databricks.getSparkVersion
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Note If you have a fully automated setup with workspaces created by databricks_mws_workspaces, 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.getNodeType data source.
Note This is experimental functionality, which aims to simplify things. In case of wrong parameters given (e.g. together
ml = true
andgenomics = true
, or something like), data source will throw an error. Similarly, if search returns multiple results, andlatest = false
, data source will throw an error.
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";
const withGpu = databricks.getNodeType({
localDisk: true,
minCores: 16,
gbPerCore: 1,
minGpus: 1,
});
const gpuMl = databricks.getSparkVersion({
gpu: true,
ml: true,
});
const research = new databricks.Cluster("research", {
clusterName: "Research Cluster",
sparkVersion: gpuMl.then(gpuMl => gpuMl.id),
nodeTypeId: withGpu.then(withGpu => withGpu.id),
autoterminationMinutes: 20,
autoscale: {
minWorkers: 1,
maxWorkers: 50,
},
});
import pulumi
import pulumi_databricks as databricks
with_gpu = databricks.get_node_type(local_disk=True,
min_cores=16,
gb_per_core=1,
min_gpus=1)
gpu_ml = databricks.get_spark_version(gpu=True,
ml=True)
research = databricks.Cluster("research",
cluster_name="Research Cluster",
spark_version=gpu_ml.id,
node_type_id=with_gpu.id,
autotermination_minutes=20,
autoscale=databricks.ClusterAutoscaleArgs(
min_workers=1,
max_workers=50,
))
package main
import (
"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
withGpu, err := databricks.GetNodeType(ctx, &databricks.GetNodeTypeArgs{
LocalDisk: pulumi.BoolRef(true),
MinCores: pulumi.IntRef(16),
GbPerCore: pulumi.IntRef(1),
MinGpus: pulumi.IntRef(1),
}, nil)
if err != nil {
return err
}
gpuMl, err := databricks.GetSparkVersion(ctx, &databricks.GetSparkVersionArgs{
Gpu: pulumi.BoolRef(true),
Ml: pulumi.BoolRef(true),
}, nil)
if err != nil {
return err
}
_, err = databricks.NewCluster(ctx, "research", &databricks.ClusterArgs{
ClusterName: pulumi.String("Research Cluster"),
SparkVersion: pulumi.String(gpuMl.Id),
NodeTypeId: pulumi.String(withGpu.Id),
AutoterminationMinutes: pulumi.Int(20),
Autoscale: &databricks.ClusterAutoscaleArgs{
MinWorkers: pulumi.Int(1),
MaxWorkers: pulumi.Int(50),
},
})
if err != nil {
return err
}
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;
return await Deployment.RunAsync(() =>
{
var withGpu = Databricks.GetNodeType.Invoke(new()
{
LocalDisk = true,
MinCores = 16,
GbPerCore = 1,
MinGpus = 1,
});
var gpuMl = Databricks.GetSparkVersion.Invoke(new()
{
Gpu = true,
Ml = true,
});
var research = new Databricks.Cluster("research", new()
{
ClusterName = "Research Cluster",
SparkVersion = gpuMl.Apply(getSparkVersionResult => getSparkVersionResult.Id),
NodeTypeId = withGpu.Apply(getNodeTypeResult => getNodeTypeResult.Id),
AutoterminationMinutes = 20,
Autoscale = new Databricks.Inputs.ClusterAutoscaleArgs
{
MinWorkers = 1,
MaxWorkers = 50,
},
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.DatabricksFunctions;
import com.pulumi.databricks.inputs.GetNodeTypeArgs;
import com.pulumi.databricks.inputs.GetSparkVersionArgs;
import com.pulumi.databricks.Cluster;
import com.pulumi.databricks.ClusterArgs;
import com.pulumi.databricks.inputs.ClusterAutoscaleArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
final var withGpu = DatabricksFunctions.getNodeType(GetNodeTypeArgs.builder()
.localDisk(true)
.minCores(16)
.gbPerCore(1)
.minGpus(1)
.build());
final var gpuMl = DatabricksFunctions.getSparkVersion(GetSparkVersionArgs.builder()
.gpu(true)
.ml(true)
.build());
var research = new Cluster("research", ClusterArgs.builder()
.clusterName("Research Cluster")
.sparkVersion(gpuMl.applyValue(getSparkVersionResult -> getSparkVersionResult.id()))
.nodeTypeId(withGpu.applyValue(getNodeTypeResult -> getNodeTypeResult.id()))
.autoterminationMinutes(20)
.autoscale(ClusterAutoscaleArgs.builder()
.minWorkers(1)
.maxWorkers(50)
.build())
.build());
}
}
resources:
research:
type: databricks:Cluster
properties:
clusterName: Research Cluster
sparkVersion: ${gpuMl.id}
nodeTypeId: ${withGpu.id}
autoterminationMinutes: 20
autoscale:
minWorkers: 1
maxWorkers: 50
variables:
withGpu:
fn::invoke:
Function: databricks:getNodeType
Arguments:
localDisk: true
minCores: 16
gbPerCore: 1
minGpus: 1
gpuMl:
fn::invoke:
Function: databricks:getSparkVersion
Arguments:
gpu: true
ml: true
Related Resources
The following resources are used in the same context:
- End to end workspace management guide.
- databricks.Cluster to create Databricks Clusters.
- databricks.ClusterPolicy to create a databricks.Cluster policy, which limits the ability to create clusters based on a set of rules.
- databricks.InstancePool 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.
Using getSparkVersion
Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.
function getSparkVersion(args: GetSparkVersionArgs, opts?: InvokeOptions): Promise<GetSparkVersionResult>
function getSparkVersionOutput(args: GetSparkVersionOutputArgs, opts?: InvokeOptions): Output<GetSparkVersionResult>
def get_spark_version(beta: Optional[bool] = None,
genomics: Optional[bool] = None,
gpu: Optional[bool] = None,
graviton: Optional[bool] = None,
latest: Optional[bool] = None,
long_term_support: Optional[bool] = None,
ml: Optional[bool] = None,
photon: Optional[bool] = None,
scala: Optional[str] = None,
spark_version: Optional[str] = None,
opts: Optional[InvokeOptions] = None) -> GetSparkVersionResult
def get_spark_version_output(beta: Optional[pulumi.Input[bool]] = None,
genomics: Optional[pulumi.Input[bool]] = None,
gpu: Optional[pulumi.Input[bool]] = None,
graviton: Optional[pulumi.Input[bool]] = None,
latest: Optional[pulumi.Input[bool]] = None,
long_term_support: Optional[pulumi.Input[bool]] = None,
ml: Optional[pulumi.Input[bool]] = None,
photon: Optional[pulumi.Input[bool]] = None,
scala: Optional[pulumi.Input[str]] = None,
spark_version: Optional[pulumi.Input[str]] = None,
opts: Optional[InvokeOptions] = None) -> Output[GetSparkVersionResult]
func GetSparkVersion(ctx *Context, args *GetSparkVersionArgs, opts ...InvokeOption) (*GetSparkVersionResult, error)
func GetSparkVersionOutput(ctx *Context, args *GetSparkVersionOutputArgs, opts ...InvokeOption) GetSparkVersionResultOutput
> Note: This function is named GetSparkVersion
in the Go SDK.
public static class GetSparkVersion
{
public static Task<GetSparkVersionResult> InvokeAsync(GetSparkVersionArgs args, InvokeOptions? opts = null)
public static Output<GetSparkVersionResult> Invoke(GetSparkVersionInvokeArgs args, InvokeOptions? opts = null)
}
public static CompletableFuture<GetSparkVersionResult> getSparkVersion(GetSparkVersionArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
fn::invoke:
function: databricks:index/getSparkVersion:getSparkVersion
arguments:
# arguments dictionary
The following arguments are supported:
- Beta bool
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - Genomics bool
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - Gpu bool
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - Graviton bool
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - Latest bool
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - Long
Term boolSupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - Ml bool
- if we should limit the search only to ML runtimes. Default to
false
. - Photon bool
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - Scala string
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - Spark
Version string - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
- Beta bool
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - Genomics bool
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - Gpu bool
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - Graviton bool
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - Latest bool
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - Long
Term boolSupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - Ml bool
- if we should limit the search only to ML runtimes. Default to
false
. - Photon bool
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - Scala string
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - Spark
Version string - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
- beta Boolean
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - genomics Boolean
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - gpu Boolean
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - graviton Boolean
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - latest Boolean
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - long
Term BooleanSupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - ml Boolean
- if we should limit the search only to ML runtimes. Default to
false
. - photon Boolean
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - scala String
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - spark
Version String - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
- beta boolean
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - genomics boolean
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - gpu boolean
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - graviton boolean
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - latest boolean
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - long
Term booleanSupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - ml boolean
- if we should limit the search only to ML runtimes. Default to
false
. - photon boolean
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - scala string
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - spark
Version string - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
- beta bool
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - genomics bool
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - gpu bool
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - graviton bool
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - latest bool
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - long_
term_ boolsupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - ml bool
- if we should limit the search only to ML runtimes. Default to
false
. - photon bool
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - scala str
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - spark_
version str - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
- beta Boolean
- if we should limit the search only to runtimes that are in Beta stage. Default to
false
. - genomics Boolean
- if we should limit the search only to Genomics (HLS) runtimes. Default to
false
. - gpu Boolean
- if we should limit the search only to runtimes that support GPUs. Default to
false
. - graviton Boolean
- if we should limit the search only to runtimes supporting AWS Graviton CPUs. Default to
false
. 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. - latest Boolean
- if we should return only the latest version if there is more than one result. Default to
true
. If set tofalse
and multiple versions are matching, throws an error. - long
Term BooleanSupport - if we should limit the search only to LTS (long term support) & ESR (extended support) versions. Default to
false
. - ml Boolean
- if we should limit the search only to ML runtimes. Default to
false
. - photon Boolean
- if we should limit the search only to Photon runtimes. Default to
false
. Deprecated with DBR 14.0 release. Specifyruntime_engine=\"PHOTON\"
in the cluster configuration instead! - scala String
- if we should limit the search only to runtimes that are based on specific Scala version. Default to
2.12
. - spark
Version String - if we should limit the search only to runtimes that are based on specific Spark version. Default to empty string. It could be specified as
3
, or3.0
, or full version, like,3.0.1
.
getSparkVersion Result
The following output properties are available:
Package Details
- Repository
- databricks pulumi/pulumi-databricks
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
databricks
Terraform Provider.