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|[databricks_current_user.me](https://registry.terraform.io/providers/databricks/databricks/latest/docs/data-sources/current_user)| data source |
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|[databricks_node_type.cluster_node_type](https://registry.terraform.io/providers/databricks/databricks/latest/docs/data-sources/node_type)| data source |
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|[databricks_spark_version.latest](https://registry.terraform.io/providers/databricks/databricks/latest/docs/data-sources/spark_version)| data source |
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## Inputs
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| Name | Description | Type | Default | Required |
| <aname="input_allow_cluster_create"></a> [allow\_cluster\_create](#input\_allow\_cluster\_create)| This is a field to allow the group to have cluster create privileges. More fine grained permissions could be assigned with databricks\_permissions and cluster\_id argument. Everyone without allow\_cluster\_create argument set, but with permission to use Cluster Policy would be able to create clusters, but within boundaries of that specific policy. |`bool`|`true`| no |
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| <aname="input_allow_instance_pool_create"></a> [allow\_instance\_pool\_create](#input\_allow\_instance\_pool\_create)| This is a field to allow the group to have instance pool create privileges. More fine grained permissions could be assigned with databricks\_permissions and instance\_pool\_id argument. |`bool`|`true`| no |
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| <aname="input_always_running"></a> [always\_running](#input\_always\_running)| Whenever the job is always running, like a Spark Streaming application, on every update restart the current active run or start it again, if nothing it is not running. False by default. |`bool`|`false`| no |
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| <aname="input_auto_scaling"></a> [auto\_scaling](#input\_auto\_scaling)| Number of min and max workers in auto scale. |`list(any)`|`null`| no |
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| <aname="input_aws_attributes"></a> [aws\_attributes](#input\_aws\_attributes)| Optional configuration block contains attributes related to clusters running on AWS. |`any`|`null`| no |
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| <aname="input_azure_attributes"></a> [azure\_attributes](#input\_azure\_attributes)| Optional configuration block contains attributes related to clusters running on Azure. |`any`|`null`| no |
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| <aname="input_category"></a> [category](#input\_category)| Node category, which can be one of: General purpose, Memory optimized, Storage optimized, Compute optimized, GPU |`string`|`"General purpose"`| no |
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| <aname="input_cluster_access_control"></a> [cluster\_access\_control](#input\_cluster\_access\_control)| Cluster access control |`any`|`null`| no |
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| <aname="input_cluster_autotermination_minutes"></a> [cluster\_autotermination\_minutes](#input\_cluster\_autotermination\_minutes)| cluster auto termination duration |`number`|`30`| no |
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| <aname="input_cluster_id"></a> [cluster\_id](#input\_cluster\_id)| Existing cluster id |`string`|`null`| no |
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| <aname="input_cluster_name"></a> [cluster\_name](#input\_cluster\_name)| Cluster name |`string`|`null`| no |
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| <aname="input_cluster_policy_id"></a> [cluster\_policy\_id](#input\_cluster\_policy\_id)| Exiting cluster policy id |`string`|`null`| no |
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| <aname="input_create_group"></a> [create\_group](#input\_create\_group)| Create a new group, if group already exists the deployment will fail. |`bool`|`false`| no |
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| <aname="input_create_user"></a> [create\_user](#input\_create\_user)| Create a new user, if user already exists the deployment will fail. |`bool`|`false`| no |
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| <aname="input_custom_tags"></a> [custom\_tags](#input\_custom\_tags)| Extra custom tags |`any`|`null`| no |
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| <aname="input_databricks_username"></a> [databricks\_username](#input\_databricks\_username)| User allowed to access the platform. |`string`|`""`| no |
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| <aname="input_deploy_cluster"></a> [deploy\_cluster](#input\_deploy\_cluster)| feature flag, true or false |`bool`|`false`| no |
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| <aname="input_deploy_cluster_policy"></a> [deploy\_cluster\_policy](#input\_deploy\_cluster\_policy)| feature flag, true or false |`bool`|`false`| no |
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| <aname="input_deploy_driver_instance_pool"></a> [deploy\_driver\_instance\_pool](#input\_deploy\_driver\_instance\_pool)| Driver instance pool |`bool`|`false`| no |
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| <aname="input_deploy_job_cluster"></a> [deploy\_job\_cluster](#input\_deploy\_job\_cluster)| feature flag, true or false |`bool`|`false`| no |
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| <aname="input_deploy_jobs"></a> [deploy\_jobs](#input\_deploy\_jobs)| feature flag, true or false |`bool`|`false`| no |
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| <aname="input_deploy_worker_instance_pool"></a> [deploy\_worker\_instance\_pool](#input\_deploy\_worker\_instance\_pool)| Worker instance pool |`bool`|`false`| no |
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| <aname="input_driver_node_type_id"></a> [driver\_node\_type\_id](#input\_driver\_node\_type\_id)| The node type of the Spark driver. This field is optional; if unset, API will set the driver node type to the same value as node\_type\_id. |`string`|`null`| no |
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| <aname="input_email_notifications"></a> [email\_notifications](#input\_email\_notifications)| Email notification block. |`any`|`null`| no |
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| <aname="input_fixed_value"></a> [fixed\_value](#input\_fixed\_value)| Number of nodes in the cluster. |`number`|`0`| no |
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| <aname="input_gb_per_core"></a> [gb\_per\_core](#input\_gb\_per\_core)| Number of gigabytes per core available on instance. Conflicts with min\_memory\_gb. Defaults to 0. |`string`|`0`| no |
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| <aname="input_gcp_attributes"></a> [gcp\_attributes](#input\_gcp\_attributes)| Optional configuration block contains attributes related to clusters running on GCP. |`any`|`null`| no |
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| <aname="input_gpu"></a> [gpu](#input\_gpu)| GPU required or not. |`bool`|`false`| no |
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| <aname="input_idle_instance_autotermination_minutes"></a> [idle\_instance\_autotermination\_minutes](#input\_idle\_instance\_autotermination\_minutes)| idle instance auto termination duration |`number`|`20`| no |
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| <aname="input_instance_pool_access_control"></a> [instance\_pool\_access\_control](#input\_instance\_pool\_access\_control)| Instance pool access control |`any`|`null`| no |
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| <aname="input_jobs_access_control"></a> [jobs\_access\_control](#input\_jobs\_access\_control)| Jobs access control |`any`|`null`| no |
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| <aname="input_libraries"></a> [libraries](#input\_libraries)| Installs a library on databricks\_cluster |`map(any)`|`{}`| no |
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| <aname="input_local_disk"></a> [local\_disk](#input\_local\_disk)| Pick only nodes with local storage. Defaults to false. |`string`|`true`| no |
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| <aname="input_local_notebooks"></a> [local\_notebooks](#input\_local\_notebooks)| Local path to the notebook(s) that will be used by the job |`any`|`[]`| no |
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| <aname="input_max_capacity"></a> [max\_capacity](#input\_max\_capacity)| instance pool maximum capacity |`number`|`3`| no |
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| <aname="input_max_concurrent_runs"></a> [max\_concurrent\_runs](#input\_max\_concurrent\_runs)| An optional maximum allowed number of concurrent runs of the job. |`number`|`null`| no |
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| <aname="input_max_retries"></a> [max\_retries](#input\_max\_retries)| An optional maximum number of times to retry an unsuccessful run. A run is considered to be unsuccessful if it completes with a FAILED result\_state or INTERNAL\_ERROR life\_cycle\_state. The value -1 means to retry indefinitely and the value 0 means to never retry. The default behavior is to never retry. |`number`|`0`| no |
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| <aname="input_min_cores"></a> [min\_cores](#input\_min\_cores)| Minimum number of CPU cores available on instance. Defaults to 0. |`string`|`0`| no |
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| <aname="input_min_gpus"></a> [min\_gpus](#input\_min\_gpus)| Minimum number of GPU's attached to instance. Defaults to 0. |`string`|`0`| no |
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| <aname="input_min_idle_instances"></a> [min\_idle\_instances](#input\_min\_idle\_instances)| instance pool minimum idle instances |`number`|`1`| no |
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| <aname="input_min_memory_gb"></a> [min\_memory\_gb](#input\_min\_memory\_gb)| Minimum amount of memory per node in gigabytes. Defaults to 0. |`string`|`0`| no |
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| <aname="input_min_retry_interval_millis"></a> [min\_retry\_interval\_millis](#input\_min\_retry\_interval\_millis)| An optional minimal interval in milliseconds between the start of the failed run and the subsequent retry run. The default behavior is that unsuccessful runs are immediately retried. |`number`|`null`| no |
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| <aname="input_ml"></a> [ml](#input\_ml)| ML required or not. |`bool`|`false`| no |
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| <aname="input_notebooks"></a> [notebooks](#input\_notebooks)| Local path to the notebook(s) that will be deployed |`any`|`[]`| no |
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| <aname="input_notebooks_access_control"></a> [notebooks\_access\_control](#input\_notebooks\_access\_control)| Notebook access control |`any`|`null`| no |
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| <aname="input_policy_access_control"></a> [policy\_access\_control](#input\_policy\_access\_control)| Policy access control |`any`|`null`| no |
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| <aname="input_policy_overrides"></a> [policy\_overrides](#input\_policy\_overrides)| Cluster policy overrides |`any`|`null`| no |
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| <aname="input_prjid"></a> [prjid](#input\_prjid)| (Required) Name of the project/stack e.g: mystack, nifieks, demoaci. Should not be changed after running 'tf apply' |`string`| n/a | yes |
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| <aname="input_remote_notebooks"></a> [remote\_notebooks](#input\_remote\_notebooks)| Path to notebook(s) in the databricks workspace that will be used by the job |`any`|`[]`| no |
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| <aname="input_retry_on_timeout"></a> [retry\_on\_timeout](#input\_retry\_on\_timeout)| An optional policy to specify whether to retry a job when it times out. The default behavior is to not retry on timeout. |`bool`|`false`| no |
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| <aname="input_schedule"></a> [schedule](#input\_schedule)| Job schedule configuration. |`map(any)`|`null`| no |
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| <aname="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. |`any`|`null`| no |
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| <aname="input_spark_env_vars"></a> [spark\_env\_vars](#input\_spark\_env\_vars)| Map with environment variable key-value pairs to fine-tune Spark clusters. Key-value pairs of the form (X,Y) are exported (i.e., X='Y') while launching the driver and workers. |`any`|`null`| no |
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| <aname="input_spark_version"></a> [spark\_version](#input\_spark\_version)| Runtime version of the cluster. Any supported databricks\_spark\_version id. We advise using Cluster Policies to restrict the list of versions for simplicity while maintaining enough control. |`string`|`null`| no |
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| <aname="input_task_parameters"></a> [task\_parameters](#input\_task\_parameters)| Base parameters to be used for each run of this job. |`map(any)`|`{}`| no |
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| <aname="input_teamid"></a> [teamid](#input\_teamid)| (Required) Name of the team/group e.g. devops, dataengineering. Should not be changed after running 'tf apply' |`string`| n/a | yes |
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| <aname="input_timeout"></a> [timeout](#input\_timeout)| An optional timeout applied to each run of this job. The default behavior is to have no timeout. |`number`|`null`| no |
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| <aname="input_worker_node_type_id"></a> [worker\_node\_type\_id](#input\_worker\_node\_type\_id)| The node type of the Spark worker. |`string`|`null`| no |
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## Outputs
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| Name | Description |
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|------|-------------|
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| <aname="output_cluster_id"></a> [cluster\_id](#output\_cluster\_id)| databricks cluster id |
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| <aname="output_cluster_name"></a> [cluster\_name](#output\_cluster\_name)| databricks cluster name |
| <aname="output_databricks_user"></a> [databricks\_user](#output\_databricks\_user)| databricks user name |
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| <aname="output_databricks_user_id"></a> [databricks\_user\_id](#output\_databricks\_user\_id)| databricks user id |
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| <aname="output_existing_cluster_new_job_existing_notebooks_id"></a> [existing\_cluster\_new\_job\_existing\_notebooks\_id](#output\_existing\_cluster\_new\_job\_existing\_notebooks\_id)| databricks new cluster job id |
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| <aname="output_existing_cluster_new_job_existing_notebooks_job"></a> [existing\_cluster\_new\_job\_existing\_notebooks\_job](#output\_existing\_cluster\_new\_job\_existing\_notebooks\_job)| databricks new cluster job url |
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| <aname="output_existing_cluster_new_job_new_notebooks_id"></a> [existing\_cluster\_new\_job\_new\_notebooks\_id](#output\_existing\_cluster\_new\_job\_new\_notebooks\_id)| databricks new cluster job id |
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| <aname="output_existing_cluster_new_job_new_notebooks_job"></a> [existing\_cluster\_new\_job\_new\_notebooks\_job](#output\_existing\_cluster\_new\_job\_new\_notebooks\_job)| databricks new cluster job url |
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