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BasicYarnAutoscalingConfig (Cloud Dataproc API v1-rev20240605-2.0.0)











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com.google.api.services.dataproc.model
Class BasicYarnAutoscalingConfig



java.lang.Object


java.util.AbstractMap<String,Object>


com.google.api.client.util.GenericData


com.google.api.client.json.GenericJson


com.google.api.services.dataproc.model.BasicYarnAutoscalingConfig













All Implemented Interfaces:
Cloneable, Map<String,Object>




public final class BasicYarnAutoscalingConfig
extends com.google.api.client.json.GenericJson
Basic autoscaling configurations for YARN.

  This is the Java data model class that specifies how to parse/serialize into the JSON that is
 transmitted over HTTP when working with the Cloud Dataproc API. For a detailed explanation see:
 https://developers.google.com/api-client-library/java/google-http-java-client/json
 

Author:
Google, Inc.












Nested Class Summary




Nested classes/interfaces inherited from class com.google.api.client.util.GenericData
com.google.api.client.util.GenericData.Flags





Nested classes/interfaces inherited from class java.util.AbstractMap
AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>





Nested classes/interfaces inherited from interface java.util.Map
Map.Entry<K,V>








Constructor Summary

Constructors 

Constructor and Description


BasicYarnAutoscalingConfig() 









Method Summary

All Methods Instance Methods Concrete Methods 

Modifier and Type
Method and Description


BasicYarnAutoscalingConfig
clone() 


String
getGracefulDecommissionTimeout()
Required.



Double
getScaleDownFactor()
Required.



Double
getScaleDownMinWorkerFraction()
Optional.



Double
getScaleUpFactor()
Required.



Double
getScaleUpMinWorkerFraction()
Optional.



BasicYarnAutoscalingConfig
set(String fieldName,
   Object value) 


BasicYarnAutoscalingConfig
setGracefulDecommissionTimeout(String gracefulDecommissionTimeout)
Required.



BasicYarnAutoscalingConfig
setScaleDownFactor(Double scaleDownFactor)
Required.



BasicYarnAutoscalingConfig
setScaleDownMinWorkerFraction(Double scaleDownMinWorkerFraction)
Optional.



BasicYarnAutoscalingConfig
setScaleUpFactor(Double scaleUpFactor)
Required.



BasicYarnAutoscalingConfig
setScaleUpMinWorkerFraction(Double scaleUpMinWorkerFraction)
Optional.







Methods inherited from class com.google.api.client.json.GenericJson
getFactory, setFactory, toPrettyString, toString





Methods inherited from class com.google.api.client.util.GenericData
entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys





Methods inherited from class java.util.AbstractMap
clear, containsKey, containsValue, isEmpty, keySet, size, values





Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait





Methods inherited from interface java.util.Map
compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll














Constructor Detail





BasicYarnAutoscalingConfig
public BasicYarnAutoscalingConfig()









Method Detail





getGracefulDecommissionTimeout
public String getGracefulDecommissionTimeout()
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.

Returns:
value or null for none








setGracefulDecommissionTimeout
public BasicYarnAutoscalingConfig setGracefulDecommissionTimeout(String gracefulDecommissionTimeout)
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.

Parameters:
gracefulDecommissionTimeout - gracefulDecommissionTimeout or null for none








getScaleDownFactor
public Double getScaleDownFactor()
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.

Returns:
value or null for none








setScaleDownFactor
public BasicYarnAutoscalingConfig setScaleDownFactor(Double scaleDownFactor)
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.

Parameters:
scaleDownFactor - scaleDownFactor or null for none








getScaleDownMinWorkerFraction
public Double getScaleDownMinWorkerFraction()
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.

Returns:
value or null for none








setScaleDownMinWorkerFraction
public BasicYarnAutoscalingConfig setScaleDownMinWorkerFraction(Double scaleDownMinWorkerFraction)
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.

Parameters:
scaleDownMinWorkerFraction - scaleDownMinWorkerFraction or null for none








getScaleUpFactor
public Double getScaleUpFactor()
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.

Returns:
value or null for none








setScaleUpFactor
public BasicYarnAutoscalingConfig setScaleUpFactor(Double scaleUpFactor)
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.

Parameters:
scaleUpFactor - scaleUpFactor or null for none








getScaleUpMinWorkerFraction
public Double getScaleUpMinWorkerFraction()
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.

Returns:
value or null for none








setScaleUpMinWorkerFraction
public BasicYarnAutoscalingConfig setScaleUpMinWorkerFraction(Double scaleUpMinWorkerFraction)
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.

Parameters:
scaleUpMinWorkerFraction - scaleUpMinWorkerFraction or null for none








set
public BasicYarnAutoscalingConfig set(String fieldName,
                                      Object value)

Overrides:
set in class com.google.api.client.json.GenericJson








clone
public BasicYarnAutoscalingConfig clone()

Overrides:
clone in class com.google.api.client.json.GenericJson














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Copyright © 2011–2024 Google. All rights reserved.

Modifier and Type	Method and Description
`BasicYarnAutoscalingConfig`	`clone()`
`String`	`getGracefulDecommissionTimeout()` Required.
`Double`	`getScaleDownFactor()` Required.
`Double`	`getScaleDownMinWorkerFraction()` Optional.
`Double`	`getScaleUpFactor()` Required.
`Double`	`getScaleUpMinWorkerFraction()` Optional.
`BasicYarnAutoscalingConfig`	`set(String fieldName, Object value)`
`BasicYarnAutoscalingConfig`	`setGracefulDecommissionTimeout(String gracefulDecommissionTimeout)` Required.
`BasicYarnAutoscalingConfig`	`setScaleDownFactor(Double scaleDownFactor)` Required.
`BasicYarnAutoscalingConfig`	`setScaleDownMinWorkerFraction(Double scaleDownMinWorkerFraction)` Optional.
`BasicYarnAutoscalingConfig`	`setScaleUpFactor(Double scaleUpFactor)` Required.
`BasicYarnAutoscalingConfig`	`setScaleUpMinWorkerFraction(Double scaleUpMinWorkerFraction)` Optional.