This product is not supported for your selected Datadog site. ().
このページは日本語には対応しておりません。随時翻訳に取り組んでいます。
翻訳に関してご質問やご意見ございましたら、お気軽にご連絡ください。

gcp_dataproc_autoscaling_policy

ancestors

Type: UNORDERED_LIST_STRING

basic_algorithm

Type: STRUCT
Provider name: basicAlgorithm

  • cooldown_period
    Type: STRING
    Provider name: cooldownPeriod
    Description: Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
  • spark_standalone_config
    Type: STRUCT
    Provider name: sparkStandaloneConfig
    Description: Optional. Spark Standalone autoscaling configuration
    • graceful_decommission_timeout
      Type: STRING
      Provider name: gracefulDecommissionTimeout
      Description: Required. Timeout for Spark graceful decommissioning of spark workers. Specifies the duration to wait for spark worker to complete spark decommissioning tasks before forcefully removing workers. Only applicable to downscaling operations.Bounds: 0s, 1d.
    • remove_only_idle_workers
      Type: BOOLEAN
      Provider name: removeOnlyIdleWorkers
      Description: Optional. Remove only idle workers when scaling down cluster
    • scale_down_factor
      Type: DOUBLE
      Provider name: scaleDownFactor
      Description: Required. Fraction of required executors to remove from Spark Serverless clusters. A scale-down factor of 1.0 will result in scaling down so that there are no more executors for the Spark Job.(more aggressive scaling). A scale-down factor closer to 0 will result in a smaller magnitude of scaling donw (less aggressive scaling).Bounds: 0.0, 1.0.
    • scale_down_min_worker_fraction
      Type: DOUBLE
      Provider name: scaleDownMinWorkerFraction
      Description: 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
      Type: DOUBLE
      Provider name: scaleUpFactor
      Description: Required. Fraction of required workers to add to Spark Standalone clusters. A scale-up factor of 1.0 will result in scaling up so that there are no more required workers for the Spark Job (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.
    • scale_up_min_worker_fraction
      Type: DOUBLE
      Provider name: scaleUpMinWorkerFraction
      Description: 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.
  • yarn_config
    Type: STRUCT
    Provider name: yarnConfig
    Description: Optional. YARN autoscaling configuration.
    • graceful_decommission_timeout
      Type: STRING
      Provider name: gracefulDecommissionTimeout
      Description: 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
      Type: DOUBLE
      Provider name: scaleDownFactor
      Description: 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
      Type: DOUBLE
      Provider name: scaleDownMinWorkerFraction
      Description: 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
      Type: DOUBLE
      Provider name: scaleUpFactor
      Description: 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
      Type: DOUBLE
      Provider name: scaleUpMinWorkerFraction
      Description: 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.

id

Type: STRING
Provider name: id
Description: Required. The policy id.The id must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). Cannot begin or end with underscore or hyphen. Must consist of between 3 and 50 characters.

labels

Type: UNORDERED_LIST_STRING

name

Type: STRING
Provider name: name
Description: Output only. The “resource name” of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}

organization_id

Type: STRING

parent

Type: STRING

project_id

Type: STRING

project_number

Type: STRING

resource_name

Type: STRING

secondary_worker_config

Type: STRUCT
Provider name: secondaryWorkerConfig
Description: Optional. Describes how the autoscaler will operate for secondary workers.

  • max_instances
    Type: INT32
    Provider name: maxInstances
    Description: Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
  • min_instances
    Type: INT32
    Provider name: minInstances
    Description: Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
  • weight
    Type: INT32
    Provider name: weight
    Description: Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.

tags

Type: UNORDERED_LIST_STRING

worker_config

Type: STRUCT
Provider name: workerConfig
Description: Required. Describes how the autoscaler will operate for primary workers.

  • max_instances
    Type: INT32
    Provider name: maxInstances
    Description: Required. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Secondary workers - Bounds: [min_instances, ). Default: 0.
  • min_instances
    Type: INT32
    Provider name: minInstances
    Description: Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
  • weight
    Type: INT32
    Provider name: weight
    Description: Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.