Merge pull request #45 from data-platform-hq/cluster-support-single-node

feat: support single node clusters

Author: owlleg6

README.md

@@ -164,14 +164,14 @@ module "metastore_assignment" {
 |------|---------|
 | <a name="requirement_terraform"></a> [terraform](#requirement\_terraform) | >=1.0.0 |
 | <a name="requirement_azurerm"></a> [azurerm](#requirement\_azurerm) | >=3.40.0 |
-| <a name="requirement_databricks"></a> [databricks](#requirement\_databricks) | >=1.14.2 |
+| <a name="requirement_databricks"></a> [databricks](#requirement\_databricks) | >=1.30.0 |
 
 ## Providers
 
 | Name | Version |
 |------|---------|
 | <a name="provider_azurerm"></a> [azurerm](#provider\_azurerm) | >=3.40.0 |
-| <a name="provider_databricks"></a> [databricks](#provider\_databricks) | >=1.14.2 |
+| <a name="provider_databricks"></a> [databricks](#provider\_databricks) | >=1.30.0 |
 
 ## Modules
 
@@ -213,7 +213,7 @@ No modules.
 
 | Name | Description | Type | Default | Required |
 |------|-------------|------|---------|:--------:|
-| <a name="input_clusters"></a> [clusters](#input\_clusters) | Set of objects with parameters to configure Databricks clusters and assign permissions to it for certain custom groups | <pre>set(object({<br>    cluster_name                 = string<br>    spark_version                = optional(string, "13.3.x-scala2.12")<br>    spark_conf                   = optional(map(any), {})<br>    cluster_conf_passthrought    = optional(bool, false)<br>    spark_env_vars               = optional(map(any), {})<br>    data_security_mode           = optional(string, "USER_ISOLATION")<br>    node_type_id                 = optional(string, "Standard_D3_v2")<br>    autotermination_minutes      = optional(number, 30)<br>    min_workers                  = optional(number, 1)<br>    max_workers                  = optional(number, 2)<br>    availability                 = optional(string, "ON_DEMAND_AZURE")<br>    first_on_demand              = optional(number, 0)<br>    spot_bid_max_price           = optional(number, 1)<br>    cluster_log_conf_destination = optional(string, null)<br>    init_scripts_workspace       = optional(set(string), [])<br>    init_scripts_volumes         = optional(set(string), [])<br>    init_scripts_dbfs            = optional(set(string), [])<br>    init_scripts_abfss           = optional(set(string), [])<br>    single_user_name             = optional(string, null)<br>    permissions = optional(set(object({<br>      group_name       = string<br>      permission_level = string<br>    })), [])<br>    pypi_library_repository = optional(set(string), [])<br>    maven_library_repository = optional(set(object({<br>      coordinates = string<br>      exclusions  = set(string)<br>    })), [])<br>  }))</pre> | `[]` | no |
+| <a name="input_clusters"></a> [clusters](#input\_clusters) | Set of objects with parameters to configure Databricks clusters and assign permissions to it for certain custom groups | <pre>set(object({<br>    cluster_name                 = string<br>    spark_version                = optional(string, "13.3.x-scala2.12")<br>    spark_conf                   = optional(map(any), {})<br>    cluster_conf_passthrought    = optional(bool, false)<br>    spark_env_vars               = optional(map(any), {})<br>    data_security_mode           = optional(string, "USER_ISOLATION")<br>    node_type_id                 = optional(string, "Standard_D3_v2")<br>    autotermination_minutes      = optional(number, 30)<br>    min_workers                  = optional(number, 1)<br>    max_workers                  = optional(number, 2)<br>    availability                 = optional(string, "ON_DEMAND_AZURE")<br>    first_on_demand              = optional(number, 0)<br>    spot_bid_max_price           = optional(number, 1)<br>    cluster_log_conf_destination = optional(string, null)<br>    init_scripts_workspace       = optional(set(string), [])<br>    init_scripts_volumes         = optional(set(string), [])<br>    init_scripts_dbfs            = optional(set(string), [])<br>    init_scripts_abfss           = optional(set(string), [])<br>    single_user_name             = optional(string, null)<br>    single_node_enable           = optional(bool, false)<br>    custom_tags                  = optional(map(string), {})<br>    permissions = optional(set(object({<br>      group_name       = string<br>      permission_level = string<br>    })), [])<br>    pypi_library_repository = optional(set(string), [])<br>    maven_library_repository = optional(set(object({<br>      coordinates = string<br>      exclusions  = set(string)<br>    })), [])<br>  }))</pre> | `[]` | no |
 | <a name="input_create_databricks_access_policy_to_key_vault"></a> [create\_databricks\_access\_policy\_to\_key\_vault](#input\_create\_databricks\_access\_policy\_to\_key\_vault) | Boolean flag to enable creation of Key Vault Access Policy for Databricks Global Service Principal. | `bool` | `true` | no |
 | <a name="input_custom_cluster_policies"></a> [custom\_cluster\_policies](#input\_custom\_cluster\_policies) | Provides an ability to create custom cluster policy, assign it to cluster and grant CAN\_USE permissions on it to certain custom groups<br>name - name of custom cluster policy to create<br>can\_use - list of string, where values are custom group names, there groups have to be created with Terraform;<br>definition - JSON document expressed in Databricks Policy Definition Language. No need to call 'jsonencode()' function on it when providing a value; | <pre>list(object({<br>    name       = string<br>    can_use    = list(string)<br>    definition = any<br>  }))</pre> | <pre>[<br>  {<br>    "can_use": null,<br>    "definition": null,<br>    "name": null<br>  }<br>]</pre> | no |
 | <a name="input_global_databricks_sp_object_id"></a> [global\_databricks\_sp\_object\_id](#input\_global\_databricks\_sp\_object\_id) | Global 'AzureDatabricks' SP object id. Used to create Key Vault Access Policy for Secret Scope | `string` | `"9b38785a-6e08-4087-a0c4-20634343f21f"` | no |

cluster.tf

@@ -1,31 +1,46 @@
+locals {
+  spark_conf_single_node = {
+    "spark.master"                     = "local[*]"
+    "spark.databricks.cluster.profile" = "singleNode"
+  }
+  conf_passthrought = {
+    "spark.databricks.cluster.profile" : "serverless",
+    "spark.databricks.repl.allowedLanguages" : "python,sql",
+    "spark.databricks.passthrough.enabled" : "true",
+    "spark.databricks.pyspark.enableProcessIsolation" : "true"
+  }
+}
+
 resource "databricks_cluster" "cluster" {
   for_each = { for cluster in var.clusters : cluster.cluster_name => cluster }
 
   cluster_name  = each.value.cluster_name
   spark_version = each.value.spark_version
-  spark_conf = each.value.cluster_conf_passthrought ? merge({
-    "spark.databricks.cluster.profile" : "serverless",
-    "spark.databricks.repl.allowedLanguages" : "python,sql",
-    "spark.databricks.passthrough.enabled" : "true",
-    "spark.databricks.pyspark.enableProcessIsolation" : "true"
-  }, each.value.spark_conf) : each.value.spark_conf
+  spark_conf = merge(
+    each.value.cluster_conf_passthrought ? local.conf_passthrought : {},
+    each.value.single_node_enable == true ? local.spark_conf_single_node : {},
+  each.value.spark_conf)
   spark_env_vars          = each.value.spark_env_vars
   data_security_mode      = each.value.cluster_conf_passthrought ? null : each.value.data_security_mode
   node_type_id            = each.value.node_type_id
   autotermination_minutes = each.value.autotermination_minutes
   single_user_name        = each.value.single_user_name
-
-  autoscale {
-    min_workers = each.value.min_workers
-    max_workers = each.value.max_workers
-  }
+  custom_tags             = merge(each.value.single_node_enable ? { "ResourceClass" = "SingleNode" } : {}, each.value.custom_tags)
 
   azure_attributes {
     availability       = each.value.availability
     first_on_demand    = each.value.first_on_demand
     spot_bid_max_price = each.value.spot_bid_max_price
   }
 
+  dynamic "autoscale" {
+    for_each = each.value.single_node_enable ? [] : [1]
+    content {
+      min_workers = each.value.min_workers
+      max_workers = each.value.max_workers
+    }
+  }
+
   dynamic "cluster_log_conf" {
     for_each = each.value.cluster_log_conf_destination != null ? [each.value.cluster_log_conf_destination] : []
     content {

variables.tf

@@ -166,6 +166,8 @@ variable "clusters" {
     init_scripts_dbfs            = optional(set(string), [])
     init_scripts_abfss           = optional(set(string), [])
     single_user_name             = optional(string, null)
+    single_node_enable           = optional(bool, false)
+    custom_tags                  = optional(map(string), {})
     permissions = optional(set(object({
       group_name       = string
       permission_level = string

versions.tf

@@ -8,7 +8,7 @@ terraform {
     }
     databricks = {
       source  = "databricks/databricks"
-      version = ">=1.14.2"
+      version = ">=1.30.0"
     }
   }
 }