AutoscalingPolicyBasicAlgorithmYarnConfig class
Constructors
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AutoscalingPolicyBasicAlgorithmYarnConfig({required Input<String> gracefulDecommissionTimeout, required Input<double> scaleDownFactor, Input<double?>? scaleDownMinWorkerFraction, required Input<double> scaleUpFactor, Input<double?>? scaleUpMinWorkerFraction})
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Creates a new AutoscalingPolicyBasicAlgorithmYarnConfig.
gracefulDecommissionTimeout Timeout for YARN graceful decommissioning of Node Managers. Specifies the
scaleDownFactor Fraction of average pending memory in the last cooldown period for which to
scaleDownMinWorkerFraction Minimum scale-down threshold as a fraction of total cluster size before scaling occurs.
scaleUpFactor Fraction of average pending memory in the last cooldown period for which to
scaleUpMinWorkerFraction Minimum scale-up threshold as a fraction of total cluster size before scaling
const
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AutoscalingPolicyBasicAlgorithmYarnConfig.fromMap(Map<String, dynamic> map)
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factory
Properties
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gracefulDecommissionTimeout
→ Input<String>
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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.
final
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hashCode
→ int
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The hash code for this object.
no setterinherited
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runtimeType
→ Type
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A representation of the runtime type of the object.
no setterinherited
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scaleDownFactor
→ Input<double>
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Fraction 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.
final
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scaleDownMinWorkerFraction
→ Input<double?>?
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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.
final
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scaleUpFactor
→ Input<double>
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Fraction 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.
final
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scaleUpMinWorkerFraction
→ Input<double?>?
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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.
final
