---
title: Getting Started with Datadog
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Infrastructure > Datadog Resource Catalog
---

# gcp_dataproc_workflow_template{% #gcp_dataproc_workflow_template %}

## `ancestors`{% #ancestors %}

**Type**: `UNORDERED_LIST_STRING`

## `create_time`{% #create_time %}

**Type**: `TIMESTAMP`**Provider name**: `createTime`**Description**: Output only. The time template was created.

## `dag_timeout`{% #dag_timeout %}

**Type**: `STRING`**Provider name**: `dagTimeout`**Description**: Optional. Timeout duration for the DAG of jobs, expressed in seconds (see JSON representation of duration ([https://developers.google.com/protocol-buffers/docs/proto3#json))](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29). The timeout duration must be from 10 minutes ("600s") to 24 hours ("86400s"). The timer begins when the first job is submitted. If the workflow is running at the end of the timeout period, any remaining jobs are cancelled, the workflow is ended, and if the workflow was running on a managed cluster, the cluster is deleted.

## `encryption_config`{% #encryption_config %}

**Type**: `STRUCT`**Provider name**: `encryptionConfig`**Description**: Optional. Encryption settings for encrypting workflow template job arguments.

- `kms_key`**Type**: `STRING`**Provider name**: `kmsKey`**Description**: Optional. The Cloud KMS key name to use for encrypting workflow template job arguments.When this this key is provided, the following workflow template job arguments ([https://cloud.google.com/dataproc/docs/concepts/workflows/use-workflows#adding_jobs_to_a_template)](https://cloud.google.com/dataproc/docs/concepts/workflows/use-workflows#adding_jobs_to_a_template%29), if present, are CMEK encrypted ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#use_cmek_with_workflow_template_data)](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#use_cmek_with_workflow_template_data%29): FlinkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/FlinkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/FlinkJob)) HadoopJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/HadoopJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/HadoopJob)) SparkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkJob)) SparkRJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkRJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkRJob)) PySparkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PySparkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PySparkJob)) SparkSqlJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkSqlJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkSqlJob)) scriptVariables and queryList.queries HiveJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/HiveJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/HiveJob)) scriptVariables and queryList.queries PigJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PigJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PigJob)) scriptVariables and queryList.queries PrestoJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PrestoJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PrestoJob)) scriptVariables and queryList.queries

## `id`{% #id %}

**Type**: `STRING`**Provider name**: `id`

## `jobs`{% #jobs %}

**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `jobs`**Description**: Required. The Directed Acyclic Graph of Jobs to submit.

- `flink_job`**Type**: `STRUCT`**Provider name**: `flinkJob`**Description**: Optional. Job is a Flink job.
  - `args`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `args`**Description**: 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`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Flink driver and tasks.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `main_class`**Type**: `STRING`**Provider name**: `mainClass`**Description**: 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.

  - `main_jar_file_uri`**Type**: `STRING`**Provider name**: `mainJarFileUri`**Description**: The HCFS URI of the jar file that contains the main class.

  - `savepoint_uri`**Type**: `STRING`**Provider name**: `savepointUri`**Description**: Optional. HCFS URI of the savepoint, which contains the last saved progress for starting the current job.
- `hadoop_job`**Type**: `STRUCT`**Provider name**: `hadoopJob`**Description**: Optional. Job is a Hadoop job.
  - `archive_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `archiveUris`**Description**: 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.

  - `args`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `args`**Description**: 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.

  - `file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `fileUris`**Description**: 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.

  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. Jar file URIs to add to the CLASSPATHs of the Hadoop driver and tasks.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `main_class`**Type**: `STRING`**Provider name**: `mainClass`**Description**: 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.

  - `main_jar_file_uri`**Type**: `STRING`**Provider name**: `mainJarFileUri`**Description**: 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'
- `hive_job`**Type**: `STRUCT`**Provider name**: `hiveJob`**Description**: Optional. Job is a Hive job.
  - `continue_on_failure`**Type**: `BOOLEAN`**Provider name**: `continueOnFailure`**Description**: 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.
  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: 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.
  - `query_file_uri`**Type**: `STRING`**Provider name**: `queryFileUri`**Description**: The HCFS URI of the script that contains Hive queries.
  - `query_list`**Type**: `STRUCT`**Provider name**: `queryList`**Description**: A list of queries.
    - `queries`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `queries`**Description**: Required. The queries to execute. You do not need to end a query expression with a semicolon. Multiple queries can be specified in one string by separating each with a semicolon. Here is an example of a Dataproc API snippet that uses a QueryList to specify a HiveJob: "hiveJob": { "queryList": { "queries": [ "query1", "query2", "query3;query4", ] } }
- `pig_job`**Type**: `STRUCT`**Provider name**: `pigJob`**Description**: Optional. Job is a Pig job.
  - `continue_on_failure`**Type**: `BOOLEAN`**Provider name**: `continueOnFailure`**Description**: 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.

  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. HCFS URIs of jar files to add to the CLASSPATH of the Pig Client and Hadoop MapReduce (MR) tasks. Can contain Pig UDFs.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `query_file_uri`**Type**: `STRING`**Provider name**: `queryFileUri`**Description**: The HCFS URI of the script that contains the Pig queries.

  - `query_list`**Type**: `STRUCT`**Provider name**: `queryList`**Description**: A list of queries.

    - `queries`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `queries`**Description**: Required. The queries to execute. You do not need to end a query expression with a semicolon. Multiple queries can be specified in one string by separating each with a semicolon. Here is an example of a Dataproc API snippet that uses a QueryList to specify a HiveJob: "hiveJob": { "queryList": { "queries": [ "query1", "query2", "query3;query4", ] } }
- `prerequisite_step_ids`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `prerequisiteStepIds`**Description**: Optional. The optional list of prerequisite job step_ids. If not specified, the job will start at the beginning of workflow.
- `presto_job`**Type**: `STRUCT`**Provider name**: `prestoJob`**Description**: Optional. Job is a Presto job.
  - `client_tags`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `clientTags`**Description**: Optional. Presto client tags to attach to this query

  - `continue_on_failure`**Type**: `BOOLEAN`**Provider name**: `continueOnFailure`**Description**: 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.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `output_format`**Type**: `STRING`**Provider name**: `outputFormat`**Description**: Optional. The format in which query output will be displayed. See the Presto documentation for supported output formats

  - `query_file_uri`**Type**: `STRING`**Provider name**: `queryFileUri`**Description**: The HCFS URI of the script that contains SQL queries.

  - `query_list`**Type**: `STRUCT`**Provider name**: `queryList`**Description**: A list of queries.

    - `queries`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `queries`**Description**: Required. The queries to execute. You do not need to end a query expression with a semicolon. Multiple queries can be specified in one string by separating each with a semicolon. Here is an example of a Dataproc API snippet that uses a QueryList to specify a HiveJob: "hiveJob": { "queryList": { "queries": [ "query1", "query2", "query3;query4", ] } }
- `pyspark_job`**Type**: `STRUCT`**Provider name**: `pysparkJob`**Description**: Optional. Job is a PySpark job.
  - `archive_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `archiveUris`**Description**: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.

  - `args`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `args`**Description**: 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 may occur that causes an incorrect job submission.

  - `file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `fileUris`**Description**: Optional. HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `main_python_file_uri`**Type**: `STRING`**Provider name**: `mainPythonFileUri`**Description**: Required. The HCFS URI of the main Python file to use as the driver. Must be a .py file.

  - `python_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `pythonFileUris`**Description**: Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip.
- `scheduling`**Type**: `STRUCT`**Provider name**: `scheduling`**Description**: Optional. Job scheduling configuration.
  - `max_failures_per_hour`**Type**: `INT32`**Provider name**: `maxFailuresPerHour`**Description**: Optional. Maximum number of times per hour a driver can be restarted as a result of driver exiting with non-zero code before job is reported failed.A job might be reported as thrashing if the driver exits with a non-zero code four times within a 10-minute window.Maximum value is 10.Note: This restartable job option is not supported in Dataproc workflow templates ([https://cloud.google.com/dataproc/docs/concepts/workflows/using-workflows#adding_jobs_to_a_template)](https://cloud.google.com/dataproc/docs/concepts/workflows/using-workflows#adding_jobs_to_a_template%29).
  - `max_failures_total`**Type**: `INT32`**Provider name**: `maxFailuresTotal`**Description**: Optional. Maximum total number of times a driver can be restarted as a result of the driver exiting with a non-zero code. After the maximum number is reached, the job will be reported as failed.Maximum value is 240.Note: Currently, this restartable job option is not supported in Dataproc workflow templates ([https://cloud.google.com/dataproc/docs/concepts/workflows/using-workflows#adding_jobs_to_a_template)](https://cloud.google.com/dataproc/docs/concepts/workflows/using-workflows#adding_jobs_to_a_template%29).
- `spark_job`**Type**: `STRUCT`**Provider name**: `sparkJob`**Description**: Optional. Job is a Spark job.
  - `archive_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `archiveUris`**Description**: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.

  - `args`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `args`**Description**: 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 may occur that causes an incorrect job submission.

  - `file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `fileUris`**Description**: Optional. HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Spark driver and tasks.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `main_class`**Type**: `STRING`**Provider name**: `mainClass`**Description**: The name of the driver's main class. The jar file that contains the class must be in the default CLASSPATH or specified in SparkJob.jar_file_uris.

  - `main_jar_file_uri`**Type**: `STRING`**Provider name**: `mainJarFileUri`**Description**: The HCFS URI of the jar file that contains the main class.
- `spark_r_job`**Type**: `STRUCT`**Provider name**: `sparkRJob`**Description**: Optional. Job is a SparkR job.
  - `archive_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `archiveUris`**Description**: Optional. HCFS URIs of archives to be extracted into the working directory of each executor. Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.

  - `args`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `args`**Description**: 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 may occur that causes an incorrect job submission.

  - `file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `fileUris`**Description**: Optional. HCFS URIs of files to be placed in the working directory of each executor. Useful for naively parallel tasks.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `main_r_file_uri`**Type**: `STRING`**Provider name**: `mainRFileUri`**Description**: Required. The HCFS URI of the main R file to use as the driver. Must be a .R file.
- `spark_sql_job`**Type**: `STRUCT`**Provider name**: `sparkSqlJob`**Description**: Optional. Job is a SparkSql job.
  - `jar_file_uris`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `jarFileUris`**Description**: Optional. HCFS URIs of jar files to be added to the Spark CLASSPATH.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `query_file_uri`**Type**: `STRING`**Provider name**: `queryFileUri`**Description**: The HCFS URI of the script that contains SQL queries.

  - `query_list`**Type**: `STRUCT`**Provider name**: `queryList`**Description**: A list of queries.

    - `queries`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `queries`**Description**: Required. The queries to execute. You do not need to end a query expression with a semicolon. Multiple queries can be specified in one string by separating each with a semicolon. Here is an example of a Dataproc API snippet that uses a QueryList to specify a HiveJob: "hiveJob": { "queryList": { "queries": [ "query1", "query2", "query3;query4", ] } }
- `step_id`**Type**: `STRING`**Provider name**: `stepId`**Description**: Required. The step id. The id must be unique among all jobs within the template.The step id is used as prefix for job id, as job goog-dataproc-workflow-step-id label, and in prerequisiteStepIds field from other steps.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.
- `trino_job`**Type**: `STRUCT`**Provider name**: `trinoJob`**Description**: Optional. Job is a Trino job.
  - `client_tags`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `clientTags`**Description**: Optional. Trino client tags to attach to this query

  - `continue_on_failure`**Type**: `BOOLEAN`**Provider name**: `continueOnFailure`**Description**: 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.

  - `logging_config`**Type**: `STRUCT`**Provider name**: `loggingConfig`**Description**: Optional. The runtime log config for job execution.

  - `output_format`**Type**: `STRING`**Provider name**: `outputFormat`**Description**: Optional. The format in which query output will be displayed. See the Trino documentation for supported output formats

  - `query_file_uri`**Type**: `STRING`**Provider name**: `queryFileUri`**Description**: The HCFS URI of the script that contains SQL queries.

  - `query_list`**Type**: `STRUCT`**Provider name**: `queryList`**Description**: A list of queries.

    - `queries`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `queries`**Description**: Required. The queries to execute. You do not need to end a query expression with a semicolon. Multiple queries can be specified in one string by separating each with a semicolon. Here is an example of a Dataproc API snippet that uses a QueryList to specify a HiveJob: "hiveJob": { "queryList": { "queries": [ "query1", "query2", "query3;query4", ] } }

## `labels`{% #labels %}

**Type**: `UNORDERED_LIST_STRING`

## `name`{% #name %}

**Type**: `STRING`**Provider name**: `name`**Description**: Output only. The resource name of the workflow template, as described in [https://cloud.google.com/apis/design/resource_names](https://cloud.google.com/apis/design/resource_names). For projects.regions.workflowTemplates, the resource name of the template has the following format: projects/{project_id}/regions/{region}/workflowTemplates/{template_id} For projects.locations.workflowTemplates, the resource name of the template has the following format: projects/{project_id}/locations/{location}/workflowTemplates/{template_id}

## `organization_id`{% #organization_id %}

**Type**: `STRING`

## `parameters`{% #parameters %}

**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `parameters`**Description**: Optional. Template parameters whose values are substituted into the template. Values for parameters must be provided when the template is instantiated.

- `description`**Type**: `STRING`**Provider name**: `description`**Description**: Optional. Brief description of the parameter. Must not exceed 1024 characters.
- `fields`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `fields`**Description**: Required. Paths to all fields that the parameter replaces. A field is allowed to appear in at most one parameter's list of field paths.A field path is similar in syntax to a google.protobuf.FieldMask. For example, a field path that references the zone field of a workflow template's cluster selector would be specified as placement.clusterSelector.zone.Also, field paths can reference fields using the following syntax: Values in maps can be referenced by key: labels'key' placement.clusterSelector.clusterLabels'key' placement.managedCluster.labels'key' placement.clusterSelector.clusterLabels'key' jobs'step-id'.labels'key' Jobs in the jobs list can be referenced by step-id: jobs'step-id'.hadoopJob.mainJarFileUri jobs'step-id'.hiveJob.queryFileUri jobs'step-id'.pySparkJob.mainPythonFileUri jobs'step-id'.hadoopJob.jarFileUris0 jobs'step-id'.hadoopJob.archiveUris0 jobs'step-id'.hadoopJob.fileUris0 jobs'step-id'.pySparkJob.pythonFileUris0 Items in repeated fields can be referenced by a zero-based index: jobs'step-id'.sparkJob.args0 Other examples: jobs'step-id'.hadoopJob.properties'key' jobs'step-id'.hadoopJob.args0 jobs'step-id'.hiveJob.scriptVariables'key' jobs'step-id'.hadoopJob.mainJarFileUri placement.clusterSelector.zoneIt may not be possible to parameterize maps and repeated fields in their entirety since only individual map values and individual items in repeated fields can be referenced. For example, the following field paths are invalid: placement.clusterSelector.clusterLabels jobs'step-id'.sparkJob.args
- `name`**Type**: `STRING`**Provider name**: `name`**Description**: Required. Parameter name. The parameter name is used as the key, and paired with the parameter value, which are passed to the template when the template is instantiated. The name must contain only capital letters (A-Z), numbers (0-9), and underscores (_), and must not start with a number. The maximum length is 40 characters.
- `validation`**Type**: `STRUCT`**Provider name**: `validation`**Description**: Optional. Validation rules to be applied to this parameter's value.
  - `regex`**Type**: `STRUCT`**Provider name**: `regex`**Description**: Validation based on regular expressions.
    - `regexes`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `regexes`**Description**: Required. RE2 regular expressions used to validate the parameter's value. The value must match the regex in its entirety (substring matches are not sufficient).
  - `values`**Type**: `STRUCT`**Provider name**: `values`**Description**: Validation based on a list of allowed values.
    - `values`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `values`**Description**: Required. List of allowed values for the parameter.

## `parent`{% #parent %}

**Type**: `STRING`

## `placement`{% #placement %}

**Type**: `STRUCT`**Provider name**: `placement`**Description**: Required. WorkflowTemplate scheduling information.

- `cluster_selector`**Type**: `STRUCT`**Provider name**: `clusterSelector`**Description**: Optional. A selector that chooses target cluster for jobs based on metadata.The selector is evaluated at the time each job is submitted.
  - `zone`**Type**: `STRING`**Provider name**: `zone`**Description**: 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.
- `managed_cluster`**Type**: `STRUCT`**Provider name**: `managedCluster`**Description**: A cluster that is managed by the workflow.
  - `cluster_name`**Type**: `STRING`**Provider name**: `clusterName`**Description**: Required. The cluster name prefix. A unique cluster name will be formed by appending a random suffix.The name must contain only lower-case letters (a-z), numbers (0-9), and hyphens (-). Must begin with a letter. Cannot begin or end with hyphen. Must consist of between 2 and 35 characters.
  - `config`**Type**: `STRUCT`**Provider name**: `config`**Description**: Required. The cluster configuration.
    - `autoscaling_config`**Type**: `STRUCT`**Provider name**: `autoscalingConfig`**Description**: Optional. Autoscaling config for the policy associated with the cluster. Cluster does not autoscale if this field is unset.
      - `policy_uri`**Type**: `STRING`**Provider name**: `policyUri`**Description**: 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]](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.
    - `auxiliary_node_groups`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `auxiliaryNodeGroups`**Description**: Optional. The node group settings.
      - `node_group`**Type**: `STRUCT`**Provider name**: `nodeGroup`**Description**: Required. Node group configuration.
        - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The Node group resource name ([https://aip.dev/122)](https://aip.dev/122%29).
        - `node_group_config`**Type**: `STRUCT`**Provider name**: `nodeGroupConfig`**Description**: Optional. The node group instance group configuration.
          - `accelerators`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `accelerators`**Description**: Optional. The Compute Engine accelerator configuration for these instances.
            - `accelerator_count`**Type**: `INT32`**Provider name**: `acceleratorCount`**Description**: The number of the accelerator cards of this type exposed to this instance.
            - `accelerator_type_uri`**Type**: `STRING`**Provider name**: `acceleratorTypeUri`**Description**: Full URL, partial URI, or short name of the accelerator type resource to expose to this instance. See Compute Engine AcceleratorTypes ([https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes).Examples](https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes%29.Examples): [https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4) projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4 nvidia-tesla-t4Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the accelerator type resource, for example, nvidia-tesla-t4.
          - `disk_config`**Type**: `STRUCT`**Provider name**: `diskConfig`**Description**: Optional. Disk option config settings.
            - `boot_disk_provisioned_iops`**Type**: `INT64`**Provider name**: `bootDiskProvisionedIops`**Description**: Optional. Indicates how many IOPS to provision for the disk. This sets the number of I/O operations per second that the disk can handle. This field is supported only if boot_disk_type is hyperdisk-balanced.
            - `boot_disk_provisioned_throughput`**Type**: `INT64`**Provider name**: `bootDiskProvisionedThroughput`**Description**: Optional. Indicates how much throughput to provision for the disk. This sets the number of throughput mb per second that the disk can handle. Values must be greater than or equal to 1. This field is supported only if boot_disk_type is hyperdisk-balanced.
            - `boot_disk_size_gb`**Type**: `INT32`**Provider name**: `bootDiskSizeGb`**Description**: Optional. Size in GB of the boot disk (default is 500GB).
            - `boot_disk_type`**Type**: `STRING`**Provider name**: `bootDiskType`**Description**: 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 ([https://cloud.google.com/compute/docs/disks#disk-types)](https://cloud.google.com/compute/docs/disks#disk-types%29).
            - `local_ssd_interface`**Type**: `STRING`**Provider name**: `localSsdInterface`**Description**: 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 ([https://cloud.google.com/compute/docs/disks/local-ssd#performance)](https://cloud.google.com/compute/docs/disks/local-ssd#performance%29).
            - `num_local_ssds`**Type**: `INT32`**Provider name**: `numLocalSsds`**Description**: 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 ([https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html](https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html)) 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.
          - `image_uri`**Type**: `STRING`**Provider name**: `imageUri`**Description**: 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]](https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/[image-id]) projects/[project_id]/global/images/[image-id] image-idImage 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]](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.
          - `instance_flexibility_policy`**Type**: `STRUCT`**Provider name**: `instanceFlexibilityPolicy`**Description**: Optional. Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.
            - `instance_selection_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionList`**Description**: Optional. List of instance selection options that the group will use when creating new VMs.
              - `machine_types`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `machineTypes`**Description**: Optional. Full machine-type names, e.g. "n1-standard-16".
              - `rank`**Type**: `INT32`**Provider name**: `rank`**Description**: 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.
            - `instance_selection_results`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionResults`**Description**: Output only. A list of instance selection results in the group.
              - `machine_type`**Type**: `STRING`**Provider name**: `machineType`**Description**: Output only. Full machine-type names, e.g. "n1-standard-16".
              - `vm_count`**Type**: `INT32`**Provider name**: `vmCount`**Description**: Output only. Number of VM provisioned with the machine_type.
            - `provisioning_model_mix`**Type**: `STRUCT`**Provider name**: `provisioningModelMix`**Description**: Optional. Defines how the Group selects the provisioning model to ensure required reliability.
              - `standard_capacity_base`**Type**: `INT32`**Provider name**: `standardCapacityBase`**Description**: Optional. The base capacity that will always use Standard VMs to avoid risk of more preemption than the minimum capacity you need. Dataproc will create only standard VMs until it reaches standard_capacity_base, then it will start using standard_capacity_percent_above_base to mix Spot with Standard VMs. eg. If 15 instances are requested and standard_capacity_base is 5, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances.
              - `standard_capacity_percent_above_base`**Type**: `INT32`**Provider name**: `standardCapacityPercentAboveBase`**Description**: Optional. The percentage of target capacity that should use Standard VM. The remaining percentage will use Spot VMs. The percentage applies only to the capacity above standard_capacity_base. eg. If 15 instances are requested and standard_capacity_base is 5 and standard_capacity_percent_above_base is 30, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances. The mix will be 30% standard and 70% spot.
          - `instance_names`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `instanceNames`**Description**: Output only. The list of instance names. Dataproc derives the names from cluster_name, num_instances, and the instance group.
          - `instance_references`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceReferences`**Description**: Output only. List of references to Compute Engine instances.
            - `instance_id`**Type**: `STRING`**Provider name**: `instanceId`**Description**: The unique identifier of the Compute Engine instance.
            - `instance_name`**Type**: `STRING`**Provider name**: `instanceName`**Description**: The user-friendly name of the Compute Engine instance.
            - `public_ecies_key`**Type**: `STRING`**Provider name**: `publicEciesKey`**Description**: The public ECIES key used for sharing data with this instance.
            - `public_key`**Type**: `STRING`**Provider name**: `publicKey`**Description**: The public RSA key used for sharing data with this instance.
          - `is_preemptible`**Type**: `BOOLEAN`**Provider name**: `isPreemptible`**Description**: Output only. Specifies that this instance group contains preemptible instances.
          - `machine_type_uri`**Type**: `STRING`**Provider name**: `machineTypeUri`**Description**: 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](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-2Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the machine type resource, for example, n1-standard-2.
          - `managed_group_config`**Type**: `STRUCT`**Provider name**: `managedGroupConfig`**Description**: Output only. The config for Compute Engine Instance Group Manager that manages this group. This is only used for preemptible instance groups.
            - `instance_group_manager_name`**Type**: `STRING`**Provider name**: `instanceGroupManagerName`**Description**: Output only. The name of the Instance Group Manager for this group.
            - `instance_group_manager_uri`**Type**: `STRING`**Provider name**: `instanceGroupManagerUri`**Description**: Output only. The partial URI to the instance group manager for this group. E.g. projects/my-project/regions/us-central1/instanceGroupManagers/my-igm.
            - `instance_template_name`**Type**: `STRING`**Provider name**: `instanceTemplateName`**Description**: Output only. The name of the Instance Template used for the Managed Instance Group.
          - `min_cpu_platform`**Type**: `STRING`**Provider name**: `minCpuPlatform`**Description**: Optional. Specifies the minimum cpu platform for the Instance Group. See Dataproc -> Minimum CPU Platform ([https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu)](https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu%29).
          - `min_num_instances`**Type**: `INT32`**Provider name**: `minNumInstances`**Description**: 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.
          - `num_instances`**Type**: `INT32`**Provider name**: `numInstances`**Description**: 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.
          - `preemptibility`**Type**: `STRING`**Provider name**: `preemptibility`**Description**: 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.**Possible values**:
            - `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 ([https://cloud.google.com/compute/docs/instances/preemptible).This](https://cloud.google.com/compute/docs/instances/preemptible%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups.
            - `SPOT` - Instances are Spot VMs ([https://cloud.google.com/compute/docs/instances/spot).This](https://cloud.google.com/compute/docs/instances/spot%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups. Spot VMs are the latest version of preemptible VMs ([https://cloud.google.com/compute/docs/instances/preemptible)](https://cloud.google.com/compute/docs/instances/preemptible%29), and provide additional features.
          - `startup_config`**Type**: `STRUCT`**Provider name**: `startupConfig`**Description**: Optional. Configuration to handle the startup of instances during cluster create and update process.
            - `required_registration_fraction`**Type**: `DOUBLE`**Provider name**: `requiredRegistrationFraction`**Description**: Optional. The config setting to enable cluster creation/ updation to be successful only after required_registration_fraction of instances are up and running. This configuration is applicable to only secondary workers for now. The cluster will fail if required_registration_fraction of instances are not available. This will include instance creation, agent registration, and service registration (if enabled).
        - `roles`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `roles`**Description**: Required. Node group roles.
      - `node_group_id`**Type**: `STRING`**Provider name**: `nodeGroupId`**Description**: 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.
    - `config_bucket`**Type**: `STRING`**Provider name**: `configBucket`**Description**: 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 ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket))](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket%29%29). This field requires a Cloud Storage bucket name, not a gs://… URI to a Cloud Storage bucket.
    - `dataproc_metric_config`**Type**: `STRUCT`**Provider name**: `dataprocMetricConfig`**Description**: Optional. The config for Dataproc metrics.
      - `metrics`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `metrics`**Description**: Required. Metrics sources to enable.
        - `metric_overrides`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `metricOverrides`**Description**: Optional. Specify one or more Custom metrics ([https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics](https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics)) to collect for the metric course (for the SPARK metric source (any Spark metric ([https://spark.apache.org/docs/latest/monitoring.html#metrics](https://spark.apache.org/docs/latest/monitoring.html#metrics)) 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 and YARN metric sources are enabled, and overrides are provided for Spark metrics only, all YARN metrics are collected.
        - `metric_source`**Type**: `STRING`**Provider name**: `metricSource`**Description**: Required. A standard set of metrics is collected unless metricOverrides are specified for the metric source (see Custom metrics ([https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics](https://cloud.google.com/dataproc/docs/guides/dataproc-metrics#custom_metrics)) for more information).**Possible values**:
          - `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
          - `FLINK` - flink metric source
    - `encryption_config`**Type**: `STRUCT`**Provider name**: `encryptionConfig`**Description**: Optional. Encryption settings for the cluster.
      - `gce_pd_kms_key_name`**Type**: `STRING`**Provider name**: `gcePdKmsKeyName`**Description**: 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 ([https://cloud.google.com//dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#use_cmek_with_cluster_data](https://cloud.google.com//dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#use_cmek_with_cluster_data)) for more information.
      - `kms_key`**Type**: `STRING`**Provider name**: `kmsKey`**Description**: Optional. The Cloud KMS key resource name to use for cluster persistent disk and job argument encryption. See Use CMEK with cluster data ([https://cloud.google.com//dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#use_cmek_with_cluster_data](https://cloud.google.com//dataproc/docs/concepts/configuring-clusters/customer-managed-encryption#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: FlinkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/FlinkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/FlinkJob)) HadoopJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/HadoopJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/HadoopJob)) SparkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkJob)) SparkRJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkRJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkRJob)) PySparkJob args ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PySparkJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PySparkJob)) SparkSqlJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkSqlJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/SparkSqlJob)) scriptVariables and queryList.queries HiveJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/HiveJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/HiveJob)) scriptVariables and queryList.queries PigJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PigJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PigJob)) scriptVariables and queryList.queries PrestoJob ([https://cloud.google.com/dataproc/docs/reference/rest/v1/PrestoJob](https://cloud.google.com/dataproc/docs/reference/rest/v1/PrestoJob)) scriptVariables and queryList.queries
    - `endpoint_config`**Type**: `STRUCT`**Provider name**: `endpointConfig`**Description**: Optional. Port/endpoint configuration for this cluster
      - `enable_http_port_access`**Type**: `BOOLEAN`**Provider name**: `enableHttpPortAccess`**Description**: Optional. If true, enable http access to specific ports on the cluster from external sources. Defaults to false.
    - `gce_cluster_config`**Type**: `STRUCT`**Provider name**: `gceClusterConfig`**Description**: Optional. The shared Compute Engine config settings for all instances in a cluster.
      - `confidential_instance_config`**Type**: `STRUCT`**Provider name**: `confidentialInstanceConfig`**Description**: Optional. Confidential Instance Config for clusters using Confidential VMs ([https://cloud.google.com/compute/confidential-vm/docs)](https://cloud.google.com/compute/confidential-vm/docs%29).
        - `enable_confidential_compute`**Type**: `BOOLEAN`**Provider name**: `enableConfidentialCompute`**Description**: Optional. Defines whether the instance should have confidential compute enabled.
      - `internal_ip_only`**Type**: `BOOLEAN`**Provider name**: `internalIpOnly`**Description**: Optional. This setting applies to subnetwork-enabled networks. It is set to true by default in clusters created with image versions 2.2.x.When set to true: All cluster VMs have internal IP addresses. Google Private Access ([https://cloud.google.com/vpc/docs/private-google-access](https://cloud.google.com/vpc/docs/private-google-access)) must be enabled to access Dataproc and other Google Cloud APIs. Off-cluster dependencies must be configured to be accessible without external IP addresses.When set to false: Cluster VMs are not restricted to internal IP addresses. Ephemeral external IP addresses are assigned to each cluster VM.
      - `network_uri`**Type**: `STRING`**Provider name**: `networkUri`**Description**: 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 ([https://cloud.google.com/compute/docs/subnetworks](https://cloud.google.com/compute/docs/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](https://www.googleapis.com/compute/v1/projects/[project_id]/global/networks/default) projects/[project_id]/global/networks/default default
      - `node_group_affinity`**Type**: `STRUCT`**Provider name**: `nodeGroupAffinity`**Description**: Optional. Node Group Affinity for sole-tenant clusters.
        - `node_group_uri`**Type**: `STRING`**Provider name**: `nodeGroupUri`**Description**: Required. The URI of a sole-tenant node group resource ([https://cloud.google.com/compute/docs/reference/rest/v1/nodeGroups](https://cloud.google.com/compute/docs/reference/rest/v1/nodeGroups)) that the cluster will be created on.A full URL, partial URI, or node group name are valid. Examples: [https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/nodeGroups/node-group-1](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/nodeGroups/node-group-1) projects/[project_id]/zones/[zone]/nodeGroups/node-group-1 node-group-1
      - `private_ipv6_google_access`**Type**: `STRING`**Provider name**: `privateIpv6GoogleAccess`**Description**: Optional. The type of IPv6 access for a cluster.**Possible values**:
        - `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.
      - `reservation_affinity`**Type**: `STRUCT`**Provider name**: `reservationAffinity`**Description**: Optional. Reservation Affinity for consuming Zonal reservation.
        - `consume_reservation_type`**Type**: `STRING`**Provider name**: `consumeReservationType`**Description**: Optional. Type of reservation to consume**Possible values**:
          - `TYPE_UNSPECIFIED`
          - `NO_RESERVATION` - Do not consume from any allocated capacity.
          - `ANY_RESERVATION` - Consume any reservation available.
          - `SPECIFIC_RESERVATION` - Must consume from a specific reservation. Must specify key value fields for specifying the reservations.
        - `key`**Type**: `STRING`**Provider name**: `key`**Description**: Optional. Corresponds to the label key of reservation resource.
        - `values`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `values`**Description**: Optional. Corresponds to the label values of reservation resource.
      - `service_account`**Type**: `STRING`**Provider name**: `serviceAccount`**Description**: Optional. The Dataproc service account ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/service-accounts#service_accounts_in_dataproc](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/service-accounts#service_accounts_in_dataproc)) (also see VM Data Plane identity ([https://cloud.google.com/dataproc/docs/concepts/iam/dataproc-principals#vm_service_account_data_plane_identity](https://cloud.google.com/dataproc/docs/concepts/iam/dataproc-principals#vm_service_account_data_plane_identity))) used by Dataproc cluster VM instances to access Google Cloud Platform services.If not specified, the Compute Engine default service account ([https://cloud.google.com/compute/docs/access/service-accounts#default_service_account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account)) is used.
      - `service_account_scopes`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `serviceAccountScopes`**Description**: Optional. The URIs of service account scopes to be included in Compute Engine instances. The following base set of scopes is always included: [https://www.googleapis.com/auth/cloud.useraccounts.readonly](https://www.googleapis.com/auth/cloud.useraccounts.readonly) [https://www.googleapis.com/auth/devstorage.read_write](https://www.googleapis.com/auth/devstorage.read_write) [https://www.googleapis.com/auth/logging.writeIf](https://www.googleapis.com/auth/logging.writeIf) no scopes are specified, the following defaults are also provided: [https://www.googleapis.com/auth/bigquery](https://www.googleapis.com/auth/bigquery) [https://www.googleapis.com/auth/bigtable.admin.table](https://www.googleapis.com/auth/bigtable.admin.table) [https://www.googleapis.com/auth/bigtable.data](https://www.googleapis.com/auth/bigtable.data) [https://www.googleapis.com/auth/devstorage.full_control](https://www.googleapis.com/auth/devstorage.full_control)
      - `shielded_instance_config`**Type**: `STRUCT`**Provider name**: `shieldedInstanceConfig`**Description**: Optional. Shielded Instance Config for clusters using Compute Engine Shielded VMs ([https://cloud.google.com/security/shielded-cloud/shielded-vm)](https://cloud.google.com/security/shielded-cloud/shielded-vm%29).
        - `enable_integrity_monitoring`**Type**: `BOOLEAN`**Provider name**: `enableIntegrityMonitoring`**Description**: Optional. Defines whether instances have integrity monitoring enabled.
        - `enable_secure_boot`**Type**: `BOOLEAN`**Provider name**: `enableSecureBoot`**Description**: Optional. Defines whether instances have Secure Boot enabled.
        - `enable_vtpm`**Type**: `BOOLEAN`**Provider name**: `enableVtpm`**Description**: Optional. Defines whether instances have the vTPM enabled.
      - `subnetwork_uri`**Type**: `STRING`**Provider name**: `subnetworkUri`**Description**: 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](https://www.googleapis.com/compute/v1/projects/[project_id]/regions/[region]/subnetworks/sub0) projects/[project_id]/regions/[region]/subnetworks/sub0 sub0
      - `zone_uri`**Type**: `STRING`**Provider name**: `zoneUri`**Description**: 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]](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]) projects/[project_id]/zones/[zone] [zone]
    - `gke_cluster_config`**Type**: `STRUCT`**Provider name**: `gkeClusterConfig`**Description**: Optional. BETA. The Kubernetes Engine config for Dataproc clusters deployed to The Kubernetes Engine config for Dataproc clusters deployed to Kubernetes. These config settings are mutually exclusive with Compute Engine-based options, such as gce_cluster_config, master_config, worker_config, secondary_worker_config, and autoscaling_config.
      - `gke_cluster_target`**Type**: `STRING`**Provider name**: `gkeClusterTarget`**Description**: 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}'
      - `namespaced_gke_deployment_target`**Type**: `STRUCT`**Provider name**: `namespacedGkeDeploymentTarget`**Description**: Optional. Deprecated. Use gkeClusterTarget. Used only for the deprecated beta. A target for the deployment.
        - `cluster_namespace`**Type**: `STRING`**Provider name**: `clusterNamespace`**Description**: Optional. A namespace within the GKE cluster to deploy into.
        - `target_gke_cluster`**Type**: `STRING`**Provider name**: `targetGkeCluster`**Description**: Optional. The target GKE cluster to deploy to. Format: 'projects/{project}/locations/{location}/clusters/{cluster_id}'
      - `node_pool_target`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `nodePoolTarget`**Description**: 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.
        - `node_pool`**Type**: `STRING`**Provider name**: `nodePool`**Description**: Required. The target GKE node pool. Format: 'projects/{project}/locations/{location}/clusters/{cluster}/nodePools/{node_pool}'
        - `node_pool_config`**Type**: `STRUCT`**Provider name**: `nodePoolConfig`**Description**: 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.
          - `autoscaling`**Type**: `STRUCT`**Provider name**: `autoscaling`**Description**: Optional. The autoscaler configuration for this node pool. The autoscaler is enabled only when a valid configuration is present.
            - `max_node_count`**Type**: `INT32`**Provider name**: `maxNodeCount`**Description**: 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.
            - `min_node_count`**Type**: `INT32`**Provider name**: `minNodeCount`**Description**: The minimum number of nodes in the node pool. Must be >= 0 and <= max_node_count.
          - `config`**Type**: `STRUCT`**Provider name**: `config`**Description**: Optional. The node pool configuration.
            - `accelerators`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `accelerators`**Description**: Optional. A list of hardware accelerators ([https://cloud.google.com/compute/docs/gpus](https://cloud.google.com/compute/docs/gpus)) to attach to each node.
              - `accelerator_count`**Type**: `INT64`**Provider name**: `acceleratorCount`**Description**: The number of accelerator cards exposed to an instance.
              - `accelerator_type`**Type**: `STRING`**Provider name**: `acceleratorType`**Description**: The accelerator type resource namename (see GPUs on Compute Engine).
              - `gpu_partition_size`**Type**: `STRING`**Provider name**: `gpuPartitionSize`**Description**: Size of partitions to create on the GPU. Valid values are described in the NVIDIA mig user guide ([https://docs.nvidia.com/datacenter/tesla/mig-user-guide/#partitioning)](https://docs.nvidia.com/datacenter/tesla/mig-user-guide/#partitioning%29).
            - `boot_disk_kms_key`**Type**: `STRING`**Provider name**: `bootDiskKmsKey`**Description**: Optional. The Customer Managed Encryption Key (CMEK) ([https://cloud.google.com/kubernetes-engine/docs/how-to/using-cmek](https://cloud.google.com/kubernetes-engine/docs/how-to/using-cmek)) used to encrypt the boot disk attached to each node in the node pool. Specify the key using the following format: projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}
            - `local_ssd_count`**Type**: `INT32`**Provider name**: `localSsdCount`**Description**: 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 ([https://cloud.google.com/compute/docs/disks/local-ssd))](https://cloud.google.com/compute/docs/disks/local-ssd%29%29).
            - `machine_type`**Type**: `STRING`**Provider name**: `machineType`**Description**: Optional. The name of a Compute Engine machine type ([https://cloud.google.com/compute/docs/machine-types)](https://cloud.google.com/compute/docs/machine-types%29).
            - `min_cpu_platform`**Type**: `STRING`**Provider name**: `minCpuPlatform`**Description**: Optional. Minimum CPU platform ([https://cloud.google.com/compute/docs/instances/specify-min-cpu-platform](https://cloud.google.com/compute/docs/instances/specify-min-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".
            - `preemptible`**Type**: `BOOLEAN`**Provider name**: `preemptible`**Description**: Optional. Whether the nodes are created as legacy preemptible VM instances ([https://cloud.google.com/compute/docs/instances/preemptible)](https://cloud.google.com/compute/docs/instances/preemptible%29). 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).
            - `spot`**Type**: `BOOLEAN`**Provider name**: `spot`**Description**: Optional. Whether the nodes are created as Spot VM instances ([https://cloud.google.com/compute/docs/instances/spot)](https://cloud.google.com/compute/docs/instances/spot%29). 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).
          - `locations`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `locations`**Description**: Optional. The list of Compute Engine zones ([https://cloud.google.com/compute/docs/zones#available](https://cloud.google.com/compute/docs/zones#available)) 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.
        - `roles`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `roles`**Description**: Required. The roles associated with the GKE node pool.
    - `initialization_actions`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `initializationActions`**Description**: 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
      - `executable_file`**Type**: `STRING`**Provider name**: `executableFile`**Description**: Required. Cloud Storage URI of executable file.
      - `execution_timeout`**Type**: `STRING`**Provider name**: `executionTimeout`**Description**: Optional. Amount of time executable has to complete. Default is 10 minutes (see JSON representation of Duration ([https://developers.google.com/protocol-buffers/docs/proto3#json)).Cluster](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29.Cluster) creation fails with an explanatory error message (the name of the executable that caused the error and the exceeded timeout period) if the executable is not completed at end of the timeout period.
    - `lifecycle_config`**Type**: `STRUCT`**Provider name**: `lifecycleConfig`**Description**: Optional. Lifecycle setting for the cluster.
      - `auto_delete_time`**Type**: `TIMESTAMP`**Provider name**: `autoDeleteTime`**Description**: Optional. The time when cluster will be auto-deleted (see JSON representation of Timestamp ([https://developers.google.com/protocol-buffers/docs/proto3#json))](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29).
      - `auto_delete_ttl`**Type**: `STRING`**Provider name**: `autoDeleteTtl`**Description**: Optional. The lifetime duration of cluster. The cluster will be auto-deleted at the end of this period. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration ([https://developers.google.com/protocol-buffers/docs/proto3#json))](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29).
      - `idle_delete_ttl`**Type**: `STRING`**Provider name**: `idleDeleteTtl`**Description**: Optional. The duration to keep the cluster alive while idling (when no jobs are running). Passing this threshold will cause the cluster to be deleted. Minimum value is 5 minutes; maximum value is 14 days (see JSON representation of Duration ([https://developers.google.com/protocol-buffers/docs/proto3#json))](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29).
      - `idle_start_time`**Type**: `TIMESTAMP`**Provider name**: `idleStartTime`**Description**: Output only. The time when cluster became idle (most recent job finished) and became eligible for deletion due to idleness (see JSON representation of Timestamp ([https://developers.google.com/protocol-buffers/docs/proto3#json))](https://developers.google.com/protocol-buffers/docs/proto3#json%29%29).
    - `master_config`**Type**: `STRUCT`**Provider name**: `masterConfig`**Description**: Optional. The Compute Engine config settings for the cluster's master instance.
      - `accelerators`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `accelerators`**Description**: Optional. The Compute Engine accelerator configuration for these instances.
        - `accelerator_count`**Type**: `INT32`**Provider name**: `acceleratorCount`**Description**: The number of the accelerator cards of this type exposed to this instance.
        - `accelerator_type_uri`**Type**: `STRING`**Provider name**: `acceleratorTypeUri`**Description**: Full URL, partial URI, or short name of the accelerator type resource to expose to this instance. See Compute Engine AcceleratorTypes ([https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes).Examples](https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes%29.Examples): [https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4) projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4 nvidia-tesla-t4Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the accelerator type resource, for example, nvidia-tesla-t4.
      - `disk_config`**Type**: `STRUCT`**Provider name**: `diskConfig`**Description**: Optional. Disk option config settings.
        - `boot_disk_provisioned_iops`**Type**: `INT64`**Provider name**: `bootDiskProvisionedIops`**Description**: Optional. Indicates how many IOPS to provision for the disk. This sets the number of I/O operations per second that the disk can handle. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_provisioned_throughput`**Type**: `INT64`**Provider name**: `bootDiskProvisionedThroughput`**Description**: Optional. Indicates how much throughput to provision for the disk. This sets the number of throughput mb per second that the disk can handle. Values must be greater than or equal to 1. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_size_gb`**Type**: `INT32`**Provider name**: `bootDiskSizeGb`**Description**: Optional. Size in GB of the boot disk (default is 500GB).
        - `boot_disk_type`**Type**: `STRING`**Provider name**: `bootDiskType`**Description**: 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 ([https://cloud.google.com/compute/docs/disks#disk-types)](https://cloud.google.com/compute/docs/disks#disk-types%29).
        - `local_ssd_interface`**Type**: `STRING`**Provider name**: `localSsdInterface`**Description**: 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 ([https://cloud.google.com/compute/docs/disks/local-ssd#performance)](https://cloud.google.com/compute/docs/disks/local-ssd#performance%29).
        - `num_local_ssds`**Type**: `INT32`**Provider name**: `numLocalSsds`**Description**: 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 ([https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html](https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html)) 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.
      - `image_uri`**Type**: `STRING`**Provider name**: `imageUri`**Description**: 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]](https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/[image-id]) projects/[project_id]/global/images/[image-id] image-idImage 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]](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.
      - `instance_flexibility_policy`**Type**: `STRUCT`**Provider name**: `instanceFlexibilityPolicy`**Description**: Optional. Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.
        - `instance_selection_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionList`**Description**: Optional. List of instance selection options that the group will use when creating new VMs.
          - `machine_types`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `machineTypes`**Description**: Optional. Full machine-type names, e.g. "n1-standard-16".
          - `rank`**Type**: `INT32`**Provider name**: `rank`**Description**: 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.
        - `instance_selection_results`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionResults`**Description**: Output only. A list of instance selection results in the group.
          - `machine_type`**Type**: `STRING`**Provider name**: `machineType`**Description**: Output only. Full machine-type names, e.g. "n1-standard-16".
          - `vm_count`**Type**: `INT32`**Provider name**: `vmCount`**Description**: Output only. Number of VM provisioned with the machine_type.
        - `provisioning_model_mix`**Type**: `STRUCT`**Provider name**: `provisioningModelMix`**Description**: Optional. Defines how the Group selects the provisioning model to ensure required reliability.
          - `standard_capacity_base`**Type**: `INT32`**Provider name**: `standardCapacityBase`**Description**: Optional. The base capacity that will always use Standard VMs to avoid risk of more preemption than the minimum capacity you need. Dataproc will create only standard VMs until it reaches standard_capacity_base, then it will start using standard_capacity_percent_above_base to mix Spot with Standard VMs. eg. If 15 instances are requested and standard_capacity_base is 5, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances.
          - `standard_capacity_percent_above_base`**Type**: `INT32`**Provider name**: `standardCapacityPercentAboveBase`**Description**: Optional. The percentage of target capacity that should use Standard VM. The remaining percentage will use Spot VMs. The percentage applies only to the capacity above standard_capacity_base. eg. If 15 instances are requested and standard_capacity_base is 5 and standard_capacity_percent_above_base is 30, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances. The mix will be 30% standard and 70% spot.
      - `instance_names`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `instanceNames`**Description**: Output only. The list of instance names. Dataproc derives the names from cluster_name, num_instances, and the instance group.
      - `instance_references`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceReferences`**Description**: Output only. List of references to Compute Engine instances.
        - `instance_id`**Type**: `STRING`**Provider name**: `instanceId`**Description**: The unique identifier of the Compute Engine instance.
        - `instance_name`**Type**: `STRING`**Provider name**: `instanceName`**Description**: The user-friendly name of the Compute Engine instance.
        - `public_ecies_key`**Type**: `STRING`**Provider name**: `publicEciesKey`**Description**: The public ECIES key used for sharing data with this instance.
        - `public_key`**Type**: `STRING`**Provider name**: `publicKey`**Description**: The public RSA key used for sharing data with this instance.
      - `is_preemptible`**Type**: `BOOLEAN`**Provider name**: `isPreemptible`**Description**: Output only. Specifies that this instance group contains preemptible instances.
      - `machine_type_uri`**Type**: `STRING`**Provider name**: `machineTypeUri`**Description**: 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](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-2Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the machine type resource, for example, n1-standard-2.
      - `managed_group_config`**Type**: `STRUCT`**Provider name**: `managedGroupConfig`**Description**: Output only. The config for Compute Engine Instance Group Manager that manages this group. This is only used for preemptible instance groups.
        - `instance_group_manager_name`**Type**: `STRING`**Provider name**: `instanceGroupManagerName`**Description**: Output only. The name of the Instance Group Manager for this group.
        - `instance_group_manager_uri`**Type**: `STRING`**Provider name**: `instanceGroupManagerUri`**Description**: Output only. The partial URI to the instance group manager for this group. E.g. projects/my-project/regions/us-central1/instanceGroupManagers/my-igm.
        - `instance_template_name`**Type**: `STRING`**Provider name**: `instanceTemplateName`**Description**: Output only. The name of the Instance Template used for the Managed Instance Group.
      - `min_cpu_platform`**Type**: `STRING`**Provider name**: `minCpuPlatform`**Description**: Optional. Specifies the minimum cpu platform for the Instance Group. See Dataproc -> Minimum CPU Platform ([https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu)](https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu%29).
      - `min_num_instances`**Type**: `INT32`**Provider name**: `minNumInstances`**Description**: 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.
      - `num_instances`**Type**: `INT32`**Provider name**: `numInstances`**Description**: 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.
      - `preemptibility`**Type**: `STRING`**Provider name**: `preemptibility`**Description**: 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.**Possible values**:
        - `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 ([https://cloud.google.com/compute/docs/instances/preemptible).This](https://cloud.google.com/compute/docs/instances/preemptible%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups.
        - `SPOT` - Instances are Spot VMs ([https://cloud.google.com/compute/docs/instances/spot).This](https://cloud.google.com/compute/docs/instances/spot%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups. Spot VMs are the latest version of preemptible VMs ([https://cloud.google.com/compute/docs/instances/preemptible)](https://cloud.google.com/compute/docs/instances/preemptible%29), and provide additional features.
      - `startup_config`**Type**: `STRUCT`**Provider name**: `startupConfig`**Description**: Optional. Configuration to handle the startup of instances during cluster create and update process.
        - `required_registration_fraction`**Type**: `DOUBLE`**Provider name**: `requiredRegistrationFraction`**Description**: Optional. The config setting to enable cluster creation/ updation to be successful only after required_registration_fraction of instances are up and running. This configuration is applicable to only secondary workers for now. The cluster will fail if required_registration_fraction of instances are not available. This will include instance creation, agent registration, and service registration (if enabled).
    - `metastore_config`**Type**: `STRUCT`**Provider name**: `metastoreConfig`**Description**: Optional. Metastore configuration.
      - `dataproc_metastore_service`**Type**: `STRING`**Provider name**: `dataprocMetastoreService`**Description**: Required. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[dataproc_region]/services/[service-name]
    - `secondary_worker_config`**Type**: `STRUCT`**Provider name**: `secondaryWorkerConfig`**Description**: Optional. The Compute Engine config settings for a cluster's secondary worker instances
      - `accelerators`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `accelerators`**Description**: Optional. The Compute Engine accelerator configuration for these instances.
        - `accelerator_count`**Type**: `INT32`**Provider name**: `acceleratorCount`**Description**: The number of the accelerator cards of this type exposed to this instance.
        - `accelerator_type_uri`**Type**: `STRING`**Provider name**: `acceleratorTypeUri`**Description**: Full URL, partial URI, or short name of the accelerator type resource to expose to this instance. See Compute Engine AcceleratorTypes ([https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes).Examples](https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes%29.Examples): [https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4) projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4 nvidia-tesla-t4Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the accelerator type resource, for example, nvidia-tesla-t4.
      - `disk_config`**Type**: `STRUCT`**Provider name**: `diskConfig`**Description**: Optional. Disk option config settings.
        - `boot_disk_provisioned_iops`**Type**: `INT64`**Provider name**: `bootDiskProvisionedIops`**Description**: Optional. Indicates how many IOPS to provision for the disk. This sets the number of I/O operations per second that the disk can handle. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_provisioned_throughput`**Type**: `INT64`**Provider name**: `bootDiskProvisionedThroughput`**Description**: Optional. Indicates how much throughput to provision for the disk. This sets the number of throughput mb per second that the disk can handle. Values must be greater than or equal to 1. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_size_gb`**Type**: `INT32`**Provider name**: `bootDiskSizeGb`**Description**: Optional. Size in GB of the boot disk (default is 500GB).
        - `boot_disk_type`**Type**: `STRING`**Provider name**: `bootDiskType`**Description**: 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 ([https://cloud.google.com/compute/docs/disks#disk-types)](https://cloud.google.com/compute/docs/disks#disk-types%29).
        - `local_ssd_interface`**Type**: `STRING`**Provider name**: `localSsdInterface`**Description**: 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 ([https://cloud.google.com/compute/docs/disks/local-ssd#performance)](https://cloud.google.com/compute/docs/disks/local-ssd#performance%29).
        - `num_local_ssds`**Type**: `INT32`**Provider name**: `numLocalSsds`**Description**: 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 ([https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html](https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html)) 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.
      - `image_uri`**Type**: `STRING`**Provider name**: `imageUri`**Description**: 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]](https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/[image-id]) projects/[project_id]/global/images/[image-id] image-idImage 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]](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.
      - `instance_flexibility_policy`**Type**: `STRUCT`**Provider name**: `instanceFlexibilityPolicy`**Description**: Optional. Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.
        - `instance_selection_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionList`**Description**: Optional. List of instance selection options that the group will use when creating new VMs.
          - `machine_types`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `machineTypes`**Description**: Optional. Full machine-type names, e.g. "n1-standard-16".
          - `rank`**Type**: `INT32`**Provider name**: `rank`**Description**: 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.
        - `instance_selection_results`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionResults`**Description**: Output only. A list of instance selection results in the group.
          - `machine_type`**Type**: `STRING`**Provider name**: `machineType`**Description**: Output only. Full machine-type names, e.g. "n1-standard-16".
          - `vm_count`**Type**: `INT32`**Provider name**: `vmCount`**Description**: Output only. Number of VM provisioned with the machine_type.
        - `provisioning_model_mix`**Type**: `STRUCT`**Provider name**: `provisioningModelMix`**Description**: Optional. Defines how the Group selects the provisioning model to ensure required reliability.
          - `standard_capacity_base`**Type**: `INT32`**Provider name**: `standardCapacityBase`**Description**: Optional. The base capacity that will always use Standard VMs to avoid risk of more preemption than the minimum capacity you need. Dataproc will create only standard VMs until it reaches standard_capacity_base, then it will start using standard_capacity_percent_above_base to mix Spot with Standard VMs. eg. If 15 instances are requested and standard_capacity_base is 5, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances.
          - `standard_capacity_percent_above_base`**Type**: `INT32`**Provider name**: `standardCapacityPercentAboveBase`**Description**: Optional. The percentage of target capacity that should use Standard VM. The remaining percentage will use Spot VMs. The percentage applies only to the capacity above standard_capacity_base. eg. If 15 instances are requested and standard_capacity_base is 5 and standard_capacity_percent_above_base is 30, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances. The mix will be 30% standard and 70% spot.
      - `instance_names`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `instanceNames`**Description**: Output only. The list of instance names. Dataproc derives the names from cluster_name, num_instances, and the instance group.
      - `instance_references`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceReferences`**Description**: Output only. List of references to Compute Engine instances.
        - `instance_id`**Type**: `STRING`**Provider name**: `instanceId`**Description**: The unique identifier of the Compute Engine instance.
        - `instance_name`**Type**: `STRING`**Provider name**: `instanceName`**Description**: The user-friendly name of the Compute Engine instance.
        - `public_ecies_key`**Type**: `STRING`**Provider name**: `publicEciesKey`**Description**: The public ECIES key used for sharing data with this instance.
        - `public_key`**Type**: `STRING`**Provider name**: `publicKey`**Description**: The public RSA key used for sharing data with this instance.
      - `is_preemptible`**Type**: `BOOLEAN`**Provider name**: `isPreemptible`**Description**: Output only. Specifies that this instance group contains preemptible instances.
      - `machine_type_uri`**Type**: `STRING`**Provider name**: `machineTypeUri`**Description**: 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](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-2Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the machine type resource, for example, n1-standard-2.
      - `managed_group_config`**Type**: `STRUCT`**Provider name**: `managedGroupConfig`**Description**: Output only. The config for Compute Engine Instance Group Manager that manages this group. This is only used for preemptible instance groups.
        - `instance_group_manager_name`**Type**: `STRING`**Provider name**: `instanceGroupManagerName`**Description**: Output only. The name of the Instance Group Manager for this group.
        - `instance_group_manager_uri`**Type**: `STRING`**Provider name**: `instanceGroupManagerUri`**Description**: Output only. The partial URI to the instance group manager for this group. E.g. projects/my-project/regions/us-central1/instanceGroupManagers/my-igm.
        - `instance_template_name`**Type**: `STRING`**Provider name**: `instanceTemplateName`**Description**: Output only. The name of the Instance Template used for the Managed Instance Group.
      - `min_cpu_platform`**Type**: `STRING`**Provider name**: `minCpuPlatform`**Description**: Optional. Specifies the minimum cpu platform for the Instance Group. See Dataproc -> Minimum CPU Platform ([https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu)](https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu%29).
      - `min_num_instances`**Type**: `INT32`**Provider name**: `minNumInstances`**Description**: 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.
      - `num_instances`**Type**: `INT32`**Provider name**: `numInstances`**Description**: 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.
      - `preemptibility`**Type**: `STRING`**Provider name**: `preemptibility`**Description**: 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.**Possible values**:
        - `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 ([https://cloud.google.com/compute/docs/instances/preemptible).This](https://cloud.google.com/compute/docs/instances/preemptible%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups.
        - `SPOT` - Instances are Spot VMs ([https://cloud.google.com/compute/docs/instances/spot).This](https://cloud.google.com/compute/docs/instances/spot%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups. Spot VMs are the latest version of preemptible VMs ([https://cloud.google.com/compute/docs/instances/preemptible)](https://cloud.google.com/compute/docs/instances/preemptible%29), and provide additional features.
      - `startup_config`**Type**: `STRUCT`**Provider name**: `startupConfig`**Description**: Optional. Configuration to handle the startup of instances during cluster create and update process.
        - `required_registration_fraction`**Type**: `DOUBLE`**Provider name**: `requiredRegistrationFraction`**Description**: Optional. The config setting to enable cluster creation/ updation to be successful only after required_registration_fraction of instances are up and running. This configuration is applicable to only secondary workers for now. The cluster will fail if required_registration_fraction of instances are not available. This will include instance creation, agent registration, and service registration (if enabled).
    - `security_config`**Type**: `STRUCT`**Provider name**: `securityConfig`**Description**: Optional. Security settings for the cluster.
      - `identity_config`**Type**: `STRUCT`**Provider name**: `identityConfig`**Description**: Optional. Identity related configuration, including service account based secure multi-tenancy user mappings.

      - `kerberos_config`**Type**: `STRUCT`**Provider name**: `kerberosConfig`**Description**: Optional. Kerberos related configuration.

        - `cross_realm_trust_admin_server`**Type**: `STRING`**Provider name**: `crossRealmTrustAdminServer`**Description**: Optional. The admin server (IP or hostname) for the remote trusted realm in a cross realm trust relationship.
        - `cross_realm_trust_kdc`**Type**: `STRING`**Provider name**: `crossRealmTrustKdc`**Description**: Optional. The KDC (IP or hostname) for the remote trusted realm in a cross realm trust relationship.
        - `cross_realm_trust_realm`**Type**: `STRING`**Provider name**: `crossRealmTrustRealm`**Description**: Optional. The remote realm the Dataproc on-cluster KDC will trust, should the user enable cross realm trust.
        - `cross_realm_trust_shared_password_uri`**Type**: `STRING`**Provider name**: `crossRealmTrustSharedPasswordUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the shared password between the on-cluster Kerberos realm and the remote trusted realm, in a cross realm trust relationship.
        - `enable_kerberos`**Type**: `BOOLEAN`**Provider name**: `enableKerberos`**Description**: Optional. Flag to indicate whether to Kerberize the cluster (default: false). Set this field to true to enable Kerberos on a cluster.
        - `kdc_db_key_uri`**Type**: `STRING`**Provider name**: `kdcDbKeyUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the master key of the KDC database.
        - `key_password_uri`**Type**: `STRING`**Provider name**: `keyPasswordUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the password to the user provided key. For the self-signed certificate, this password is generated by Dataproc.
        - `keystore_password_uri`**Type**: `STRING`**Provider name**: `keystorePasswordUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the password to the user provided keystore. For the self-signed certificate, this password is generated by Dataproc.
        - `keystore_uri`**Type**: `STRING`**Provider name**: `keystoreUri`**Description**: Optional. The Cloud Storage URI of the keystore file used for SSL encryption. If not provided, Dataproc will provide a self-signed certificate.
        - `kms_key_uri`**Type**: `STRING`**Provider name**: `kmsKeyUri`**Description**: Optional. The URI of the KMS key used to encrypt sensitive files.
        - `realm`**Type**: `STRING`**Provider name**: `realm`**Description**: Optional. The name of the on-cluster Kerberos realm. If not specified, the uppercased domain of hostnames will be the realm.
        - `root_principal_password_uri`**Type**: `STRING`**Provider name**: `rootPrincipalPasswordUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the root principal password.
        - `tgt_lifetime_hours`**Type**: `INT32`**Provider name**: `tgtLifetimeHours`**Description**: Optional. The lifetime of the ticket granting ticket, in hours. If not specified, or user specifies 0, then default value 10 will be used.
        - `truststore_password_uri`**Type**: `STRING`**Provider name**: `truststorePasswordUri`**Description**: Optional. The Cloud Storage URI of a KMS encrypted file containing the password to the user provided truststore. For the self-signed certificate, this password is generated by Dataproc.
        - `truststore_uri`**Type**: `STRING`**Provider name**: `truststoreUri`**Description**: Optional. The Cloud Storage URI of the truststore file used for SSL encryption. If not provided, Dataproc will provide a self-signed certificate.
    - `software_config`**Type**: `STRUCT`**Provider name**: `softwareConfig`**Description**: Optional. The config settings for cluster software.
      - `image_version`**Type**: `STRING`**Provider name**: `imageVersion`**Description**: Optional. The version of software inside the cluster. It must be one of the supported Dataproc Versions ([https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#supported-dataproc-image-versions)](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#supported-dataproc-image-versions%29), such as "1.2" (including a subminor version, such as "1.2.29"), or the "preview" version ([https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#other_versions)](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#other_versions%29). If unspecified, it defaults to the latest Debian version.
      - `optional_components`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `optionalComponents`**Description**: Optional. The set of components to activate on the cluster.
    - `temp_bucket`**Type**: `STRING`**Provider name**: `tempBucket`**Description**: 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 ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket))](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket%29%29). This field requires a Cloud Storage bucket name, not a gs://… URI to a Cloud Storage bucket.
    - `worker_config`**Type**: `STRUCT`**Provider name**: `workerConfig`**Description**: Optional. The Compute Engine config settings for the cluster's worker instances.
      - `accelerators`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `accelerators`**Description**: Optional. The Compute Engine accelerator configuration for these instances.
        - `accelerator_count`**Type**: `INT32`**Provider name**: `acceleratorCount`**Description**: The number of the accelerator cards of this type exposed to this instance.
        - `accelerator_type_uri`**Type**: `STRING`**Provider name**: `acceleratorTypeUri`**Description**: Full URL, partial URI, or short name of the accelerator type resource to expose to this instance. See Compute Engine AcceleratorTypes ([https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes).Examples](https://cloud.google.com/compute/docs/reference/v1/acceleratorTypes%29.Examples): [https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4](https://www.googleapis.com/compute/v1/projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4) projects/[project_id]/zones/[zone]/acceleratorTypes/nvidia-tesla-t4 nvidia-tesla-t4Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the accelerator type resource, for example, nvidia-tesla-t4.
      - `disk_config`**Type**: `STRUCT`**Provider name**: `diskConfig`**Description**: Optional. Disk option config settings.
        - `boot_disk_provisioned_iops`**Type**: `INT64`**Provider name**: `bootDiskProvisionedIops`**Description**: Optional. Indicates how many IOPS to provision for the disk. This sets the number of I/O operations per second that the disk can handle. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_provisioned_throughput`**Type**: `INT64`**Provider name**: `bootDiskProvisionedThroughput`**Description**: Optional. Indicates how much throughput to provision for the disk. This sets the number of throughput mb per second that the disk can handle. Values must be greater than or equal to 1. This field is supported only if boot_disk_type is hyperdisk-balanced.
        - `boot_disk_size_gb`**Type**: `INT32`**Provider name**: `bootDiskSizeGb`**Description**: Optional. Size in GB of the boot disk (default is 500GB).
        - `boot_disk_type`**Type**: `STRING`**Provider name**: `bootDiskType`**Description**: 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 ([https://cloud.google.com/compute/docs/disks#disk-types)](https://cloud.google.com/compute/docs/disks#disk-types%29).
        - `local_ssd_interface`**Type**: `STRING`**Provider name**: `localSsdInterface`**Description**: 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 ([https://cloud.google.com/compute/docs/disks/local-ssd#performance)](https://cloud.google.com/compute/docs/disks/local-ssd#performance%29).
        - `num_local_ssds`**Type**: `INT32`**Provider name**: `numLocalSsds`**Description**: 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 ([https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html](https://hadoop.apache.org/docs/r1.2.1/hdfs_user_guide.html)) 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.
      - `image_uri`**Type**: `STRING`**Provider name**: `imageUri`**Description**: 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]](https://www.googleapis.com/compute/v1/projects/[project_id]/global/images/[image-id]) projects/[project_id]/global/images/[image-id] image-idImage 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]](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.
      - `instance_flexibility_policy`**Type**: `STRUCT`**Provider name**: `instanceFlexibilityPolicy`**Description**: Optional. Instance flexibility Policy allowing a mixture of VM shapes and provisioning models.
        - `instance_selection_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionList`**Description**: Optional. List of instance selection options that the group will use when creating new VMs.
          - `machine_types`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `machineTypes`**Description**: Optional. Full machine-type names, e.g. "n1-standard-16".
          - `rank`**Type**: `INT32`**Provider name**: `rank`**Description**: 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.
        - `instance_selection_results`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceSelectionResults`**Description**: Output only. A list of instance selection results in the group.
          - `machine_type`**Type**: `STRING`**Provider name**: `machineType`**Description**: Output only. Full machine-type names, e.g. "n1-standard-16".
          - `vm_count`**Type**: `INT32`**Provider name**: `vmCount`**Description**: Output only. Number of VM provisioned with the machine_type.
        - `provisioning_model_mix`**Type**: `STRUCT`**Provider name**: `provisioningModelMix`**Description**: Optional. Defines how the Group selects the provisioning model to ensure required reliability.
          - `standard_capacity_base`**Type**: `INT32`**Provider name**: `standardCapacityBase`**Description**: Optional. The base capacity that will always use Standard VMs to avoid risk of more preemption than the minimum capacity you need. Dataproc will create only standard VMs until it reaches standard_capacity_base, then it will start using standard_capacity_percent_above_base to mix Spot with Standard VMs. eg. If 15 instances are requested and standard_capacity_base is 5, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances.
          - `standard_capacity_percent_above_base`**Type**: `INT32`**Provider name**: `standardCapacityPercentAboveBase`**Description**: Optional. The percentage of target capacity that should use Standard VM. The remaining percentage will use Spot VMs. The percentage applies only to the capacity above standard_capacity_base. eg. If 15 instances are requested and standard_capacity_base is 5 and standard_capacity_percent_above_base is 30, Dataproc will create 5 standard VMs and then start mixing spot and standard VMs for remaining 10 instances. The mix will be 30% standard and 70% spot.
      - `instance_names`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `instanceNames`**Description**: Output only. The list of instance names. Dataproc derives the names from cluster_name, num_instances, and the instance group.
      - `instance_references`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `instanceReferences`**Description**: Output only. List of references to Compute Engine instances.
        - `instance_id`**Type**: `STRING`**Provider name**: `instanceId`**Description**: The unique identifier of the Compute Engine instance.
        - `instance_name`**Type**: `STRING`**Provider name**: `instanceName`**Description**: The user-friendly name of the Compute Engine instance.
        - `public_ecies_key`**Type**: `STRING`**Provider name**: `publicEciesKey`**Description**: The public ECIES key used for sharing data with this instance.
        - `public_key`**Type**: `STRING`**Provider name**: `publicKey`**Description**: The public RSA key used for sharing data with this instance.
      - `is_preemptible`**Type**: `BOOLEAN`**Provider name**: `isPreemptible`**Description**: Output only. Specifies that this instance group contains preemptible instances.
      - `machine_type_uri`**Type**: `STRING`**Provider name**: `machineTypeUri`**Description**: 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](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-2Auto Zone Exception: If you are using the Dataproc Auto Zone Placement ([https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/auto-zone#using_auto_zone_placement)) feature, you must use the short name of the machine type resource, for example, n1-standard-2.
      - `managed_group_config`**Type**: `STRUCT`**Provider name**: `managedGroupConfig`**Description**: Output only. The config for Compute Engine Instance Group Manager that manages this group. This is only used for preemptible instance groups.
        - `instance_group_manager_name`**Type**: `STRING`**Provider name**: `instanceGroupManagerName`**Description**: Output only. The name of the Instance Group Manager for this group.
        - `instance_group_manager_uri`**Type**: `STRING`**Provider name**: `instanceGroupManagerUri`**Description**: Output only. The partial URI to the instance group manager for this group. E.g. projects/my-project/regions/us-central1/instanceGroupManagers/my-igm.
        - `instance_template_name`**Type**: `STRING`**Provider name**: `instanceTemplateName`**Description**: Output only. The name of the Instance Template used for the Managed Instance Group.
      - `min_cpu_platform`**Type**: `STRING`**Provider name**: `minCpuPlatform`**Description**: Optional. Specifies the minimum cpu platform for the Instance Group. See Dataproc -> Minimum CPU Platform ([https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu)](https://cloud.google.com/dataproc/docs/concepts/compute/dataproc-min-cpu%29).
      - `min_num_instances`**Type**: `INT32`**Provider name**: `minNumInstances`**Description**: 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.
      - `num_instances`**Type**: `INT32`**Provider name**: `numInstances`**Description**: 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.
      - `preemptibility`**Type**: `STRING`**Provider name**: `preemptibility`**Description**: 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.**Possible values**:
        - `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 ([https://cloud.google.com/compute/docs/instances/preemptible).This](https://cloud.google.com/compute/docs/instances/preemptible%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups.
        - `SPOT` - Instances are Spot VMs ([https://cloud.google.com/compute/docs/instances/spot).This](https://cloud.google.com/compute/docs/instances/spot%29.This) option is allowed only for secondary worker ([https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms](https://cloud.google.com/dataproc/docs/concepts/compute/secondary-vms)) groups. Spot VMs are the latest version of preemptible VMs ([https://cloud.google.com/compute/docs/instances/preemptible)](https://cloud.google.com/compute/docs/instances/preemptible%29), and provide additional features.
      - `startup_config`**Type**: `STRUCT`**Provider name**: `startupConfig`**Description**: Optional. Configuration to handle the startup of instances during cluster create and update process.
        - `required_registration_fraction`**Type**: `DOUBLE`**Provider name**: `requiredRegistrationFraction`**Description**: Optional. The config setting to enable cluster creation/ updation to be successful only after required_registration_fraction of instances are up and running. This configuration is applicable to only secondary workers for now. The cluster will fail if required_registration_fraction of instances are not available. This will include instance creation, agent registration, and service registration (if enabled).

## `project_id`{% #project_id %}

**Type**: `STRING`

## `project_number`{% #project_number %}

**Type**: `STRING`

## `region_id`{% #region_id %}

**Type**: `STRING`

## `resource_name`{% #resource_name %}

**Type**: `STRING`

## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`

## `update_time`{% #update_time %}

**Type**: `TIMESTAMP`**Provider name**: `updateTime`**Description**: Output only. The time template was last updated.

## `version`{% #version %}

**Type**: `INT32`**Provider name**: `version`**Description**: Optional. Used to perform a consistent read-modify-write.This field should be left blank for a CreateWorkflowTemplate request. It is required for an UpdateWorkflowTemplate request, and must match the current server version. A typical update template flow would fetch the current template with a GetWorkflowTemplate request, which will return the current template with the version field filled in with the current server version. The user updates other fields in the template, then returns it as part of the UpdateWorkflowTemplate request.

## `zone_id`{% #zone_id %}

**Type**: `STRING`