def Run(self, args):
dataproc = dp.Dataproc(self.ReleaseTrack())
template_ref = args.CONCEPTS.template.Parse()
workflow_template = dataproc.GetRegionsWorkflowTemplate(
template_ref, args.version)
if args.cluster_name:
cluster_name = args.cluster_name
else:
cluster_name = template_ref.workflowTemplatesId
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), cluster_name)
beta = self.ReleaseTrack() == base.ReleaseTrack.BETA
cluster_config = clusters.GetClusterConfig(args, dataproc,
template_ref.projectsId,
compute_resources, beta)
labels = labels_util.ParseCreateArgs(
args, dataproc.messages.ManagedCluster.LabelsValue)
managed_cluster = dataproc.messages.ManagedCluster(
clusterName=cluster_name, config=cluster_config, labels=labels)
workflow_template.placement = dataproc.messages.WorkflowTemplatePlacement(
managedCluster=managed_cluster)
response = dataproc.client.projects_regions_workflowTemplates.Update(
workflow_template)
return response
def Run(self, args):
self.ValidateArgs(args)
dataproc = dp.Dataproc(self.ReleaseTrack())
cluster_ref = args.CONCEPTS.cluster.Parse()
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), cluster_ref.clusterName, cluster_ref.region)
cluster_config = clusters.GetClusterConfig(args,
dataproc,
cluster_ref.projectId,
compute_resources,
self.BETA,
include_ttl_config=True)
cluster = dataproc.messages.Cluster(
config=cluster_config,
clusterName=cluster_ref.clusterName,
projectId=cluster_ref.projectId)
self.ConfigureCluster(dataproc.messages, args, cluster)
return clusters.CreateCluster(dataproc, cluster_ref, cluster,
args.async_, args.timeout)
def Run(self, args):
dataproc = dp.Dataproc(self.ReleaseTrack())
template = util.ParseWorkflowTemplates(args.template, dataproc)
workflow_template = dataproc.GetRegionsWorkflowTemplate(
template, args.version)
cluster_name = template.workflowTemplatesId
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), cluster_name)
use_accelerators = self.ReleaseTrack() == base.ReleaseTrack.BETA
use_auto_delete_ttl = self.ReleaseTrack() == base.ReleaseTrack.BETA
use_min_cpu_platform = self.ReleaseTrack() == base.ReleaseTrack.BETA
cluster_config = clusters.GetClusterConfig(
args, dataproc, template.projectsId, compute_resources,
use_accelerators, use_auto_delete_ttl, use_min_cpu_platform)
labels = labels_util.ParseCreateArgs(
args, dataproc.messages.ManagedCluster.LabelsValue)
managed_cluster = dataproc.messages.ManagedCluster(
clusterName=cluster_name, config=cluster_config, labels=labels)
workflow_template.placement = dataproc.messages.WorkflowTemplatePlacement(
managedCluster=managed_cluster)
response = dataproc.client.projects_regions_workflowTemplates.Update(
workflow_template)
return response
def Run(self, args):
self.ValidateArgs(args)
dataproc = dp.Dataproc(self.ReleaseTrack())
cluster_ref = args.CONCEPTS.cluster.Parse()
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), cluster_ref.clusterName, cluster_ref.region)
cluster_config = clusters.GetClusterConfig(
args,
dataproc,
cluster_ref.projectId,
compute_resources,
self.BETA,
include_ttl_config=True,
include_gke_platform_args=self.BETA)
action_on_failed_primary_workers = None
if not self.BETA:
action_on_failed_primary_workers = arg_utils.ChoiceToEnum(
args.action_on_failed_primary_workers,
dataproc.messages.DataprocProjectsRegionsClustersCreateRequest
.ActionOnFailedPrimaryWorkersValueValuesEnum)
cluster = dataproc.messages.Cluster(
config=cluster_config,
clusterName=cluster_ref.clusterName,
projectId=cluster_ref.projectId)
self.ConfigureCluster(dataproc.messages, args, cluster)
return clusters.CreateCluster(
dataproc,
cluster_ref,
cluster,
args.async_,
args.timeout,
enable_create_on_gke=self.BETA,
action_on_failed_primary_workers=action_on_failed_primary_workers)
def Run(self, args):
self.ValidateArgs(args)
dataproc = dp.Dataproc(self.ReleaseTrack())
cluster_ref = util.ParseCluster(args.name, dataproc)
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), args.name)
beta = self.ReleaseTrack() == base.ReleaseTrack.BETA
cluster_config = clusters.GetClusterConfig(
args, dataproc, cluster_ref.projectId, compute_resources, beta)
cluster = dataproc.messages.Cluster(
config=cluster_config,
clusterName=cluster_ref.clusterName,
projectId=cluster_ref.projectId)
self.ConfigureCluster(dataproc.messages, args, cluster)
return clusters.CreateCluster(dataproc, cluster, args.async, args.timeout)
def Run(self, args):
self.ValidateArgs(args)
dataproc = dp.Dataproc(self.ReleaseTrack())
cluster_ref = util.ParseCluster(args.name, dataproc)
compute_resources = compute_helpers.GetComputeResources(
self.ReleaseTrack(), args.name)
beta = self.ReleaseTrack() == base.ReleaseTrack.BETA
cluster_config = clusters.GetClusterConfig(args, dataproc,
cluster_ref.projectId,
compute_resources, beta)
cluster = dataproc.messages.Cluster(
config=cluster_config,
clusterName=cluster_ref.clusterName,
projectId=cluster_ref.projectId)
self.ConfigureCluster(dataproc.messages, args, cluster)
operation = dataproc.client.projects_regions_clusters.Create(
dataproc.messages.DataprocProjectsRegionsClustersCreateRequest(
projectId=cluster_ref.projectId,
region=cluster_ref.region,
cluster=cluster))
if args. async:
log.status.write('Creating [{0}] with operation [{1}].'.format(
cluster_ref, operation.name))
return
operation = util.WaitForOperation(
dataproc,
operation,
message='Waiting for cluster creation operation',
timeout_s=args.timeout)
get_request = dataproc.messages.DataprocProjectsRegionsClustersGetRequest(
projectId=cluster_ref.projectId,
region=cluster_ref.region,
clusterName=cluster_ref.clusterName)
cluster = dataproc.client.projects_regions_clusters.Get(get_request)
if cluster.status.state == (
dataproc.messages.ClusterStatus.StateValueValuesEnum.RUNNING):
zone_uri = cluster.config.gceClusterConfig.zoneUri
zone_short_name = zone_uri.split('/')[-1]
# Log the URL of the cluster
log.CreatedResource(
cluster_ref,
# Also indicate which zone the cluster was placed in. This is helpful
# if the server picked a zone (auto zone)
details='Cluster placed in zone [{0}]'.format(zone_short_name))
else:
log.error('Create cluster failed!')
if operation.details:
log.error('Details:\n' + operation.details)
return cluster
