feat: add support for temp_bucket, endpoint_config in clusters; add preemptibility for instance group configs

google/cloud/dataproc_v1/gapic/enums.py

@@ -24,7 +24,7 @@ class Component(enum.IntEnum):
     Cluster components that can be activated.
 
     Attributes:
-      COMPONENT_UNSPECIFIED (int): Unspecified component.
+      COMPONENT_UNSPECIFIED (int): Unspecified component. Specifying this will cause Cluster creation to fail.
       ANACONDA (int): The Anaconda python distribution.
       HIVE_WEBHCAT (int): The Hive Web HCatalog (the REST service for accessing HCatalog).
       JUPYTER (int): The Jupyter Notebook.
@@ -103,6 +103,30 @@ class Substate(enum.IntEnum):
         STALE_STATUS = 2
 
 
+class InstanceGroupConfig(object):
+    class Preemptibility(enum.IntEnum):
+        """
+        Controls the use of [preemptible instances]
+        (https://cloud.google.com/compute/docs/instances/preemptible) within the
+        group.
+
+        Attributes:
+          PREEMPTIBILITY_UNSPECIFIED (int): Preemptibility is unspecified, the system will choose the
+          appropriate setting for each instance group.
+          NON_PREEMPTIBLE (int): Instances are non-preemptible.
+
+          This option is allowed for all instance groups and is the only valid
+          value for Master and Worker instance groups.
+          PREEMPTIBLE (int): Instances are preemptible.
+
+          This option is allowed only for secondary worker groups.
+        """
+
+        PREEMPTIBILITY_UNSPECIFIED = 0
+        NON_PREEMPTIBLE = 1
+        PREEMPTIBLE = 2
+
+
 class JobStatus(object):
     class State(enum.IntEnum):
         """

google/cloud/dataproc_v1/proto/autoscaling_policies.proto

@@ -164,20 +164,26 @@ message BasicYarnAutoscalingConfig {
   // Bounds: [0s, 1d].
   google.protobuf.Duration graceful_decommission_timeout = 5 [(google.api.field_behavior) = REQUIRED];
 
-  // 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].
   double scale_up_factor = 1 [(google.api.field_behavior) = REQUIRED];
 
-  // 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].
   double scale_down_factor = 2 [(google.api.field_behavior) = REQUIRED];

google/cloud/dataproc_v1/proto/clusters.proto

@@ -170,6 +170,17 @@ message ClusterConfig {
   // bucket](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/staging-bucket)).
   string config_bucket = 1 [(google.api.field_behavior) = OPTIONAL];
 
+  // Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data,
+  // such as Spark and MapReduce history files.
+  // If you do not specify a temp bucket,
+  // Dataproc will determine a Cloud Storage location (US,
+  // ASIA, or EU) for your cluster's temp bucket according to the
+  // Compute Engine zone where your cluster is deployed, and then create
+  // and manage this project-level, per-location bucket. The default bucket has
+  // a TTL of 90 days, but you can use any TTL (or none) if you specify a
+  // bucket.
+  string temp_bucket = 2 [(google.api.field_behavior) = OPTIONAL];
+
   // Optional. The shared Compute Engine config settings for
   // all instances in a cluster.
   GceClusterConfig gce_cluster_config = 8 [(google.api.field_behavior) = OPTIONAL];
@@ -216,6 +227,20 @@ message ClusterConfig {
 
   // Optional. Lifecycle setting for the cluster.
   LifecycleConfig lifecycle_config = 17 [(google.api.field_behavior) = OPTIONAL];
+
+  // Optional. Port/endpoint configuration for this cluster
+  EndpointConfig endpoint_config = 19 [(google.api.field_behavior) = OPTIONAL];
+}
+
+// Endpoint config for this cluster
+message EndpointConfig {
+  // Output only. The map of port descriptions to URLs. Will only be populated
+  // if enable_http_port_access is true.
+  map<string, string> http_ports = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
+
+  // Optional. If true, enable http access to specific ports on the cluster
+  // from external sources. Defaults to false.
+  bool enable_http_port_access = 2 [(google.api.field_behavior) = OPTIONAL];
 }
 
 // Autoscaling Policy config associated with the cluster.
@@ -288,7 +313,7 @@ message GceClusterConfig {
   bool internal_ip_only = 7 [(google.api.field_behavior) = OPTIONAL];
 
   // Optional. The [Dataproc service
-  // account](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/service-accounts#service_accounts_in_cloud_dataproc)
+  // account](https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/service-accounts#service_accounts_in_dataproc)
   // (also see [VM Data Plane
   // identity](https://cloud.google.com/dataproc/docs/concepts/iam/dataproc-principals#vm_service_account_data_plane_identity))
   // used by Dataproc cluster VM instances to access Google Cloud Platform
@@ -332,6 +357,27 @@ message GceClusterConfig {
 // The config settings for Compute Engine resources in
 // an instance group, such as a master or worker group.
 message InstanceGroupConfig {
+  // Controls the use of
+  // [preemptible instances]
+  // (https://cloud.google.com/compute/docs/instances/preemptible)
+  // within the group.
+  enum Preemptibility {
+    // Preemptibility is unspecified, the system will choose the
+    // appropriate setting for each instance group.
+    PREEMPTIBILITY_UNSPECIFIED = 0;
+
+    // Instances are non-preemptible.
+    //
+    // This option is allowed for all instance groups and is the only valid
+    // value for Master and Worker instance groups.
+    NON_PREEMPTIBLE = 1;
+
+    // Instances are preemptible.
+    //
+    // This option is allowed only for secondary worker groups.
+    PREEMPTIBLE = 2;
+  }
+
   // Optional. The number of VM instances in the instance group.
   // For master instance groups, must be set to 1.
   int32 num_instances = 1 [(google.api.field_behavior) = OPTIONAL];
@@ -382,6 +428,15 @@ message InstanceGroupConfig {
   // instances.
   bool is_preemptible = 6 [(google.api.field_behavior) = OUTPUT_ONLY];
 
+  // Optional. Specifies the preemptibility of the instance group.
+  //
+  // The default value for master and worker groups is
+  // `NON_PREEMPTIBLE`. This default cannot be changed.
+  //
+  // The default value for secondary instances is
+  // `PREEMPTIBLE`.
+  Preemptibility preemptibility = 10 [(google.api.field_behavior) = OPTIONAL];
+
   // Output only. The config for Compute Engine Instance Group
   // Manager that manages this group.
   // This is only used for preemptible instance groups.
@@ -608,7 +663,7 @@ message KerberosConfig {
 message SoftwareConfig {
   // Optional. The version of software inside the cluster. It must be one of the
   // supported [Dataproc
-  // Versions](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#supported_cloud_dataproc_versions),
+  // Versions](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#supported_dataproc_versions),
   // such as "1.2" (including a subminor version, such as "1.2.29"), or the
   // ["preview"
   // version](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions#other_versions).