---
title: Getting Started with Datadog
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Infrastructure > Datadog Resource Catalog
---

# gcp_dataproc_autoscaling_policy{% #gcp_dataproc_autoscaling_policy %}

## `ancestors`{% #ancestors %}

**Type**: `UNORDERED_LIST_STRING`

## `basic_algorithm`{% #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](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](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`{% #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`{% #labels %}

**Type**: `UNORDERED_LIST_STRING`

## `name`{% #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](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`{% #organization_id %}

**Type**: `STRING`

## `parent`{% #parent %}

**Type**: `STRING`

## `project_id`{% #project_id %}

**Type**: `STRING`

## `project_number`{% #project_number %}

**Type**: `STRING`

## `region_id`{% #region_id %}

**Type**: `STRING`

## `resource_name`{% #resource_name %}

**Type**: `STRING`

## `secondary_worker_config`{% #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`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`

## `worker_config`{% #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.

## `zone_id`{% #zone_id %}

**Type**: `STRING`