Struct google_dataproc1::api::BasicYarnAutoscalingConfig

pub struct BasicYarnAutoscalingConfig {
    pub graceful_decommission_timeout: Option<String>,
    pub scale_down_factor: Option<f64>,
    pub scale_down_min_worker_fraction: Option<f64>,
    pub scale_up_factor: Option<f64>,
    pub scale_up_min_worker_fraction: Option<f64>,
}

Basic autoscaling configurations for YARN.

This type is not used in any activity, and only used as part of another schema.

Fields

graceful_decommission_timeout: Option<String>

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.

scale_down_factor: Option<f64>

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 (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.

scale_down_min_worker_fraction: Option<f64>

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.

scale_up_factor: Option<f64>

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 (https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works) for more information.Bounds: 0.0, 1.0.

scale_up_min_worker_fraction: Option<f64>

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.

Trait Implementations

impl Clone for BasicYarnAutoscalingConfig

fn clone(&self) -> BasicYarnAutoscalingConfig

Returns a copy of the value.

pub fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for BasicYarnAutoscalingConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for BasicYarnAutoscalingConfig

fn default() -> BasicYarnAutoscalingConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for BasicYarnAutoscalingConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl Part for BasicYarnAutoscalingConfig

impl Serialize for BasicYarnAutoscalingConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.