Output only. A list of instance selection results in the group.

InstanceSelection

Defines machines types and a rank to which the machines types belong.

Fields
machine_types[]

string

Optional. Full machine-type names, e.g. "n1-standard-16".

rank

int32

Optional. Preference of this instance selection. Lower number means higher preference. Dataproc will first try to create a VM based on the machine-type with priority rank and fallback to next rank based on availability. Machine types and instance selections with the same priority have the same preference.

InstanceSelectionResult

Defines a mapping from machine types to the number of VMs that are created with each machine type.

Fields
machine_type

string

Output only. Full machine-type names, e.g. "n1-standard-16".

vm_count

int32

Output only. Number of VM provisioned with the machine_type.

InstanceGroupAutoscalingPolicyConfig

Configuration for the size bounds of an instance group, including its proportional size to other groups.

Fields
min_instances

int32

Optional. Minimum number of instances for this group.

Primary workers - Bounds: [2, max_instances]. Default: 2. Secondary workers - Bounds: [0, max_instances]. Default: 0.

max_instances

int32

Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.

Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.

weight

int32

Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.

The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.

If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.

InstanceGroupConfig

The config settings for Compute Engine resources in an instance group, such as a master or worker group.

Fields
num_instances

int32

Optional. The number of VM instances in the instance group. For HA cluster master_config groups, must be set to 3. For standard cluster master_config groups, must be set to 1.

instance_names[]

string

Output only. The list of instance names. Dataproc derives the names from cluster_name, num_instances, and the instance group.

image_uri

string

Optional. The Compute Engine image resource used for cluster instances.

The URI can represent an image or image family.

Image examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/[image-id]
  • projects/[project_id]/global/images/[image-id]
  • image-id

Image family examples. Dataproc will use the most recent image from the family:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/family/[custom-image-family-name]
  • projects/[project_id]/global/images/family/[custom-image-family-name]

If the URI is unspecified, it will be inferred from SoftwareConfig.image_version or the system default.

machine_type_uri

string

Optional. The Compute Engine machine type used for cluster instances.

A full URL, partial URI, or short name are valid. Examples:

  • https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/machineTypes/n1-standard-2
  • projects/[project_id]/zones/[zone]/machineTypes/n1-standard-2
  • n1-standard-2

Auto Zone Exception: If you are using the Dataproc Auto Zone Placement feature, you must use the short name of the machine type resource, for example, n1-standard-2.

disk_config

DiskConfig

Optional. Disk option config settings.

is_preemptible

bool

Output only. Specifies that this instance group contains preemptible instances.

preemptibility

Preemptibility

Optional. Specifies the preemptibility of the instance group.

The default value for master and worker groups is NON_PREEMPTIBLE. This default cannot be changed.

The default value for secondary instances is PREEMPTIBLE.

managed_group_config

ManagedGroupConfig

Output only. The config for Compute Engine Instance Group Manager that manages this group. This is only used for preemptible instance groups.

accelerators[]

AcceleratorConfig

Optional. The Compute Engine accelerator configuration for these instances.

min_cpu_platform

string

Optional. Specifies the minimum cpu platform for the Instance Group. See Dataproc -> Minimum CPU Platform.

min_num_instances

int32

Optional. The minimum number of primary worker instances to create. If min_num_instances is set, cluster creation will succeed if the number of primary workers created is at least equal to the min_num_instances number.

Example: Cluster creation request with num_instances = 5 and min_num_instances = 3:

  • If 4 VMs are created and 1 instance fails, the failed VM is deleted. The cluster is resized to 4 instances and placed in a RUNNING state.
  • If 2 instances are created and 3 instances fail, the cluster in placed in an ERROR state. The failed VMs are not deleted.
instance_flexibility_policy

InstanceFlexibilityPolicy

Optional. Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.

startup_config

StartupConfig

Optional. Configuration to handle the startup of instances during cluster create and update process.

Preemptibility

Controls the use of preemptible instances within the group.

Enums
PREEMPTIBILITY_UNSPECIFIED Preemptibility is unspecified, the system will choose the appropriate setting for each instance group.
NON_PREEMPTIBLE

Instances are non-preemptible.

This option is allowed for all instance groups and is the only valid value for Master and Worker instance groups.

PREEMPTIBLE

Instances are preemptible.

This option is allowed only for secondary worker groups.

SPOT

Instances are Spot VMs.

This option is allowed only for secondary worker groups. Spot VMs are the latest version of preemptible VMs, and provide additional features.

InstantiateInlineWorkflowTemplateRequest

A request to instantiate an inline workflow template.

Fields
parent

string

Required. The resource name of the region or location, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.workflowTemplates,instantiateinline, the resource name of the region has the following format: projects/{project_id}/regions/{region}

  • For projects.locations.workflowTemplates.instantiateinline, the resource name of the location has the following format: projects/{project_id}/locations/{location}

Authorization requires the following IAM permission on the specified resource parent:

  • dataproc.workflowTemplates.instantiateInline
template

WorkflowTemplate

Required. The workflow template to instantiate.

request_id

string

Optional. A tag that prevents multiple concurrent workflow instances with the same tag from running. This mitigates risk of concurrent instances started due to retries.

It is recommended to always set this value to a UUID.

The tag must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.

InstantiateWorkflowTemplateRequest

A request to instantiate a workflow template.

Fields
name

string

Required. The resource name of the workflow template, as described in https://cloud.google.com/apis/design/resource_names.

  • For projects.regions.workflowTemplates.instantiate, the resource name of the template has the following format: projects/{project_id}/regions/{region}/workflowTemplates/{template_id}

  • For projects.locations.workflowTemplates.instantiate, the resource name of the template has the following format: projects/{project_id}/locations/{location}/workflowTemplates/{template_id}

Authorization requires the following IAM permission on the specified resource name:

  • dataproc.workflowTemplates.instantiate
version

int32

Optional. The version of workflow template to instantiate. If specified, the workflow will be instantiated only if the current version of the workflow template has the supplied version.

This option cannot be used to instantiate a previous version of workflow template.

request_id

string

Optional. A tag that prevents multiple concurrent workflow instances with the same tag from running. This mitigates risk of concurrent instances started due to retries.

It is recommended to always set this value to a UUID.

The tag must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.

parameters

map<string, string>

Optional. Map from parameter names to values that should be used for those parameters. Values ma