Added runtime_engine support for databricks_cluster

clusters/clusters_api.go

@@ -397,6 +397,7 @@ type Cluster struct {
 	SingleUserName   string        `json:"single_user_name,omitempty"`
 	IdempotencyToken string        `json:"idempotency_token,omitempty" tf:"force_new"`
 	WorkloadType     *WorkloadType `json:"workload_type,omitempty"`
+	RuntimeEngine    string        `json:"runtime_engine,omitempty"`
 }
 
 func (cluster Cluster) Validate() error {
@@ -489,6 +490,7 @@ type ClusterInfo struct {
 	ClusterLogStatus          *LogSyncStatus     `json:"cluster_log_status,omitempty"`
 	TerminationReason         *TerminationReason `json:"termination_reason,omitempty"`
 	DataSecurityMode          string             `json:"data_security_mode,omitempty"`
+	RuntimeEngine             string             `json:"runtime_engine,omitempty"`
 }
 
 // IsRunningOrResizing returns true if cluster is running or resizing

clusters/resource_cluster.go

@@ -83,6 +83,8 @@ func resourceClusterSchema() map[string]*schema.Schema {
 		s["driver_node_type_id"].ConflictsWith = []string{"driver_instance_pool_id", "instance_pool_id"}
 		s["node_type_id"].ConflictsWith = []string{"driver_instance_pool_id", "instance_pool_id"}
 
+		s["runtime_engine"].ValidateFunc = validation.StringInSlice([]string{"PHOTON", "STANDARD"}, false)
+
 		s["is_pinned"] = &schema.Schema{
 			Type:     schema.TypeBool,
 			Optional: true,

clusters/resource_cluster_test.go

@@ -359,6 +359,78 @@ func TestResourceClusterCreate_WithLibraries(t *testing.T) {
 	assert.Equal(t, "abc", d.Id())
 }
 
+func TestResourceClusterCreatePhoton(t *testing.T) {
+	d, err := qa.ResourceFixture{
+		Fixtures: []qa.HTTPFixture{
+			{
+				Method:   "POST",
+				Resource: "/api/2.0/clusters/create",
+				ExpectedRequest: Cluster{
+					NumWorkers:             100,
+					ClusterName:            "Shared Autoscaling",
+					SparkVersion:           "7.1-scala12",
+					NodeTypeID:             "i3.xlarge",
+					AutoterminationMinutes: 15,
+					RuntimeEngine:          "PHOTON",
+				},
+				Response: ClusterInfo{
+					ClusterID: "abc",
+					State:     ClusterStateRunning,
+				},
+			},
+			{
+				Method:       "GET",
+				ReuseRequest: true,
+				Resource:     "/api/2.0/clusters/get?cluster_id=abc",
+				Response: ClusterInfo{
+					ClusterID:              "abc",
+					NumWorkers:             100,
+					ClusterName:            "Shared Autoscaling",
+					SparkVersion:           "7.1-scala12",
+					NodeTypeID:             "i3.xlarge",
+					AutoterminationMinutes: 15,
+					State:                  ClusterStateRunning,
+					RuntimeEngine:          "PHOTON",
+				},
+			},
+			{
+				Method:   "POST",
+				Resource: "/api/2.0/clusters/events",
+				ExpectedRequest: EventsRequest{
+					ClusterID:  "abc",
+					Limit:      1,
+					Order:      SortDescending,
+					EventTypes: []ClusterEventType{EvTypePinned, EvTypeUnpinned},
+				},
+				Response: EventsResponse{
+					Events:     []ClusterEvent{},
+					TotalCount: 0,
+				},
+			},
+			{
+				Method:   "GET",
+				Resource: "/api/2.0/libraries/cluster-status?cluster_id=abc",
+				Response: libraries.ClusterLibraryStatuses{
+					LibraryStatuses: []libraries.LibraryStatus{},
+				},
+			},
+		},
+		Create:   true,
+		Resource: ResourceCluster(),
+		State: map[string]any{
+			"autotermination_minutes": 15,
+			"cluster_name":            "Shared Autoscaling",
+			"spark_version":           "7.1-scala12",
+			"node_type_id":            "i3.xlarge",
+			"num_workers":             100,
+			"is_pinned":               false,
+			"runtime_engine":          "PHOTON",
+		},
+	}.Apply(t)
+	assert.NoError(t, err, err)
+	assert.Equal(t, "abc", d.Id())
+}
+
 func TestResourceClusterCreate_Error(t *testing.T) {
 	d, err := qa.ResourceFixture{
 		Fixtures: []qa.HTTPFixture{

docs/data-sources/cluster.md

@@ -29,9 +29,11 @@ data "databricks_cluster" "all" {
 ## Attribute Reference
 
 This data source exports the following attributes:
+
 * `cluster_info` block, consisting of following fields:
   * `cluster_name` - Cluster name, which doesn’t have to be unique.
   * `spark_version` - [Runtime version](https://docs.databricks.com/runtime/index.html) of the cluster.
+  * `runtime_engine` - The type of runtime of the cluster
   * `driver_node_type_id` - The node type of the Spark driver.
   * `node_type_id` - Any supported [databricks_node_type](../data-sources/node_type.md) id.
   * `instance_pool_id` The [pool of idle instances](instance_pool.md) the cluster is attached to.
@@ -58,4 +60,4 @@ The following resources are often used in the same context:
 * [databricks_instance_pool](../resources/instance_pool.md) to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce [cluster](../resources/cluster.md) start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
 * [databricks_job](../resources/job.md) to manage [Databricks Jobs](https://docs.databricks.com/jobs.html) to run non-interactive code in a [databricks_cluster](../resources/cluster.md).
 * [databricks_library](../resources/library.md) to install a [library](https://docs.databricks.com/libraries/index.html) on [databricks_cluster](../resources/cluster.md).
-* [databricks_pipeline](../resources/pipeline.md) to deploy [Delta Live Tables](https://docs.databricks.com/data-engineering/delta-live-tables/index.html). 
+* [databricks_pipeline](../resources/pipeline.md) to deploy [Delta Live Tables](https://docs.databricks.com/data-engineering/delta-live-tables/index.html).