Class DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Jsii$Proxy
- java.lang.Object
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- software.amazon.jsii.JsiiObject
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- com.hashicorp.cdktf.providers.google.dataproc_autoscaling_policy.DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Jsii$Proxy
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- All Implemented Interfaces:
DataprocAutoscalingPolicyBasicAlgorithmYarnConfig,software.amazon.jsii.JsiiSerializable
- Enclosing interface:
- DataprocAutoscalingPolicyBasicAlgorithmYarnConfig
@Stability(Stable) @Internal public static final class DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Jsii$Proxy extends software.amazon.jsii.JsiiObject implements DataprocAutoscalingPolicyBasicAlgorithmYarnConfig
An implementation forDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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Nested Class Summary
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Nested classes/interfaces inherited from class software.amazon.jsii.JsiiObject
software.amazon.jsii.JsiiObject.InitializationMode
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Nested classes/interfaces inherited from interface com.hashicorp.cdktf.providers.google.dataproc_autoscaling_policy.DataprocAutoscalingPolicyBasicAlgorithmYarnConfig
DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Builder, DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Jsii$Proxy
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Constructor Summary
Constructors Modifier Constructor Description protectedJsii$Proxy(DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Builder builder)Constructor that initializes the object based on literal property values passed by theDataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Builder.protectedJsii$Proxy(software.amazon.jsii.JsiiObjectRef objRef)Constructor that initializes the object based on values retrieved from the JsiiObject.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description com.fasterxml.jackson.databind.JsonNode$jsii$toJson()booleanequals(Object o)StringgetGracefulDecommissionTimeout()Timeout for YARN graceful decommissioning of Node Managers.NumbergetScaleDownFactor()Fraction of average pending memory in the last cooldown period for which to remove workers.NumbergetScaleDownMinWorkerFraction()Minimum scale-down threshold as a fraction of total cluster size before scaling occurs.NumbergetScaleUpFactor()Fraction of average pending memory in the last cooldown period for which to add workers.NumbergetScaleUpMinWorkerFraction()Minimum scale-up threshold as a fraction of total cluster size before scaling occurs.inthashCode()
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Constructor Detail
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Jsii$Proxy
protected Jsii$Proxy(software.amazon.jsii.JsiiObjectRef objRef)
Constructor that initializes the object based on values retrieved from the JsiiObject.- Parameters:
objRef- Reference to the JSII managed object.
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Jsii$Proxy
protected Jsii$Proxy(DataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Builder builder)
Constructor that initializes the object based on literal property values passed by theDataprocAutoscalingPolicyBasicAlgorithmYarnConfig.Builder.
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Method Detail
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getGracefulDecommissionTimeout
public final String getGracefulDecommissionTimeout()
Description copied from interface:DataprocAutoscalingPolicyBasicAlgorithmYarnConfigTimeout 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]. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dataproc_autoscaling_policy#graceful_decommission_timeout DataprocAutoscalingPolicy#graceful_decommission_timeout}
- Specified by:
getGracefulDecommissionTimeoutin interfaceDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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getScaleDownFactor
public final Number getScaleDownFactor()
Description copied from interface:DataprocAutoscalingPolicyBasicAlgorithmYarnConfigFraction of average 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. Bounds: [0.0, 1.0]. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dataproc_autoscaling_policy#scale_down_factor DataprocAutoscalingPolicy#scale_down_factor}
- Specified by:
getScaleDownFactorin interfaceDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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getScaleUpFactor
public final Number getScaleUpFactor()
Description copied from interface:DataprocAutoscalingPolicyBasicAlgorithmYarnConfigFraction of average 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). Bounds: [0.0, 1.0]. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dataproc_autoscaling_policy#scale_up_factor DataprocAutoscalingPolicy#scale_up_factor}
- Specified by:
getScaleUpFactorin interfaceDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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getScaleDownMinWorkerFraction
public final Number getScaleDownMinWorkerFraction()
Description copied from interface:DataprocAutoscalingPolicyBasicAlgorithmYarnConfigMinimum 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. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dataproc_autoscaling_policy#scale_down_min_worker_fraction DataprocAutoscalingPolicy#scale_down_min_worker_fraction}
- Specified by:
getScaleDownMinWorkerFractionin interfaceDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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getScaleUpMinWorkerFraction
public final Number getScaleUpMinWorkerFraction()
Description copied from interface:DataprocAutoscalingPolicyBasicAlgorithmYarnConfigMinimum 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. Docs at Terraform Registry: {@link https://registry.terraform.io/providers/hashicorp/google/5.43.1/docs/resources/dataproc_autoscaling_policy#scale_up_min_worker_fraction DataprocAutoscalingPolicy#scale_up_min_worker_fraction}
- Specified by:
getScaleUpMinWorkerFractionin interfaceDataprocAutoscalingPolicyBasicAlgorithmYarnConfig
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$jsii$toJson
@Internal public com.fasterxml.jackson.databind.JsonNode $jsii$toJson()
- Specified by:
$jsii$toJsonin interfacesoftware.amazon.jsii.JsiiSerializable
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