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Merge pull request #20 from data-platform-hq/cluster-single-user-mode
feat: single user cluster mode
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README.md

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| <a name="input_autotermination_minutes"></a> [autotermination\_minutes](#input\_autotermination\_minutes) | Automatically terminate the cluster after being inactive for this time in minutes. If not set, Databricks won't automatically terminate an inactive cluster. If specified, the threshold must be between 10 and 10000 minutes. You can also set this value to 0 to explicitly disable automatic termination | `number` | 15 | no |
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| <a name="input_min_workers"></a> [min\_workers](#input\_min\_workers) | The minimum number of workers to which the cluster can scale down when underutilized. It is also the initial number of workers the cluster will have after creation | `number` | 1 | no |
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| <a name="input_max_workers"></a> [max\_workers](#input\_max\_workers) | The maximum number of workers to which the cluster can scale up when overloaded. max_workers must be strictly greater than min_workers | `number` | 2 | no |
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| <a name="input_data_security_mode"></a> [data\_security\_mode](#input\_data\_security\_mode) | Security features of the cluster | `string` | "NONE" | no |
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| <a name="input_data_security_mode"></a> [data\_security\_mode](#input\_data\_security\_mode)| Security features of the cluster| `string`| "NONE"| no |
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| <a name="input_single_user_name"></a> [single\_user\_name](#input\_single\_user\_name)| single user cluster mode | `string`| null| no |
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| <a name="input_custom_default_cluster_name"></a> [custom\_default\_cluster\_name](#input\_custom\_default\_cluster\_name) | Databricks cluster name, which does not have to be unique | `string` | `null` | no |
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| <a name="input_spark_version"></a> [spark\_version](#input\_spark\_version) | Runtime version | `string` | "11.3.x-scala2.12" | no |
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| <a name="input_spark_conf"></a> [spark\_conf](#input\_spark\_conf) | Map with key-value pairs to fine-tune Spark clusters, where you can provide custom Spark configuration properties in a cluster configuration. | `map(any)` | {} | no |

main.tf

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spark_env_vars = var.spark_env_vars
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data_security_mode = var.data_security_mode
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single_user_name = var.single_user_name
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node_type_id = var.node_type
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autotermination_minutes = var.autotermination_minutes
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variables.tf

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}
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}
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variable "single_user_name" {
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type = string
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description = "single user cluster mode"
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default = null
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}
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variable "custom_default_cluster_name" {
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type = string
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description = "Databricks cluster name, which does not have to be unique"

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