subcategory |
---|
Compute |
-> Note If you have a fully automated setup with workspaces created by databricks_mws_workspaces or azurerm_databricks_workspace, please make sure to add depends_on attribute in order to prevent default auth: cannot configure default credentials errors.
Gets Databricks Runtime (DBR) version that could be used for spark_version
parameter in databricks_cluster and other resources that fits search criteria, like specific Spark or Scala version, ML or Genomics runtime, etc., similar to executing databricks clusters spark-versions
, and filters it to return the latest version that matches criteria. Often used along databricks_node_type data source.
-> Note This is experimental functionality, which aims to simplify things. In case of wrong parameters given (e.g. together ml = true
and genomics = true
, or something like), data source will throw an error. Similarly, if search returns multiple results, and latest = false
, data source will throw an error.
data "databricks_node_type" "with_gpu" {
local_disk = true
min_cores = 16
gb_per_core = 1
min_gpus = 1
}
data "databricks_spark_version" "gpu_ml" {
gpu = true
ml = true
}
resource "databricks_cluster" "research" {
cluster_name = "Research Cluster"
spark_version = data.databricks_spark_version.gpu_ml.id
node_type_id = data.databricks_node_type.with_gpu.id
autotermination_minutes = 20
autoscale {
min_workers = 1
max_workers = 50
}
}
Data source allows you to pick groups by the following attributes:
latest
- (boolean, optional) if we should return only the latest version if there is more than one result. Default totrue
. If set tofalse
and multiple versions are matching, throws an error.long_term_support
- (boolean, optional) if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default tofalse
.ml
- (boolean, optional) if we should limit the search only to ML runtimes. Default tofalse
.genomics
- (boolean, optional) if we should limit the search only to Genomics (HLS) runtimes. Default tofalse
.gpu
- (boolean, optional) if we should limit the search only to runtimes that support GPUs. Default tofalse
.beta
- (boolean, optional) if we should limit the search only to runtimes that are in Beta stage. Default tofalse
.scala
- (string, optional) if we should limit the search only to runtimes that are based on specific Scala version. Default to2.12
.spark_version
- (string, optional) if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as3
, or3.0
, or full version, like,3.0.1
.photon
- (boolean, optional) if we should limit the search only to Photon runtimes. Default tofalse
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead!graviton
- (boolean, optional) if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default tofalse
. Deprecated with DBR 14.0 release. DBR version compiled for Graviton will be automatically installed when nodes with Graviton CPUs are specified in the cluster configuration.
Data source exposes the following attributes:
id
- Databricks Runtime version, that can be used asspark_version
field in databricks_job, databricks_cluster, or databricks_instance_pool.
The following resources are used in the same context:
- End to end workspace management guide.
- databricks_cluster to create Databricks Clusters.
- databricks_cluster_policy to create a databricks_cluster policy, which limits the ability to create clusters based on a set of rules.
- databricks_instance_pool to manage instance pools to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
- databricks_job to manage Databricks Jobs to run non-interactive code in a databricks_cluster.