chore: Update discovery artifacts (#1425)
## Deleted keys were detected in the following stable discovery artifacts:
admin directory_v1 https://github.com/googleapis/google-api-python-client/commit/1534f8926019f43dc87a29c1ca32191884556e3b
bigquery v2 https://github.com/googleapis/google-api-python-client/commit/59c51e319602741632201d2ce61a6b03f13e4003
file v1 https://github.com/googleapis/google-api-python-client/commit/0cd409a2d15c68aca3ea864400fc4772b9b4e503
memcache v1 https://github.com/googleapis/google-api-python-client/commit/665ce5b47b9b3238dcfa201b9343bf6447df5994
youtube v3 https://github.com/googleapis/google-api-python-client/commit/5046950872559fe93b954dc9a4f71fd724176247
## Deleted keys were detected in the following pre-stable discovery artifacts:
analyticsadmin v1alpha https://github.com/googleapis/google-api-python-client/commit/934358e5c041ffd1449e7c744463e61e94381ed5
documentai v1beta3 https://github.com/googleapis/google-api-python-client/commit/e8aaabbc7670aefc4a745916fccb31424745f748
file v1beta1 https://github.com/googleapis/google-api-python-client/commit/0cd409a2d15c68aca3ea864400fc4772b9b4e503
memcache v1beta2 https://github.com/googleapis/google-api-python-client/commit/665ce5b47b9b3238dcfa201b9343bf6447df5994
networkconnectivity v1alpha1 https://github.com/googleapis/google-api-python-client/commit/2cc462638aec61f4e775bfce883e725b104eeabb
## Discovery Artifact Change Summary:
feat(admin): update the api https://github.com/googleapis/google-api-python-client/commit/1534f8926019f43dc87a29c1ca32191884556e3b
feat(alertcenter): update the api https://github.com/googleapis/google-api-python-client/commit/7a488d3f0deef3e1f106cff63b1e4f66ad1727bb
feat(analyticsadmin): update the api https://github.com/googleapis/google-api-python-client/commit/934358e5c041ffd1449e7c744463e61e94381ed5
feat(analyticsdata): update the api https://github.com/googleapis/google-api-python-client/commit/40f712130674cec09c1dd7560f69a330a335b226
feat(androiddeviceprovisioning): update the api https://github.com/googleapis/google-api-python-client/commit/81a0002a7051aeab647a3296fb18ce7973bf7137
feat(apigee): update the api https://github.com/googleapis/google-api-python-client/commit/2e6c78a93b2c0ee7001eb163ec95f9afc8f35575
feat(appengine): update the api https://github.com/googleapis/google-api-python-client/commit/125f74a61a94af17c01930841a79db46d3a059c5
feat(bigquery): update the api https://github.com/googleapis/google-api-python-client/commit/59c51e319602741632201d2ce61a6b03f13e4003
feat(cloudasset): update the api https://github.com/googleapis/google-api-python-client/commit/e615264971ccee6eb9b450fe3d85614209c0fee8
feat(cloudbuild): update the api https://github.com/googleapis/google-api-python-client/commit/ceddaccf23eb8b809688907cfdef8906cd77d65d
feat(cloudidentity): update the api https://github.com/googleapis/google-api-python-client/commit/22cd08b69b034c2cdfd854e1ac784f834539db3a
feat(container): update the api https://github.com/googleapis/google-api-python-client/commit/f494c63a42dc418559292c6269289317d9cebc23
feat(documentai): update the api https://github.com/googleapis/google-api-python-client/commit/e8aaabbc7670aefc4a745916fccb31424745f748
feat(drive): update the api https://github.com/googleapis/google-api-python-client/commit/72cab88ce591d906ea1cfcbe4dee354cccb623f2
feat(file): update the api https://github.com/googleapis/google-api-python-client/commit/0cd409a2d15c68aca3ea864400fc4772b9b4e503
feat(firebaseappcheck): update the api https://github.com/googleapis/google-api-python-client/commit/9a0131b2326327109d1ba7af97b1f4808dd7a898
feat(healthcare): update the api https://github.com/googleapis/google-api-python-client/commit/45ee6b28b86a43f44c707e15a7e06fdf8fce6a0f
feat(ideahub): update the api https://github.com/googleapis/google-api-python-client/commit/73b86d9d37f33aeaed74772d0319ba1350e54ed5
feat(managedidentities): update the api https://github.com/googleapis/google-api-python-client/commit/a07ed4558c93cb8f7fae49c7b353f46ccfea6c10
feat(memcache): update the api https://github.com/googleapis/google-api-python-client/commit/665ce5b47b9b3238dcfa201b9343bf6447df5994
feat(metastore): update the api https://github.com/googleapis/google-api-python-client/commit/9fd5ffbf37fb052323f5fa68d307c68391c519ac
feat(ml): update the api https://github.com/googleapis/google-api-python-client/commit/cf54d564915a558569c093287b448a7819e215f6
feat(monitoring): update the api https://github.com/googleapis/google-api-python-client/commit/d1ffbfc041f23f904cd8bc35a450871b2909473b
feat(networkconnectivity): update the api https://github.com/googleapis/google-api-python-client/commit/2cc462638aec61f4e775bfce883e725b104eeabb
feat(notebooks): update the api https://github.com/googleapis/google-api-python-client/commit/831ba938855aa4bdefafedf63e01af43350e7ed2
feat(ondemandscanning): update the api https://github.com/googleapis/google-api-python-client/commit/c04b4023477393cbb41984b14e0c734fc8587d45
feat(paymentsresellersubscription): update the api https://github.com/googleapis/google-api-python-client/commit/2cd5b1c2ef524f3ab00630508710cce7bee53574
feat(prod_tt_sasportal): update the api https://github.com/googleapis/google-api-python-client/commit/8b6bd24e57a79f470c750ad04052f79a3cafe0fa
feat(realtimebidding): update the api https://github.com/googleapis/google-api-python-client/commit/fd514dc8d86182dc17698f3293144928535f709c
feat(reseller): update the api https://github.com/googleapis/google-api-python-client/commit/20226c4401956732772e2a563c7920666135e605
feat(sasportal): update the api https://github.com/googleapis/google-api-python-client/commit/38d5156350b79a9933b2806f4bbe443043a33185
feat(sts): update the api https://github.com/googleapis/google-api-python-client/commit/190e13ebe5a4660d8825d3a8708559077a342bdf
feat(transcoder): update the api https://github.com/googleapis/google-api-python-client/commit/fbcacce6a17c1cae45b22f4a2058e730ec84b55a
feat(youtube): update the api https://github.com/googleapis/google-api-python-client/commit/5046950872559fe93b954dc9a4f71fd724176247
diff --git a/docs/dyn/dataproc_v1beta2.projects.regions.autoscalingPolicies.html b/docs/dyn/dataproc_v1beta2.projects.regions.autoscalingPolicies.html
index da824ef..9e60534 100644
--- a/docs/dyn/dataproc_v1beta2.projects.regions.autoscalingPolicies.html
+++ b/docs/dyn/dataproc_v1beta2.projects.regions.autoscalingPolicies.html
@@ -122,7 +122,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.
@@ -155,7 +155,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.
@@ -213,7 +213,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.
@@ -293,7 +293,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.
@@ -432,7 +432,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.
@@ -465,7 +465,7 @@
{ # Describes an autoscaling policy for Dataproc cluster autoscaler.
"basicAlgorithm": { # Basic algorithm for autoscaling.
"cooldownPeriod": "A String", # Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- "yarnConfig": { # Basic autoscaling configurations for YARN. # Required. YARN autoscaling configuration.
+ "yarnConfig": { # Basic autoscaling configurations for YARN. # Optional. YARN autoscaling configuration.
"gracefulDecommissionTimeout": "A String", # 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.
"scaleDownFactor": 3.14, # 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.
"scaleDownMinWorkerFraction": 3.14, # 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.