com.google.api.services.dataproc.v1beta2.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.v1beta2.model.BasicYarnAutoscalingConfig

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class BasicYarnAutoscalingConfig
extends 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

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

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 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 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 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 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 GenericJson

clone

public BasicYarnAutoscalingConfig clone()

Overrides:

clone in class GenericJson