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ancestors
Type: UNORDERED_LIST_STRING
create_time
Type: TIMESTAMP
Provider name: createTime
Description: Output only. The time template was created.
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)). 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
Type: STRUCT
Provider name: encryptionConfig
Description: Optional. Encryption settings for encrypting workflow template job arguments.
id
Type: STRING
Provider name: id
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).
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).
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
Type: UNORDERED_LIST_STRING
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. 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
Type: STRING
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
Type: STRING
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.
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).
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.
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).
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).
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) 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] 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] 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 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) 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).
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:
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)). 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) to collect for the metric course (for the SPARK metric source (any Spark metric (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) 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.
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).
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) 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) for more information).A full URL, partial URI, or short name are valid. Examples: https://www.googleapis.com/compute/v1/projects/[project_id]/global/networks/default projects/[project_id]/global/networks/default default
node_group_affinity
Type: STRUCT
Provider name: nodeGroupAffinity
Description: Optional. Node Group Affinity for sole-tenant clusters.
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_UNSPECIFIEDNO_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) (also see VM 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) 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/devstorage.read_write 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/bigtable.admin.table https://www.googleapis.com/auth/bigtable.data 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).
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 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] 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) 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).
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) 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)).
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).
min_cpu_platform
Type: STRING
Provider name: minCpuPlatform
Description: Optional. Minimum 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). 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). 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) 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 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.
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.
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).
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).
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) 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] 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] 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 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) 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).
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:
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.
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).
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).
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) 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] 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] 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 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) 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).
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:
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.
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)). 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.
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).
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).
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) 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] 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] 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 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) 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).
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:
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
Type: STRING
project_number
Type: STRING
resource_name
Type: STRING
Type: UNORDERED_LIST_STRING
update_time
Type: TIMESTAMP
Provider name: updateTime
Description: Output only. The time template was last updated.
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.
