gcloud dataproc workflow-templates set-managed-cluster

NAME

gcloud dataproc workflow-templates set-managed-cluster - set a managed cluster for the workflow template

SYNOPSIS

gcloud dataproc workflow-templates set-managed-cluster (TEMPLATE : --region=REGION) [--autoscaling-policy=AUTOSCALING_POLICY] [--bucket=BUCKET] [--cluster-name=CLUSTER_NAME] [--confidential-compute] [--dataproc-metastore=DATAPROC_METASTORE] [--enable-component-gateway] [--initialization-action-timeout=TIMEOUT; default="10m"] [--initialization-actions=CLOUD_STORAGE_URI,[…]] [--labels=[KEY=VALUE,…]] [--master-accelerator=[type=TYPE,[count=COUNT],…]] [--master-boot-disk-provisioned-iops=MASTER_BOOT_DISK_PROVISIONED_IOPS] [--master-boot-disk-provisioned-throughput=MASTER_BOOT_DISK_PROVISIONED_THROUGHPUT] [--master-boot-disk-size=MASTER_BOOT_DISK_SIZE] [--master-boot-disk-type=MASTER_BOOT_DISK_TYPE] [--master-local-ssd-interface=MASTER_LOCAL_SSD_INTERFACE] [--master-machine-type=MASTER_MACHINE_TYPE] [--master-min-cpu-platform=PLATFORM] [--min-secondary-worker-fraction=MIN_SECONDARY_WORKER_FRACTION] [--node-group=NODE_GROUP] [--num-master-local-ssds=NUM_MASTER_LOCAL_SSDS] [--num-masters=NUM_MASTERS] [--num-secondary-worker-local-ssds=NUM_SECONDARY_WORKER_LOCAL_SSDS] [--num-worker-local-ssds=NUM_WORKER_LOCAL_SSDS] [--optional-components=[COMPONENT,…]] [--private-ipv6-google-access-type=PRIVATE_IPV6_GOOGLE_ACCESS_TYPE] [--properties=[PREFIX:PROPERTY=VALUE,…]] [--secondary-worker-accelerator=[type=TYPE,[count=COUNT],…]] [--secondary-worker-boot-disk-size=SECONDARY_WORKER_BOOT_DISK_SIZE] [--secondary-worker-boot-disk-type=SECONDARY_WORKER_BOOT_DISK_TYPE] [--secondary-worker-local-ssd-interface=SECONDARY_WORKER_LOCAL_SSD_INTERFACE] [--secondary-worker-machine-types=type=MACHINE_TYPE[,type=MACHINE_TYPE…][,rank=RANK]] [--secondary-worker-standard-capacity-base=SECONDARY_WORKER_STANDARD_CAPACITY_BASE] [--secondary-worker-standard-capacity-percent-above-base=SECONDARY_WORKER_STANDARD_CAPACITY_PERCENT_ABOVE_BASE] [--shielded-integrity-monitoring] [--shielded-secure-boot] [--shielded-vtpm] [--temp-bucket=TEMP_BUCKET] [--worker-accelerator=[type=TYPE,[count=COUNT],…]] [--worker-boot-disk-provisioned-iops=WORKER_BOOT_DISK_PROVISIONED_IOPS] [--worker-boot-disk-provisioned-throughput=WORKER_BOOT_DISK_PROVISIONED_THROUGHPUT] [--worker-boot-disk-size=WORKER_BOOT_DISK_SIZE] [--worker-boot-disk-type=WORKER_BOOT_DISK_TYPE] [--worker-local-ssd-interface=WORKER_LOCAL_SSD_INTERFACE] [--worker-min-cpu-platform=PLATFORM] [--zone=ZONE] [--identity-config-file=IDENTITY_CONFIG_FILE     | --secure-multi-tenancy-user-mapping=SECURE_MULTI_TENANCY_USER_MAPPING] [--image=IMAGE     | --image-version=VERSION] [--kerberos-config-file=KERBEROS_CONFIG_FILE     | --enable-kerberos --kerberos-root-principal-password-uri=KERBEROS_ROOT_PRINCIPAL_PASSWORD_URI [--kerberos-kms-key=KERBEROS_KMS_KEY : --kerberos-kms-key-keyring=KERBEROS_KMS_KEY_KEYRING --kerberos-kms-key-location=KERBEROS_KMS_KEY_LOCATION --kerberos-kms-key-project=KERBEROS_KMS_KEY_PROJECT]] [--kms-key=KMS_KEY : --kms-keyring=KMS_KEYRING --kms-location=KMS_LOCATION --kms-project=KMS_PROJECT] [--metadata=KEY=VALUE,[KEY=VALUE,…] --scopes=SCOPE,[SCOPE,…] --service-account=SERVICE_ACCOUNT --tags=TAG,[TAG,…] --network=NETWORK     | --subnet=SUBNET --reservation=RESERVATION --reservation-affinity=RESERVATION_AFFINITY; default="any"] [[--metric-sources=[METRIC_SOURCE,…] : --metric-overrides=[METRIC_SOURCE:INSTANCE:GROUP:METRIC,…] | --metric-overrides-file=METRIC_OVERRIDES_FILE]] [--no-address     | --public-ip-address] [--single-node     | --min-num-workers=MIN_NUM_WORKERS --num-secondary-workers=NUM_SECONDARY_WORKERS --num-workers=NUM_WORKERS --secondary-worker-type=TYPE; default="preemptible"] [--worker-machine-type=WORKER_MACHINE_TYPE     | --worker-machine-types=type=MACHINE_TYPE[,type=MACHINE_TYPE…][,rank=RANK]] [GCLOUD_WIDE_FLAG …]

DESCRIPTION

Set a managed cluster for the workflow template.

EXAMPLES

To update managed cluster in a workflow template, run:

gcloud dataproc workflow-templates set-managed-cluster my_template --region=us-central1 --no-address --num-workers=10 --worker-machine-type=custom-6-23040

POSITIONAL ARGUMENTS

Template resource - The name of the workflow template to set managed cluster. The arguments in this group can be used to specify the attributes of this resource. (NOTE) Some attributes are not given arguments in this group but can be set in other ways.

To set the project attribute:

• provide the argument template on the command line with a fully specified name;
• provide the argument --project on the command line;
• set the property core/project.

This must be specified.

TEMPLATE

ID of the template or fully qualified identifier for the template.

To set the template attribute:

• provide the argument template on the command line.

This positional argument must be specified if any of the other arguments in this group are specified.

--region=REGION

Dataproc region for the template. Each Dataproc region constitutes an independent resource namespace constrained to deploying instances into Compute Engine zones inside the region. Overrides the default dataproc/region property value for this command invocation.

To set the region attribute:

• provide the argument template on the command line with a fully specified name;
• provide the argument --region on the command line;
• set the property dataproc/region.

FLAGS

--autoscaling-policy=AUTOSCALING_POLICY

ID of the autoscaling policy or fully qualified identifier for the autoscaling policy.

To set the autoscaling_policy attribute:

• provide the argument --autoscaling-policy on the command line.

--bucket=BUCKET

The Google Cloud Storage bucket to use by default to stage job dependencies, miscellaneous config files, and job driver console output when using this cluster.

--cluster-name=CLUSTER_NAME

The name of the managed dataproc cluster. If unspecified, the workflow template ID will be used.

--confidential-compute

Enables Confidential VM. See https://cloud.google.com/compute/confidential-vm/docs for more information. Note that Confidential VM can only be enabled when the machine types are N2D (https://cloud.google.com/compute/docs/machine-types#n2d_machine_types) and the image is SEV Compatible.

--dataproc-metastore=DATAPROC_METASTORE

Specify the name of a Dataproc Metastore service to be used as an external metastore in the format: "projects/{project-id}/locations/{region}/services/{service-name}".

--enable-component-gateway

Enable access to the web UIs of selected components on the cluster through the component gateway.

--initialization-action-timeout=TIMEOUT; default="10m"

The maximum duration of each initialization action. See $ gcloud topic datetimes for information on duration formats.

--initialization-actions=CLOUD_STORAGE_URI,[…]

A list of Google Cloud Storage URIs of executables to run on each node in the cluster.

--labels=[KEY=VALUE,…]

List of label KEY=VALUE pairs to add.

Keys must start with a lowercase character and contain only hyphens (-), underscores (_), lowercase characters, and numbers. Values must contain only hyphens (-), underscores (_), lowercase characters, and numbers.

--master-accelerator=[type=TYPE,[count=COUNT],…]

Attaches accelerators, such as GPUs, to the master instance(s).

type

The specific type of accelerator to attach to the instances, such as nvidia-tesla-t4 for NVIDIA T4. Use gcloud compute accelerator-types list to display available accelerator types.

count

The number of accelerators to attach to each instance. The default value is 1.

--master-boot-disk-provisioned-iops=MASTER_BOOT_DISK_PROVISIONED_IOPS

Indicates the IOPS to provision for the disk. This sets the limit for disk I/O operations per second. This is only supported if the bootdisk type is hyperdisk-balanced.

--master-boot-disk-provisioned-throughput=MASTER_BOOT_DISK_PROVISIONED_THROUGHPUT

Indicates the throughput to provision for the disk. This sets the limit for throughput in MiB per second. This is only supported if the bootdisk type is hyperdisk-balanced.

--master-boot-disk-size=MASTER_BOOT_DISK_SIZE

The size of the boot disk. The value must be a whole number followed by a size unit of KB for kilobyte, MB for megabyte, GB for gigabyte, or TB for terabyte. For example, 10GB will produce a 10 gigabyte disk. The minimum boot disk size is 10 GB. Boot disk size must be a multiple of 1 GB.

--master-boot-disk-type=MASTER_BOOT_DISK_TYPE

The type of the boot disk. The value must be pd-balanced, pd-ssd, or pd-standard.

--master-local-ssd-interface=MASTER_LOCAL_SSD_INTERFACE

Interface to use to attach local SSDs to master node(s) in a cluster.

--master-machine-type=MASTER_MACHINE_TYPE

The type of machine to use for the master. Defaults to server-specified.

--master-min-cpu-platform=PLATFORM

When specified, the VM is scheduled on the host with a specified CPU architecture or a more recent CPU platform that's available in that zone. To list available CPU platforms in a zone, run:

gcloud compute zones describe ZONE

CPU platform selection may not be available in a zone. Zones that support CPU platform selection provide an availableCpuPlatforms field, which contains the list of available CPU platforms in the zone (see Availability of CPU platforms for more information).

--min-secondary-worker-fraction=MIN_SECONDARY_WORKER_FRACTION

Minimum fraction of secondary worker nodes required to create the cluster. If it is not met, cluster creation will fail. Must be a decimal value between 0 and 1. The number of required secondary workers is calculated by ceil(min-secondary-worker-fraction * num_secondary_workers). Defaults to 0.0001.

--node-group=NODE_GROUP

The name of the sole-tenant node group to create the cluster on. Can be a short name ("node-group-name") or in the format "projects/{project-id}/zones/{zone}/nodeGroups/{node-group-name}".

--num-master-local-ssds=NUM_MASTER_LOCAL_SSDS

The number of local SSDs to attach to the master in a cluster.

--num-masters=NUM_MASTERS

The number of master nodes in the cluster.

Number of Masters	Cluster Mode
1	Standard
3	High Availability

--num-secondary-worker-local-ssds=NUM_SECONDARY_WORKER_LOCAL_SSDS

The number of local SSDs to attach to each preemptible worker in a cluster.

--num-worker-local-ssds=NUM_WORKER_LOCAL_SSDS

The number of local SSDs to attach to each worker in a cluster.

--optional-components=[COMPONENT,…]

List of optional components to be installed on cluster machines.

The following page documents the optional components that can be installed: https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/optional-components.

--private-ipv6-google-access-type=PRIVATE_IPV6_GOOGLE_ACCESS_TYPE

The private IPv6 Google access type for the cluster. PRIVATE_IPV6_GOOGLE_ACCESS_TYPE must be one of: inherit-subnetwork, outbound, bidirectional.

--properties=[PREFIX:PROPERTY=VALUE,…]

Specifies configuration properties for installed packages, such as Hadoop and Spark.

Properties are mapped to configuration files by specifying a prefix, such as "core:io.serializations". The following are supported prefixes and their mappings:

Prefix	File	Purpose of file
capacity-scheduler	capacity-scheduler.xml	Hadoop YARN Capacity Scheduler configuration
core	core-site.xml	Hadoop general configuration
distcp	distcp-default.xml	Hadoop Distributed Copy configuration
hadoop-env	hadoop-env.sh	Hadoop specific environment variables
hdfs	hdfs-site.xml	Hadoop HDFS configuration
hive	hive-site.xml	Hive configuration
mapred	mapred-site.xml	Hadoop MapReduce configuration
mapred-env	mapred-env.sh	Hadoop MapReduce specific environment variables
pig	pig.properties	Pig configuration
spark	spark-defaults.conf	Spark configuration
spark-env	spark-env.sh	Spark specific environment variables
yarn	yarn-site.xml	Hadoop YARN configuration
yarn-env	yarn-env.sh	Hadoop YARN specific environment variables

See https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/cluster-properties for more information.

--secondary-worker-accelerator=[type=TYPE,[count=COUNT],…]

Attaches accelerators, such as GPUs, to the secondary-worker instance(s).

type

The specific type of accelerator to attach to the instances, such as nvidia-tesla-t4 for NVIDIA T4. Use gcloud compute accelerator-types list to display available accelerator types.

count

The number of accelerators to attach to each instance. The default value is 1.

--secondary-worker-boot-disk-size=SECONDARY_WORKER_BOOT_DISK_SIZE

The size of the boot disk. The value must be a whole number followed by a size unit of KB for kilobyte, MB for megabyte, GB for gigabyte, or TB for terabyte. For example, 10GB will produce a 10 gigabyte disk. The minimum boot disk size is 10 GB. Boot disk size must be a multiple of 1 GB.

--secondary-worker-boot-disk-type=SECONDARY_WORKER_BOOT_DISK_TYPE

The type of the boot disk. The value must be pd-balanced, pd-ssd, or pd-standard.

--secondary-worker-local-ssd-interface=SECONDARY_WORKER_LOCAL_SSD_INTERFACE

Interface to use to attach local SSDs to each secondary worker in a cluster.

--secondary-worker-machine-types=type=MACHINE_TYPE[,type=MACHINE_TYPE…][,rank=RANK]

Types of machines with optional rank for secondary workers to use. Defaults to server-specified.eg. --secondary-worker-machine-types="type=e2-standard-8,type=t2d-standard-8,rank=0"

--secondary-worker-standard-capacity-base=SECONDARY_WORKER_STANDARD_CAPACITY_BASE

This flag sets the base number of Standard VMs to use for secondary workers. Dataproc will create only standard VMs until it reaches this number, then it will mix Spot and Standard VMs according to SECONDARY_WORKER_STANDARD_CAPACITY_PERCENT_ABOVE_BASE.

--secondary-worker-standard-capacity-percent-above-base=SECONDARY_WORKER_STANDARD_CAPACITY_PERCENT_ABOVE_BASE

When combining Standard and Spot VMs for secondary-workers once the number of Standard VMs specified by SECONDARY_WORKER_STANDARD_CAPACITY_BASE has been used, this flag specifies the percentage of the total number of additional Standard VMs secondary workers will use. Spot VMs will be used for the remaining percentage.

--shielded-integrity-monitoring

Enables monitoring and attestation of the boot integrity of the cluster's VMs. vTPM (virtual Trusted Platform Module) must also be enabled. A TPM is a hardware module that can be used for different security operations, such as remote attestation, encryption, and sealing of keys.

--shielded-secure-boot

The cluster's VMs will boot with secure boot enabled.

--shielded-vtpm

The cluster's VMs will boot with the TPM (Trusted Platform Module) enabled. A TPM is a hardware module that can be used for different security operations, such as remote attestation, encryption, and sealing of keys.

--temp-bucket=TEMP_BUCKET

The Google Cloud Storage bucket to use by default to store ephemeral cluster and jobs data, such as Spark and MapReduce history files.

--worker-accelerator=[type=TYPE,[count=COUNT],…]

Attaches accelerators, such as GPUs, to the worker instance(s).

type

The specific type of accelerator to attach to the instances, such as nvidia-tesla-t4 for NVIDIA T4. Use gcloud compute accelerator-types list to display available accelerator types.

count

The number of accelerators to attach to each instance. The default value is 1.

--worker-boot-disk-provisioned-iops=WORKER_BOOT_DISK_PROVISIONED_IOPS

Indicates the IOPS to provision for the disk. This sets the limit for disk I/O operations per second. This is only supported if the bootdisk type is hyperdisk-balanced.

--worker-boot-disk-provisioned-throughput=WORKER_BOOT_DISK_PROVISIONED_THROUGHPUT

Indicates the throughput to provision for the disk. This sets the limit for throughput in MiB per second. This is only supported if the bootdisk type is hyperdisk-balanced.

--worker-boot-disk-size=WORKER_BOOT_DISK_SIZE

The size of the boot disk. The value must be a whole number followed by a size unit of KB for kilobyte, MB for megabyte, GB for gigabyte, or TB for terabyte. For example, 10GB will produce a 10 gigabyte disk. The minimum boot disk size is 10 GB. Boot disk size must be a multiple of 1 GB.

--worker-boot-disk-type=WORKER_BOOT_DISK_TYPE

The type of the boot disk. The value must be pd-balanced, pd-ssd, or pd-standard.

--worker-local-ssd-interface=WORKER_LOCAL_SSD_INTERFACE

Interface to use to attach local SSDs to each worker in a cluster.

--worker-min-cpu-platform=PLATFORM

When specified, the VM is scheduled on the host with a specified CPU architecture or a more recent CPU platform that's available in that zone. To list available CPU platforms in a zone, run:

gcloud compute zones describe ZONE

CPU platform selection may not be available in a zone. Zones that support CPU platform selection provide an availableCpuPlatforms field, which contains the list of available CPU platforms in the zone (see Availability of CPU platforms for more information).

--zone=ZONE

The compute zone (e.g. us-central1-a) for the cluster. If empty and --region is set to a value other than global, the server will pick a zone in the region. Overrides the default compute/zone property value for this command invocation.

Specifying these flags will enable Secure Multi-Tenancy for the cluster.

At most one of these can be specified:

--identity-config-file=IDENTITY_CONFIG_FILE

Path to a YAML (or JSON) file containing the configuration for Secure Multi-Tenancy on the cluster. The path can be a Cloud Storage URL (Example: 'gs://path/to/file') or a local file system path. If you pass "-" as the value of the flag the file content will be read from stdin.

The YAML file is formatted as follows:

  # Required. The mapping from user accounts to service accounts.
  user_service_account_mapping:
    [e-mail]: [e-mail]
    [e-mail]: [e-mail]

--secure-multi-tenancy-user-mapping=SECURE_MULTI_TENANCY_USER_MAPPING

A string of user-to-service-account mappings. Mappings are separated by commas, and each mapping takes the form of "user-account:service-account". Example: "[e-mail]:[e-mail],[e-mail]:[e-mail]".

At most one of these can be specified:

--image=IMAGE

The custom image used to create the cluster. It can be the image name, the image URI, or the image family URI, which selects the latest image from the family.

--image-version=VERSION

The image version to use for the cluster. Defaults to the latest version.

Specifying these flags will enable Kerberos for the cluster.

At most one of these can be specified:

--kerberos-config-file=KERBEROS_CONFIG_FILE

Path to a YAML (or JSON) file containing the configuration for Kerberos on the cluster. If you pass - as the value of the flag the file content will be read from stdin.

The YAML file is formatted as follows:

  # Optional. Flag to indicate whether to Kerberize the cluster.
  # The default value is true.
  enable_kerberos: true

  # Optional. The Google Cloud Storage URI of a KMS encrypted file
  # containing the root principal password.
  root_principal_password_uri: gs://bucket/password.encrypted

  # Optional. The URI of the Cloud KMS key used to encrypt
  # sensitive files.
  kms_key_uri:
    projects/myproject/locations/global/keyRings/mykeyring/cryptoKeys/my-key

  # Configuration of SSL encryption. If specified, all sub-fields
  # are required. Otherwise, Dataproc will provide a self-signed
  # certificate and generate the passwords.
  ssl:
    # Optional. The Google Cloud Storage URI of the keystore file.
    keystore_uri: gs://bucket/keystore.jks

    # Optional. The Google Cloud Storage URI of a KMS encrypted
    # file containing the password to the keystore.
    keystore_password_uri: gs://bucket/keystore_password.encrypted

    # Optional. The Google Cloud Storage URI of a KMS encrypted
    # file containing the password to the user provided key.
    key_password_uri: gs://bucket/key_password.encrypted

    # Optional. The Google Cloud Storage URI of the truststore
    # file.
    truststore_uri: gs://bucket/truststore.jks

    # Optional. The Google Cloud Storage URI of a KMS encrypted
    # file containing the password to the user provided
    # truststore.
    truststore_password_uri:
      gs://bucket/truststore_password.encrypted

  # Configuration of cross realm trust.
  cross_realm_trust:
    # Optional. The remote realm the Dataproc on-cluster KDC will
    # trust, should the user enable cross realm trust.
    realm: REMOTE.REALM

    # Optional. The KDC (IP or hostname) for the remote trusted
    # realm in a cross realm trust relationship.
    kdc: kdc.remote.realm

    # Optional. The admin server (IP or hostname) for the remote
    # trusted realm in a cross realm trust relationship.
    admin_server: admin-server.remote.realm

    # Optional. The Google 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.
    shared_password_uri:
      gs://bucket/cross-realm.password.encrypted

  # Optional. The Google Cloud Storage URI of a KMS encrypted file
  # containing the master key of the KDC database.
  kdc_db_key_uri: gs://bucket/kdc_db_key.encrypted

  # Optional. The lifetime of the ticket granting ticket, in
  # hours. If not specified, or user specifies 0, then default
  # value 10 will be used.
  tgt_lifetime_hours: 1

  # Optional. The name of the Kerberos realm. If not specified,
  # the uppercased domain name of the cluster will be used.
  realm: REALM.NAME

--enable-kerberos

Enable Kerberos on the cluster.

--kerberos-root-principal-password-uri=KERBEROS_ROOT_PRINCIPAL_PASSWORD_URI

Google Cloud Storage URI of a KMS encrypted file containing the root principal password. Must be a Cloud Storage URL beginning with 'gs://'.

Key resource - The Cloud KMS (Key Management Service) cryptokey that will be used to protect the password. The 'Compute Engine Service Agent' service account must hold permission 'Cloud KMS CryptoKey Encrypter/Decrypter'. The arguments in this group can be used to specify the attributes of this resource.

--kerberos-kms-key=KERBEROS_KMS_KEY

ID of the key or fully qualified identifier for the key.

To set the kms-key attribute:

• provide the argument --kerberos-kms-key on the command line.

This flag argument must be specified if any of the other arguments in this group are specified.

--kerberos-kms-key-keyring=KERBEROS_KMS_KEY_KEYRING

The KMS keyring of the key.

To set the kms-keyring attribute:

• provide the argument --kerberos-kms-key on the command line with a fully specified name;
• provide the argument --kerberos-kms-key-keyring on the command line.

--kerberos-kms-key-location=KERBEROS_KMS_KEY_LOCATION

The Google Cloud location for the key.

To set the kms-location attribute:

• provide the argument --kerberos-kms-key on the command line with a fully specified name;
• provide the argument --kerberos-kms-key-location on the command line.

--kerberos-kms-key-project=KERBEROS_KMS_KEY_PROJECT

The Google Cloud project for the key.

To set the kms-project attribute:

• provide the argument --kerberos-kms-key on the command line with a fully specified name;
• provide the argument --kerberos-kms-key-project on the command line;
• set the property core/project.

Key resource - The Cloud KMS (Key Management Service) cryptokey that will be used to protect the cluster. The 'Compute Engine Service Agent' service account must hold permission 'Cloud KMS CryptoKey Encrypter/Decrypter'. The arguments in this group can be used to specify the attributes of this resource.

--kms-key=KMS_KEY

ID of the key or fully qualified identifier for the key.

To set the kms-key attribute:

• provide the argument --kms-key on the command line.

This flag argument must be specified if any of the other arguments in this group are specified.

--kms-keyring=KMS_KEYRING

The KMS keyring of the key.

To set the kms-keyring attribute:

• provide the argument --kms-key on the command line with a fully specified name;
• provide the argument --kms-keyring on the command line.

--kms-location=KMS_LOCATION

The Google Cloud location for the key.

To set the kms-location attribute:

• provide the argument --kms-key on the command line with a fully specified name;
• provide the argument --kms-location on the command line.

--kms-project=KMS_PROJECT

The Google Cloud project for the key.

To set the kms-project attribute:

• provide the argument --kms-key on the command line with a fully specified name;
• provide the argument --kms-project on the command line;
• set the property core/project.

Compute Engine options for Dataproc clusters.

--metadata=KEY=VALUE,[KEY=VALUE,…]

Metadata to be made available to the guest operating system running on the instances

--scopes=SCOPE,[SCOPE,…]

Specifies scopes for the node instances. Multiple SCOPEs can be specified, separated by commas. Examples:

gcloud dataproc workflow-templates set-managed-cluster example-cluster --scopes https://www.googleapis.com/auth/bigtable.admin

gcloud dataproc workflow-templates set-managed-cluster example-cluster --scopes sqlservice,bigquery

The following minimum scopes are necessary for the cluster to function properly and are always added, even if not explicitly specified:

https://www.googleapis.com/auth/devstorage.read_write
https://www.googleapis.com/auth/logging.write

If the --scopes flag is not specified, the following default scopes are also included:

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

If you want to enable all scopes use the 'cloud-platform' scope.

SCOPE can be either the full URI of the scope or an alias. Default scopes are assigned to all instances. Available aliases are:

Alias	URI
bigquery	https://www.googleapis.com/auth/bigquery
cloud-platform	https://www.googleapis.com/auth/cloud-platform
cloud-source-repos	https://www.googleapis.com/auth/source.full_control
cloud-source-repos-ro	https://www.googleapis.com/auth/source.read_only
compute-ro	https://www.googleapis.com/auth/compute.readonly
compute-rw	https://www.googleapis.com/auth/compute
datastore	https://www.googleapis.com/auth/datastore
default	https://www.googleapis.com/auth/devstorage.read_only
	https://www.googleapis.com/auth/logging.write
	https://www.googleapis.com/auth/monitoring.write
	https://www.googleapis.com/auth/pubsub
	https://www.googleapis.com/auth/service.management.readonly
	https://www.googleapis.com/auth/servicecontrol
	https://www.googleapis.com/auth/trace.append
gke-default	https://www.googleapis.com/auth/devstorage.read_only
	https://www.googleapis.com/auth/logging.write
	https://www.googleapis.com/auth/monitoring
	https://www.googleapis.com/auth/service.management.readonly
	https://www.googleapis.com/auth/servicecontrol
	https://www.googleapis.com/auth/trace.append
logging-write	https://www.googleapis.com/auth/logging.write
monitoring	https://www.googleapis.com/auth/monitoring
monitoring-read	https://www.googleapis.com/auth/monitoring.read
monitoring-write	https://www.googleapis.com/auth/monitoring.write
pubsub	https://www.googleapis.com/auth/pubsub
service-control	https://www.googleapis.com/auth/servicecontrol
service-management	https://www.googleapis.com/auth/service.management.readonly
sql (deprecated)	https://www.googleapis.com/auth/sqlservice
sql-admin	https://www.googleapis.com/auth/sqlservice.admin
storage-full	https://www.googleapis.com/auth/devstorage.full_control
storage-ro	https://www.googleapis.com/auth/devstorage.read_only
storage-rw	https://www.googleapis.com/auth/devstorage.read_write
taskqueue	https://www.googleapis.com/auth/taskqueue
trace	https://www.googleapis.com/auth/trace.append
userinfo-email	https://www.googleapis.com/auth/userinfo.email

DEPRECATION WARNING: https://www.googleapis.com/auth/sqlservice account scope and sql alias do not provide SQL instance management capabilities and have been deprecated. Please, use https://www.googleapis.com/auth/sqlservice.admin or sql-admin to manage your Google SQL Service instances.

--service-account=SERVICE_ACCOUNT

The Google Cloud IAM service account to be authenticated as.

--tags=TAG,[TAG,…]

Specifies a list of tags to apply to the instance. These tags allow network firewall rules and routes to be applied to specified VM instances. See gcloud compute firewall-rules create(1) for more details.

To read more about configuring network tags, read this guide: https://cloud.google.com/vpc/docs/add-remove-network-tags

To list instances with their respective status and tags, run:

gcloud compute instances list --format='table(name,status,tags.list())'

To list instances tagged with a specific tag, tag1, run:

gcloud compute instances list --filter='tags:tag1'

At most one of these can be specified:

--network=NETWORK

The Compute Engine network that the VM instances of the cluster will be part of. This is mutually exclusive with --subnet. If neither is specified, this defaults to the "default" network.

--subnet=SUBNET

Specifies the subnet that the cluster will be part of. This is mutally exclusive with --network.

Specifies the reservation for the instance.

--reservation=RESERVATION

The name of the reservation, required when --reservation-affinity=specific.

--reservation-affinity=RESERVATION_AFFINITY; default="any"

The type of reservation for the instance. RESERVATION_AFFINITY must be one of: any, none, specific.

--metric-sources=[METRIC_SOURCE,…]

Specifies a list of cluster Metric Sources to collect custom metrics. METRIC_SOURCE must be one of: FLINK, HDFS, HIVEMETASTORE, HIVESERVER2, MONITORING_AGENT_DEFAULTS, SPARK, SPARK_HISTORY_SERVER, YARN.

At most one of these can be specified:

--metric-overrides=[METRIC_SOURCE:INSTANCE:GROUP:METRIC,…]

List of metrics that override the default metrics enabled for the metric sources. Any of the available OSS metrics and all Spark metrics, can be listed for collection as a metric override. Override metric values are case sensitive, and must be provided, if appropriate, in CamelCase format, for example:

sparkHistoryServer:JVM:Memory:NonHeapMemoryUsage.committed hiveserver2:JVM:Memory:NonHeapMemoryUsage.used

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

The source of the specified metric override must be enabled. For example, if one or more spark:driver metrics are provided as metric overrides, the spark metric source must be enabled (--metric-sources=spark).

--metric-overrides-file=METRIC_OVERRIDES_FILE

Path to a file containing list of Metrics that override the default metrics enabled for the metric sources. The path can be a Cloud Storage URL (example: gs://path/to/file) or a local file system path.

At most one of these can be specified:

--no-address

If provided, the instances in the cluster will not be assigned external IP addresses.

If omitted, then the Dataproc service will apply a default policy to determine if each instance in the cluster gets an external IP address or not.

Note: Dataproc VMs need access to the Dataproc API. This can be achieved without external IP addresses using Private Google Access (https://cloud.google.com/compute/docs/private-google-access).

--public-ip-address

If provided, cluster instances are assigned external IP addresses.

If omitted, the Dataproc service applies a default policy to determine whether or not each instance in the cluster gets an external IP address.

Note: Dataproc VMs need access to the Dataproc API. This can be achieved without external IP addresses using Private Google Access (https://cloud.google.com/compute/docs/private-google-access).

At most one of these can be specified:

--single-node

Create a single node cluster.

A single node cluster has all master and worker components. It cannot have any separate worker nodes. If this flag is not specified, a cluster with separate workers is created.

Multi-node cluster flags

--min-num-workers=MIN_NUM_WORKERS

Minimum number of primary worker nodes to provision for cluster creation to succeed.

--num-secondary-workers=NUM_SECONDARY_WORKERS

The number of secondary worker nodes in the cluster.

--num-workers=NUM_WORKERS

The number of worker nodes in the cluster. Defaults to server-specified.

--secondary-worker-type=TYPE; default="preemptible"

The type of the secondary worker group. TYPE must be one of: preemptible, non-preemptible, spot.

At most one of these can be specified:

--worker-machine-type=WORKER_MACHINE_TYPE

The type of machine to use for primary workers. Defaults to server-specified.

--worker-machine-types=type=MACHINE_TYPE[,type=MACHINE_TYPE…][,rank=RANK]

Machine types for primary worker nodes to use with optional rank. A lower rank number is given higher preference. Based on availablilty, Dataproc tries to create primary worker VMs using the worker machine type with the lowest rank, and then tries to use machine types with higher ranks as necessary. Machine types with the same rank are given the same preference. Example use: --worker-machine-types="type=e2-standard-8,type=n2-standard-8,rank=0". For more information, see Dataproc Flexible VMs

GCLOUD WIDE FLAGS

These flags are available to all commands: --access-token-file, --account, --billing-project, --configuration, --flags-file, --flatten, --format, --help, --impersonate-service-account, --log-http, --project, --quiet, --trace-token, --user-output-enabled, --verbosity.

Run $ gcloud help for details.

NOTES

These variants are also available:

gcloud alpha dataproc workflow-templates set-managed-cluster

gcloud beta dataproc workflow-templates set-managed-cluster