class Google::Apis::DataprocV1::BasicYarnAutoscalingConfig

Basic autoscaling configurations for YARN.

Attributes

graceful_decommission_timeout[RW]

Required. Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d. Corresponds to the JSON property `gracefulDecommissionTimeout` @return [String]

scale_down_factor[RW]

Required. Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works ( cloud.google.com/dataproc/docs/concepts/configuring-clusters/ autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0. Corresponds to the JSON property `scaleDownFactor` @return [Float]

scale_down_min_worker_fraction[RW]

Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0. Corresponds to the JSON property `scaleDownMinWorkerFraction` @return [Float]

scale_up_factor[RW]

Required. Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works (cloud. google.com/dataproc/docs/concepts/configuring-clusters/autoscaling# how_autoscaling_works) for more information.Bounds: 0.0, 1.0. Corresponds to the JSON property `scaleUpFactor` @return [Float]

scale_up_min_worker_fraction[RW]

Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0. Corresponds to the JSON property `scaleUpMinWorkerFraction` @return [Float]

Public Class Methods

new(**args) click to toggle source
# File lib/google/apis/dataproc_v1/classes.rb, line 217
def initialize(**args)
   update!(**args)
end

Public Instance Methods

update!(**args) click to toggle source

Update properties of this object

# File lib/google/apis/dataproc_v1/classes.rb, line 222
def update!(**args)
  @graceful_decommission_timeout = args[:graceful_decommission_timeout] if args.key?(:graceful_decommission_timeout)
  @scale_down_factor = args[:scale_down_factor] if args.key?(:scale_down_factor)
  @scale_down_min_worker_fraction = args[:scale_down_min_worker_fraction] if args.key?(:scale_down_min_worker_fraction)
  @scale_up_factor = args[:scale_up_factor] if args.key?(:scale_up_factor)
  @scale_up_min_worker_fraction = args[:scale_up_min_worker_fraction] if args.key?(:scale_up_min_worker_fraction)
end