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feat: Additional fields for the ClusterConfig and `InstanceGroupCon…
…fig` messages. (#253)

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PiperOrigin-RevId: 323829608
Source-Link: googleapis/googleapis@d8a3dfb
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yoshi-automation committed Jul 31, 2020
1 parent 60d3066 commit 9f43c64e464c5ac2418e2d399e72584db885ec57
Showing with 3,725 additions and 673 deletions.
  1. +32 −8 ...ogle-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/BasicYarnAutoscalingConfig.java
  2. +8 −2 ...d-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/BasicYarnAutoscalingConfigOrBuilder.java
  3. +537 −0 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/ClusterConfig.java
  4. +82 −0 ...o-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/ClusterConfigOrBuilder.java
  5. +238 −200 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/ClustersProto.java
  6. +2 −2 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/Component.java
  7. +899 −0 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/EndpointConfig.java
  8. +103 −0 ...-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/EndpointConfigOrBuilder.java
  9. +7 −7 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/GceClusterConfig.java
  10. +2 −2 ...oogle-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/GceClusterConfigOrBuilder.java
  11. +371 −0 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/InstanceGroupConfig.java
  12. +37 −0 ...le-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/InstanceGroupConfigOrBuilder.java
  13. +21 −21 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/JobReference.java
  14. +6 −6 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/JobReferenceOrBuilder.java
  15. +1 −1 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/JobsProto.java
  16. +828 −123 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/OrderedJob.java
  17. +192 −30 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/OrderedJobOrBuilder.java
  18. +52 −39 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/PySparkJob.java
  19. +16 −12 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/PySparkJobOrBuilder.java
  20. +7 −7 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SoftwareConfig.java
  21. +2 −2 ...-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SoftwareConfigOrBuilder.java
  22. +52 −52 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SparkJob.java
  23. +16 −16 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SparkJobOrBuilder.java
  24. +52 −52 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SparkRJob.java
  25. +16 −16 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/SparkRJobOrBuilder.java
  26. +23 −23 proto-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/WorkflowTemplate.java
  27. +5 −5 ...oogle-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/WorkflowTemplateOrBuilder.java
  28. +14 −13 ...o-google-cloud-dataproc-v1/src/main/java/com/google/cloud/dataproc/v1/WorkflowTemplatesProto.java
  29. +8 −2 proto-google-cloud-dataproc-v1/src/main/proto/google/cloud/dataproc/v1/autoscaling_policies.proto
  30. +57 −2 proto-google-cloud-dataproc-v1/src/main/proto/google/cloud/dataproc/v1/clusters.proto
  31. +15 −14 proto-google-cloud-dataproc-v1/src/main/proto/google/cloud/dataproc/v1/jobs.proto
  32. +1 −1 proto-google-cloud-dataproc-v1/src/main/proto/google/cloud/dataproc/v1/shared.proto
  33. +17 −11 proto-google-cloud-dataproc-v1/src/main/proto/google/cloud/dataproc/v1/workflow_templates.proto
  34. +6 −4 synth.metadata
@@ -209,11 +209,14 @@ public com.google.protobuf.DurationOrBuilder getGracefulDecommissionTimeoutOrBui
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -232,11 +235,14 @@ public double getScaleUpFactor() {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -952,11 +958,14 @@ public com.google.protobuf.DurationOrBuilder getGracefulDecommissionTimeoutOrBui
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -972,11 +981,14 @@ public double getScaleUpFactor() {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -995,11 +1007,14 @@ public Builder setScaleUpFactor(double value) {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -1019,11 +1034,14 @@ public Builder clearScaleUpFactor() {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -1039,11 +1057,14 @@ public double getScaleDownFactor() {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -1062,11 +1083,14 @@ public Builder setScaleDownFactor(double value) {
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -80,11 +80,14 @@
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*
@@ -98,11 +101,14 @@
*
*
* <pre>
* Required. Fraction of average pending memory in the last cooldown period
* 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](/dataproc/docs/concepts/configuring-clusters/autoscaling#how_autoscaling_works)
* for more information.
* Bounds: [0.0, 1.0].
* </pre>
*

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